Detailed changes
@@ -629,13 +629,17 @@ version = "0.1.0"
dependencies = [
"anyhow",
"chrono",
+ "collections",
"futures 0.3.32",
"http_client",
+ "language_model_core",
+ "log",
"schemars",
"serde",
"serde_json",
"strum 0.27.2",
"thiserror 2.0.17",
+ "tiktoken-rs",
]
[[package]]
@@ -2903,7 +2907,6 @@ dependencies = [
"http_client",
"http_client_tls",
"httparse",
- "language_model",
"log",
"objc2-foundation",
"parking_lot",
@@ -2959,6 +2962,7 @@ dependencies = [
"http_client",
"parking_lot",
"serde_json",
+ "smol",
"thiserror 2.0.17",
"yawc",
]
@@ -3204,7 +3208,6 @@ dependencies = [
"anyhow",
"call",
"channel",
- "chrono",
"client",
"collections",
"db",
@@ -3213,7 +3216,6 @@ dependencies = [
"fuzzy",
"gpui",
"livekit_client",
- "log",
"menu",
"notifications",
"picker",
@@ -3228,7 +3230,6 @@ dependencies = [
"theme",
"theme_settings",
"time",
- "time_format",
"title_bar",
"ui",
"util",
@@ -5161,6 +5162,7 @@ dependencies = [
"buffer_diff",
"client",
"clock",
+ "cloud_api_client",
"cloud_api_types",
"cloud_llm_client",
"collections",
@@ -5640,7 +5642,7 @@ dependencies = [
name = "env_var"
version = "0.1.0"
dependencies = [
- "gpui",
+ "gpui_shared_string",
]
[[package]]
@@ -6182,6 +6184,7 @@ dependencies = [
"file_icons",
"futures 0.3.32",
"fuzzy",
+ "fuzzy_nucleo",
"gpui",
"menu",
"open_path_prompt",
@@ -6739,6 +6742,15 @@ dependencies = [
"thread_local",
]
+[[package]]
+name = "fuzzy_nucleo"
+version = "0.1.0"
+dependencies = [
+ "gpui",
+ "nucleo",
+ "util",
+]
+
[[package]]
name = "gaoya"
version = "0.2.0"
@@ -7457,11 +7469,13 @@ dependencies = [
"anyhow",
"futures 0.3.32",
"http_client",
+ "language_model_core",
+ "log",
"schemars",
"serde",
"serde_json",
- "settings",
"strum 0.27.2",
+ "tiktoken-rs",
]
[[package]]
@@ -7530,6 +7544,7 @@ dependencies = [
"getrandom 0.3.4",
"gpui_macros",
"gpui_platform",
+ "gpui_shared_string",
"gpui_util",
"gpui_web",
"http_client",
@@ -7699,6 +7714,16 @@ dependencies = [
"gpui_windows",
]
+[[package]]
+name = "gpui_shared_string"
+version = "0.1.0"
+dependencies = [
+ "derive_more",
+ "gpui_util",
+ "schemars",
+ "serde",
+]
+
[[package]]
name = "gpui_tokio"
version = "0.1.0"
@@ -9348,7 +9373,7 @@ version = "0.1.0"
dependencies = [
"anyhow",
"collections",
- "gpui",
+ "gpui_shared_string",
"log",
"lsp",
"parking_lot",
@@ -9387,12 +9412,8 @@ dependencies = [
name = "language_model"
version = "0.1.0"
dependencies = [
- "anthropic",
"anyhow",
"base64 0.22.1",
- "cloud_api_client",
- "cloud_api_types",
- "cloud_llm_client",
"collections",
"credentials_provider",
"env_var",
@@ -9401,16 +9422,31 @@ dependencies = [
"http_client",
"icons",
"image",
+ "language_model_core",
"log",
- "open_ai",
- "open_router",
"parking_lot",
+ "serde",
+ "serde_json",
+ "thiserror 2.0.17",
+ "util",
+]
+
+[[package]]
+name = "language_model_core"
+version = "0.1.0"
+dependencies = [
+ "anyhow",
+ "cloud_llm_client",
+ "futures 0.3.32",
+ "gpui_shared_string",
+ "http_client",
+ "partial-json-fixer",
"schemars",
"serde",
"serde_json",
"smol",
+ "strum 0.27.2",
"thiserror 2.0.17",
- "util",
]
[[package]]
@@ -9426,8 +9462,8 @@ dependencies = [
"base64 0.22.1",
"bedrock",
"client",
+ "cloud_api_client",
"cloud_api_types",
- "cloud_llm_client",
"collections",
"component",
"convert_case 0.8.0",
@@ -9446,6 +9482,7 @@ dependencies = [
"http_client",
"language",
"language_model",
+ "language_models_cloud",
"lmstudio",
"log",
"menu",
@@ -9455,19 +9492,16 @@ dependencies = [
"open_router",
"opencode",
"parking_lot",
- "partial-json-fixer",
"pretty_assertions",
"rand 0.9.2",
"release_channel",
"schemars",
- "semver",
"serde",
"serde_json",
"settings",
"sha2",
"smol",
"strum 0.27.2",
- "thiserror 2.0.17",
"tiktoken-rs",
"tokio",
"ui",
@@ -9478,6 +9512,28 @@ dependencies = [
"x_ai",
]
+[[package]]
+name = "language_models_cloud"
+version = "0.1.0"
+dependencies = [
+ "anthropic",
+ "anyhow",
+ "cloud_llm_client",
+ "futures 0.3.32",
+ "google_ai",
+ "gpui",
+ "http_client",
+ "language_model",
+ "open_ai",
+ "schemars",
+ "semver",
+ "serde",
+ "serde_json",
+ "smol",
+ "thiserror 2.0.17",
+ "x_ai",
+]
+
[[package]]
name = "language_onboarding"
version = "0.1.0"
@@ -11067,6 +11123,27 @@ dependencies = [
"windows-sys 0.61.2",
]
+[[package]]
+name = "nucleo"
+version = "0.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5262af4c94921c2646c5ac6ff7900c2af9cbb08dc26a797e18130a7019c039d4"
+dependencies = [
+ "nucleo-matcher",
+ "parking_lot",
+ "rayon",
+]
+
+[[package]]
+name = "nucleo-matcher"
+version = "0.3.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "bf33f538733d1a5a3494b836ba913207f14d9d4a1d3cd67030c5061bdd2cac85"
+dependencies = [
+ "memchr",
+ "unicode-segmentation",
+]
+
[[package]]
name = "num"
version = "0.4.3"
@@ -11604,16 +11681,19 @@ name = "open_ai"
version = "0.1.0"
dependencies = [
"anyhow",
+ "collections",
"futures 0.3.32",
"http_client",
+ "language_model_core",
"log",
+ "pretty_assertions",
"rand 0.9.2",
"schemars",
"serde",
"serde_json",
- "settings",
"strum 0.27.2",
"thiserror 2.0.17",
+ "tiktoken-rs",
]
[[package]]
@@ -11645,6 +11725,7 @@ dependencies = [
"anyhow",
"futures 0.3.32",
"http_client",
+ "language_model_core",
"schemars",
"serde",
"serde_json",
@@ -13207,6 +13288,7 @@ dependencies = [
"fs",
"futures 0.3.32",
"fuzzy",
+ "fuzzy_nucleo",
"git",
"git2",
"git_hosting_providers",
@@ -15773,6 +15855,7 @@ dependencies = [
"collections",
"derive_more",
"gpui",
+ "language_model_core",
"log",
"schemars",
"serde",
@@ -20152,6 +20235,7 @@ version = "0.1.0"
dependencies = [
"anyhow",
"client",
+ "cloud_api_client",
"cloud_api_types",
"cloud_llm_client",
"futures 0.3.32",
@@ -21755,9 +21839,11 @@ name = "x_ai"
version = "0.1.0"
dependencies = [
"anyhow",
+ "language_model_core",
"schemars",
"serde",
"strum 0.27.2",
+ "tiktoken-rs",
]
[[package]]
@@ -78,6 +78,7 @@ members = [
"crates/fs",
"crates/fs_benchmarks",
"crates/fuzzy",
+ "crates/fuzzy_nucleo",
"crates/git",
"crates/git_graph",
"crates/git_hosting_providers",
@@ -86,6 +87,7 @@ members = [
"crates/google_ai",
"crates/grammars",
"crates/gpui",
+ "crates/gpui_shared_string",
"crates/gpui_linux",
"crates/gpui_macos",
"crates/gpui_macros",
@@ -109,7 +111,9 @@ members = [
"crates/language_core",
"crates/language_extension",
"crates/language_model",
+ "crates/language_model_core",
"crates/language_models",
+ "crates/language_models_cloud",
"crates/language_onboarding",
"crates/language_selector",
"crates/language_tools",
@@ -325,6 +329,7 @@ file_finder = { path = "crates/file_finder" }
file_icons = { path = "crates/file_icons" }
fs = { path = "crates/fs" }
fuzzy = { path = "crates/fuzzy" }
+fuzzy_nucleo = { path = "crates/fuzzy_nucleo" }
git = { path = "crates/git" }
git_graph = { path = "crates/git_graph" }
git_hosting_providers = { path = "crates/git_hosting_providers" }
@@ -333,6 +338,7 @@ go_to_line = { path = "crates/go_to_line" }
google_ai = { path = "crates/google_ai" }
grammars = { path = "crates/grammars" }
gpui = { path = "crates/gpui", default-features = false }
+gpui_shared_string = { path = "crates/gpui_shared_string" }
gpui_linux = { path = "crates/gpui_linux", default-features = false }
gpui_macos = { path = "crates/gpui_macos", default-features = false }
gpui_macros = { path = "crates/gpui_macros" }
@@ -359,7 +365,9 @@ language = { path = "crates/language" }
language_core = { path = "crates/language_core" }
language_extension = { path = "crates/language_extension" }
language_model = { path = "crates/language_model" }
+language_model_core = { path = "crates/language_model_core" }
language_models = { path = "crates/language_models" }
+language_models_cloud = { path = "crates/language_models_cloud" }
language_onboarding = { path = "crates/language_onboarding" }
language_selector = { path = "crates/language_selector" }
language_tools = { path = "crates/language_tools" }
@@ -609,6 +617,7 @@ naga = { version = "29.0", features = ["wgsl-in"] }
nanoid = "0.4"
nbformat = "1.2.0"
nix = "0.29"
+nucleo = "0.5"
num-format = "0.4.4"
objc = "0.2"
objc2-app-kit = { version = "0.3", default-features = false, features = [ "NSGraphics" ] }
@@ -0,0 +1,5 @@
+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M4.24135 9.23279L5.18103 7.41608C5.28319 7.21319 5.43858 7.0419 5.63058 6.92052C5.82258 6.79914 6.04397 6.73224 6.27106 6.72698H13.0117M13.0117 6.72698C13.2031 6.72664 13.392 6.77016 13.564 6.8542C13.736 6.93824 13.8864 7.06056 14.0037 7.21177C14.1211 7.36298 14.2022 7.53907 14.2409 7.72652C14.2796 7.91397 14.2749 8.10779 14.227 8.29311L13.9858 9.23279M13.0117 6.72698V5.47407C13.0117 5.14178 12.8797 4.8231 12.6447 4.58813C12.4098 4.35317 12.0911 4.22116 11.7588 4.22116H8.04392C7.8365 4.22113 7.63233 4.1696 7.44973 4.07119C7.26714 3.97279 7.11183 3.83059 6.99774 3.65736L6.49032 2.90561C6.37507 2.7306 6.21778 2.58728 6.03282 2.48878C5.84786 2.39028 5.64115 2.33975 5.43161 2.3418H2.98844C2.65615 2.3418 2.33747 2.47381 2.1025 2.70877C1.86754 2.94374 1.73553 3.26242 1.73553 3.59471V11.7386C1.73553 12.0709 1.86754 12.3896 2.1025 12.6245C2.33747 12.8595 2.65615 12.9915 2.98844 12.9915H7.3118" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M11.6 9.88724L11.6 14.1318" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M9.47626 12.5234L11.6 14.6471L13.7237 12.5234" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+</svg>
@@ -1,5 +0,0 @@
-<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
-<path d="M8 7.29524V10.6536" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
-<path d="M6.3208 8.97442H9.67917" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
-<path d="M12.8 13C13.1183 13 13.4235 12.8761 13.6486 12.6554C13.8735 12.4349 14 12.1356 14 11.8236V5.94118C14 5.62916 13.8735 5.32992 13.6486 5.10929C13.4235 4.88866 13.1183 4.76471 12.8 4.76471H8.06C7.8593 4.76664 7.66133 4.71919 7.48418 4.6267C7.30703 4.53421 7.15637 4.39964 7.046 4.2353L6.56 3.52941C6.45073 3.36675 6.30199 3.23322 6.1271 3.14082C5.95221 3.04842 5.75666 3.00004 5.558 3H3.2C2.88174 3 2.57651 3.12395 2.35148 3.34458C2.12643 3.56521 2 3.86445 2 4.17647V11.8236C2 12.1356 2.12643 12.4349 2.35148 12.6554C2.57651 12.8761 2.88174 13 3.2 13H12.8Z" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
-</svg>
@@ -0,0 +1,7 @@
+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M14.4381 11.5973V4.40274C14.4381 3.7405 13.8616 3.20366 13.1505 3.20366H2.84956C2.13843 3.20366 1.56195 3.7405 1.56195 4.40274V11.5973C1.56195 12.2595 2.13843 12.7963 2.84956 12.7963H5.69262" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M6.71237 3.20366V5.75366" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M1.56195 5.75365H14.4381" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M4.13715 3.20366V5.75366" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+<path d="M9.01288 13.0158H10.8129M10.8129 13.0158H12.6129M10.8129 13.0158V11.2158M10.8129 13.0158V14.8158" stroke="#C6CAD0" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round"/>
+</svg>
@@ -936,16 +936,6 @@
// For example: typing `:wave:` gets replaced with `π`.
"auto_replace_emoji_shortcode": true,
},
- "notification_panel": {
- // Whether to show the notification panel button in the status bar.
- "button": true,
- // Where to dock the notification panel. Can be 'left' or 'right'.
- "dock": "right",
- // Default width of the notification panel.
- "default_width": 380,
- // Whether to show a badge on the notification panel icon with the count of unread notifications.
- "show_count_badge": false,
- },
"agent": {
// Whether the inline assistant should use streaming tools, when available
"inline_assistant_use_streaming_tools": true,
@@ -965,6 +955,9 @@
"default_width": 640,
// Default height when the agent panel is docked to the bottom.
"default_height": 320,
+ // Maximum content width when the agent panel is wider than this value.
+ // Content will be centered within the panel.
+ "max_content_width": 850,
// The default model to use when creating new threads.
"default_model": {
// The provider to use.
@@ -574,6 +574,7 @@ mod tests {
flexible: true,
default_width: px(300.),
default_height: px(600.),
+ max_content_width: px(850.),
default_model: None,
inline_assistant_model: None,
inline_assistant_use_streaming_tools: false,
@@ -5,7 +5,7 @@ use futures::FutureExt as _;
use gpui::{App, Entity, SharedString, Task};
use indoc::formatdoc;
use language::Point;
-use language_model::{LanguageModelImage, LanguageModelToolResultContent};
+use language_model::{LanguageModelImage, LanguageModelImageExt, LanguageModelToolResultContent};
use project::{AgentLocation, ImageItem, Project, WorktreeSettings, image_store};
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
@@ -325,7 +325,7 @@ impl AcpConnection {
// Use the one the agent provides if we have one
.map(|info| info.name.into())
// Otherwise, just use the name
- .unwrap_or_else(|| agent_id.0.to_string().into());
+ .unwrap_or_else(|| agent_id.0.clone());
let session_list = if response
.agent_capabilities
@@ -31,7 +31,6 @@ pub struct PanelLayout {
pub(crate) outline_panel_dock: Option<DockSide>,
pub(crate) collaboration_panel_dock: Option<DockPosition>,
pub(crate) git_panel_dock: Option<DockPosition>,
- pub(crate) notification_panel_button: Option<bool>,
}
impl PanelLayout {
@@ -41,7 +40,6 @@ impl PanelLayout {
outline_panel_dock: Some(DockSide::Right),
collaboration_panel_dock: Some(DockPosition::Right),
git_panel_dock: Some(DockPosition::Right),
- notification_panel_button: Some(false),
};
const EDITOR: Self = Self {
@@ -50,7 +48,6 @@ impl PanelLayout {
outline_panel_dock: Some(DockSide::Left),
collaboration_panel_dock: Some(DockPosition::Left),
git_panel_dock: Some(DockPosition::Left),
- notification_panel_button: Some(true),
};
pub fn is_agent_layout(&self) -> bool {
@@ -68,7 +65,6 @@ impl PanelLayout {
outline_panel_dock: content.outline_panel.as_ref().and_then(|p| p.dock),
collaboration_panel_dock: content.collaboration_panel.as_ref().and_then(|p| p.dock),
git_panel_dock: content.git_panel.as_ref().and_then(|p| p.dock),
- notification_panel_button: content.notification_panel.as_ref().and_then(|p| p.button),
}
}
@@ -78,7 +74,6 @@ impl PanelLayout {
settings.outline_panel.get_or_insert_default().dock = self.outline_panel_dock;
settings.collaboration_panel.get_or_insert_default().dock = self.collaboration_panel_dock;
settings.git_panel.get_or_insert_default().dock = self.git_panel_dock;
- settings.notification_panel.get_or_insert_default().button = self.notification_panel_button;
}
fn write_diff_to(&self, current_merged: &PanelLayout, settings: &mut SettingsContent) {
@@ -98,10 +93,6 @@ impl PanelLayout {
if self.git_panel_dock != current_merged.git_panel_dock {
settings.git_panel.get_or_insert_default().dock = self.git_panel_dock;
}
- if self.notification_panel_button != current_merged.notification_panel_button {
- settings.notification_panel.get_or_insert_default().button =
- self.notification_panel_button;
- }
}
fn backfill_to(&self, user_layout: &PanelLayout, settings: &mut SettingsContent) {
@@ -121,10 +112,6 @@ impl PanelLayout {
if user_layout.git_panel_dock.is_none() {
settings.git_panel.get_or_insert_default().dock = self.git_panel_dock;
}
- if user_layout.notification_panel_button.is_none() {
- settings.notification_panel.get_or_insert_default().button =
- self.notification_panel_button;
- }
}
}
@@ -154,6 +141,7 @@ pub struct AgentSettings {
pub sidebar_side: SidebarDockPosition,
pub default_width: Pixels,
pub default_height: Pixels,
+ pub max_content_width: Pixels,
pub default_model: Option<LanguageModelSelection>,
pub inline_assistant_model: Option<LanguageModelSelection>,
pub inline_assistant_use_streaming_tools: bool,
@@ -600,6 +588,7 @@ impl Settings for AgentSettings {
sidebar_side: agent.sidebar_side.unwrap(),
default_width: px(agent.default_width.unwrap()),
default_height: px(agent.default_height.unwrap()),
+ max_content_width: px(agent.max_content_width.unwrap()),
flexible: agent.flexible.unwrap(),
default_model: Some(agent.default_model.unwrap()),
inline_assistant_model: agent.inline_assistant_model,
@@ -1255,7 +1244,6 @@ mod tests {
assert_eq!(user_layout.outline_panel_dock, None);
assert_eq!(user_layout.collaboration_panel_dock, None);
assert_eq!(user_layout.git_panel_dock, None);
- assert_eq!(user_layout.notification_panel_button, None);
// User sets a combination that doesn't match either preset:
// agent on the left but project panel also on the left.
@@ -1478,7 +1466,6 @@ mod tests {
Some(DockPosition::Left)
);
assert_eq!(user_layout.git_panel_dock, Some(DockPosition::Left));
- assert_eq!(user_layout.notification_panel_button, Some(true));
// Now switch defaults to agent V2.
set_agent_v2_defaults(cx);
@@ -28,21 +28,20 @@ use zed_actions::agent::{
use crate::thread_metadata_store::ThreadMetadataStore;
use crate::{
AddContextServer, AgentDiffPane, ConversationView, CopyThreadToClipboard, CycleStartThreadIn,
- Follow, InlineAssistant, LoadThreadFromClipboard, NewThread, OpenActiveThreadAsMarkdown,
- OpenAgentDiff, OpenHistory, ResetTrialEndUpsell, ResetTrialUpsell, StartThreadIn,
- ToggleNavigationMenu, ToggleNewThreadMenu, ToggleOptionsMenu,
+ Follow, InlineAssistant, LoadThreadFromClipboard, NewThread, NewWorktreeBranchTarget,
+ OpenActiveThreadAsMarkdown, OpenAgentDiff, OpenHistory, ResetTrialEndUpsell, ResetTrialUpsell,
+ StartThreadIn, ToggleNavigationMenu, ToggleNewThreadMenu, ToggleOptionsMenu,
agent_configuration::{AgentConfiguration, AssistantConfigurationEvent},
conversation_view::{AcpThreadViewEvent, ThreadView},
+ thread_branch_picker::ThreadBranchPicker,
+ thread_worktree_picker::ThreadWorktreePicker,
ui::EndTrialUpsell,
};
use crate::{
Agent, AgentInitialContent, ExternalSourcePrompt, NewExternalAgentThread,
NewNativeAgentThreadFromSummary,
};
-use crate::{
- DEFAULT_THREAD_TITLE,
- ui::{AcpOnboardingModal, HoldForDefault},
-};
+use crate::{DEFAULT_THREAD_TITLE, ui::AcpOnboardingModal};
use crate::{ExpandMessageEditor, ThreadHistoryView};
use crate::{ManageProfiles, ThreadHistoryViewEvent};
use crate::{ThreadHistory, agent_connection_store::AgentConnectionStore};
@@ -73,8 +72,8 @@ use terminal::terminal_settings::TerminalSettings;
use terminal_view::{TerminalView, terminal_panel::TerminalPanel};
use theme_settings::ThemeSettings;
use ui::{
- Button, Callout, CommonAnimationExt, ContextMenu, ContextMenuEntry, DocumentationSide,
- PopoverMenu, PopoverMenuHandle, Tab, Tooltip, prelude::*, utils::WithRemSize,
+ Button, Callout, CommonAnimationExt, ContextMenu, ContextMenuEntry, PopoverMenu,
+ PopoverMenuHandle, Tab, Tooltip, prelude::*, utils::WithRemSize,
};
use util::{ResultExt as _, debug_panic};
use workspace::{
@@ -620,7 +619,31 @@ impl StartThreadIn {
fn label(&self) -> SharedString {
match self {
Self::LocalProject => "Current Worktree".into(),
- Self::NewWorktree => "New Git Worktree".into(),
+ Self::NewWorktree {
+ worktree_name: Some(worktree_name),
+ ..
+ } => format!("New: {worktree_name}").into(),
+ Self::NewWorktree { .. } => "New Git Worktree".into(),
+ Self::LinkedWorktree { display_name, .. } => format!("From: {}", &display_name).into(),
+ }
+ }
+
+ fn worktree_branch_label(&self, default_branch_label: SharedString) -> Option<SharedString> {
+ match self {
+ Self::NewWorktree { branch_target, .. } => match branch_target {
+ NewWorktreeBranchTarget::CurrentBranch => Some(default_branch_label),
+ NewWorktreeBranchTarget::ExistingBranch { name } => {
+ Some(format!("From: {name}").into())
+ }
+ NewWorktreeBranchTarget::CreateBranch { name, from_ref } => {
+ if let Some(from_ref) = from_ref {
+ Some(format!("From: {from_ref}").into())
+ } else {
+ Some(format!("From: {name}").into())
+ }
+ }
+ },
+ _ => None,
}
}
}
@@ -632,6 +655,17 @@ pub enum WorktreeCreationStatus {
Error(SharedString),
}
+#[derive(Clone, Debug)]
+enum WorktreeCreationArgs {
+ New {
+ worktree_name: Option<String>,
+ branch_target: NewWorktreeBranchTarget,
+ },
+ Linked {
+ worktree_path: PathBuf,
+ },
+}
+
impl ActiveView {
pub fn which_font_size_used(&self) -> WhichFontSize {
match self {
@@ -662,7 +696,8 @@ pub struct AgentPanel {
previous_view: Option<ActiveView>,
background_threads: HashMap<acp::SessionId, Entity<ConversationView>>,
new_thread_menu_handle: PopoverMenuHandle<ContextMenu>,
- start_thread_in_menu_handle: PopoverMenuHandle<ContextMenu>,
+ start_thread_in_menu_handle: PopoverMenuHandle<ThreadWorktreePicker>,
+ thread_branch_menu_handle: PopoverMenuHandle<ThreadBranchPicker>,
agent_panel_menu_handle: PopoverMenuHandle<ContextMenu>,
agent_navigation_menu_handle: PopoverMenuHandle<ContextMenu>,
agent_navigation_menu: Option<Entity<ContextMenu>>,
@@ -689,7 +724,7 @@ impl AgentPanel {
};
let selected_agent = self.selected_agent.clone();
- let start_thread_in = Some(self.start_thread_in);
+ let start_thread_in = Some(self.start_thread_in.clone());
let last_active_thread = self.active_agent_thread(cx).map(|thread| {
let thread = thread.read(cx);
@@ -794,18 +829,21 @@ impl AgentPanel {
} else if let Some(agent) = global_fallback {
panel.selected_agent = agent;
}
- if let Some(start_thread_in) = serialized_panel.start_thread_in {
+ if let Some(ref start_thread_in) = serialized_panel.start_thread_in {
let is_worktree_flag_enabled =
cx.has_flag::<AgentV2FeatureFlag>();
let is_valid = match &start_thread_in {
StartThreadIn::LocalProject => true,
- StartThreadIn::NewWorktree => {
+ StartThreadIn::NewWorktree { .. } => {
let project = panel.project.read(cx);
is_worktree_flag_enabled && !project.is_via_collab()
}
+ StartThreadIn::LinkedWorktree { path, .. } => {
+ is_worktree_flag_enabled && path.exists()
+ }
};
if is_valid {
- panel.start_thread_in = start_thread_in;
+ panel.start_thread_in = start_thread_in.clone();
} else {
log::info!(
"deserialized start_thread_in {:?} is no longer valid, falling back to LocalProject",
@@ -979,6 +1017,7 @@ impl AgentPanel {
background_threads: HashMap::default(),
new_thread_menu_handle: PopoverMenuHandle::default(),
start_thread_in_menu_handle: PopoverMenuHandle::default(),
+ thread_branch_menu_handle: PopoverMenuHandle::default(),
agent_panel_menu_handle: PopoverMenuHandle::default(),
agent_navigation_menu_handle: PopoverMenuHandle::default(),
agent_navigation_menu: None,
@@ -1948,24 +1987,43 @@ impl AgentPanel {
window: &mut Window,
cx: &mut Context<Self>,
) {
- if matches!(action, StartThreadIn::NewWorktree) && !cx.has_flag::<AgentV2FeatureFlag>() {
- return;
- }
-
- let new_target = match *action {
+ let new_target = match action {
StartThreadIn::LocalProject => StartThreadIn::LocalProject,
- StartThreadIn::NewWorktree => {
+ StartThreadIn::NewWorktree { .. } => {
+ if !cx.has_flag::<AgentV2FeatureFlag>() {
+ return;
+ }
if !self.project_has_git_repository(cx) {
log::error!(
- "set_start_thread_in: cannot use NewWorktree without a git repository"
+ "set_start_thread_in: cannot use worktree mode without a git repository"
);
return;
}
if self.project.read(cx).is_via_collab() {
- log::error!("set_start_thread_in: cannot use NewWorktree in a collab project");
+ log::error!(
+ "set_start_thread_in: cannot use worktree mode in a collab project"
+ );
return;
}
- StartThreadIn::NewWorktree
+ action.clone()
+ }
+ StartThreadIn::LinkedWorktree { .. } => {
+ if !cx.has_flag::<AgentV2FeatureFlag>() {
+ return;
+ }
+ if !self.project_has_git_repository(cx) {
+ log::error!(
+ "set_start_thread_in: cannot use LinkedWorktree without a git repository"
+ );
+ return;
+ }
+ if self.project.read(cx).is_via_collab() {
+ log::error!(
+ "set_start_thread_in: cannot use LinkedWorktree in a collab project"
+ );
+ return;
+ }
+ action.clone()
}
};
self.start_thread_in = new_target;
@@ -1977,9 +2035,14 @@ impl AgentPanel {
}
fn cycle_start_thread_in(&mut self, window: &mut Window, cx: &mut Context<Self>) {
- let next = match self.start_thread_in {
- StartThreadIn::LocalProject => StartThreadIn::NewWorktree,
- StartThreadIn::NewWorktree => StartThreadIn::LocalProject,
+ let next = match &self.start_thread_in {
+ StartThreadIn::LocalProject => StartThreadIn::NewWorktree {
+ worktree_name: None,
+ branch_target: NewWorktreeBranchTarget::default(),
+ },
+ StartThreadIn::NewWorktree { .. } | StartThreadIn::LinkedWorktree { .. } => {
+ StartThreadIn::LocalProject
+ }
};
self.set_start_thread_in(&next, window, cx);
}
@@ -1991,7 +2054,10 @@ impl AgentPanel {
NewThreadLocation::LocalProject => StartThreadIn::LocalProject,
NewThreadLocation::NewWorktree => {
if self.project_has_git_repository(cx) {
- StartThreadIn::NewWorktree
+ StartThreadIn::NewWorktree {
+ worktree_name: None,
+ branch_target: NewWorktreeBranchTarget::default(),
+ }
} else {
StartThreadIn::LocalProject
}
@@ -2219,15 +2285,39 @@ impl AgentPanel {
window: &mut Window,
cx: &mut Context<Self>,
) {
- if self.start_thread_in == StartThreadIn::NewWorktree {
- self.handle_worktree_creation_requested(content, window, cx);
- } else {
- cx.defer_in(window, move |_this, window, cx| {
- thread_view.update(cx, |thread_view, cx| {
- let editor = thread_view.message_editor.clone();
- thread_view.send_impl(editor, window, cx);
+ match &self.start_thread_in {
+ StartThreadIn::NewWorktree {
+ worktree_name,
+ branch_target,
+ } => {
+ self.handle_worktree_requested(
+ content,
+ WorktreeCreationArgs::New {
+ worktree_name: worktree_name.clone(),
+ branch_target: branch_target.clone(),
+ },
+ window,
+ cx,
+ );
+ }
+ StartThreadIn::LinkedWorktree { path, .. } => {
+ self.handle_worktree_requested(
+ content,
+ WorktreeCreationArgs::Linked {
+ worktree_path: path.clone(),
+ },
+ window,
+ cx,
+ );
+ }
+ StartThreadIn::LocalProject => {
+ cx.defer_in(window, move |_this, window, cx| {
+ thread_view.update(cx, |thread_view, cx| {
+ let editor = thread_view.message_editor.clone();
+ thread_view.send_impl(editor, window, cx);
+ });
});
- });
+ }
}
}
@@ -2289,6 +2379,33 @@ impl AgentPanel {
(git_repos, non_git_paths)
}
+ fn resolve_worktree_branch_target(
+ branch_target: &NewWorktreeBranchTarget,
+ existing_branches: &HashSet<String>,
+ occupied_branches: &HashSet<String>,
+ ) -> Result<(String, bool, Option<String>)> {
+ let generate_branch_name = || -> Result<String> {
+ let refs: Vec<&str> = existing_branches.iter().map(|s| s.as_str()).collect();
+ let mut rng = rand::rng();
+ crate::branch_names::generate_branch_name(&refs, &mut rng)
+ .ok_or_else(|| anyhow!("Failed to generate a unique branch name"))
+ };
+
+ match branch_target {
+ NewWorktreeBranchTarget::CreateBranch { name, from_ref } => {
+ Ok((name.clone(), false, from_ref.clone()))
+ }
+ NewWorktreeBranchTarget::ExistingBranch { name } => {
+ if occupied_branches.contains(name) {
+ Ok((generate_branch_name()?, false, Some(name.clone())))
+ } else {
+ Ok((name.clone(), true, None))
+ }
+ }
+ NewWorktreeBranchTarget::CurrentBranch => Ok((generate_branch_name()?, false, None)),
+ }
+ }
+
/// Kicks off an async git-worktree creation for each repository. Returns:
///
/// - `creation_infos`: a vec of `(repo, new_path, receiver)` tuplesβthe
@@ -2297,7 +2414,10 @@ impl AgentPanel {
/// later to remap open editor tabs into the new workspace.
fn start_worktree_creations(
git_repos: &[Entity<project::git_store::Repository>],
+ worktree_name: Option<String>,
branch_name: &str,
+ use_existing_branch: bool,
+ start_point: Option<String>,
worktree_directory_setting: &str,
cx: &mut Context<Self>,
) -> Result<(
@@ -2311,12 +2431,27 @@ impl AgentPanel {
let mut creation_infos = Vec::new();
let mut path_remapping = Vec::new();
+ let worktree_name = worktree_name.unwrap_or_else(|| branch_name.to_string());
+
for repo in git_repos {
let (work_dir, new_path, receiver) = repo.update(cx, |repo, _cx| {
let new_path =
- repo.path_for_new_linked_worktree(branch_name, worktree_directory_setting)?;
- let receiver =
- repo.create_worktree(branch_name.to_string(), new_path.clone(), None);
+ repo.path_for_new_linked_worktree(&worktree_name, worktree_directory_setting)?;
+ let target = if use_existing_branch {
+ debug_assert!(
+ git_repos.len() == 1,
+ "use_existing_branch should only be true for a single repo"
+ );
+ git::repository::CreateWorktreeTarget::ExistingBranch {
+ branch_name: branch_name.to_string(),
+ }
+ } else {
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: branch_name.to_string(),
+ base_sha: start_point.clone(),
+ }
+ };
+ let receiver = repo.create_worktree(target, new_path.clone());
let work_dir = repo.work_directory_abs_path.clone();
anyhow::Ok((work_dir, new_path, receiver))
})?;
@@ -2419,9 +2554,10 @@ impl AgentPanel {
cx.notify();
}
- fn handle_worktree_creation_requested(
+ fn handle_worktree_requested(
&mut self,
content: Vec<acp::ContentBlock>,
+ args: WorktreeCreationArgs,
window: &mut Window,
cx: &mut Context<Self>,
) {
@@ -2437,7 +2573,7 @@ impl AgentPanel {
let (git_repos, non_git_paths) = self.classify_worktrees(cx);
- if git_repos.is_empty() {
+ if matches!(args, WorktreeCreationArgs::New { .. }) && git_repos.is_empty() {
self.set_worktree_creation_error(
"No git repositories found in the project".into(),
window,
@@ -2446,17 +2582,31 @@ impl AgentPanel {
return;
}
- // Kick off branch listing as early as possible so it can run
- // concurrently with the remaining synchronous setup work.
- let branch_receivers: Vec<_> = git_repos
- .iter()
- .map(|repo| repo.update(cx, |repo, _cx| repo.branches()))
- .collect();
-
- let worktree_directory_setting = ProjectSettings::get_global(cx)
- .git
- .worktree_directory
- .clone();
+ let (branch_receivers, worktree_receivers, worktree_directory_setting) =
+ if matches!(args, WorktreeCreationArgs::New { .. }) {
+ (
+ Some(
+ git_repos
+ .iter()
+ .map(|repo| repo.update(cx, |repo, _cx| repo.branches()))
+ .collect::<Vec<_>>(),
+ ),
+ Some(
+ git_repos
+ .iter()
+ .map(|repo| repo.update(cx, |repo, _cx| repo.worktrees()))
+ .collect::<Vec<_>>(),
+ ),
+ Some(
+ ProjectSettings::get_global(cx)
+ .git
+ .worktree_directory
+ .clone(),
+ ),
+ )
+ } else {
+ (None, None, None)
+ };
let active_file_path = self.workspace.upgrade().and_then(|workspace| {
let workspace = workspace.read(cx);
@@ -2476,77 +2626,124 @@ impl AgentPanel {
let selected_agent = self.selected_agent();
let task = cx.spawn_in(window, async move |this, cx| {
- // Await the branch listings we kicked off earlier.
- let mut existing_branches = Vec::new();
- for result in futures::future::join_all(branch_receivers).await {
- match result {
- Ok(Ok(branches)) => {
- for branch in branches {
- existing_branches.push(branch.name().to_string());
+ let (all_paths, path_remapping, has_non_git) = match args {
+ WorktreeCreationArgs::New {
+ worktree_name,
+ branch_target,
+ } => {
+ let branch_receivers = branch_receivers
+ .expect("branch receivers must be prepared for new worktree creation");
+ let worktree_receivers = worktree_receivers
+ .expect("worktree receivers must be prepared for new worktree creation");
+ let worktree_directory_setting = worktree_directory_setting
+ .expect("worktree directory must be prepared for new worktree creation");
+
+ let mut existing_branches = HashSet::default();
+ for result in futures::future::join_all(branch_receivers).await {
+ match result {
+ Ok(Ok(branches)) => {
+ for branch in branches {
+ existing_branches.insert(branch.name().to_string());
+ }
+ }
+ Ok(Err(err)) => {
+ Err::<(), _>(err).log_err();
+ }
+ Err(_) => {}
}
}
- Ok(Err(err)) => {
- Err::<(), _>(err).log_err();
+
+ let mut occupied_branches = HashSet::default();
+ for result in futures::future::join_all(worktree_receivers).await {
+ match result {
+ Ok(Ok(worktrees)) => {
+ for worktree in worktrees {
+ if let Some(branch_name) = worktree.branch_name() {
+ occupied_branches.insert(branch_name.to_string());
+ }
+ }
+ }
+ Ok(Err(err)) => {
+ Err::<(), _>(err).log_err();
+ }
+ Err(_) => {}
+ }
}
- Err(_) => {}
- }
- }
- let existing_branch_refs: Vec<&str> =
- existing_branches.iter().map(|s| s.as_str()).collect();
- let mut rng = rand::rng();
- let branch_name =
- match crate::branch_names::generate_branch_name(&existing_branch_refs, &mut rng) {
- Some(name) => name,
- None => {
- this.update_in(cx, |this, window, cx| {
- this.set_worktree_creation_error(
- "Failed to generate a unique branch name".into(),
- window,
+ let (branch_name, use_existing_branch, start_point) =
+ match Self::resolve_worktree_branch_target(
+ &branch_target,
+ &existing_branches,
+ &occupied_branches,
+ ) {
+ Ok(target) => target,
+ Err(err) => {
+ this.update_in(cx, |this, window, cx| {
+ this.set_worktree_creation_error(
+ err.to_string().into(),
+ window,
+ cx,
+ );
+ })?;
+ return anyhow::Ok(());
+ }
+ };
+
+ let (creation_infos, path_remapping) =
+ match this.update_in(cx, |_this, _window, cx| {
+ Self::start_worktree_creations(
+ &git_repos,
+ worktree_name,
+ &branch_name,
+ use_existing_branch,
+ start_point,
+ &worktree_directory_setting,
cx,
- );
- })?;
- return anyhow::Ok(());
- }
- };
+ )
+ }) {
+ Ok(Ok(result)) => result,
+ Ok(Err(err)) | Err(err) => {
+ this.update_in(cx, |this, window, cx| {
+ this.set_worktree_creation_error(
+ format!("Failed to validate worktree directory: {err}")
+ .into(),
+ window,
+ cx,
+ );
+ })
+ .log_err();
+ return anyhow::Ok(());
+ }
+ };
- let (creation_infos, path_remapping) = match this.update_in(cx, |_this, _window, cx| {
- Self::start_worktree_creations(
- &git_repos,
- &branch_name,
- &worktree_directory_setting,
- cx,
- )
- }) {
- Ok(Ok(result)) => result,
- Ok(Err(err)) | Err(err) => {
- this.update_in(cx, |this, window, cx| {
- this.set_worktree_creation_error(
- format!("Failed to validate worktree directory: {err}").into(),
- window,
- cx,
- );
- })
- .log_err();
- return anyhow::Ok(());
- }
- };
+ let created_paths =
+ match Self::await_and_rollback_on_failure(creation_infos, cx).await {
+ Ok(paths) => paths,
+ Err(err) => {
+ this.update_in(cx, |this, window, cx| {
+ this.set_worktree_creation_error(
+ format!("{err}").into(),
+ window,
+ cx,
+ );
+ })?;
+ return anyhow::Ok(());
+ }
+ };
- let created_paths = match Self::await_and_rollback_on_failure(creation_infos, cx).await
- {
- Ok(paths) => paths,
- Err(err) => {
- this.update_in(cx, |this, window, cx| {
- this.set_worktree_creation_error(format!("{err}").into(), window, cx);
- })?;
- return anyhow::Ok(());
+ let mut all_paths = created_paths;
+ let has_non_git = !non_git_paths.is_empty();
+ all_paths.extend(non_git_paths.iter().cloned());
+ (all_paths, path_remapping, has_non_git)
+ }
+ WorktreeCreationArgs::Linked { worktree_path } => {
+ let mut all_paths = vec![worktree_path];
+ let has_non_git = !non_git_paths.is_empty();
+ all_paths.extend(non_git_paths.iter().cloned());
+ (all_paths, Vec::new(), has_non_git)
}
};
- let mut all_paths = created_paths;
- let has_non_git = !non_git_paths.is_empty();
- all_paths.extend(non_git_paths.iter().cloned());
-
let app_state = match workspace.upgrade() {
Some(workspace) => cx.update(|_, cx| workspace.read(cx).app_state().clone())?,
None => {
@@ -2562,7 +2759,7 @@ impl AgentPanel {
};
let this_for_error = this.clone();
- if let Err(err) = Self::setup_new_workspace(
+ if let Err(err) = Self::open_worktree_workspace_and_start_thread(
this,
all_paths,
app_state,
@@ -2595,7 +2792,7 @@ impl AgentPanel {
}));
}
- async fn setup_new_workspace(
+ async fn open_worktree_workspace_and_start_thread(
this: WeakEntity<Self>,
all_paths: Vec<PathBuf>,
app_state: Arc<workspace::AppState>,
@@ -2989,17 +3186,11 @@ impl AgentPanel {
fn render_panel_options_menu(
&self,
- window: &mut Window,
+ _window: &mut Window,
cx: &mut Context<Self>,
) -> impl IntoElement {
let focus_handle = self.focus_handle(cx);
- let full_screen_label = if self.is_zoomed(window, cx) {
- "Disable Full Screen"
- } else {
- "Enable Full Screen"
- };
-
let conversation_view = match &self.active_view {
ActiveView::AgentThread { conversation_view } => Some(conversation_view.clone()),
_ => None,
@@ -3075,8 +3266,7 @@ impl AgentPanel {
.action("Profiles", Box::new(ManageProfiles::default()))
.action("Settings", Box::new(OpenSettings))
.separator()
- .action("Toggle Threads Sidebar", Box::new(ToggleWorkspaceSidebar))
- .action(full_screen_label, Box::new(ToggleZoom));
+ .action("Toggle Threads Sidebar", Box::new(ToggleWorkspaceSidebar));
if has_auth_methods {
menu = menu.action("Reauthenticate", Box::new(ReauthenticateAgent))
@@ -3149,25 +3339,15 @@ impl AgentPanel {
}
fn render_start_thread_in_selector(&self, cx: &mut Context<Self>) -> impl IntoElement {
- use settings::{NewThreadLocation, Settings};
-
let focus_handle = self.focus_handle(cx);
- let has_git_repo = self.project_has_git_repository(cx);
- let is_via_collab = self.project.read(cx).is_via_collab();
- let fs = self.fs.clone();
let is_creating = matches!(
self.worktree_creation_status,
Some(WorktreeCreationStatus::Creating)
);
- let current_target = self.start_thread_in;
let trigger_label = self.start_thread_in.label();
- let new_thread_location = AgentSettings::get_global(cx).new_thread_location;
- let is_local_default = new_thread_location == NewThreadLocation::LocalProject;
- let is_new_worktree_default = new_thread_location == NewThreadLocation::NewWorktree;
-
let icon = if self.start_thread_in_menu_handle.is_deployed() {
IconName::ChevronUp
} else {
@@ -3178,13 +3358,9 @@ impl AgentPanel {
.end_icon(Icon::new(icon).size(IconSize::XSmall).color(Color::Muted))
.disabled(is_creating);
- let dock_position = AgentSettings::get_global(cx).dock;
- let documentation_side = match dock_position {
- settings::DockPosition::Left => DocumentationSide::Right,
- settings::DockPosition::Bottom | settings::DockPosition::Right => {
- DocumentationSide::Left
- }
- };
+ let project = self.project.clone();
+ let current_target = self.start_thread_in.clone();
+ let fs = self.fs.clone();
PopoverMenu::new("thread-target-selector")
.trigger_with_tooltip(trigger_button, {
@@ -3198,89 +3374,66 @@ impl AgentPanel {
}
})
.menu(move |window, cx| {
- let is_local_selected = current_target == StartThreadIn::LocalProject;
- let is_new_worktree_selected = current_target == StartThreadIn::NewWorktree;
let fs = fs.clone();
+ Some(cx.new(|cx| {
+ ThreadWorktreePicker::new(project.clone(), ¤t_target, fs, window, cx)
+ }))
+ })
+ .with_handle(self.start_thread_in_menu_handle.clone())
+ .anchor(Corner::TopLeft)
+ .offset(gpui::Point {
+ x: px(1.0),
+ y: px(1.0),
+ })
+ }
- Some(ContextMenu::build(window, cx, move |menu, _window, _cx| {
- let new_worktree_disabled = !has_git_repo || is_via_collab;
+ fn render_new_worktree_branch_selector(&self, cx: &mut Context<Self>) -> impl IntoElement {
+ let is_creating = matches!(
+ self.worktree_creation_status,
+ Some(WorktreeCreationStatus::Creating)
+ );
+ let default_branch_label = if self.project.read(cx).repositories(cx).len() > 1 {
+ SharedString::from("From: current branches")
+ } else {
+ self.project
+ .read(cx)
+ .active_repository(cx)
+ .and_then(|repo| {
+ repo.read(cx)
+ .branch
+ .as_ref()
+ .map(|branch| SharedString::from(format!("From: {}", branch.name())))
+ })
+ .unwrap_or_else(|| SharedString::from("From: HEAD"))
+ };
+ let trigger_label = self
+ .start_thread_in
+ .worktree_branch_label(default_branch_label)
+ .unwrap_or_else(|| SharedString::from("From: HEAD"));
+ let icon = if self.thread_branch_menu_handle.is_deployed() {
+ IconName::ChevronUp
+ } else {
+ IconName::ChevronDown
+ };
+ let trigger_button = Button::new("thread-branch-trigger", trigger_label)
+ .start_icon(
+ Icon::new(IconName::GitBranch)
+ .size(IconSize::Small)
+ .color(Color::Muted),
+ )
+ .end_icon(Icon::new(icon).size(IconSize::XSmall).color(Color::Muted))
+ .disabled(is_creating);
+ let project = self.project.clone();
+ let current_target = self.start_thread_in.clone();
- menu.header("Start Thread Inβ¦")
- .item(
- ContextMenuEntry::new("Current Worktree")
- .toggleable(IconPosition::End, is_local_selected)
- .documentation_aside(documentation_side, move |_| {
- HoldForDefault::new(is_local_default)
- .more_content(false)
- .into_any_element()
- })
- .handler({
- let fs = fs.clone();
- move |window, cx| {
- if window.modifiers().secondary() {
- update_settings_file(fs.clone(), cx, |settings, _| {
- settings
- .agent
- .get_or_insert_default()
- .set_new_thread_location(
- NewThreadLocation::LocalProject,
- );
- });
- }
- window.dispatch_action(
- Box::new(StartThreadIn::LocalProject),
- cx,
- );
- }
- }),
- )
- .item({
- let entry = ContextMenuEntry::new("New Git Worktree")
- .toggleable(IconPosition::End, is_new_worktree_selected)
- .disabled(new_worktree_disabled)
- .handler({
- let fs = fs.clone();
- move |window, cx| {
- if window.modifiers().secondary() {
- update_settings_file(fs.clone(), cx, |settings, _| {
- settings
- .agent
- .get_or_insert_default()
- .set_new_thread_location(
- NewThreadLocation::NewWorktree,
- );
- });
- }
- window.dispatch_action(
- Box::new(StartThreadIn::NewWorktree),
- cx,
- );
- }
- });
-
- if new_worktree_disabled {
- entry.documentation_aside(documentation_side, move |_| {
- let reason = if !has_git_repo {
- "No git repository found in this project."
- } else {
- "Not available for remote/collab projects yet."
- };
- Label::new(reason)
- .color(Color::Muted)
- .size(LabelSize::Small)
- .into_any_element()
- })
- } else {
- entry.documentation_aside(documentation_side, move |_| {
- HoldForDefault::new(is_new_worktree_default)
- .more_content(false)
- .into_any_element()
- })
- }
- })
+ PopoverMenu::new("thread-branch-selector")
+ .trigger_with_tooltip(trigger_button, Tooltip::text("Choose Worktree Branchβ¦"))
+ .menu(move |window, cx| {
+ Some(cx.new(|cx| {
+ ThreadBranchPicker::new(project.clone(), ¤t_target, window, cx)
}))
})
- .with_handle(self.start_thread_in_menu_handle.clone())
+ .with_handle(self.thread_branch_menu_handle.clone())
.anchor(Corner::TopLeft)
.offset(gpui::Point {
x: px(1.0),
@@ -3549,21 +3702,37 @@ impl AgentPanel {
);
let is_full_screen = self.is_zoomed(window, cx);
+ let full_screen_button = if is_full_screen {
+ IconButton::new("disable-full-screen", IconName::Minimize)
+ .icon_size(IconSize::Small)
+ .tooltip(move |_, cx| Tooltip::for_action("Disable Full Screen", &ToggleZoom, cx))
+ .on_click(cx.listener(move |this, _, window, cx| {
+ this.toggle_zoom(&ToggleZoom, window, cx);
+ }))
+ } else {
+ IconButton::new("enable-full-screen", IconName::Maximize)
+ .icon_size(IconSize::Small)
+ .tooltip(move |_, cx| Tooltip::for_action("Enable Full Screen", &ToggleZoom, cx))
+ .on_click(cx.listener(move |this, _, window, cx| {
+ this.toggle_zoom(&ToggleZoom, window, cx);
+ }))
+ };
let use_v2_empty_toolbar = has_v2_flag && is_empty_state && !is_in_history_or_config;
+ let max_content_width = AgentSettings::get_global(cx).max_content_width;
+
let base_container = h_flex()
- .id("agent-panel-toolbar")
- .h(Tab::container_height(cx))
- .max_w_full()
+ .size_full()
+ // TODO: This is only until we remove Agent settings from the panel.
+ .when(!is_in_history_or_config, |this| {
+ this.max_w(max_content_width).mx_auto()
+ })
.flex_none()
.justify_between()
- .gap_2()
- .bg(cx.theme().colors().tab_bar_background)
- .border_b_1()
- .border_color(cx.theme().colors().border);
+ .gap_2();
- if use_v2_empty_toolbar {
+ let toolbar_content = if use_v2_empty_toolbar {
let (chevron_icon, icon_color, label_color) =
if self.new_thread_menu_handle.is_deployed() {
(IconName::ChevronUp, Color::Accent, Color::Accent)
@@ -3621,6 +3790,14 @@ impl AgentPanel {
.when(
has_visible_worktrees && self.project_has_git_repository(cx),
|this| this.child(self.render_start_thread_in_selector(cx)),
+ )
+ .when(
+ has_v2_flag
+ && matches!(
+ self.start_thread_in,
+ StartThreadIn::NewWorktree { .. }
+ ),
+ |this| this.child(self.render_new_worktree_branch_selector(cx)),
),
)
.child(
@@ -3637,20 +3814,7 @@ impl AgentPanel {
cx,
))
})
- .when(is_full_screen, |this| {
- this.child(
- IconButton::new("disable-full-screen", IconName::Minimize)
- .icon_size(IconSize::Small)
- .tooltip(move |_, cx| {
- Tooltip::for_action("Disable Full Screen", &ToggleZoom, cx)
- })
- .on_click({
- cx.listener(move |_, _, window, cx| {
- window.dispatch_action(ToggleZoom.boxed_clone(), cx);
- })
- }),
- )
- })
+ .child(full_screen_button)
.child(self.render_panel_options_menu(window, cx)),
)
.into_any_element()
@@ -3703,24 +3867,21 @@ impl AgentPanel {
cx,
))
})
- .when(is_full_screen, |this| {
- this.child(
- IconButton::new("disable-full-screen", IconName::Minimize)
- .icon_size(IconSize::Small)
- .tooltip(move |_, cx| {
- Tooltip::for_action("Disable Full Screen", &ToggleZoom, cx)
- })
- .on_click({
- cx.listener(move |_, _, window, cx| {
- window.dispatch_action(ToggleZoom.boxed_clone(), cx);
- })
- }),
- )
- })
+ .child(full_screen_button)
.child(self.render_panel_options_menu(window, cx)),
)
.into_any_element()
- }
+ };
+
+ h_flex()
+ .id("agent-panel-toolbar")
+ .h(Tab::container_height(cx))
+ .flex_shrink_0()
+ .max_w_full()
+ .bg(cx.theme().colors().tab_bar_background)
+ .border_b_1()
+ .border_color(cx.theme().colors().border)
+ .child(toolbar_content)
}
fn render_worktree_creation_status(&self, cx: &mut Context<Self>) -> Option<AnyElement> {
@@ -5265,13 +5426,23 @@ mod tests {
// Change thread target to NewWorktree.
panel.update_in(cx, |panel, window, cx| {
- panel.set_start_thread_in(&StartThreadIn::NewWorktree, window, cx);
+ panel.set_start_thread_in(
+ &StartThreadIn::NewWorktree {
+ worktree_name: None,
+ branch_target: NewWorktreeBranchTarget::default(),
+ },
+ window,
+ cx,
+ );
});
panel.read_with(cx, |panel, _cx| {
assert_eq!(
*panel.start_thread_in(),
- StartThreadIn::NewWorktree,
+ StartThreadIn::NewWorktree {
+ worktree_name: None,
+ branch_target: NewWorktreeBranchTarget::default(),
+ },
"thread target should be NewWorktree after set_thread_target"
);
});
@@ -5289,7 +5460,10 @@ mod tests {
loaded_panel.read_with(cx, |panel, _cx| {
assert_eq!(
*panel.start_thread_in(),
- StartThreadIn::NewWorktree,
+ StartThreadIn::NewWorktree {
+ worktree_name: None,
+ branch_target: NewWorktreeBranchTarget::default(),
+ },
"thread target should survive serialization round-trip"
);
});
@@ -5420,6 +5594,53 @@ mod tests {
);
}
+ #[test]
+ fn test_resolve_worktree_branch_target() {
+ let existing_branches = HashSet::from_iter([
+ "main".to_string(),
+ "feature".to_string(),
+ "origin/main".to_string(),
+ ]);
+
+ let resolved = AgentPanel::resolve_worktree_branch_target(
+ &NewWorktreeBranchTarget::CreateBranch {
+ name: "new-branch".to_string(),
+ from_ref: Some("main".to_string()),
+ },
+ &existing_branches,
+ &HashSet::from_iter(["main".to_string()]),
+ )
+ .unwrap();
+ assert_eq!(
+ resolved,
+ ("new-branch".to_string(), false, Some("main".to_string()))
+ );
+
+ let resolved = AgentPanel::resolve_worktree_branch_target(
+ &NewWorktreeBranchTarget::ExistingBranch {
+ name: "feature".to_string(),
+ },
+ &existing_branches,
+ &HashSet::default(),
+ )
+ .unwrap();
+ assert_eq!(resolved, ("feature".to_string(), true, None));
+
+ let resolved = AgentPanel::resolve_worktree_branch_target(
+ &NewWorktreeBranchTarget::ExistingBranch {
+ name: "main".to_string(),
+ },
+ &existing_branches,
+ &HashSet::from_iter(["main".to_string()]),
+ )
+ .unwrap();
+ assert_eq!(resolved.1, false);
+ assert_eq!(resolved.2, Some("main".to_string()));
+ assert_ne!(resolved.0, "main");
+ assert!(existing_branches.contains("main"));
+ assert!(!existing_branches.contains(&resolved.0));
+ }
+
#[gpui::test]
async fn test_worktree_creation_preserves_selected_agent(cx: &mut TestAppContext) {
init_test(cx);
@@ -382,7 +382,7 @@ impl AgentRegistryPage {
self.install_button(agent, install_status, supports_current_platform, cx);
let repository_button = agent.repository().map(|repository| {
- let repository_for_tooltip: SharedString = repository.to_string().into();
+ let repository_for_tooltip = repository.clone();
let repository_for_click = repository.to_string();
IconButton::new(
@@ -28,13 +28,16 @@ mod terminal_codegen;
mod terminal_inline_assistant;
#[cfg(any(test, feature = "test-support"))]
pub mod test_support;
+mod thread_branch_picker;
mod thread_history;
mod thread_history_view;
mod thread_import;
pub mod thread_metadata_store;
+mod thread_worktree_picker;
pub mod threads_archive_view;
mod ui;
+use std::path::PathBuf;
use std::rc::Rc;
use std::sync::Arc;
@@ -314,16 +317,42 @@ impl Agent {
}
}
+/// Describes which branch to use when creating a new git worktree.
+#[derive(Clone, Debug, Default, PartialEq, Eq, Serialize, Deserialize, JsonSchema)]
+#[serde(rename_all = "snake_case", tag = "kind")]
+pub enum NewWorktreeBranchTarget {
+ /// Create a new randomly named branch from the current HEAD.
+ /// Will match worktree name if the newly created worktree was also randomly named.
+ #[default]
+ CurrentBranch,
+ /// Check out an existing branch, or create a new branch from it if it's
+ /// already occupied by another worktree.
+ ExistingBranch { name: String },
+ /// Create a new branch with an explicit name, optionally from a specific ref.
+ CreateBranch {
+ name: String,
+ #[serde(default)]
+ from_ref: Option<String>,
+ },
+}
+
/// Sets where new threads will run.
-#[derive(
- Clone, Copy, Debug, Default, PartialEq, Eq, Serialize, Deserialize, JsonSchema, Action,
-)]
+#[derive(Clone, Debug, Default, PartialEq, Eq, Serialize, Deserialize, JsonSchema, Action)]
#[action(namespace = agent)]
#[serde(rename_all = "snake_case", tag = "kind")]
pub enum StartThreadIn {
#[default]
LocalProject,
- NewWorktree,
+ NewWorktree {
+ /// When this is None, Zed will randomly generate a worktree name
+ /// otherwise, the provided name will be used.
+ #[serde(default)]
+ worktree_name: Option<String>,
+ #[serde(default)]
+ branch_target: NewWorktreeBranchTarget,
+ },
+ /// A linked worktree that already exists on disk.
+ LinkedWorktree { path: PathBuf, display_name: String },
}
/// Content to initialize new external agent with.
@@ -495,7 +524,6 @@ pub fn init(
defaults.collaboration_panel.get_or_insert_default().dock =
Some(DockPosition::Right);
defaults.git_panel.get_or_insert_default().dock = Some(DockPosition::Right);
- defaults.notification_panel.get_or_insert_default().button = Some(false);
} else {
defaults.agent.get_or_insert_default().dock = Some(DockPosition::Right);
defaults.project_panel.get_or_insert_default().dock = Some(DockSide::Left);
@@ -503,7 +531,6 @@ pub fn init(
defaults.collaboration_panel.get_or_insert_default().dock =
Some(DockPosition::Left);
defaults.git_panel.get_or_insert_default().dock = Some(DockPosition::Left);
- defaults.notification_panel.get_or_insert_default().button = Some(true);
}
});
});
@@ -713,6 +740,7 @@ mod tests {
flexible: true,
default_width: px(300.),
default_height: px(600.),
+ max_content_width: px(850.),
default_model: None,
inline_assistant_model: None,
inline_assistant_use_streaming_tools: false,
@@ -869,7 +869,10 @@ impl ThreadView {
.upgrade()
.and_then(|workspace| workspace.read(cx).panel::<AgentPanel>(cx))
.is_some_and(|panel| {
- panel.read(cx).start_thread_in() == &StartThreadIn::NewWorktree
+ !matches!(
+ panel.read(cx).start_thread_in(),
+ StartThreadIn::LocalProject
+ )
});
if intercept_first_send {
@@ -3011,14 +3014,12 @@ impl ThreadView {
let is_done = thread.read(cx).status() == ThreadStatus::Idle;
let is_canceled_or_failed = self.is_subagent_canceled_or_failed(cx);
+ let max_content_width = AgentSettings::get_global(cx).max_content_width;
+
Some(
h_flex()
- .h(Tab::container_height(cx))
- .pl_2()
- .pr_1p5()
.w_full()
- .justify_between()
- .gap_1()
+ .h(Tab::container_height(cx))
.border_b_1()
.when(is_done && is_canceled_or_failed, |this| {
this.border_dashed()
@@ -3027,50 +3028,61 @@ impl ThreadView {
.bg(cx.theme().colors().editor_background.opacity(0.2))
.child(
h_flex()
- .flex_1()
- .gap_2()
+ .size_full()
+ .max_w(max_content_width)
+ .mx_auto()
+ .pl_2()
+ .pr_1()
+ .flex_shrink_0()
+ .justify_between()
+ .gap_1()
.child(
- Icon::new(IconName::ForwardArrowUp)
- .size(IconSize::Small)
- .color(Color::Muted),
+ h_flex()
+ .flex_1()
+ .gap_2()
+ .child(
+ Icon::new(IconName::ForwardArrowUp)
+ .size(IconSize::Small)
+ .color(Color::Muted),
+ )
+ .child(self.title_editor.clone())
+ .when(is_done && is_canceled_or_failed, |this| {
+ this.child(Icon::new(IconName::Close).color(Color::Error))
+ })
+ .when(is_done && !is_canceled_or_failed, |this| {
+ this.child(Icon::new(IconName::Check).color(Color::Success))
+ }),
)
- .child(self.title_editor.clone())
- .when(is_done && is_canceled_or_failed, |this| {
- this.child(Icon::new(IconName::Close).color(Color::Error))
- })
- .when(is_done && !is_canceled_or_failed, |this| {
- this.child(Icon::new(IconName::Check).color(Color::Success))
- }),
- )
- .child(
- h_flex()
- .gap_0p5()
- .when(!is_done, |this| {
- this.child(
- IconButton::new("stop_subagent", IconName::Stop)
- .icon_size(IconSize::Small)
- .icon_color(Color::Error)
- .tooltip(Tooltip::text("Stop Subagent"))
- .on_click(move |_, _, cx| {
- thread.update(cx, |thread, cx| {
- thread.cancel(cx).detach();
- });
- }),
- )
- })
.child(
- IconButton::new("minimize_subagent", IconName::Minimize)
- .icon_size(IconSize::Small)
- .tooltip(Tooltip::text("Minimize Subagent"))
- .on_click(move |_, window, cx| {
- let _ = server_view.update(cx, |server_view, cx| {
- server_view.navigate_to_session(
- parent_session_id.clone(),
- window,
- cx,
- );
- });
- }),
+ h_flex()
+ .gap_0p5()
+ .when(!is_done, |this| {
+ this.child(
+ IconButton::new("stop_subagent", IconName::Stop)
+ .icon_size(IconSize::Small)
+ .icon_color(Color::Error)
+ .tooltip(Tooltip::text("Stop Subagent"))
+ .on_click(move |_, _, cx| {
+ thread.update(cx, |thread, cx| {
+ thread.cancel(cx).detach();
+ });
+ }),
+ )
+ })
+ .child(
+ IconButton::new("minimize_subagent", IconName::Dash)
+ .icon_size(IconSize::Small)
+ .tooltip(Tooltip::text("Minimize Subagent"))
+ .on_click(move |_, window, cx| {
+ let _ = server_view.update(cx, |server_view, cx| {
+ server_view.navigate_to_session(
+ parent_session_id.clone(),
+ window,
+ cx,
+ );
+ });
+ }),
+ ),
),
),
)
@@ -3096,6 +3108,8 @@ impl ThreadView {
(IconName::Maximize, "Expand Message Editor")
};
+ let max_content_width = AgentSettings::get_global(cx).max_content_width;
+
v_flex()
.on_action(cx.listener(Self::expand_message_editor))
.p_2()
@@ -3110,73 +3124,80 @@ impl ThreadView {
})
.child(
v_flex()
- .relative()
- .size_full()
- .when(v2_empty_state, |this| this.flex_1())
- .pt_1()
- .pr_2p5()
- .child(self.message_editor.clone())
- .when(!v2_empty_state, |this| {
- this.child(
- h_flex()
- .absolute()
- .top_0()
- .right_0()
- .opacity(0.5)
- .hover(|this| this.opacity(1.0))
- .child(
- IconButton::new("toggle-height", expand_icon)
- .icon_size(IconSize::Small)
- .icon_color(Color::Muted)
- .tooltip({
- move |_window, cx| {
- Tooltip::for_action_in(
- expand_tooltip,
- &ExpandMessageEditor,
- &focus_handle,
- cx,
- )
- }
- })
- .on_click(cx.listener(|this, _, window, cx| {
- this.expand_message_editor(
- &ExpandMessageEditor,
- window,
- cx,
- );
- })),
- ),
- )
- }),
- )
- .child(
- h_flex()
- .flex_none()
- .flex_wrap()
- .justify_between()
+ .flex_1()
+ .w_full()
+ .max_w(max_content_width)
+ .mx_auto()
.child(
- h_flex()
- .gap_0p5()
- .child(self.render_add_context_button(cx))
- .child(self.render_follow_toggle(cx))
- .children(self.render_fast_mode_control(cx))
- .children(self.render_thinking_control(cx)),
+ v_flex()
+ .relative()
+ .size_full()
+ .when(v2_empty_state, |this| this.flex_1())
+ .pt_1()
+ .pr_2p5()
+ .child(self.message_editor.clone())
+ .when(!v2_empty_state, |this| {
+ this.child(
+ h_flex()
+ .absolute()
+ .top_0()
+ .right_0()
+ .opacity(0.5)
+ .hover(|this| this.opacity(1.0))
+ .child(
+ IconButton::new("toggle-height", expand_icon)
+ .icon_size(IconSize::Small)
+ .icon_color(Color::Muted)
+ .tooltip({
+ move |_window, cx| {
+ Tooltip::for_action_in(
+ expand_tooltip,
+ &ExpandMessageEditor,
+ &focus_handle,
+ cx,
+ )
+ }
+ })
+ .on_click(cx.listener(|this, _, window, cx| {
+ this.expand_message_editor(
+ &ExpandMessageEditor,
+ window,
+ cx,
+ );
+ })),
+ ),
+ )
+ }),
)
.child(
h_flex()
- .gap_1()
- .children(self.render_token_usage(cx))
- .children(self.profile_selector.clone())
- .map(|this| {
- // Either config_options_view OR (mode_selector + model_selector)
- match self.config_options_view.clone() {
- Some(config_view) => this.child(config_view),
- None => this
- .children(self.mode_selector.clone())
- .children(self.model_selector.clone()),
- }
- })
- .child(self.render_send_button(cx)),
+ .flex_none()
+ .flex_wrap()
+ .justify_between()
+ .child(
+ h_flex()
+ .gap_0p5()
+ .child(self.render_add_context_button(cx))
+ .child(self.render_follow_toggle(cx))
+ .children(self.render_fast_mode_control(cx))
+ .children(self.render_thinking_control(cx)),
+ )
+ .child(
+ h_flex()
+ .gap_1()
+ .children(self.render_token_usage(cx))
+ .children(self.profile_selector.clone())
+ .map(|this| {
+ // Either config_options_view OR (mode_selector + model_selector)
+ match self.config_options_view.clone() {
+ Some(config_view) => this.child(config_view),
+ None => this
+ .children(self.mode_selector.clone())
+ .children(self.model_selector.clone()),
+ }
+ })
+ .child(self.render_send_button(cx)),
+ ),
),
)
.into_any()
@@ -8556,8 +8577,12 @@ impl Render for ThreadView {
let has_messages = self.list_state.item_count() > 0;
let v2_empty_state = cx.has_flag::<AgentV2FeatureFlag>() && !has_messages;
+ let max_content_width = AgentSettings::get_global(cx).max_content_width;
+
let conversation = v_flex()
- .when(!v2_empty_state, |this| this.flex_1())
+ .mx_auto()
+ .max_w(max_content_width)
+ .when(!v2_empty_state, |this| this.flex_1().size_full())
.map(|this| {
let this = this.when(self.resumed_without_history, |this| {
this.child(Self::render_resume_notice(cx))
@@ -18,7 +18,7 @@ use gpui::{
use http_client::{AsyncBody, HttpClientWithUrl};
use itertools::Either;
use language::Buffer;
-use language_model::LanguageModelImage;
+use language_model::{LanguageModelImage, LanguageModelImageExt};
use multi_buffer::MultiBufferRow;
use postage::stream::Stream as _;
use project::{Project, ProjectItem, ProjectPath, Worktree};
@@ -0,0 +1,695 @@
+use std::collections::{HashMap, HashSet};
+
+use collections::HashSet as CollectionsHashSet;
+use std::path::PathBuf;
+use std::sync::Arc;
+
+use fuzzy::StringMatchCandidate;
+use git::repository::Branch as GitBranch;
+use gpui::{
+ App, Context, DismissEvent, Entity, EventEmitter, FocusHandle, Focusable, IntoElement,
+ ParentElement, Render, SharedString, Styled, Task, Window, rems,
+};
+use picker::{Picker, PickerDelegate, PickerEditorPosition};
+use project::Project;
+use ui::{
+ HighlightedLabel, Icon, IconName, Label, LabelCommon, ListItem, ListItemSpacing, Tooltip,
+ prelude::*,
+};
+use util::ResultExt as _;
+
+use crate::{NewWorktreeBranchTarget, StartThreadIn};
+
+pub(crate) struct ThreadBranchPicker {
+ picker: Entity<Picker<ThreadBranchPickerDelegate>>,
+ focus_handle: FocusHandle,
+ _subscription: gpui::Subscription,
+}
+
+impl ThreadBranchPicker {
+ pub fn new(
+ project: Entity<Project>,
+ current_target: &StartThreadIn,
+ window: &mut Window,
+ cx: &mut Context<Self>,
+ ) -> Self {
+ let project_worktree_paths: HashSet<PathBuf> = project
+ .read(cx)
+ .visible_worktrees(cx)
+ .map(|worktree| worktree.read(cx).abs_path().to_path_buf())
+ .collect();
+
+ let has_multiple_repositories = project.read(cx).repositories(cx).len() > 1;
+ let current_branch_name = project
+ .read(cx)
+ .active_repository(cx)
+ .and_then(|repo| {
+ repo.read(cx)
+ .branch
+ .as_ref()
+ .map(|branch| branch.name().to_string())
+ })
+ .unwrap_or_else(|| "HEAD".to_string());
+
+ let repository = if has_multiple_repositories {
+ None
+ } else {
+ project.read(cx).active_repository(cx)
+ };
+ let branches_request = repository
+ .clone()
+ .map(|repo| repo.update(cx, |repo, _| repo.branches()));
+ let default_branch_request = repository
+ .clone()
+ .map(|repo| repo.update(cx, |repo, _| repo.default_branch(false)));
+ let worktrees_request = repository.map(|repo| repo.update(cx, |repo, _| repo.worktrees()));
+
+ let (worktree_name, branch_target) = match current_target {
+ StartThreadIn::NewWorktree {
+ worktree_name,
+ branch_target,
+ } => (worktree_name.clone(), branch_target.clone()),
+ _ => (None, NewWorktreeBranchTarget::default()),
+ };
+
+ let delegate = ThreadBranchPickerDelegate {
+ matches: vec![ThreadBranchEntry::CurrentBranch],
+ all_branches: None,
+ occupied_branches: None,
+ selected_index: 0,
+ worktree_name,
+ branch_target,
+ project_worktree_paths,
+ current_branch_name,
+ default_branch_name: None,
+ has_multiple_repositories,
+ };
+
+ let picker = cx.new(|cx| {
+ Picker::list(delegate, window, cx)
+ .list_measure_all()
+ .modal(false)
+ .max_height(Some(rems(20.).into()))
+ });
+
+ let focus_handle = picker.focus_handle(cx);
+
+ if let (Some(branches_request), Some(default_branch_request), Some(worktrees_request)) =
+ (branches_request, default_branch_request, worktrees_request)
+ {
+ let picker_handle = picker.downgrade();
+ cx.spawn_in(window, async move |_this, cx| {
+ let branches = branches_request.await??;
+ let default_branch = default_branch_request.await.ok().and_then(Result::ok).flatten();
+ let worktrees = worktrees_request.await??;
+
+ let remote_upstreams: CollectionsHashSet<_> = branches
+ .iter()
+ .filter_map(|branch| {
+ branch
+ .upstream
+ .as_ref()
+ .filter(|upstream| upstream.is_remote())
+ .map(|upstream| upstream.ref_name.clone())
+ })
+ .collect();
+
+ let mut occupied_branches = HashMap::new();
+ for worktree in worktrees {
+ let Some(branch_name) = worktree.branch_name().map(ToOwned::to_owned) else {
+ continue;
+ };
+
+ let reason = if picker_handle
+ .read_with(cx, |picker, _| {
+ picker
+ .delegate
+ .project_worktree_paths
+ .contains(&worktree.path)
+ })
+ .unwrap_or(false)
+ {
+ format!(
+ "This branch is already checked out in the current project worktree at {}.",
+ worktree.path.display()
+ )
+ } else {
+ format!(
+ "This branch is already checked out in a linked worktree at {}.",
+ worktree.path.display()
+ )
+ };
+
+ occupied_branches.insert(branch_name, reason);
+ }
+
+ let mut all_branches: Vec<_> = branches
+ .into_iter()
+ .filter(|branch| !remote_upstreams.contains(&branch.ref_name))
+ .collect();
+ all_branches.sort_by_key(|branch| {
+ (
+ branch.is_remote(),
+ !branch.is_head,
+ branch
+ .most_recent_commit
+ .as_ref()
+ .map(|commit| 0 - commit.commit_timestamp),
+ )
+ });
+
+ picker_handle.update_in(cx, |picker, window, cx| {
+ picker.delegate.all_branches = Some(all_branches);
+ picker.delegate.occupied_branches = Some(occupied_branches);
+ picker.delegate.default_branch_name = default_branch.map(|branch| branch.to_string());
+ picker.refresh(window, cx);
+ })?;
+
+ anyhow::Ok(())
+ })
+ .detach_and_log_err(cx);
+ }
+
+ let subscription = cx.subscribe(&picker, |_, _, _, cx| {
+ cx.emit(DismissEvent);
+ });
+
+ Self {
+ picker,
+ focus_handle,
+ _subscription: subscription,
+ }
+ }
+}
+
+impl Focusable for ThreadBranchPicker {
+ fn focus_handle(&self, _cx: &App) -> FocusHandle {
+ self.focus_handle.clone()
+ }
+}
+
+impl EventEmitter<DismissEvent> for ThreadBranchPicker {}
+
+impl Render for ThreadBranchPicker {
+ fn render(&mut self, _window: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
+ v_flex()
+ .w(rems(22.))
+ .elevation_3(cx)
+ .child(self.picker.clone())
+ .on_mouse_down_out(cx.listener(|_, _, _, cx| {
+ cx.emit(DismissEvent);
+ }))
+ }
+}
+
+#[derive(Clone)]
+enum ThreadBranchEntry {
+ CurrentBranch,
+ DefaultBranch,
+ ExistingBranch {
+ branch: GitBranch,
+ positions: Vec<usize>,
+ occupied_reason: Option<String>,
+ },
+ CreateNamed {
+ name: String,
+ },
+}
+
+pub(crate) struct ThreadBranchPickerDelegate {
+ matches: Vec<ThreadBranchEntry>,
+ all_branches: Option<Vec<GitBranch>>,
+ occupied_branches: Option<HashMap<String, String>>,
+ selected_index: usize,
+ worktree_name: Option<String>,
+ branch_target: NewWorktreeBranchTarget,
+ project_worktree_paths: HashSet<PathBuf>,
+ current_branch_name: String,
+ default_branch_name: Option<String>,
+ has_multiple_repositories: bool,
+}
+
+impl ThreadBranchPickerDelegate {
+ fn new_worktree_action(&self, branch_target: NewWorktreeBranchTarget) -> StartThreadIn {
+ StartThreadIn::NewWorktree {
+ worktree_name: self.worktree_name.clone(),
+ branch_target,
+ }
+ }
+
+ fn selected_entry_name(&self) -> Option<&str> {
+ match &self.branch_target {
+ NewWorktreeBranchTarget::CurrentBranch => None,
+ NewWorktreeBranchTarget::ExistingBranch { name } => Some(name),
+ NewWorktreeBranchTarget::CreateBranch {
+ from_ref: Some(from_ref),
+ ..
+ } => Some(from_ref),
+ NewWorktreeBranchTarget::CreateBranch { name, .. } => Some(name),
+ }
+ }
+
+ fn prefer_create_entry(&self) -> bool {
+ matches!(
+ &self.branch_target,
+ NewWorktreeBranchTarget::CreateBranch { from_ref: None, .. }
+ )
+ }
+
+ fn fixed_matches(&self) -> Vec<ThreadBranchEntry> {
+ let mut matches = vec![ThreadBranchEntry::CurrentBranch];
+ if !self.has_multiple_repositories
+ && self
+ .default_branch_name
+ .as_ref()
+ .is_some_and(|default_branch_name| default_branch_name != &self.current_branch_name)
+ {
+ matches.push(ThreadBranchEntry::DefaultBranch);
+ }
+ matches
+ }
+
+ fn current_branch_label(&self) -> SharedString {
+ if self.has_multiple_repositories {
+ SharedString::from("New branch from: current branches")
+ } else {
+ SharedString::from(format!("New branch from: {}", self.current_branch_name))
+ }
+ }
+
+ fn default_branch_label(&self) -> Option<SharedString> {
+ let default_branch_name = self
+ .default_branch_name
+ .as_ref()
+ .filter(|name| *name != &self.current_branch_name)?;
+ let is_occupied = self
+ .occupied_branches
+ .as_ref()
+ .is_some_and(|occupied| occupied.contains_key(default_branch_name));
+ let prefix = if is_occupied {
+ "New branch from"
+ } else {
+ "From"
+ };
+ Some(SharedString::from(format!(
+ "{prefix}: {default_branch_name}"
+ )))
+ }
+
+ fn branch_label_prefix(&self, branch_name: &str) -> &'static str {
+ let is_occupied = self
+ .occupied_branches
+ .as_ref()
+ .is_some_and(|occupied| occupied.contains_key(branch_name));
+ if is_occupied {
+ "New branch from: "
+ } else {
+ "From: "
+ }
+ }
+
+ fn sync_selected_index(&mut self) {
+ let selected_entry_name = self.selected_entry_name().map(ToOwned::to_owned);
+ let prefer_create = self.prefer_create_entry();
+
+ if prefer_create {
+ if let Some(ref selected_entry_name) = selected_entry_name {
+ if let Some(index) = self.matches.iter().position(|entry| {
+ matches!(
+ entry,
+ ThreadBranchEntry::CreateNamed { name } if name == selected_entry_name
+ )
+ }) {
+ self.selected_index = index;
+ return;
+ }
+ }
+ } else if let Some(ref selected_entry_name) = selected_entry_name {
+ if selected_entry_name == &self.current_branch_name {
+ if let Some(index) = self
+ .matches
+ .iter()
+ .position(|entry| matches!(entry, ThreadBranchEntry::CurrentBranch))
+ {
+ self.selected_index = index;
+ return;
+ }
+ }
+
+ if self
+ .default_branch_name
+ .as_ref()
+ .is_some_and(|default_branch_name| default_branch_name == selected_entry_name)
+ {
+ if let Some(index) = self
+ .matches
+ .iter()
+ .position(|entry| matches!(entry, ThreadBranchEntry::DefaultBranch))
+ {
+ self.selected_index = index;
+ return;
+ }
+ }
+
+ if let Some(index) = self.matches.iter().position(|entry| {
+ matches!(
+ entry,
+ ThreadBranchEntry::ExistingBranch { branch, .. }
+ if branch.name() == selected_entry_name.as_str()
+ )
+ }) {
+ self.selected_index = index;
+ return;
+ }
+ }
+
+ if self.matches.len() > 1
+ && self
+ .matches
+ .iter()
+ .skip(1)
+ .all(|entry| matches!(entry, ThreadBranchEntry::CreateNamed { .. }))
+ {
+ self.selected_index = 1;
+ return;
+ }
+
+ self.selected_index = 0;
+ }
+}
+
+impl PickerDelegate for ThreadBranchPickerDelegate {
+ type ListItem = ListItem;
+
+ fn placeholder_text(&self, _window: &mut Window, _cx: &mut App) -> Arc<str> {
+ "Search branchesβ¦".into()
+ }
+
+ fn editor_position(&self) -> PickerEditorPosition {
+ PickerEditorPosition::Start
+ }
+
+ fn match_count(&self) -> usize {
+ self.matches.len()
+ }
+
+ fn selected_index(&self) -> usize {
+ self.selected_index
+ }
+
+ fn set_selected_index(
+ &mut self,
+ ix: usize,
+ _window: &mut Window,
+ _cx: &mut Context<Picker<Self>>,
+ ) {
+ self.selected_index = ix;
+ }
+
+ fn update_matches(
+ &mut self,
+ query: String,
+ window: &mut Window,
+ cx: &mut Context<Picker<Self>>,
+ ) -> Task<()> {
+ if self.has_multiple_repositories {
+ let mut matches = self.fixed_matches();
+
+ if query.is_empty() {
+ if let Some(name) = self.selected_entry_name().map(ToOwned::to_owned) {
+ if self.prefer_create_entry() {
+ matches.push(ThreadBranchEntry::CreateNamed { name });
+ }
+ }
+ } else {
+ matches.push(ThreadBranchEntry::CreateNamed {
+ name: query.replace(' ', "-"),
+ });
+ }
+
+ self.matches = matches;
+ self.sync_selected_index();
+ return Task::ready(());
+ }
+
+ let Some(all_branches) = self.all_branches.clone() else {
+ self.matches = self.fixed_matches();
+ self.selected_index = 0;
+ return Task::ready(());
+ };
+ let occupied_branches = self.occupied_branches.clone().unwrap_or_default();
+
+ if query.is_empty() {
+ let mut matches = self.fixed_matches();
+ for branch in all_branches.into_iter().filter(|branch| {
+ branch.name() != self.current_branch_name
+ && self
+ .default_branch_name
+ .as_ref()
+ .is_none_or(|default_branch_name| branch.name() != default_branch_name)
+ }) {
+ matches.push(ThreadBranchEntry::ExistingBranch {
+ occupied_reason: occupied_branches.get(branch.name()).cloned(),
+ branch,
+ positions: Vec::new(),
+ });
+ }
+
+ if let Some(selected_entry_name) = self.selected_entry_name().map(ToOwned::to_owned) {
+ let has_existing = matches.iter().any(|entry| {
+ matches!(
+ entry,
+ ThreadBranchEntry::ExistingBranch { branch, .. }
+ if branch.name() == selected_entry_name
+ )
+ });
+ if self.prefer_create_entry() && !has_existing {
+ matches.push(ThreadBranchEntry::CreateNamed {
+ name: selected_entry_name,
+ });
+ }
+ }
+
+ self.matches = matches;
+ self.sync_selected_index();
+ return Task::ready(());
+ }
+
+ let candidates: Vec<_> = all_branches
+ .iter()
+ .enumerate()
+ .map(|(ix, branch)| StringMatchCandidate::new(ix, branch.name()))
+ .collect();
+ let executor = cx.background_executor().clone();
+ let query_clone = query.clone();
+ let normalized_query = query.replace(' ', "-");
+
+ let task = cx.background_executor().spawn(async move {
+ fuzzy::match_strings(
+ &candidates,
+ &query_clone,
+ true,
+ true,
+ 10000,
+ &Default::default(),
+ executor,
+ )
+ .await
+ });
+
+ let all_branches_clone = all_branches;
+ cx.spawn_in(window, async move |picker, cx| {
+ let fuzzy_matches = task.await;
+
+ picker
+ .update_in(cx, |picker, _window, cx| {
+ let mut matches = picker.delegate.fixed_matches();
+
+ for candidate in &fuzzy_matches {
+ let branch = all_branches_clone[candidate.candidate_id].clone();
+ if branch.name() == picker.delegate.current_branch_name
+ || picker.delegate.default_branch_name.as_ref().is_some_and(
+ |default_branch_name| branch.name() == default_branch_name,
+ )
+ {
+ continue;
+ }
+ let occupied_reason = occupied_branches.get(branch.name()).cloned();
+ matches.push(ThreadBranchEntry::ExistingBranch {
+ branch,
+ positions: candidate.positions.clone(),
+ occupied_reason,
+ });
+ }
+
+ if fuzzy_matches.is_empty() {
+ matches.push(ThreadBranchEntry::CreateNamed {
+ name: normalized_query.clone(),
+ });
+ }
+
+ picker.delegate.matches = matches;
+ if let Some(index) =
+ picker.delegate.matches.iter().position(|entry| {
+ matches!(entry, ThreadBranchEntry::ExistingBranch { .. })
+ })
+ {
+ picker.delegate.selected_index = index;
+ } else if !fuzzy_matches.is_empty() {
+ picker.delegate.selected_index = 0;
+ } else if let Some(index) =
+ picker.delegate.matches.iter().position(|entry| {
+ matches!(entry, ThreadBranchEntry::CreateNamed { .. })
+ })
+ {
+ picker.delegate.selected_index = index;
+ } else {
+ picker.delegate.sync_selected_index();
+ }
+ cx.notify();
+ })
+ .log_err();
+ })
+ }
+
+ fn confirm(&mut self, _secondary: bool, window: &mut Window, cx: &mut Context<Picker<Self>>) {
+ let Some(entry) = self.matches.get(self.selected_index) else {
+ return;
+ };
+
+ match entry {
+ ThreadBranchEntry::CurrentBranch => {
+ window.dispatch_action(
+ Box::new(self.new_worktree_action(NewWorktreeBranchTarget::CurrentBranch)),
+ cx,
+ );
+ }
+ ThreadBranchEntry::DefaultBranch => {
+ let Some(default_branch_name) = self.default_branch_name.clone() else {
+ return;
+ };
+ window.dispatch_action(
+ Box::new(
+ self.new_worktree_action(NewWorktreeBranchTarget::ExistingBranch {
+ name: default_branch_name,
+ }),
+ ),
+ cx,
+ );
+ }
+ ThreadBranchEntry::ExistingBranch { branch, .. } => {
+ let branch_target = if branch.is_remote() {
+ let branch_name = branch
+ .ref_name
+ .as_ref()
+ .strip_prefix("refs/remotes/")
+ .and_then(|stripped| stripped.split_once('/').map(|(_, name)| name))
+ .unwrap_or(branch.name())
+ .to_string();
+ NewWorktreeBranchTarget::CreateBranch {
+ name: branch_name,
+ from_ref: Some(branch.name().to_string()),
+ }
+ } else {
+ NewWorktreeBranchTarget::ExistingBranch {
+ name: branch.name().to_string(),
+ }
+ };
+ window.dispatch_action(Box::new(self.new_worktree_action(branch_target)), cx);
+ }
+ ThreadBranchEntry::CreateNamed { name } => {
+ window.dispatch_action(
+ Box::new(
+ self.new_worktree_action(NewWorktreeBranchTarget::CreateBranch {
+ name: name.clone(),
+ from_ref: None,
+ }),
+ ),
+ cx,
+ );
+ }
+ }
+
+ cx.emit(DismissEvent);
+ }
+
+ fn dismissed(&mut self, _window: &mut Window, _cx: &mut Context<Picker<Self>>) {}
+
+ fn separators_after_indices(&self) -> Vec<usize> {
+ let fixed_count = self.fixed_matches().len();
+ if self.matches.len() > fixed_count {
+ vec![fixed_count - 1]
+ } else {
+ Vec::new()
+ }
+ }
+
+ fn render_match(
+ &self,
+ ix: usize,
+ selected: bool,
+ _window: &mut Window,
+ _cx: &mut Context<Picker<Self>>,
+ ) -> Option<Self::ListItem> {
+ let entry = self.matches.get(ix)?;
+
+ match entry {
+ ThreadBranchEntry::CurrentBranch => Some(
+ ListItem::new("current-branch")
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .start_slot(Icon::new(IconName::GitBranch).color(Color::Muted))
+ .child(Label::new(self.current_branch_label())),
+ ),
+ ThreadBranchEntry::DefaultBranch => Some(
+ ListItem::new("default-branch")
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .start_slot(Icon::new(IconName::GitBranch).color(Color::Muted))
+ .child(Label::new(self.default_branch_label()?)),
+ ),
+ ThreadBranchEntry::ExistingBranch {
+ branch,
+ positions,
+ occupied_reason,
+ } => {
+ let prefix = self.branch_label_prefix(branch.name());
+ let branch_name = branch.name().to_string();
+ let full_label = format!("{prefix}{branch_name}");
+ let adjusted_positions: Vec<usize> =
+ positions.iter().map(|&p| p + prefix.len()).collect();
+
+ let item = ListItem::new(SharedString::from(format!("branch-{ix}")))
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .start_slot(Icon::new(IconName::GitBranch).color(Color::Muted))
+ .child(HighlightedLabel::new(full_label, adjusted_positions).truncate());
+
+ Some(if let Some(reason) = occupied_reason.clone() {
+ item.tooltip(Tooltip::text(reason))
+ } else if branch.is_remote() {
+ item.tooltip(Tooltip::text(
+ "Create a new local branch from this remote branch",
+ ))
+ } else {
+ item
+ })
+ }
+ ThreadBranchEntry::CreateNamed { name } => Some(
+ ListItem::new("create-named-branch")
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .start_slot(Icon::new(IconName::Plus).color(Color::Accent))
+ .child(Label::new(format!("Create Branch: \"{name}\"β¦"))),
+ ),
+ }
+ }
+
+ fn no_matches_text(&self, _window: &mut Window, _cx: &mut App) -> Option<SharedString> {
+ None
+ }
+}
@@ -0,0 +1,485 @@
+use std::path::PathBuf;
+use std::sync::Arc;
+
+use agent_settings::AgentSettings;
+use fs::Fs;
+use fuzzy::StringMatchCandidate;
+use git::repository::Worktree as GitWorktree;
+use gpui::{
+ App, Context, DismissEvent, Entity, EventEmitter, FocusHandle, Focusable, IntoElement,
+ ParentElement, Render, SharedString, Styled, Task, Window, rems,
+};
+use picker::{Picker, PickerDelegate, PickerEditorPosition};
+use project::{Project, git_store::RepositoryId};
+use settings::{NewThreadLocation, Settings, update_settings_file};
+use ui::{
+ HighlightedLabel, Icon, IconName, Label, LabelCommon, ListItem, ListItemSpacing, Tooltip,
+ prelude::*,
+};
+use util::ResultExt as _;
+
+use crate::ui::HoldForDefault;
+use crate::{NewWorktreeBranchTarget, StartThreadIn};
+
+pub(crate) struct ThreadWorktreePicker {
+ picker: Entity<Picker<ThreadWorktreePickerDelegate>>,
+ focus_handle: FocusHandle,
+ _subscription: gpui::Subscription,
+}
+
+impl ThreadWorktreePicker {
+ pub fn new(
+ project: Entity<Project>,
+ current_target: &StartThreadIn,
+ fs: Arc<dyn Fs>,
+ window: &mut Window,
+ cx: &mut Context<Self>,
+ ) -> Self {
+ let project_worktree_paths: Vec<PathBuf> = project
+ .read(cx)
+ .visible_worktrees(cx)
+ .map(|wt| wt.read(cx).abs_path().to_path_buf())
+ .collect();
+
+ let preserved_branch_target = match current_target {
+ StartThreadIn::NewWorktree { branch_target, .. } => branch_target.clone(),
+ _ => NewWorktreeBranchTarget::default(),
+ };
+
+ let delegate = ThreadWorktreePickerDelegate {
+ matches: vec![
+ ThreadWorktreeEntry::CurrentWorktree,
+ ThreadWorktreeEntry::NewWorktree,
+ ],
+ all_worktrees: project
+ .read(cx)
+ .repositories(cx)
+ .iter()
+ .map(|(repo_id, repo)| (*repo_id, repo.read(cx).linked_worktrees.clone()))
+ .collect(),
+ project_worktree_paths,
+ selected_index: match current_target {
+ StartThreadIn::LocalProject => 0,
+ StartThreadIn::NewWorktree { .. } => 1,
+ _ => 0,
+ },
+ project: project.clone(),
+ preserved_branch_target,
+ fs,
+ };
+
+ let picker = cx.new(|cx| {
+ Picker::list(delegate, window, cx)
+ .list_measure_all()
+ .modal(false)
+ .max_height(Some(rems(20.).into()))
+ });
+
+ let subscription = cx.subscribe(&picker, |_, _, _, cx| {
+ cx.emit(DismissEvent);
+ });
+
+ Self {
+ focus_handle: picker.focus_handle(cx),
+ picker,
+ _subscription: subscription,
+ }
+ }
+}
+
+impl Focusable for ThreadWorktreePicker {
+ fn focus_handle(&self, _cx: &App) -> FocusHandle {
+ self.focus_handle.clone()
+ }
+}
+
+impl EventEmitter<DismissEvent> for ThreadWorktreePicker {}
+
+impl Render for ThreadWorktreePicker {
+ fn render(&mut self, _window: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
+ v_flex()
+ .w(rems(20.))
+ .elevation_3(cx)
+ .child(self.picker.clone())
+ .on_mouse_down_out(cx.listener(|_, _, _, cx| {
+ cx.emit(DismissEvent);
+ }))
+ }
+}
+
+#[derive(Clone)]
+enum ThreadWorktreeEntry {
+ CurrentWorktree,
+ NewWorktree,
+ LinkedWorktree {
+ worktree: GitWorktree,
+ positions: Vec<usize>,
+ },
+ CreateNamed {
+ name: String,
+ disabled_reason: Option<String>,
+ },
+}
+
+pub(crate) struct ThreadWorktreePickerDelegate {
+ matches: Vec<ThreadWorktreeEntry>,
+ all_worktrees: Vec<(RepositoryId, Arc<[GitWorktree]>)>,
+ project_worktree_paths: Vec<PathBuf>,
+ selected_index: usize,
+ preserved_branch_target: NewWorktreeBranchTarget,
+ project: Entity<Project>,
+ fs: Arc<dyn Fs>,
+}
+
+impl ThreadWorktreePickerDelegate {
+ fn new_worktree_action(&self, worktree_name: Option<String>) -> StartThreadIn {
+ StartThreadIn::NewWorktree {
+ worktree_name,
+ branch_target: self.preserved_branch_target.clone(),
+ }
+ }
+
+ fn sync_selected_index(&mut self) {
+ if let Some(index) = self
+ .matches
+ .iter()
+ .position(|entry| matches!(entry, ThreadWorktreeEntry::LinkedWorktree { .. }))
+ {
+ self.selected_index = index;
+ } else if let Some(index) = self
+ .matches
+ .iter()
+ .position(|entry| matches!(entry, ThreadWorktreeEntry::CreateNamed { .. }))
+ {
+ self.selected_index = index;
+ } else {
+ self.selected_index = 0;
+ }
+ }
+}
+
+impl PickerDelegate for ThreadWorktreePickerDelegate {
+ type ListItem = ListItem;
+
+ fn placeholder_text(&self, _window: &mut Window, _cx: &mut App) -> Arc<str> {
+ "Search or create worktreesβ¦".into()
+ }
+
+ fn editor_position(&self) -> PickerEditorPosition {
+ PickerEditorPosition::Start
+ }
+
+ fn match_count(&self) -> usize {
+ self.matches.len()
+ }
+
+ fn selected_index(&self) -> usize {
+ self.selected_index
+ }
+
+ fn set_selected_index(
+ &mut self,
+ ix: usize,
+ _window: &mut Window,
+ _cx: &mut Context<Picker<Self>>,
+ ) {
+ self.selected_index = ix;
+ }
+
+ fn separators_after_indices(&self) -> Vec<usize> {
+ if self.matches.len() > 2 {
+ vec![1]
+ } else {
+ Vec::new()
+ }
+ }
+
+ fn update_matches(
+ &mut self,
+ query: String,
+ window: &mut Window,
+ cx: &mut Context<Picker<Self>>,
+ ) -> Task<()> {
+ let has_multiple_repositories = self.all_worktrees.len() > 1;
+
+ let linked_worktrees: Vec<_> = if has_multiple_repositories {
+ Vec::new()
+ } else {
+ self.all_worktrees
+ .iter()
+ .flat_map(|(_, worktrees)| worktrees.iter())
+ .filter(|worktree| {
+ !self
+ .project_worktree_paths
+ .iter()
+ .any(|project_path| project_path == &worktree.path)
+ })
+ .cloned()
+ .collect()
+ };
+
+ let normalized_query = query.replace(' ', "-");
+ let has_named_worktree = self.all_worktrees.iter().any(|(_, worktrees)| {
+ worktrees
+ .iter()
+ .any(|worktree| worktree.display_name() == normalized_query)
+ });
+ let create_named_disabled_reason = if has_multiple_repositories {
+ Some("Cannot create a named worktree in a project with multiple repositories".into())
+ } else if has_named_worktree {
+ Some("A worktree with this name already exists".into())
+ } else {
+ None
+ };
+
+ let mut matches = vec![
+ ThreadWorktreeEntry::CurrentWorktree,
+ ThreadWorktreeEntry::NewWorktree,
+ ];
+
+ if query.is_empty() {
+ for worktree in &linked_worktrees {
+ matches.push(ThreadWorktreeEntry::LinkedWorktree {
+ worktree: worktree.clone(),
+ positions: Vec::new(),
+ });
+ }
+ } else if linked_worktrees.is_empty() {
+ matches.push(ThreadWorktreeEntry::CreateNamed {
+ name: normalized_query,
+ disabled_reason: create_named_disabled_reason,
+ });
+ } else {
+ let candidates: Vec<_> = linked_worktrees
+ .iter()
+ .enumerate()
+ .map(|(ix, worktree)| StringMatchCandidate::new(ix, worktree.display_name()))
+ .collect();
+
+ let executor = cx.background_executor().clone();
+ let query_clone = query.clone();
+
+ let task = cx.background_executor().spawn(async move {
+ fuzzy::match_strings(
+ &candidates,
+ &query_clone,
+ true,
+ true,
+ 10000,
+ &Default::default(),
+ executor,
+ )
+ .await
+ });
+
+ let linked_worktrees_clone = linked_worktrees;
+ return cx.spawn_in(window, async move |picker, cx| {
+ let fuzzy_matches = task.await;
+
+ picker
+ .update_in(cx, |picker, _window, cx| {
+ let mut new_matches = vec![
+ ThreadWorktreeEntry::CurrentWorktree,
+ ThreadWorktreeEntry::NewWorktree,
+ ];
+
+ for candidate in &fuzzy_matches {
+ new_matches.push(ThreadWorktreeEntry::LinkedWorktree {
+ worktree: linked_worktrees_clone[candidate.candidate_id].clone(),
+ positions: candidate.positions.clone(),
+ });
+ }
+
+ let has_exact_match = linked_worktrees_clone
+ .iter()
+ .any(|worktree| worktree.display_name() == query);
+
+ if !has_exact_match {
+ new_matches.push(ThreadWorktreeEntry::CreateNamed {
+ name: normalized_query.clone(),
+ disabled_reason: create_named_disabled_reason.clone(),
+ });
+ }
+
+ picker.delegate.matches = new_matches;
+ picker.delegate.sync_selected_index();
+
+ cx.notify();
+ })
+ .log_err();
+ });
+ }
+
+ self.matches = matches;
+ self.sync_selected_index();
+
+ Task::ready(())
+ }
+
+ fn confirm(&mut self, secondary: bool, window: &mut Window, cx: &mut Context<Picker<Self>>) {
+ let Some(entry) = self.matches.get(self.selected_index) else {
+ return;
+ };
+
+ match entry {
+ ThreadWorktreeEntry::CurrentWorktree => {
+ if secondary {
+ update_settings_file(self.fs.clone(), cx, |settings, _| {
+ settings
+ .agent
+ .get_or_insert_default()
+ .set_new_thread_location(NewThreadLocation::LocalProject);
+ });
+ }
+ window.dispatch_action(Box::new(StartThreadIn::LocalProject), cx);
+ }
+ ThreadWorktreeEntry::NewWorktree => {
+ if secondary {
+ update_settings_file(self.fs.clone(), cx, |settings, _| {
+ settings
+ .agent
+ .get_or_insert_default()
+ .set_new_thread_location(NewThreadLocation::NewWorktree);
+ });
+ }
+ window.dispatch_action(Box::new(self.new_worktree_action(None)), cx);
+ }
+ ThreadWorktreeEntry::LinkedWorktree { worktree, .. } => {
+ window.dispatch_action(
+ Box::new(StartThreadIn::LinkedWorktree {
+ path: worktree.path.clone(),
+ display_name: worktree.display_name().to_string(),
+ }),
+ cx,
+ );
+ }
+ ThreadWorktreeEntry::CreateNamed {
+ name,
+ disabled_reason: None,
+ } => {
+ window.dispatch_action(Box::new(self.new_worktree_action(Some(name.clone()))), cx);
+ }
+ ThreadWorktreeEntry::CreateNamed {
+ disabled_reason: Some(_),
+ ..
+ } => {
+ return;
+ }
+ }
+
+ cx.emit(DismissEvent);
+ }
+
+ fn dismissed(&mut self, _window: &mut Window, _cx: &mut Context<Picker<Self>>) {}
+
+ fn render_match(
+ &self,
+ ix: usize,
+ selected: bool,
+ _window: &mut Window,
+ cx: &mut Context<Picker<Self>>,
+ ) -> Option<Self::ListItem> {
+ let entry = self.matches.get(ix)?;
+ let project = self.project.read(cx);
+ let is_new_worktree_disabled =
+ project.repositories(cx).is_empty() || project.is_via_collab();
+ let new_thread_location = AgentSettings::get_global(cx).new_thread_location;
+ let is_local_default = new_thread_location == NewThreadLocation::LocalProject;
+ let is_new_worktree_default = new_thread_location == NewThreadLocation::NewWorktree;
+
+ match entry {
+ ThreadWorktreeEntry::CurrentWorktree => Some(
+ ListItem::new("current-worktree")
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .start_slot(Icon::new(IconName::Folder).color(Color::Muted))
+ .child(Label::new("Current Worktree"))
+ .end_slot(HoldForDefault::new(is_local_default).more_content(false))
+ .tooltip(Tooltip::text("Use the current project worktree")),
+ ),
+ ThreadWorktreeEntry::NewWorktree => {
+ let item = ListItem::new("new-worktree")
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .disabled(is_new_worktree_disabled)
+ .start_slot(
+ Icon::new(IconName::Plus).color(if is_new_worktree_disabled {
+ Color::Disabled
+ } else {
+ Color::Muted
+ }),
+ )
+ .child(
+ Label::new("New Git Worktree").color(if is_new_worktree_disabled {
+ Color::Disabled
+ } else {
+ Color::Default
+ }),
+ );
+
+ Some(if is_new_worktree_disabled {
+ item.tooltip(Tooltip::text("Requires a Git repository in the project"))
+ } else {
+ item.end_slot(HoldForDefault::new(is_new_worktree_default).more_content(false))
+ .tooltip(Tooltip::text("Start a thread in a new Git worktree"))
+ })
+ }
+ ThreadWorktreeEntry::LinkedWorktree {
+ worktree,
+ positions,
+ } => {
+ let display_name = worktree.display_name();
+ let first_line = display_name.lines().next().unwrap_or(display_name);
+ let positions: Vec<_> = positions
+ .iter()
+ .copied()
+ .filter(|&pos| pos < first_line.len())
+ .collect();
+
+ Some(
+ ListItem::new(SharedString::from(format!("linked-worktree-{ix}")))
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .start_slot(Icon::new(IconName::GitWorktree).color(Color::Muted))
+ .child(HighlightedLabel::new(first_line.to_owned(), positions).truncate()),
+ )
+ }
+ ThreadWorktreeEntry::CreateNamed {
+ name,
+ disabled_reason,
+ } => {
+ let is_disabled = disabled_reason.is_some();
+ let item = ListItem::new("create-named-worktree")
+ .inset(true)
+ .spacing(ListItemSpacing::Sparse)
+ .toggle_state(selected)
+ .disabled(is_disabled)
+ .start_slot(Icon::new(IconName::Plus).color(if is_disabled {
+ Color::Disabled
+ } else {
+ Color::Accent
+ }))
+ .child(Label::new(format!("Create Worktree: \"{name}\"β¦")).color(
+ if is_disabled {
+ Color::Disabled
+ } else {
+ Color::Default
+ },
+ ));
+
+ Some(if let Some(reason) = disabled_reason.clone() {
+ item.tooltip(Tooltip::text(reason))
+ } else {
+ item
+ })
+ }
+ }
+ }
+
+ fn no_matches_text(&self, _window: &mut Window, _cx: &mut App) -> Option<SharedString> {
+ None
+ }
+}
@@ -1236,6 +1236,7 @@ impl PickerDelegate for ProjectPickerDelegate {
},
match_label: HighlightedMatch::join(match_labels.into_iter().flatten(), ", "),
paths: Vec::new(),
+ active: false,
};
Some(
@@ -18,12 +18,16 @@ path = "src/anthropic.rs"
[dependencies]
anyhow.workspace = true
chrono.workspace = true
+collections.workspace = true
futures.workspace = true
http_client.workspace = true
+language_model_core.workspace = true
+log.workspace = true
schemars = { workspace = true, optional = true }
serde.workspace = true
serde_json.workspace = true
strum.workspace = true
thiserror.workspace = true
+tiktoken-rs.workspace = true
@@ -12,6 +12,7 @@ use strum::{EnumIter, EnumString};
use thiserror::Error;
pub mod batches;
+pub mod completion;
pub const ANTHROPIC_API_URL: &str = "https://api.anthropic.com";
@@ -1026,6 +1027,89 @@ pub async fn count_tokens(
}
}
+// -- Conversions from/to `language_model_core` types --
+
+impl From<language_model_core::Speed> for Speed {
+ fn from(speed: language_model_core::Speed) -> Self {
+ match speed {
+ language_model_core::Speed::Standard => Speed::Standard,
+ language_model_core::Speed::Fast => Speed::Fast,
+ }
+ }
+}
+
+impl From<AnthropicError> for language_model_core::LanguageModelCompletionError {
+ fn from(error: AnthropicError) -> Self {
+ let provider = language_model_core::ANTHROPIC_PROVIDER_NAME;
+ match error {
+ AnthropicError::SerializeRequest(error) => Self::SerializeRequest { provider, error },
+ AnthropicError::BuildRequestBody(error) => Self::BuildRequestBody { provider, error },
+ AnthropicError::HttpSend(error) => Self::HttpSend { provider, error },
+ AnthropicError::DeserializeResponse(error) => {
+ Self::DeserializeResponse { provider, error }
+ }
+ AnthropicError::ReadResponse(error) => Self::ApiReadResponseError { provider, error },
+ AnthropicError::HttpResponseError {
+ status_code,
+ message,
+ } => Self::HttpResponseError {
+ provider,
+ status_code,
+ message,
+ },
+ AnthropicError::RateLimit { retry_after } => Self::RateLimitExceeded {
+ provider,
+ retry_after: Some(retry_after),
+ },
+ AnthropicError::ServerOverloaded { retry_after } => Self::ServerOverloaded {
+ provider,
+ retry_after,
+ },
+ AnthropicError::ApiError(api_error) => api_error.into(),
+ }
+ }
+}
+
+impl From<ApiError> for language_model_core::LanguageModelCompletionError {
+ fn from(error: ApiError) -> Self {
+ use ApiErrorCode::*;
+ let provider = language_model_core::ANTHROPIC_PROVIDER_NAME;
+ match error.code() {
+ Some(code) => match code {
+ InvalidRequestError => Self::BadRequestFormat {
+ provider,
+ message: error.message,
+ },
+ AuthenticationError => Self::AuthenticationError {
+ provider,
+ message: error.message,
+ },
+ PermissionError => Self::PermissionError {
+ provider,
+ message: error.message,
+ },
+ NotFoundError => Self::ApiEndpointNotFound { provider },
+ RequestTooLarge => Self::PromptTooLarge {
+ tokens: language_model_core::parse_prompt_too_long(&error.message),
+ },
+ RateLimitError => Self::RateLimitExceeded {
+ provider,
+ retry_after: None,
+ },
+ ApiError => Self::ApiInternalServerError {
+ provider,
+ message: error.message,
+ },
+ OverloadedError => Self::ServerOverloaded {
+ provider,
+ retry_after: None,
+ },
+ },
+ None => Self::Other(error.into()),
+ }
+ }
+}
+
#[test]
fn test_match_window_exceeded() {
let error = ApiError {
@@ -0,0 +1,765 @@
+use anyhow::Result;
+use collections::HashMap;
+use futures::{Stream, StreamExt};
+use language_model_core::{
+ LanguageModelCompletionError, LanguageModelCompletionEvent, LanguageModelRequest,
+ LanguageModelToolChoice, LanguageModelToolResultContent, LanguageModelToolUse, MessageContent,
+ Role, StopReason, TokenUsage,
+ util::{fix_streamed_json, parse_tool_arguments},
+};
+use std::pin::Pin;
+use std::str::FromStr;
+
+use crate::{
+ AnthropicError, AnthropicModelMode, CacheControl, CacheControlType, ContentDelta,
+ CountTokensRequest, Event, ImageSource, Message, RequestContent, ResponseContent,
+ StringOrContents, Thinking, Tool, ToolChoice, ToolResultContent, ToolResultPart, Usage,
+};
+
+fn to_anthropic_content(content: MessageContent) -> Option<RequestContent> {
+ match content {
+ MessageContent::Text(text) => {
+ let text = if text.chars().last().is_some_and(|c| c.is_whitespace()) {
+ text.trim_end().to_string()
+ } else {
+ text
+ };
+ if !text.is_empty() {
+ Some(RequestContent::Text {
+ text,
+ cache_control: None,
+ })
+ } else {
+ None
+ }
+ }
+ MessageContent::Thinking {
+ text: thinking,
+ signature,
+ } => {
+ if let Some(signature) = signature
+ && !thinking.is_empty()
+ {
+ Some(RequestContent::Thinking {
+ thinking,
+ signature,
+ cache_control: None,
+ })
+ } else {
+ None
+ }
+ }
+ MessageContent::RedactedThinking(data) => {
+ if !data.is_empty() {
+ Some(RequestContent::RedactedThinking { data })
+ } else {
+ None
+ }
+ }
+ MessageContent::Image(image) => Some(RequestContent::Image {
+ source: ImageSource {
+ source_type: "base64".to_string(),
+ media_type: "image/png".to_string(),
+ data: image.source.to_string(),
+ },
+ cache_control: None,
+ }),
+ MessageContent::ToolUse(tool_use) => Some(RequestContent::ToolUse {
+ id: tool_use.id.to_string(),
+ name: tool_use.name.to_string(),
+ input: tool_use.input,
+ cache_control: None,
+ }),
+ MessageContent::ToolResult(tool_result) => Some(RequestContent::ToolResult {
+ tool_use_id: tool_result.tool_use_id.to_string(),
+ is_error: tool_result.is_error,
+ content: match tool_result.content {
+ LanguageModelToolResultContent::Text(text) => {
+ ToolResultContent::Plain(text.to_string())
+ }
+ LanguageModelToolResultContent::Image(image) => {
+ ToolResultContent::Multipart(vec![ToolResultPart::Image {
+ source: ImageSource {
+ source_type: "base64".to_string(),
+ media_type: "image/png".to_string(),
+ data: image.source.to_string(),
+ },
+ }])
+ }
+ },
+ cache_control: None,
+ }),
+ }
+}
+
+/// Convert a LanguageModelRequest to an Anthropic CountTokensRequest.
+pub fn into_anthropic_count_tokens_request(
+ request: LanguageModelRequest,
+ model: String,
+ mode: AnthropicModelMode,
+) -> CountTokensRequest {
+ let mut new_messages: Vec<Message> = Vec::new();
+ let mut system_message = String::new();
+
+ for message in request.messages {
+ if message.contents_empty() {
+ continue;
+ }
+
+ match message.role {
+ Role::User | Role::Assistant => {
+ let anthropic_message_content: Vec<RequestContent> = message
+ .content
+ .into_iter()
+ .filter_map(to_anthropic_content)
+ .collect();
+ let anthropic_role = match message.role {
+ Role::User => crate::Role::User,
+ Role::Assistant => crate::Role::Assistant,
+ Role::System => unreachable!("System role should never occur here"),
+ };
+ if anthropic_message_content.is_empty() {
+ continue;
+ }
+
+ if let Some(last_message) = new_messages.last_mut()
+ && last_message.role == anthropic_role
+ {
+ last_message.content.extend(anthropic_message_content);
+ continue;
+ }
+
+ new_messages.push(Message {
+ role: anthropic_role,
+ content: anthropic_message_content,
+ });
+ }
+ Role::System => {
+ if !system_message.is_empty() {
+ system_message.push_str("\n\n");
+ }
+ system_message.push_str(&message.string_contents());
+ }
+ }
+ }
+
+ CountTokensRequest {
+ model,
+ messages: new_messages,
+ system: if system_message.is_empty() {
+ None
+ } else {
+ Some(StringOrContents::String(system_message))
+ },
+ thinking: if request.thinking_allowed {
+ match mode {
+ AnthropicModelMode::Thinking { budget_tokens } => {
+ Some(Thinking::Enabled { budget_tokens })
+ }
+ AnthropicModelMode::AdaptiveThinking => Some(Thinking::Adaptive),
+ AnthropicModelMode::Default => None,
+ }
+ } else {
+ None
+ },
+ tools: request
+ .tools
+ .into_iter()
+ .map(|tool| Tool {
+ name: tool.name,
+ description: tool.description,
+ input_schema: tool.input_schema,
+ eager_input_streaming: tool.use_input_streaming,
+ })
+ .collect(),
+ tool_choice: request.tool_choice.map(|choice| match choice {
+ LanguageModelToolChoice::Auto => ToolChoice::Auto,
+ LanguageModelToolChoice::Any => ToolChoice::Any,
+ LanguageModelToolChoice::None => ToolChoice::None,
+ }),
+ }
+}
+
+/// Estimate tokens using tiktoken. Used as a fallback when the API is unavailable,
+/// or by providers (like Zed Cloud) that don't have direct Anthropic API access.
+pub fn count_anthropic_tokens_with_tiktoken(request: LanguageModelRequest) -> Result<u64> {
+ let messages = request.messages;
+ let mut tokens_from_images = 0;
+ let mut string_messages = Vec::with_capacity(messages.len());
+
+ for message in messages {
+ let mut string_contents = String::new();
+
+ for content in message.content {
+ match content {
+ MessageContent::Text(text) => {
+ string_contents.push_str(&text);
+ }
+ MessageContent::Thinking { .. } => {
+ // Thinking blocks are not included in the input token count.
+ }
+ MessageContent::RedactedThinking(_) => {
+ // Thinking blocks are not included in the input token count.
+ }
+ MessageContent::Image(image) => {
+ tokens_from_images += image.estimate_tokens();
+ }
+ MessageContent::ToolUse(_tool_use) => {
+ // TODO: Estimate token usage from tool uses.
+ }
+ MessageContent::ToolResult(tool_result) => match &tool_result.content {
+ LanguageModelToolResultContent::Text(text) => {
+ string_contents.push_str(text);
+ }
+ LanguageModelToolResultContent::Image(image) => {
+ tokens_from_images += image.estimate_tokens();
+ }
+ },
+ }
+ }
+
+ if !string_contents.is_empty() {
+ string_messages.push(tiktoken_rs::ChatCompletionRequestMessage {
+ role: match message.role {
+ Role::User => "user".into(),
+ Role::Assistant => "assistant".into(),
+ Role::System => "system".into(),
+ },
+ content: Some(string_contents),
+ name: None,
+ function_call: None,
+ });
+ }
+ }
+
+ // Tiktoken doesn't yet support these models, so we manually use the
+ // same tokenizer as GPT-4.
+ tiktoken_rs::num_tokens_from_messages("gpt-4", &string_messages)
+ .map(|tokens| (tokens + tokens_from_images) as u64)
+}
+
+pub fn into_anthropic(
+ request: LanguageModelRequest,
+ model: String,
+ default_temperature: f32,
+ max_output_tokens: u64,
+ mode: AnthropicModelMode,
+) -> crate::Request {
+ let mut new_messages: Vec<Message> = Vec::new();
+ let mut system_message = String::new();
+
+ for message in request.messages {
+ if message.contents_empty() {
+ continue;
+ }
+
+ match message.role {
+ Role::User | Role::Assistant => {
+ let mut anthropic_message_content: Vec<RequestContent> = message
+ .content
+ .into_iter()
+ .filter_map(to_anthropic_content)
+ .collect();
+ let anthropic_role = match message.role {
+ Role::User => crate::Role::User,
+ Role::Assistant => crate::Role::Assistant,
+ Role::System => unreachable!("System role should never occur here"),
+ };
+ if anthropic_message_content.is_empty() {
+ continue;
+ }
+
+ if let Some(last_message) = new_messages.last_mut()
+ && last_message.role == anthropic_role
+ {
+ last_message.content.extend(anthropic_message_content);
+ continue;
+ }
+
+ // Mark the last segment of the message as cached
+ if message.cache {
+ let cache_control_value = Some(CacheControl {
+ cache_type: CacheControlType::Ephemeral,
+ });
+ for message_content in anthropic_message_content.iter_mut().rev() {
+ match message_content {
+ RequestContent::RedactedThinking { .. } => {
+ // Caching is not possible, fallback to next message
+ }
+ RequestContent::Text { cache_control, .. }
+ | RequestContent::Thinking { cache_control, .. }
+ | RequestContent::Image { cache_control, .. }
+ | RequestContent::ToolUse { cache_control, .. }
+ | RequestContent::ToolResult { cache_control, .. } => {
+ *cache_control = cache_control_value;
+ break;
+ }
+ }
+ }
+ }
+
+ new_messages.push(Message {
+ role: anthropic_role,
+ content: anthropic_message_content,
+ });
+ }
+ Role::System => {
+ if !system_message.is_empty() {
+ system_message.push_str("\n\n");
+ }
+ system_message.push_str(&message.string_contents());
+ }
+ }
+ }
+
+ crate::Request {
+ model,
+ messages: new_messages,
+ max_tokens: max_output_tokens,
+ system: if system_message.is_empty() {
+ None
+ } else {
+ Some(StringOrContents::String(system_message))
+ },
+ thinking: if request.thinking_allowed {
+ match mode {
+ AnthropicModelMode::Thinking { budget_tokens } => {
+ Some(Thinking::Enabled { budget_tokens })
+ }
+ AnthropicModelMode::AdaptiveThinking => Some(Thinking::Adaptive),
+ AnthropicModelMode::Default => None,
+ }
+ } else {
+ None
+ },
+ tools: request
+ .tools
+ .into_iter()
+ .map(|tool| Tool {
+ name: tool.name,
+ description: tool.description,
+ input_schema: tool.input_schema,
+ eager_input_streaming: tool.use_input_streaming,
+ })
+ .collect(),
+ tool_choice: request.tool_choice.map(|choice| match choice {
+ LanguageModelToolChoice::Auto => ToolChoice::Auto,
+ LanguageModelToolChoice::Any => ToolChoice::Any,
+ LanguageModelToolChoice::None => ToolChoice::None,
+ }),
+ metadata: None,
+ output_config: if request.thinking_allowed
+ && matches!(mode, AnthropicModelMode::AdaptiveThinking)
+ {
+ request.thinking_effort.as_deref().and_then(|effort| {
+ let effort = match effort {
+ "low" => Some(crate::Effort::Low),
+ "medium" => Some(crate::Effort::Medium),
+ "high" => Some(crate::Effort::High),
+ "max" => Some(crate::Effort::Max),
+ _ => None,
+ };
+ effort.map(|effort| crate::OutputConfig {
+ effort: Some(effort),
+ })
+ })
+ } else {
+ None
+ },
+ stop_sequences: Vec::new(),
+ speed: request.speed.map(Into::into),
+ temperature: request.temperature.or(Some(default_temperature)),
+ top_k: None,
+ top_p: None,
+ }
+}
+
+pub struct AnthropicEventMapper {
+ tool_uses_by_index: HashMap<usize, RawToolUse>,
+ usage: Usage,
+ stop_reason: StopReason,
+}
+
+impl AnthropicEventMapper {
+ pub fn new() -> Self {
+ Self {
+ tool_uses_by_index: HashMap::default(),
+ usage: Usage::default(),
+ stop_reason: StopReason::EndTurn,
+ }
+ }
+
+ pub fn map_stream(
+ mut self,
+ events: Pin<Box<dyn Send + Stream<Item = Result<Event, AnthropicError>>>>,
+ ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
+ {
+ events.flat_map(move |event| {
+ futures::stream::iter(match event {
+ Ok(event) => self.map_event(event),
+ Err(error) => vec![Err(error.into())],
+ })
+ })
+ }
+
+ pub fn map_event(
+ &mut self,
+ event: Event,
+ ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
+ match event {
+ Event::ContentBlockStart {
+ index,
+ content_block,
+ } => match content_block {
+ ResponseContent::Text { text } => {
+ vec![Ok(LanguageModelCompletionEvent::Text(text))]
+ }
+ ResponseContent::Thinking { thinking } => {
+ vec![Ok(LanguageModelCompletionEvent::Thinking {
+ text: thinking,
+ signature: None,
+ })]
+ }
+ ResponseContent::RedactedThinking { data } => {
+ vec![Ok(LanguageModelCompletionEvent::RedactedThinking { data })]
+ }
+ ResponseContent::ToolUse { id, name, .. } => {
+ self.tool_uses_by_index.insert(
+ index,
+ RawToolUse {
+ id,
+ name,
+ input_json: String::new(),
+ },
+ );
+ Vec::new()
+ }
+ },
+ Event::ContentBlockDelta { index, delta } => match delta {
+ ContentDelta::TextDelta { text } => {
+ vec![Ok(LanguageModelCompletionEvent::Text(text))]
+ }
+ ContentDelta::ThinkingDelta { thinking } => {
+ vec![Ok(LanguageModelCompletionEvent::Thinking {
+ text: thinking,
+ signature: None,
+ })]
+ }
+ ContentDelta::SignatureDelta { signature } => {
+ vec![Ok(LanguageModelCompletionEvent::Thinking {
+ text: "".to_string(),
+ signature: Some(signature),
+ })]
+ }
+ ContentDelta::InputJsonDelta { partial_json } => {
+ if let Some(tool_use) = self.tool_uses_by_index.get_mut(&index) {
+ tool_use.input_json.push_str(&partial_json);
+
+ // Try to convert invalid (incomplete) JSON into
+ // valid JSON that serde can accept, e.g. by closing
+ // unclosed delimiters. This way, we can update the
+ // UI with whatever has been streamed back so far.
+ if let Ok(input) =
+ serde_json::Value::from_str(&fix_streamed_json(&tool_use.input_json))
+ {
+ return vec![Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id: tool_use.id.clone().into(),
+ name: tool_use.name.clone().into(),
+ is_input_complete: false,
+ raw_input: tool_use.input_json.clone(),
+ input,
+ thought_signature: None,
+ },
+ ))];
+ }
+ }
+ vec![]
+ }
+ },
+ Event::ContentBlockStop { index } => {
+ if let Some(tool_use) = self.tool_uses_by_index.remove(&index) {
+ let input_json = tool_use.input_json.trim();
+ let event_result = match parse_tool_arguments(input_json) {
+ Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id: tool_use.id.into(),
+ name: tool_use.name.into(),
+ is_input_complete: true,
+ input,
+ raw_input: tool_use.input_json.clone(),
+ thought_signature: None,
+ },
+ )),
+ Err(json_parse_err) => {
+ Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
+ id: tool_use.id.into(),
+ tool_name: tool_use.name.into(),
+ raw_input: input_json.into(),
+ json_parse_error: json_parse_err.to_string(),
+ })
+ }
+ };
+
+ vec![event_result]
+ } else {
+ Vec::new()
+ }
+ }
+ Event::MessageStart { message } => {
+ update_usage(&mut self.usage, &message.usage);
+ vec![
+ Ok(LanguageModelCompletionEvent::UsageUpdate(convert_usage(
+ &self.usage,
+ ))),
+ Ok(LanguageModelCompletionEvent::StartMessage {
+ message_id: message.id,
+ }),
+ ]
+ }
+ Event::MessageDelta { delta, usage } => {
+ update_usage(&mut self.usage, &usage);
+ if let Some(stop_reason) = delta.stop_reason.as_deref() {
+ self.stop_reason = match stop_reason {
+ "end_turn" => StopReason::EndTurn,
+ "max_tokens" => StopReason::MaxTokens,
+ "tool_use" => StopReason::ToolUse,
+ "refusal" => StopReason::Refusal,
+ _ => {
+ log::error!("Unexpected anthropic stop_reason: {stop_reason}");
+ StopReason::EndTurn
+ }
+ };
+ }
+ vec![Ok(LanguageModelCompletionEvent::UsageUpdate(
+ convert_usage(&self.usage),
+ ))]
+ }
+ Event::MessageStop => {
+ vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))]
+ }
+ Event::Error { error } => {
+ vec![Err(error.into())]
+ }
+ _ => Vec::new(),
+ }
+ }
+}
+
+struct RawToolUse {
+ id: String,
+ name: String,
+ input_json: String,
+}
+
+/// Updates usage data by preferring counts from `new`.
+fn update_usage(usage: &mut Usage, new: &Usage) {
+ if let Some(input_tokens) = new.input_tokens {
+ usage.input_tokens = Some(input_tokens);
+ }
+ if let Some(output_tokens) = new.output_tokens {
+ usage.output_tokens = Some(output_tokens);
+ }
+ if let Some(cache_creation_input_tokens) = new.cache_creation_input_tokens {
+ usage.cache_creation_input_tokens = Some(cache_creation_input_tokens);
+ }
+ if let Some(cache_read_input_tokens) = new.cache_read_input_tokens {
+ usage.cache_read_input_tokens = Some(cache_read_input_tokens);
+ }
+}
+
+fn convert_usage(usage: &Usage) -> TokenUsage {
+ TokenUsage {
+ input_tokens: usage.input_tokens.unwrap_or(0),
+ output_tokens: usage.output_tokens.unwrap_or(0),
+ cache_creation_input_tokens: usage.cache_creation_input_tokens.unwrap_or(0),
+ cache_read_input_tokens: usage.cache_read_input_tokens.unwrap_or(0),
+ }
+}
+
+#[cfg(test)]
+mod tests {
+ use super::*;
+ use crate::AnthropicModelMode;
+ use language_model_core::{LanguageModelImage, LanguageModelRequestMessage, MessageContent};
+
+ #[test]
+ fn test_cache_control_only_on_last_segment() {
+ let request = LanguageModelRequest {
+ messages: vec![LanguageModelRequestMessage {
+ role: Role::User,
+ content: vec![
+ MessageContent::Text("Some prompt".to_string()),
+ MessageContent::Image(LanguageModelImage::empty()),
+ MessageContent::Image(LanguageModelImage::empty()),
+ MessageContent::Image(LanguageModelImage::empty()),
+ MessageContent::Image(LanguageModelImage::empty()),
+ ],
+ cache: true,
+ reasoning_details: None,
+ }],
+ thread_id: None,
+ prompt_id: None,
+ intent: None,
+ stop: vec![],
+ temperature: None,
+ tools: vec![],
+ tool_choice: None,
+ thinking_allowed: true,
+ thinking_effort: None,
+ speed: None,
+ };
+
+ let anthropic_request = into_anthropic(
+ request,
+ "claude-3-5-sonnet".to_string(),
+ 0.7,
+ 4096,
+ AnthropicModelMode::Default,
+ );
+
+ assert_eq!(anthropic_request.messages.len(), 1);
+
+ let message = &anthropic_request.messages[0];
+ assert_eq!(message.content.len(), 5);
+
+ assert!(matches!(
+ message.content[0],
+ RequestContent::Text {
+ cache_control: None,
+ ..
+ }
+ ));
+ for i in 1..3 {
+ assert!(matches!(
+ message.content[i],
+ RequestContent::Image {
+ cache_control: None,
+ ..
+ }
+ ));
+ }
+
+ assert!(matches!(
+ message.content[4],
+ RequestContent::Image {
+ cache_control: Some(CacheControl {
+ cache_type: CacheControlType::Ephemeral,
+ }),
+ ..
+ }
+ ));
+ }
+
+ fn request_with_assistant_content(assistant_content: Vec<MessageContent>) -> crate::Request {
+ let mut request = LanguageModelRequest {
+ messages: vec![LanguageModelRequestMessage {
+ role: Role::User,
+ content: vec![MessageContent::Text("Hello".to_string())],
+ cache: false,
+ reasoning_details: None,
+ }],
+ thinking_effort: None,
+ thread_id: None,
+ prompt_id: None,
+ intent: None,
+ stop: vec![],
+ temperature: None,
+ tools: vec![],
+ tool_choice: None,
+ thinking_allowed: true,
+ speed: None,
+ };
+ request.messages.push(LanguageModelRequestMessage {
+ role: Role::Assistant,
+ content: assistant_content,
+ cache: false,
+ reasoning_details: None,
+ });
+ into_anthropic(
+ request,
+ "claude-sonnet-4-5".to_string(),
+ 1.0,
+ 16000,
+ AnthropicModelMode::Thinking {
+ budget_tokens: Some(10000),
+ },
+ )
+ }
+
+ #[test]
+ fn test_unsigned_thinking_blocks_stripped() {
+ let result = request_with_assistant_content(vec![
+ MessageContent::Thinking {
+ text: "Cancelled mid-think, no signature".to_string(),
+ signature: None,
+ },
+ MessageContent::Text("Some response text".to_string()),
+ ]);
+
+ let assistant_message = result
+ .messages
+ .iter()
+ .find(|m| m.role == crate::Role::Assistant)
+ .expect("assistant message should still exist");
+
+ assert_eq!(
+ assistant_message.content.len(),
+ 1,
+ "Only the text content should remain; unsigned thinking block should be stripped"
+ );
+ assert!(matches!(
+ &assistant_message.content[0],
+ RequestContent::Text { text, .. } if text == "Some response text"
+ ));
+ }
+
+ #[test]
+ fn test_signed_thinking_blocks_preserved() {
+ let result = request_with_assistant_content(vec![
+ MessageContent::Thinking {
+ text: "Completed thinking".to_string(),
+ signature: Some("valid-signature".to_string()),
+ },
+ MessageContent::Text("Response".to_string()),
+ ]);
+
+ let assistant_message = result
+ .messages
+ .iter()
+ .find(|m| m.role == crate::Role::Assistant)
+ .expect("assistant message should exist");
+
+ assert_eq!(
+ assistant_message.content.len(),
+ 2,
+ "Both the signed thinking block and text should be preserved"
+ );
+ assert!(matches!(
+ &assistant_message.content[0],
+ RequestContent::Thinking { thinking, signature, .. }
+ if thinking == "Completed thinking" && signature == "valid-signature"
+ ));
+ }
+
+ #[test]
+ fn test_only_unsigned_thinking_block_omits_entire_message() {
+ let result = request_with_assistant_content(vec![MessageContent::Thinking {
+ text: "Cancelled before any text or signature".to_string(),
+ signature: None,
+ }]);
+
+ let assistant_messages: Vec<_> = result
+ .messages
+ .iter()
+ .filter(|m| m.role == crate::Role::Assistant)
+ .collect();
+
+ assert_eq!(
+ assistant_messages.len(),
+ 0,
+ "An assistant message whose only content was an unsigned thinking block \
+ should be omitted entirely"
+ );
+ }
+}
@@ -113,6 +113,10 @@ pub enum Model {
MistralLarge3,
#[serde(rename = "pixtral-large")]
PixtralLarge,
+ #[serde(rename = "devstral-2-123b")]
+ Devstral2_123B,
+ #[serde(rename = "ministral-14b")]
+ Ministral14B,
// Qwen models
#[serde(rename = "qwen3-32b")]
@@ -146,9 +150,27 @@ pub enum Model {
#[serde(rename = "gpt-oss-120b")]
GptOss120B,
+ // NVIDIA Nemotron models
+ #[serde(rename = "nemotron-super-3-120b")]
+ NemotronSuper3_120B,
+ #[serde(rename = "nemotron-nano-3-30b")]
+ NemotronNano3_30B,
+
// MiniMax models
#[serde(rename = "minimax-m2")]
MiniMaxM2,
+ #[serde(rename = "minimax-m2-1")]
+ MiniMaxM2_1,
+ #[serde(rename = "minimax-m2-5")]
+ MiniMaxM2_5,
+
+ // Z.AI GLM models
+ #[serde(rename = "glm-5")]
+ GLM5,
+ #[serde(rename = "glm-4-7")]
+ GLM4_7,
+ #[serde(rename = "glm-4-7-flash")]
+ GLM4_7Flash,
// Moonshot models
#[serde(rename = "kimi-k2-thinking")]
@@ -217,6 +239,8 @@ impl Model {
Self::MagistralSmall => "magistral-small",
Self::MistralLarge3 => "mistral-large-3",
Self::PixtralLarge => "pixtral-large",
+ Self::Devstral2_123B => "devstral-2-123b",
+ Self::Ministral14B => "ministral-14b",
Self::Qwen3_32B => "qwen3-32b",
Self::Qwen3VL235B => "qwen3-vl-235b",
Self::Qwen3_235B => "qwen3-235b",
@@ -230,7 +254,14 @@ impl Model {
Self::Nova2Lite => "nova-2-lite",
Self::GptOss20B => "gpt-oss-20b",
Self::GptOss120B => "gpt-oss-120b",
+ Self::NemotronSuper3_120B => "nemotron-super-3-120b",
+ Self::NemotronNano3_30B => "nemotron-nano-3-30b",
Self::MiniMaxM2 => "minimax-m2",
+ Self::MiniMaxM2_1 => "minimax-m2-1",
+ Self::MiniMaxM2_5 => "minimax-m2-5",
+ Self::GLM5 => "glm-5",
+ Self::GLM4_7 => "glm-4-7",
+ Self::GLM4_7Flash => "glm-4-7-flash",
Self::KimiK2Thinking => "kimi-k2-thinking",
Self::KimiK2_5 => "kimi-k2-5",
Self::DeepSeekR1 => "deepseek-r1",
@@ -257,6 +288,8 @@ impl Model {
Self::MagistralSmall => "mistral.magistral-small-2509",
Self::MistralLarge3 => "mistral.mistral-large-3-675b-instruct",
Self::PixtralLarge => "mistral.pixtral-large-2502-v1:0",
+ Self::Devstral2_123B => "mistral.devstral-2-123b",
+ Self::Ministral14B => "mistral.ministral-3-14b-instruct",
Self::Qwen3VL235B => "qwen.qwen3-vl-235b-a22b",
Self::Qwen3_32B => "qwen.qwen3-32b-v1:0",
Self::Qwen3_235B => "qwen.qwen3-235b-a22b-2507-v1:0",
@@ -270,7 +303,14 @@ impl Model {
Self::Nova2Lite => "amazon.nova-2-lite-v1:0",
Self::GptOss20B => "openai.gpt-oss-20b-1:0",
Self::GptOss120B => "openai.gpt-oss-120b-1:0",
+ Self::NemotronSuper3_120B => "nvidia.nemotron-super-3-120b",
+ Self::NemotronNano3_30B => "nvidia.nemotron-nano-3-30b",
Self::MiniMaxM2 => "minimax.minimax-m2",
+ Self::MiniMaxM2_1 => "minimax.minimax-m2.1",
+ Self::MiniMaxM2_5 => "minimax.minimax-m2.5",
+ Self::GLM5 => "zai.glm-5",
+ Self::GLM4_7 => "zai.glm-4.7",
+ Self::GLM4_7Flash => "zai.glm-4.7-flash",
Self::KimiK2Thinking => "moonshot.kimi-k2-thinking",
Self::KimiK2_5 => "moonshotai.kimi-k2.5",
Self::DeepSeekR1 => "deepseek.r1-v1:0",
@@ -297,6 +337,8 @@ impl Model {
Self::MagistralSmall => "Magistral Small",
Self::MistralLarge3 => "Mistral Large 3",
Self::PixtralLarge => "Pixtral Large",
+ Self::Devstral2_123B => "Devstral 2 123B",
+ Self::Ministral14B => "Ministral 14B",
Self::Qwen3VL235B => "Qwen3 VL 235B",
Self::Qwen3_32B => "Qwen3 32B",
Self::Qwen3_235B => "Qwen3 235B",
@@ -310,7 +352,14 @@ impl Model {
Self::Nova2Lite => "Amazon Nova 2 Lite",
Self::GptOss20B => "GPT OSS 20B",
Self::GptOss120B => "GPT OSS 120B",
+ Self::NemotronSuper3_120B => "Nemotron Super 3 120B",
+ Self::NemotronNano3_30B => "Nemotron Nano 3 30B",
Self::MiniMaxM2 => "MiniMax M2",
+ Self::MiniMaxM2_1 => "MiniMax M2.1",
+ Self::MiniMaxM2_5 => "MiniMax M2.5",
+ Self::GLM5 => "GLM 5",
+ Self::GLM4_7 => "GLM 4.7",
+ Self::GLM4_7Flash => "GLM 4.7 Flash",
Self::KimiK2Thinking => "Kimi K2 Thinking",
Self::KimiK2_5 => "Kimi K2.5",
Self::DeepSeekR1 => "DeepSeek R1",
@@ -338,6 +387,7 @@ impl Model {
Self::Llama4Scout17B | Self::Llama4Maverick17B => 128_000,
Self::Gemma3_4B | Self::Gemma3_12B | Self::Gemma3_27B => 128_000,
Self::MagistralSmall | Self::MistralLarge3 | Self::PixtralLarge => 128_000,
+ Self::Devstral2_123B | Self::Ministral14B => 256_000,
Self::Qwen3_32B
| Self::Qwen3VL235B
| Self::Qwen3_235B
@@ -349,7 +399,9 @@ impl Model {
Self::NovaPremier => 1_000_000,
Self::Nova2Lite => 300_000,
Self::GptOss20B | Self::GptOss120B => 128_000,
- Self::MiniMaxM2 => 128_000,
+ Self::NemotronSuper3_120B | Self::NemotronNano3_30B => 262_000,
+ Self::MiniMaxM2 | Self::MiniMaxM2_1 | Self::MiniMaxM2_5 => 196_000,
+ Self::GLM5 | Self::GLM4_7 | Self::GLM4_7Flash => 203_000,
Self::KimiK2Thinking | Self::KimiK2_5 => 128_000,
Self::DeepSeekR1 | Self::DeepSeekV3_1 | Self::DeepSeekV3_2 => 128_000,
Self::Custom { max_tokens, .. } => *max_tokens,
@@ -373,6 +425,7 @@ impl Model {
| Self::MagistralSmall
| Self::MistralLarge3
| Self::PixtralLarge => 8_192,
+ Self::Devstral2_123B | Self::Ministral14B => 131_000,
Self::Qwen3_32B
| Self::Qwen3VL235B
| Self::Qwen3_235B
@@ -382,7 +435,9 @@ impl Model {
| Self::Qwen3Coder480B => 8_192,
Self::NovaLite | Self::NovaPro | Self::NovaPremier | Self::Nova2Lite => 5_000,
Self::GptOss20B | Self::GptOss120B => 16_000,
- Self::MiniMaxM2 => 16_000,
+ Self::NemotronSuper3_120B | Self::NemotronNano3_30B => 131_000,
+ Self::MiniMaxM2 | Self::MiniMaxM2_1 | Self::MiniMaxM2_5 => 98_000,
+ Self::GLM5 | Self::GLM4_7 | Self::GLM4_7Flash => 101_000,
Self::KimiK2Thinking | Self::KimiK2_5 => 16_000,
Self::DeepSeekR1 | Self::DeepSeekV3_1 | Self::DeepSeekV3_2 => 16_000,
Self::Custom {
@@ -419,6 +474,7 @@ impl Model {
| Self::ClaudeSonnet4_6 => true,
Self::NovaLite | Self::NovaPro | Self::NovaPremier | Self::Nova2Lite => true,
Self::MistralLarge3 | Self::PixtralLarge | Self::MagistralSmall => true,
+ Self::Devstral2_123B | Self::Ministral14B => true,
// Gemma accepts toolConfig without error but produces unreliable tool
// calls -- malformed JSON args, hallucinated tool names, dropped calls.
Self::Qwen3_32B
@@ -428,7 +484,9 @@ impl Model {
| Self::Qwen3Coder30B
| Self::Qwen3CoderNext
| Self::Qwen3Coder480B => true,
- Self::MiniMaxM2 => true,
+ Self::MiniMaxM2 | Self::MiniMaxM2_1 | Self::MiniMaxM2_5 => true,
+ Self::NemotronSuper3_120B | Self::NemotronNano3_30B => true,
+ Self::GLM5 | Self::GLM4_7 | Self::GLM4_7Flash => true,
Self::KimiK2Thinking | Self::KimiK2_5 => true,
Self::DeepSeekR1 | Self::DeepSeekV3_1 | Self::DeepSeekV3_2 => true,
_ => false,
@@ -36,7 +36,6 @@ gpui_tokio.workspace = true
http_client.workspace = true
http_client_tls.workspace = true
httparse = "1.10"
-language_model.workspace = true
log.workspace = true
parking_lot.workspace = true
paths.workspace = true
@@ -14,6 +14,7 @@ use async_tungstenite::tungstenite::{
http::{HeaderValue, Request, StatusCode},
};
use clock::SystemClock;
+use cloud_api_client::LlmApiToken;
use cloud_api_client::websocket_protocol::MessageToClient;
use cloud_api_client::{ClientApiError, CloudApiClient};
use cloud_api_types::OrganizationId;
@@ -26,7 +27,6 @@ use futures::{
};
use gpui::{App, AsyncApp, Entity, Global, Task, WeakEntity, actions};
use http_client::{HttpClient, HttpClientWithUrl, http, read_proxy_from_env};
-use language_model::LlmApiToken;
use parking_lot::{Mutex, RwLock};
use postage::watch;
use proxy::connect_proxy_stream;
@@ -1,10 +1,10 @@
use super::{Client, UserStore};
+use cloud_api_client::LlmApiToken;
use cloud_api_types::websocket_protocol::MessageToClient;
use cloud_llm_client::{EXPIRED_LLM_TOKEN_HEADER_NAME, OUTDATED_LLM_TOKEN_HEADER_NAME};
use gpui::{
App, AppContext as _, Context, Entity, EventEmitter, Global, ReadGlobal as _, Subscription,
};
-use language_model::LlmApiToken;
use std::sync::Arc;
pub trait NeedsLlmTokenRefresh {
@@ -20,5 +20,6 @@ gpui_tokio.workspace = true
http_client.workspace = true
parking_lot.workspace = true
serde_json.workspace = true
+smol.workspace = true
thiserror.workspace = true
yawc.workspace = true
@@ -1,3 +1,4 @@
+mod llm_token;
mod websocket;
use std::sync::Arc;
@@ -18,6 +19,8 @@ use yawc::WebSocket;
use crate::websocket::Connection;
+pub use llm_token::LlmApiToken;
+
struct Credentials {
user_id: u32,
access_token: String,
@@ -0,0 +1,74 @@
+use std::sync::Arc;
+
+use cloud_api_types::OrganizationId;
+use smol::lock::{RwLock, RwLockUpgradableReadGuard, RwLockWriteGuard};
+
+use crate::{ClientApiError, CloudApiClient};
+
+#[derive(Clone, Default)]
+pub struct LlmApiToken(Arc<RwLock<Option<String>>>);
+
+impl LlmApiToken {
+ pub async fn acquire(
+ &self,
+ client: &CloudApiClient,
+ system_id: Option<String>,
+ organization_id: Option<OrganizationId>,
+ ) -> Result<String, ClientApiError> {
+ let lock = self.0.upgradable_read().await;
+ if let Some(token) = lock.as_ref() {
+ Ok(token.to_string())
+ } else {
+ Self::fetch(
+ RwLockUpgradableReadGuard::upgrade(lock).await,
+ client,
+ system_id,
+ organization_id,
+ )
+ .await
+ }
+ }
+
+ pub async fn refresh(
+ &self,
+ client: &CloudApiClient,
+ system_id: Option<String>,
+ organization_id: Option<OrganizationId>,
+ ) -> Result<String, ClientApiError> {
+ Self::fetch(self.0.write().await, client, system_id, organization_id).await
+ }
+
+ /// Clears the existing token before attempting to fetch a new one.
+ ///
+ /// Used when switching organizations so that a failed refresh doesn't
+ /// leave a token for the wrong organization.
+ pub async fn clear_and_refresh(
+ &self,
+ client: &CloudApiClient,
+ system_id: Option<String>,
+ organization_id: Option<OrganizationId>,
+ ) -> Result<String, ClientApiError> {
+ let mut lock = self.0.write().await;
+ *lock = None;
+ Self::fetch(lock, client, system_id, organization_id).await
+ }
+
+ async fn fetch(
+ mut lock: RwLockWriteGuard<'_, Option<String>>,
+ client: &CloudApiClient,
+ system_id: Option<String>,
+ organization_id: Option<OrganizationId>,
+ ) -> Result<String, ClientApiError> {
+ let result = client.create_llm_token(system_id, organization_id).await;
+ match result {
+ Ok(response) => {
+ *lock = Some(response.token.0.clone());
+ Ok(response.token.0)
+ }
+ Err(err) => {
+ *lock = None;
+ Err(err)
+ }
+ }
+ }
+}
@@ -7,6 +7,7 @@ license = "Apache-2.0"
[features]
test-support = []
+predict-edits = ["dep:zeta_prompt"]
[lints]
workspace = true
@@ -20,6 +21,6 @@ serde = { workspace = true, features = ["derive", "rc"] }
serde_json.workspace = true
strum = { workspace = true, features = ["derive"] }
uuid = { workspace = true, features = ["serde"] }
-zeta_prompt.workspace = true
+zeta_prompt = { workspace = true, optional = true }
@@ -1,3 +1,4 @@
+#[cfg(feature = "predict-edits")]
pub mod predict_edits_v3;
use std::str::FromStr;
@@ -269,9 +269,11 @@ async fn test_remote_git_worktrees(
cx_b.update(|cx| {
repo_b.update(cx, |repository, _| {
repository.create_worktree(
- "feature-branch".to_string(),
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: "feature-branch".to_string(),
+ base_sha: Some("abc123".to_string()),
+ },
worktree_directory.join("feature-branch"),
- Some("abc123".to_string()),
)
})
})
@@ -323,9 +325,11 @@ async fn test_remote_git_worktrees(
cx_b.update(|cx| {
repo_b.update(cx, |repository, _| {
repository.create_worktree(
- "bugfix-branch".to_string(),
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: "bugfix-branch".to_string(),
+ base_sha: None,
+ },
worktree_directory.join("bugfix-branch"),
- None,
)
})
})
@@ -473,9 +473,11 @@ async fn test_ssh_collaboration_git_worktrees(
cx_b.update(|cx| {
repo_b.update(cx, |repo, _| {
repo.create_worktree(
- "feature-branch".to_string(),
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: "feature-branch".to_string(),
+ base_sha: Some("abc123".to_string()),
+ },
worktree_directory.join("feature-branch"),
- Some("abc123".to_string()),
)
})
})
@@ -32,7 +32,6 @@ test-support = [
anyhow.workspace = true
call.workspace = true
channel.workspace = true
-chrono.workspace = true
client.workspace = true
collections.workspace = true
db.workspace = true
@@ -41,7 +40,6 @@ futures.workspace = true
fuzzy.workspace = true
gpui.workspace = true
livekit_client.workspace = true
-log.workspace = true
menu.workspace = true
notifications.workspace = true
picker.workspace = true
@@ -56,7 +54,6 @@ telemetry.workspace = true
theme.workspace = true
theme_settings.workspace = true
time.workspace = true
-time_format.workspace = true
title_bar.workspace = true
ui.workspace = true
util.workspace = true
@@ -6,7 +6,7 @@ use crate::{CollaborationPanelSettings, channel_view::ChannelView};
use anyhow::Context as _;
use call::ActiveCall;
use channel::{Channel, ChannelEvent, ChannelStore};
-use client::{ChannelId, Client, Contact, User, UserStore};
+use client::{ChannelId, Client, Contact, Notification, User, UserStore};
use collections::{HashMap, HashSet};
use contact_finder::ContactFinder;
use db::kvp::KeyValueStore;
@@ -21,6 +21,7 @@ use gpui::{
};
use menu::{Cancel, Confirm, SecondaryConfirm, SelectNext, SelectPrevious};
+use notifications::{NotificationEntry, NotificationEvent, NotificationStore};
use project::{Fs, Project};
use rpc::{
ErrorCode, ErrorExt,
@@ -29,19 +30,23 @@ use rpc::{
use serde::{Deserialize, Serialize};
use settings::Settings;
use smallvec::SmallVec;
-use std::{mem, sync::Arc};
+use std::{mem, sync::Arc, time::Duration};
use theme::ActiveTheme;
use theme_settings::ThemeSettings;
use ui::{
- Avatar, AvatarAvailabilityIndicator, ContextMenu, CopyButton, Facepile, HighlightedLabel,
- IconButtonShape, Indicator, ListHeader, ListItem, Tab, Tooltip, prelude::*, tooltip_container,
+ Avatar, AvatarAvailabilityIndicator, CollabNotification, ContextMenu, CopyButton, Facepile,
+ HighlightedLabel, IconButtonShape, Indicator, ListHeader, ListItem, Tab, Tooltip, prelude::*,
+ tooltip_container,
};
use util::{ResultExt, TryFutureExt, maybe};
use workspace::{
CopyRoomId, Deafen, LeaveCall, MultiWorkspace, Mute, OpenChannelNotes, OpenChannelNotesById,
ScreenShare, ShareProject, Workspace,
dock::{DockPosition, Panel, PanelEvent},
- notifications::{DetachAndPromptErr, NotifyResultExt},
+ notifications::{
+ DetachAndPromptErr, Notification as WorkspaceNotification, NotificationId, NotifyResultExt,
+ SuppressEvent,
+ },
};
const FILTER_OCCUPIED_CHANNELS_KEY: &str = "filter_occupied_channels";
@@ -87,6 +92,7 @@ struct ChannelMoveClipboard {
}
const COLLABORATION_PANEL_KEY: &str = "CollaborationPanel";
+const TOAST_DURATION: Duration = Duration::from_secs(5);
pub fn init(cx: &mut App) {
cx.observe_new(|workspace: &mut Workspace, _, _| {
@@ -267,6 +273,9 @@ pub struct CollabPanel {
collapsed_channels: Vec<ChannelId>,
filter_occupied_channels: bool,
workspace: WeakEntity<Workspace>,
+ notification_store: Entity<NotificationStore>,
+ current_notification_toast: Option<(u64, Task<()>)>,
+ mark_as_read_tasks: HashMap<u64, Task<anyhow::Result<()>>>,
}
#[derive(Serialize, Deserialize)]
@@ -394,6 +403,9 @@ impl CollabPanel {
channel_editing_state: None,
selection: None,
channel_store: ChannelStore::global(cx),
+ notification_store: NotificationStore::global(cx),
+ current_notification_toast: None,
+ mark_as_read_tasks: HashMap::default(),
user_store: workspace.user_store().clone(),
project: workspace.project().clone(),
subscriptions: Vec::default(),
@@ -437,6 +449,11 @@ impl CollabPanel {
}
},
));
+ this.subscriptions.push(cx.subscribe_in(
+ &this.notification_store,
+ window,
+ Self::on_notification_event,
+ ));
this
})
@@ -1181,7 +1198,7 @@ impl CollabPanel {
.into();
ListItem::new(project_id as usize)
- .height(px(24.))
+ .height(rems_from_px(24.))
.toggle_state(is_selected)
.on_click(cx.listener(move |this, _, window, cx| {
this.workspace
@@ -1222,7 +1239,7 @@ impl CollabPanel {
let id = peer_id.map_or(usize::MAX, |id| id.as_u64() as usize);
ListItem::new(("screen", id))
- .height(px(24.))
+ .height(rems_from_px(24.))
.toggle_state(is_selected)
.start_slot(
h_flex()
@@ -1269,7 +1286,7 @@ impl CollabPanel {
let has_channel_buffer_changed = channel_store.has_channel_buffer_changed(channel_id);
ListItem::new("channel-notes")
- .height(px(24.))
+ .height(rems_from_px(24.))
.toggle_state(is_selected)
.on_click(cx.listener(move |this, _, window, cx| {
this.open_channel_notes(channel_id, window, cx);
@@ -2665,26 +2682,28 @@ impl CollabPanel {
window: &mut Window,
cx: &mut Context<Self>,
) -> AnyElement {
- let entry = &self.entries[ix];
+ let entry = self.entries[ix].clone();
let is_selected = self.selection == Some(ix);
match entry {
ListEntry::Header(section) => {
- let is_collapsed = self.collapsed_sections.contains(section);
- self.render_header(*section, is_selected, is_collapsed, cx)
+ let is_collapsed = self.collapsed_sections.contains(§ion);
+ self.render_header(section, is_selected, is_collapsed, cx)
+ .into_any_element()
+ }
+ ListEntry::Contact { contact, calling } => {
+ self.mark_contact_request_accepted_notifications_read(contact.user.id, cx);
+ self.render_contact(&contact, calling, is_selected, cx)
.into_any_element()
}
- ListEntry::Contact { contact, calling } => self
- .render_contact(contact, *calling, is_selected, cx)
- .into_any_element(),
ListEntry::ContactPlaceholder => self
.render_contact_placeholder(is_selected, cx)
.into_any_element(),
ListEntry::IncomingRequest(user) => self
- .render_contact_request(user, true, is_selected, cx)
+ .render_contact_request(&user, true, is_selected, cx)
.into_any_element(),
ListEntry::OutgoingRequest(user) => self
- .render_contact_request(user, false, is_selected, cx)
+ .render_contact_request(&user, false, is_selected, cx)
.into_any_element(),
ListEntry::Channel {
channel,
@@ -2694,9 +2713,9 @@ impl CollabPanel {
..
} => self
.render_channel(
- channel,
- *depth,
- *has_children,
+ &channel,
+ depth,
+ has_children,
is_selected,
ix,
string_match.as_ref(),
@@ -2704,10 +2723,10 @@ impl CollabPanel {
)
.into_any_element(),
ListEntry::ChannelEditor { depth } => self
- .render_channel_editor(*depth, window, cx)
+ .render_channel_editor(depth, window, cx)
.into_any_element(),
ListEntry::ChannelInvite(channel) => self
- .render_channel_invite(channel, is_selected, cx)
+ .render_channel_invite(&channel, is_selected, cx)
.into_any_element(),
ListEntry::CallParticipant {
user,
@@ -2715,7 +2734,7 @@ impl CollabPanel {
is_pending,
role,
} => self
- .render_call_participant(user, *peer_id, *is_pending, *role, is_selected, cx)
+ .render_call_participant(&user, peer_id, is_pending, role, is_selected, cx)
.into_any_element(),
ListEntry::ParticipantProject {
project_id,
@@ -2724,20 +2743,20 @@ impl CollabPanel {
is_last,
} => self
.render_participant_project(
- *project_id,
- worktree_root_names,
- *host_user_id,
- *is_last,
+ project_id,
+ &worktree_root_names,
+ host_user_id,
+ is_last,
is_selected,
window,
cx,
)
.into_any_element(),
ListEntry::ParticipantScreen { peer_id, is_last } => self
- .render_participant_screen(*peer_id, *is_last, is_selected, window, cx)
+ .render_participant_screen(peer_id, is_last, is_selected, window, cx)
.into_any_element(),
ListEntry::ChannelNotes { channel_id } => self
- .render_channel_notes(*channel_id, is_selected, window, cx)
+ .render_channel_notes(channel_id, is_selected, window, cx)
.into_any_element(),
}
}
@@ -2846,11 +2865,11 @@ impl CollabPanel {
}
};
- Some(channel.name.as_ref())
+ Some(channel.name.clone())
});
if let Some(name) = channel_name {
- SharedString::from(name.to_string())
+ name
} else {
SharedString::from("Current Call")
}
@@ -3210,7 +3229,7 @@ impl CollabPanel {
(IconName::Star, Color::Default, "Add to Favorites")
};
- let height = px(24.);
+ let height = rems_from_px(24.);
h_flex()
.id(ix)
@@ -3397,6 +3416,178 @@ impl CollabPanel {
item.child(self.channel_name_editor.clone())
}
}
+
+ fn on_notification_event(
+ &mut self,
+ _: &Entity<NotificationStore>,
+ event: &NotificationEvent,
+ _window: &mut Window,
+ cx: &mut Context<Self>,
+ ) {
+ match event {
+ NotificationEvent::NewNotification { entry } => {
+ self.add_toast(entry, cx);
+ cx.notify();
+ }
+ NotificationEvent::NotificationRemoved { entry }
+ | NotificationEvent::NotificationRead { entry } => {
+ self.remove_toast(entry.id, cx);
+ cx.notify();
+ }
+ NotificationEvent::NotificationsUpdated { .. } => {
+ cx.notify();
+ }
+ }
+ }
+
+ fn present_notification(
+ &self,
+ entry: &NotificationEntry,
+ cx: &App,
+ ) -> Option<(Option<Arc<User>>, String)> {
+ let user_store = self.user_store.read(cx);
+ match &entry.notification {
+ Notification::ContactRequest { sender_id } => {
+ let requester = user_store.get_cached_user(*sender_id)?;
+ Some((
+ Some(requester.clone()),
+ format!("{} wants to add you as a contact", requester.github_login),
+ ))
+ }
+ Notification::ContactRequestAccepted { responder_id } => {
+ let responder = user_store.get_cached_user(*responder_id)?;
+ Some((
+ Some(responder.clone()),
+ format!("{} accepted your contact request", responder.github_login),
+ ))
+ }
+ Notification::ChannelInvitation {
+ channel_name,
+ inviter_id,
+ ..
+ } => {
+ let inviter = user_store.get_cached_user(*inviter_id)?;
+ Some((
+ Some(inviter.clone()),
+ format!(
+ "{} invited you to join the #{channel_name} channel",
+ inviter.github_login
+ ),
+ ))
+ }
+ }
+ }
+
+ fn add_toast(&mut self, entry: &NotificationEntry, cx: &mut Context<Self>) {
+ let Some((actor, text)) = self.present_notification(entry, cx) else {
+ return;
+ };
+
+ let notification = entry.notification.clone();
+ let needs_response = matches!(
+ notification,
+ Notification::ContactRequest { .. } | Notification::ChannelInvitation { .. }
+ );
+
+ let notification_id = entry.id;
+
+ self.current_notification_toast = Some((
+ notification_id,
+ cx.spawn(async move |this, cx| {
+ cx.background_executor().timer(TOAST_DURATION).await;
+ this.update(cx, |this, cx| this.remove_toast(notification_id, cx))
+ .ok();
+ }),
+ ));
+
+ let collab_panel = cx.entity().downgrade();
+ self.workspace
+ .update(cx, |workspace, cx| {
+ let id = NotificationId::unique::<CollabNotificationToast>();
+
+ workspace.dismiss_notification(&id, cx);
+ workspace.show_notification(id, cx, |cx| {
+ let workspace = cx.entity().downgrade();
+ cx.new(|cx| CollabNotificationToast {
+ actor,
+ text,
+ notification: needs_response.then(|| notification),
+ workspace,
+ collab_panel: collab_panel.clone(),
+ focus_handle: cx.focus_handle(),
+ })
+ })
+ })
+ .ok();
+ }
+
+ fn mark_notification_read(&mut self, notification_id: u64, cx: &mut Context<Self>) {
+ let client = self.client.clone();
+ self.mark_as_read_tasks
+ .entry(notification_id)
+ .or_insert_with(|| {
+ cx.spawn(async move |this, cx| {
+ let request_result = client
+ .request(proto::MarkNotificationRead { notification_id })
+ .await;
+
+ this.update(cx, |this, _| {
+ this.mark_as_read_tasks.remove(¬ification_id);
+ })?;
+
+ request_result?;
+ Ok(())
+ })
+ });
+ }
+
+ fn mark_contact_request_accepted_notifications_read(
+ &mut self,
+ contact_user_id: u64,
+ cx: &mut Context<Self>,
+ ) {
+ let notification_ids = self.notification_store.read_with(cx, |store, _| {
+ (0..store.notification_count())
+ .filter_map(|index| {
+ let entry = store.notification_at(index)?;
+ if entry.is_read {
+ return None;
+ }
+
+ match &entry.notification {
+ Notification::ContactRequestAccepted { responder_id }
+ if *responder_id == contact_user_id =>
+ {
+ Some(entry.id)
+ }
+ _ => None,
+ }
+ })
+ .collect::<Vec<_>>()
+ });
+
+ for notification_id in notification_ids {
+ self.mark_notification_read(notification_id, cx);
+ }
+ }
+
+ fn remove_toast(&mut self, notification_id: u64, cx: &mut Context<Self>) {
+ if let Some((current_id, _)) = &self.current_notification_toast {
+ if *current_id == notification_id {
+ self.dismiss_toast(cx);
+ }
+ }
+ }
+
+ fn dismiss_toast(&mut self, cx: &mut Context<Self>) {
+ self.current_notification_toast.take();
+ self.workspace
+ .update(cx, |workspace, cx| {
+ let id = NotificationId::unique::<CollabNotificationToast>();
+ workspace.dismiss_notification(&id, cx)
+ })
+ .ok();
+ }
}
fn render_tree_branch(
@@ -3516,12 +3707,38 @@ impl Panel for CollabPanel {
CollaborationPanelSettings::get_global(cx).default_width
}
+ fn set_active(&mut self, active: bool, _window: &mut Window, cx: &mut Context<Self>) {
+ if active && self.current_notification_toast.is_some() {
+ self.current_notification_toast.take();
+ let workspace = self.workspace.clone();
+ cx.defer(move |cx| {
+ workspace
+ .update(cx, |workspace, cx| {
+ let id = NotificationId::unique::<CollabNotificationToast>();
+ workspace.dismiss_notification(&id, cx)
+ })
+ .ok();
+ });
+ }
+ }
+
fn icon(&self, _window: &Window, cx: &App) -> Option<ui::IconName> {
CollaborationPanelSettings::get_global(cx)
.button
.then_some(ui::IconName::UserGroup)
}
+ fn icon_label(&self, _window: &Window, cx: &App) -> Option<String> {
+ let user_store = self.user_store.read(cx);
+ let count = user_store.incoming_contact_requests().len()
+ + self.channel_store.read(cx).channel_invitations().len();
+ if count == 0 {
+ None
+ } else {
+ Some(count.to_string())
+ }
+ }
+
fn icon_tooltip(&self, _window: &Window, _cx: &App) -> Option<&'static str> {
Some("Collab Panel")
}
@@ -3702,6 +3919,101 @@ impl Render for JoinChannelTooltip {
}
}
+pub struct CollabNotificationToast {
+ actor: Option<Arc<User>>,
+ text: String,
+ notification: Option<Notification>,
+ workspace: WeakEntity<Workspace>,
+ collab_panel: WeakEntity<CollabPanel>,
+ focus_handle: FocusHandle,
+}
+
+impl Focusable for CollabNotificationToast {
+ fn focus_handle(&self, _cx: &App) -> FocusHandle {
+ self.focus_handle.clone()
+ }
+}
+
+impl WorkspaceNotification for CollabNotificationToast {}
+
+impl CollabNotificationToast {
+ fn focus_collab_panel(&self, window: &mut Window, cx: &mut Context<Self>) {
+ let workspace = self.workspace.clone();
+ window.defer(cx, move |window, cx| {
+ workspace
+ .update(cx, |workspace, cx| {
+ workspace.focus_panel::<CollabPanel>(window, cx)
+ })
+ .ok();
+ })
+ }
+
+ fn respond(&mut self, accept: bool, window: &mut Window, cx: &mut Context<Self>) {
+ if let Some(notification) = self.notification.take() {
+ self.collab_panel
+ .update(cx, |collab_panel, cx| match notification {
+ Notification::ContactRequest { sender_id } => {
+ collab_panel.respond_to_contact_request(sender_id, accept, window, cx);
+ }
+ Notification::ChannelInvitation { channel_id, .. } => {
+ collab_panel.respond_to_channel_invite(ChannelId(channel_id), accept, cx);
+ }
+ Notification::ContactRequestAccepted { .. } => {}
+ })
+ .ok();
+ }
+ cx.emit(DismissEvent);
+ }
+}
+
+impl Render for CollabNotificationToast {
+ fn render(&mut self, _window: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
+ let needs_response = self.notification.is_some();
+
+ let accept_button = if needs_response {
+ Button::new("accept", "Accept").on_click(cx.listener(|this, _, window, cx| {
+ this.respond(true, window, cx);
+ cx.stop_propagation();
+ }))
+ } else {
+ Button::new("dismiss", "Dismiss").on_click(cx.listener(|_, _, _, cx| {
+ cx.emit(DismissEvent);
+ }))
+ };
+
+ let decline_button = if needs_response {
+ Button::new("decline", "Decline").on_click(cx.listener(|this, _, window, cx| {
+ this.respond(false, window, cx);
+ cx.stop_propagation();
+ }))
+ } else {
+ Button::new("close", "Close").on_click(cx.listener(|_, _, _, cx| {
+ cx.emit(DismissEvent);
+ }))
+ };
+
+ let avatar_uri = self
+ .actor
+ .as_ref()
+ .map(|user| user.avatar_uri.clone())
+ .unwrap_or_default();
+
+ div()
+ .id("collab_notification_toast")
+ .on_click(cx.listener(|this, _, window, cx| {
+ this.focus_collab_panel(window, cx);
+ cx.emit(DismissEvent);
+ }))
+ .child(
+ CollabNotification::new(avatar_uri, accept_button, decline_button)
+ .child(Label::new(self.text.clone())),
+ )
+ }
+}
+
+impl EventEmitter<DismissEvent> for CollabNotificationToast {}
+impl EventEmitter<SuppressEvent> for CollabNotificationToast {}
+
#[cfg(any(test, feature = "test-support"))]
impl CollabPanel {
pub fn entries_as_strings(&self) -> Vec<String> {
@@ -1,7 +1,6 @@
mod call_stats_modal;
pub mod channel_view;
pub mod collab_panel;
-pub mod notification_panel;
pub mod notifications;
mod panel_settings;
@@ -12,7 +11,7 @@ use gpui::{
App, Pixels, PlatformDisplay, Size, WindowBackgroundAppearance, WindowBounds,
WindowDecorations, WindowKind, WindowOptions, point,
};
-pub use panel_settings::{CollaborationPanelSettings, NotificationPanelSettings};
+pub use panel_settings::CollaborationPanelSettings;
use release_channel::ReleaseChannel;
use ui::px;
use workspace::AppState;
@@ -22,7 +21,6 @@ pub fn init(app_state: &Arc<AppState>, cx: &mut App) {
call_stats_modal::init(cx);
channel_view::init(cx);
collab_panel::init(cx);
- notification_panel::init(cx);
notifications::init(app_state, cx);
title_bar::init(cx);
}
@@ -1,727 +0,0 @@
-use crate::NotificationPanelSettings;
-use anyhow::Result;
-use channel::ChannelStore;
-use client::{ChannelId, Client, Notification, User, UserStore};
-use collections::HashMap;
-use futures::StreamExt;
-use gpui::{
- AnyElement, App, AsyncWindowContext, ClickEvent, Context, DismissEvent, Element, Entity,
- EventEmitter, FocusHandle, Focusable, InteractiveElement, IntoElement, ListAlignment,
- ListScrollEvent, ListState, ParentElement, Render, StatefulInteractiveElement, Styled, Task,
- WeakEntity, Window, actions, div, img, list, px,
-};
-use notifications::{NotificationEntry, NotificationEvent, NotificationStore};
-use project::Fs;
-use rpc::proto;
-
-use settings::{Settings, SettingsStore};
-use std::{sync::Arc, time::Duration};
-use time::{OffsetDateTime, UtcOffset};
-use ui::{
- Avatar, Button, Icon, IconButton, IconName, Label, Tab, Tooltip, h_flex, prelude::*, v_flex,
-};
-use util::ResultExt;
-use workspace::notifications::{
- Notification as WorkspaceNotification, NotificationId, SuppressEvent,
-};
-use workspace::{
- Workspace,
- dock::{DockPosition, Panel, PanelEvent},
-};
-
-const LOADING_THRESHOLD: usize = 30;
-const MARK_AS_READ_DELAY: Duration = Duration::from_secs(1);
-const TOAST_DURATION: Duration = Duration::from_secs(5);
-const NOTIFICATION_PANEL_KEY: &str = "NotificationPanel";
-
-pub struct NotificationPanel {
- client: Arc<Client>,
- user_store: Entity<UserStore>,
- channel_store: Entity<ChannelStore>,
- notification_store: Entity<NotificationStore>,
- fs: Arc<dyn Fs>,
- active: bool,
- notification_list: ListState,
- subscriptions: Vec<gpui::Subscription>,
- workspace: WeakEntity<Workspace>,
- current_notification_toast: Option<(u64, Task<()>)>,
- local_timezone: UtcOffset,
- focus_handle: FocusHandle,
- mark_as_read_tasks: HashMap<u64, Task<Result<()>>>,
- unseen_notifications: Vec<NotificationEntry>,
-}
-
-#[derive(Debug)]
-pub enum Event {
- DockPositionChanged,
- Focus,
- Dismissed,
-}
-
-pub struct NotificationPresenter {
- pub actor: Option<Arc<client::User>>,
- pub text: String,
- pub icon: &'static str,
- pub needs_response: bool,
-}
-
-actions!(
- notification_panel,
- [
- /// Toggles the notification panel.
- Toggle,
- /// Toggles focus on the notification panel.
- ToggleFocus
- ]
-);
-
-pub fn init(cx: &mut App) {
- cx.observe_new(|workspace: &mut Workspace, _, _| {
- workspace.register_action(|workspace, _: &ToggleFocus, window, cx| {
- workspace.toggle_panel_focus::<NotificationPanel>(window, cx);
- });
- workspace.register_action(|workspace, _: &Toggle, window, cx| {
- if !workspace.toggle_panel_focus::<NotificationPanel>(window, cx) {
- workspace.close_panel::<NotificationPanel>(window, cx);
- }
- });
- })
- .detach();
-}
-
-impl NotificationPanel {
- pub fn new(
- workspace: &mut Workspace,
- window: &mut Window,
- cx: &mut Context<Workspace>,
- ) -> Entity<Self> {
- let fs = workspace.app_state().fs.clone();
- let client = workspace.app_state().client.clone();
- let user_store = workspace.app_state().user_store.clone();
- let workspace_handle = workspace.weak_handle();
-
- cx.new(|cx| {
- let mut status = client.status();
- cx.spawn_in(window, async move |this, cx| {
- while (status.next().await).is_some() {
- if this
- .update(cx, |_: &mut Self, cx| {
- cx.notify();
- })
- .is_err()
- {
- break;
- }
- }
- })
- .detach();
-
- let notification_list = ListState::new(0, ListAlignment::Top, px(1000.));
- notification_list.set_scroll_handler(cx.listener(
- |this, event: &ListScrollEvent, _, cx| {
- if event.count.saturating_sub(event.visible_range.end) < LOADING_THRESHOLD
- && let Some(task) = this
- .notification_store
- .update(cx, |store, cx| store.load_more_notifications(false, cx))
- {
- task.detach();
- }
- },
- ));
-
- let local_offset = chrono::Local::now().offset().local_minus_utc();
- let mut this = Self {
- fs,
- client,
- user_store,
- local_timezone: UtcOffset::from_whole_seconds(local_offset).unwrap(),
- channel_store: ChannelStore::global(cx),
- notification_store: NotificationStore::global(cx),
- notification_list,
- workspace: workspace_handle,
- focus_handle: cx.focus_handle(),
- subscriptions: Default::default(),
- current_notification_toast: None,
- active: false,
- mark_as_read_tasks: Default::default(),
- unseen_notifications: Default::default(),
- };
-
- let mut old_dock_position = this.position(window, cx);
- this.subscriptions.extend([
- cx.observe(&this.notification_store, |_, _, cx| cx.notify()),
- cx.subscribe_in(
- &this.notification_store,
- window,
- Self::on_notification_event,
- ),
- cx.observe_global_in::<SettingsStore>(
- window,
- move |this: &mut Self, window, cx| {
- let new_dock_position = this.position(window, cx);
- if new_dock_position != old_dock_position {
- old_dock_position = new_dock_position;
- cx.emit(Event::DockPositionChanged);
- }
- cx.notify();
- },
- ),
- ]);
- this
- })
- }
-
- pub fn load(
- workspace: WeakEntity<Workspace>,
- cx: AsyncWindowContext,
- ) -> Task<Result<Entity<Self>>> {
- cx.spawn(async move |cx| {
- workspace.update_in(cx, |workspace, window, cx| Self::new(workspace, window, cx))
- })
- }
-
- fn render_notification(
- &mut self,
- ix: usize,
- window: &mut Window,
- cx: &mut Context<Self>,
- ) -> Option<AnyElement> {
- let entry = self.notification_store.read(cx).notification_at(ix)?;
- let notification_id = entry.id;
- let now = OffsetDateTime::now_utc();
- let timestamp = entry.timestamp;
- let NotificationPresenter {
- actor,
- text,
- needs_response,
- ..
- } = self.present_notification(entry, cx)?;
-
- let response = entry.response;
- let notification = entry.notification.clone();
-
- if self.active && !entry.is_read {
- self.did_render_notification(notification_id, ¬ification, window, cx);
- }
-
- let relative_timestamp = time_format::format_localized_timestamp(
- timestamp,
- now,
- self.local_timezone,
- time_format::TimestampFormat::Relative,
- );
-
- let absolute_timestamp = time_format::format_localized_timestamp(
- timestamp,
- now,
- self.local_timezone,
- time_format::TimestampFormat::Absolute,
- );
-
- Some(
- div()
- .id(ix)
- .flex()
- .flex_row()
- .size_full()
- .px_2()
- .py_1()
- .gap_2()
- .hover(|style| style.bg(cx.theme().colors().element_hover))
- .children(actor.map(|actor| {
- img(actor.avatar_uri.clone())
- .flex_none()
- .w_8()
- .h_8()
- .rounded_full()
- }))
- .child(
- v_flex()
- .gap_1()
- .size_full()
- .overflow_hidden()
- .child(Label::new(text))
- .child(
- h_flex()
- .child(
- div()
- .id("notification_timestamp")
- .hover(|style| {
- style
- .bg(cx.theme().colors().element_selected)
- .rounded_sm()
- })
- .child(Label::new(relative_timestamp).color(Color::Muted))
- .tooltip(move |_, cx| {
- Tooltip::simple(absolute_timestamp.clone(), cx)
- }),
- )
- .children(if let Some(is_accepted) = response {
- Some(div().flex().flex_grow().justify_end().child(Label::new(
- if is_accepted {
- "You accepted"
- } else {
- "You declined"
- },
- )))
- } else if needs_response {
- Some(
- h_flex()
- .flex_grow()
- .justify_end()
- .child(Button::new("decline", "Decline").on_click({
- let notification = notification.clone();
- let entity = cx.entity();
- move |_, _, cx| {
- entity.update(cx, |this, cx| {
- this.respond_to_notification(
- notification.clone(),
- false,
- cx,
- )
- });
- }
- }))
- .child(Button::new("accept", "Accept").on_click({
- let notification = notification.clone();
- let entity = cx.entity();
- move |_, _, cx| {
- entity.update(cx, |this, cx| {
- this.respond_to_notification(
- notification.clone(),
- true,
- cx,
- )
- });
- }
- })),
- )
- } else {
- None
- }),
- ),
- )
- .into_any(),
- )
- }
-
- fn present_notification(
- &self,
- entry: &NotificationEntry,
- cx: &App,
- ) -> Option<NotificationPresenter> {
- let user_store = self.user_store.read(cx);
- let channel_store = self.channel_store.read(cx);
- match entry.notification {
- Notification::ContactRequest { sender_id } => {
- let requester = user_store.get_cached_user(sender_id)?;
- Some(NotificationPresenter {
- icon: "icons/plus.svg",
- text: format!("{} wants to add you as a contact", requester.github_login),
- needs_response: user_store.has_incoming_contact_request(requester.id),
- actor: Some(requester),
- })
- }
- Notification::ContactRequestAccepted { responder_id } => {
- let responder = user_store.get_cached_user(responder_id)?;
- Some(NotificationPresenter {
- icon: "icons/plus.svg",
- text: format!("{} accepted your contact invite", responder.github_login),
- needs_response: false,
- actor: Some(responder),
- })
- }
- Notification::ChannelInvitation {
- ref channel_name,
- channel_id,
- inviter_id,
- } => {
- let inviter = user_store.get_cached_user(inviter_id)?;
- Some(NotificationPresenter {
- icon: "icons/hash.svg",
- text: format!(
- "{} invited you to join the #{channel_name} channel",
- inviter.github_login
- ),
- needs_response: channel_store.has_channel_invitation(ChannelId(channel_id)),
- actor: Some(inviter),
- })
- }
- }
- }
-
- fn did_render_notification(
- &mut self,
- notification_id: u64,
- notification: &Notification,
- window: &mut Window,
- cx: &mut Context<Self>,
- ) {
- let should_mark_as_read = match notification {
- Notification::ContactRequestAccepted { .. } => true,
- Notification::ContactRequest { .. } | Notification::ChannelInvitation { .. } => false,
- };
-
- if should_mark_as_read {
- self.mark_as_read_tasks
- .entry(notification_id)
- .or_insert_with(|| {
- let client = self.client.clone();
- cx.spawn_in(window, async move |this, cx| {
- cx.background_executor().timer(MARK_AS_READ_DELAY).await;
- client
- .request(proto::MarkNotificationRead { notification_id })
- .await?;
- this.update(cx, |this, _| {
- this.mark_as_read_tasks.remove(¬ification_id);
- })?;
- Ok(())
- })
- });
- }
- }
-
- fn on_notification_event(
- &mut self,
- _: &Entity<NotificationStore>,
- event: &NotificationEvent,
- window: &mut Window,
- cx: &mut Context<Self>,
- ) {
- match event {
- NotificationEvent::NewNotification { entry } => {
- self.unseen_notifications.push(entry.clone());
- self.add_toast(entry, window, cx);
- }
- NotificationEvent::NotificationRemoved { entry }
- | NotificationEvent::NotificationRead { entry } => {
- self.unseen_notifications.retain(|n| n.id != entry.id);
- self.remove_toast(entry.id, cx);
- }
- NotificationEvent::NotificationsUpdated {
- old_range,
- new_count,
- } => {
- self.notification_list.splice(old_range.clone(), *new_count);
- cx.notify();
- }
- }
- }
-
- fn add_toast(
- &mut self,
- entry: &NotificationEntry,
- window: &mut Window,
- cx: &mut Context<Self>,
- ) {
- let Some(NotificationPresenter { actor, text, .. }) = self.present_notification(entry, cx)
- else {
- return;
- };
-
- let notification_id = entry.id;
- self.current_notification_toast = Some((
- notification_id,
- cx.spawn_in(window, async move |this, cx| {
- cx.background_executor().timer(TOAST_DURATION).await;
- this.update(cx, |this, cx| this.remove_toast(notification_id, cx))
- .ok();
- }),
- ));
-
- self.workspace
- .update(cx, |workspace, cx| {
- let id = NotificationId::unique::<NotificationToast>();
-
- workspace.dismiss_notification(&id, cx);
- workspace.show_notification(id, cx, |cx| {
- let workspace = cx.entity().downgrade();
- cx.new(|cx| NotificationToast {
- actor,
- text,
- workspace,
- focus_handle: cx.focus_handle(),
- })
- })
- })
- .ok();
- }
-
- fn remove_toast(&mut self, notification_id: u64, cx: &mut Context<Self>) {
- if let Some((current_id, _)) = &self.current_notification_toast
- && *current_id == notification_id
- {
- self.current_notification_toast.take();
- self.workspace
- .update(cx, |workspace, cx| {
- let id = NotificationId::unique::<NotificationToast>();
- workspace.dismiss_notification(&id, cx)
- })
- .ok();
- }
- }
-
- fn respond_to_notification(
- &mut self,
- notification: Notification,
- response: bool,
-
- cx: &mut Context<Self>,
- ) {
- self.notification_store.update(cx, |store, cx| {
- store.respond_to_notification(notification, response, cx);
- });
- }
-}
-
-impl Render for NotificationPanel {
- fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
- v_flex()
- .size_full()
- .child(
- h_flex()
- .justify_between()
- .px_2()
- .py_1()
- // Match the height of the tab bar so they line up.
- .h(Tab::container_height(cx))
- .border_b_1()
- .border_color(cx.theme().colors().border)
- .child(Label::new("Notifications"))
- .child(Icon::new(IconName::Envelope)),
- )
- .map(|this| {
- if !self.client.status().borrow().is_connected() {
- this.child(
- v_flex()
- .gap_2()
- .p_4()
- .child(
- Button::new("connect_prompt_button", "Connect")
- .start_icon(Icon::new(IconName::Github).color(Color::Muted))
- .style(ButtonStyle::Filled)
- .full_width()
- .on_click({
- let client = self.client.clone();
- move |_, window, cx| {
- let client = client.clone();
- window
- .spawn(cx, async move |cx| {
- match client.connect(true, cx).await {
- util::ConnectionResult::Timeout => {
- log::error!("Connection timeout");
- }
- util::ConnectionResult::ConnectionReset => {
- log::error!("Connection reset");
- }
- util::ConnectionResult::Result(r) => {
- r.log_err();
- }
- }
- })
- .detach()
- }
- }),
- )
- .child(
- div().flex().w_full().items_center().child(
- Label::new("Connect to view notifications.")
- .color(Color::Muted)
- .size(LabelSize::Small),
- ),
- ),
- )
- } else if self.notification_list.item_count() == 0 {
- this.child(
- v_flex().p_4().child(
- div().flex().w_full().items_center().child(
- Label::new("You have no notifications.")
- .color(Color::Muted)
- .size(LabelSize::Small),
- ),
- ),
- )
- } else {
- this.child(
- list(
- self.notification_list.clone(),
- cx.processor(|this, ix, window, cx| {
- this.render_notification(ix, window, cx)
- .unwrap_or_else(|| div().into_any())
- }),
- )
- .size_full(),
- )
- }
- })
- }
-}
-
-impl Focusable for NotificationPanel {
- fn focus_handle(&self, _: &App) -> FocusHandle {
- self.focus_handle.clone()
- }
-}
-
-impl EventEmitter<Event> for NotificationPanel {}
-impl EventEmitter<PanelEvent> for NotificationPanel {}
-
-impl Panel for NotificationPanel {
- fn persistent_name() -> &'static str {
- "NotificationPanel"
- }
-
- fn panel_key() -> &'static str {
- NOTIFICATION_PANEL_KEY
- }
-
- fn position(&self, _: &Window, cx: &App) -> DockPosition {
- NotificationPanelSettings::get_global(cx).dock
- }
-
- fn position_is_valid(&self, position: DockPosition) -> bool {
- matches!(position, DockPosition::Left | DockPosition::Right)
- }
-
- fn set_position(&mut self, position: DockPosition, _: &mut Window, cx: &mut Context<Self>) {
- settings::update_settings_file(self.fs.clone(), cx, move |settings, _| {
- settings.notification_panel.get_or_insert_default().dock = Some(position.into())
- });
- }
-
- fn default_size(&self, _: &Window, cx: &App) -> Pixels {
- NotificationPanelSettings::get_global(cx).default_width
- }
-
- fn set_active(&mut self, active: bool, _: &mut Window, cx: &mut Context<Self>) {
- self.active = active;
-
- if self.active {
- self.unseen_notifications = Vec::new();
- cx.notify();
- }
-
- if self.notification_store.read(cx).notification_count() == 0 {
- cx.emit(Event::Dismissed);
- }
- }
-
- fn icon(&self, _: &Window, cx: &App) -> Option<IconName> {
- let show_button = NotificationPanelSettings::get_global(cx).button;
- if !show_button {
- return None;
- }
-
- if self.unseen_notifications.is_empty() {
- return Some(IconName::Bell);
- }
-
- Some(IconName::BellDot)
- }
-
- fn icon_tooltip(&self, _window: &Window, _cx: &App) -> Option<&'static str> {
- Some("Notification Panel")
- }
-
- fn icon_label(&self, _window: &Window, cx: &App) -> Option<String> {
- if !NotificationPanelSettings::get_global(cx).show_count_badge {
- return None;
- }
- let count = self.notification_store.read(cx).unread_notification_count();
- if count == 0 {
- None
- } else {
- Some(count.to_string())
- }
- }
-
- fn toggle_action(&self) -> Box<dyn gpui::Action> {
- Box::new(ToggleFocus)
- }
-
- fn activation_priority(&self) -> u32 {
- 4
- }
-}
-
-pub struct NotificationToast {
- actor: Option<Arc<User>>,
- text: String,
- workspace: WeakEntity<Workspace>,
- focus_handle: FocusHandle,
-}
-
-impl Focusable for NotificationToast {
- fn focus_handle(&self, _cx: &App) -> FocusHandle {
- self.focus_handle.clone()
- }
-}
-
-impl WorkspaceNotification for NotificationToast {}
-
-impl NotificationToast {
- fn focus_notification_panel(&self, window: &mut Window, cx: &mut Context<Self>) {
- let workspace = self.workspace.clone();
- window.defer(cx, move |window, cx| {
- workspace
- .update(cx, |workspace, cx| {
- workspace.focus_panel::<NotificationPanel>(window, cx)
- })
- .ok();
- })
- }
-}
-
-impl Render for NotificationToast {
- fn render(&mut self, window: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
- let user = self.actor.clone();
-
- let suppress = window.modifiers().shift;
- let (close_id, close_icon) = if suppress {
- ("suppress", IconName::Minimize)
- } else {
- ("close", IconName::Close)
- };
-
- h_flex()
- .id("notification_panel_toast")
- .elevation_3(cx)
- .p_2()
- .justify_between()
- .children(user.map(|user| Avatar::new(user.avatar_uri.clone())))
- .child(Label::new(self.text.clone()))
- .on_modifiers_changed(cx.listener(|_, _, _, cx| cx.notify()))
- .child(
- IconButton::new(close_id, close_icon)
- .tooltip(move |_window, cx| {
- if suppress {
- Tooltip::for_action(
- "Suppress.\nClose with click.",
- &workspace::SuppressNotification,
- cx,
- )
- } else {
- Tooltip::for_action(
- "Close.\nSuppress with shift-click",
- &menu::Cancel,
- cx,
- )
- }
- })
- .on_click(cx.listener(move |_, _: &ClickEvent, _, cx| {
- if suppress {
- cx.emit(SuppressEvent);
- } else {
- cx.emit(DismissEvent);
- }
- })),
- )
- .on_click(cx.listener(|this, _, window, cx| {
- this.focus_notification_panel(window, cx);
- cx.emit(DismissEvent);
- }))
- }
-}
-
-impl EventEmitter<DismissEvent> for NotificationToast {}
-impl EventEmitter<SuppressEvent> for NotificationToast {}
@@ -10,14 +10,6 @@ pub struct CollaborationPanelSettings {
pub default_width: Pixels,
}
-#[derive(Debug, RegisterSetting)]
-pub struct NotificationPanelSettings {
- pub button: bool,
- pub dock: DockPosition,
- pub default_width: Pixels,
- pub show_count_badge: bool,
-}
-
impl Settings for CollaborationPanelSettings {
fn from_settings(content: &settings::SettingsContent) -> Self {
let panel = content.collaboration_panel.as_ref().unwrap();
@@ -29,15 +21,3 @@ impl Settings for CollaborationPanelSettings {
}
}
}
-
-impl Settings for NotificationPanelSettings {
- fn from_settings(content: &settings::SettingsContent) -> Self {
- let panel = content.notification_panel.as_ref().unwrap();
- return Self {
- button: panel.button.unwrap(),
- dock: panel.dock.unwrap().into(),
- default_width: panel.default_width.map(px).unwrap(),
- show_count_badge: panel.show_count_badge.unwrap(),
- };
- }
-}
@@ -21,8 +21,9 @@ heapless.workspace = true
buffer_diff.workspace = true
client.workspace = true
clock.workspace = true
+cloud_api_client.workspace = true
cloud_api_types.workspace = true
-cloud_llm_client.workspace = true
+cloud_llm_client = { workspace = true, features = ["predict-edits"] }
collections.workspace = true
copilot.workspace = true
copilot_ui.workspace = true
@@ -1,5 +1,6 @@
use anyhow::Result;
use client::{Client, EditPredictionUsage, NeedsLlmTokenRefresh, UserStore, global_llm_token};
+use cloud_api_client::LlmApiToken;
use cloud_api_types::{OrganizationId, SubmitEditPredictionFeedbackBody};
use cloud_llm_client::predict_edits_v3::{
PredictEditsV3Request, PredictEditsV3Response, RawCompletionRequest, RawCompletionResponse,
@@ -31,7 +32,6 @@ use heapless::Vec as ArrayVec;
use language::language_settings::all_language_settings;
use language::{Anchor, Buffer, File, Point, TextBufferSnapshot, ToOffset, ToPoint};
use language::{BufferSnapshot, OffsetRangeExt};
-use language_model::LlmApiToken;
use project::{DisableAiSettings, Project, ProjectPath, WorktreeId};
use release_channel::AppVersion;
use semver::Version;
@@ -57,7 +57,7 @@ pub fn fetch_models(cx: &mut App) -> Vec<SharedString> {
let mut models: Vec<SharedString> = provider
.provided_models(cx)
.into_iter()
- .map(|model| SharedString::from(model.id().0.to_string()))
+ .map(|model| model.id().0)
.collect();
models.sort();
models
@@ -177,7 +177,7 @@ impl EditPredictionDelegate for ZedEditPredictionDelegate {
BufferEditPrediction::Local { prediction } => prediction,
BufferEditPrediction::Jump { prediction } => {
return Some(edit_prediction_types::EditPrediction::Jump {
- id: Some(prediction.id.to_string().into()),
+ id: Some(prediction.id.0.clone()),
snapshot: prediction.snapshot.clone(),
target: prediction.edits.first().unwrap().0.start,
});
@@ -228,7 +228,7 @@ impl EditPredictionDelegate for ZedEditPredictionDelegate {
}
Some(edit_prediction_types::EditPrediction::Local {
- id: Some(prediction.id.to_string().into()),
+ id: Some(prediction.id.0.clone()),
edits: edits[edit_start_ix..edit_end_ix].to_vec(),
cursor_position: prediction.cursor_position,
edit_preview: Some(prediction.edit_preview.clone()),
@@ -22,7 +22,7 @@ http_client.workspace = true
chrono.workspace = true
clap = "4"
client.workspace = true
-cloud_llm_client.workspace= true
+cloud_llm_client = { workspace = true, features = ["predict-edits"] }
collections.workspace = true
db.workspace = true
debug_adapter_extension.workspace = true
@@ -98,7 +98,7 @@ use gpui::{
WeakEntity,
};
use language::{
- Point, Subscription as BufferSubscription,
+ LanguageAwareStyling, Point, Subscription as BufferSubscription,
language_settings::{AllLanguageSettings, LanguageSettings},
};
@@ -1769,7 +1769,10 @@ impl DisplaySnapshot {
self.block_snapshot
.chunks(
BlockRow(display_row.0)..BlockRow(self.max_point().row().next_row().0),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
self.masked,
Highlights::default(),
)
@@ -1783,7 +1786,10 @@ impl DisplaySnapshot {
self.block_snapshot
.chunks(
BlockRow(row)..BlockRow(row + 1),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
self.masked,
Highlights::default(),
)
@@ -1798,7 +1804,7 @@ impl DisplaySnapshot {
pub fn chunks(
&self,
display_rows: Range<DisplayRow>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
highlight_styles: HighlightStyles,
) -> DisplayChunks<'_> {
self.block_snapshot.chunks(
@@ -1818,7 +1824,7 @@ impl DisplaySnapshot {
pub fn highlighted_chunks<'a>(
&'a self,
display_rows: Range<DisplayRow>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
editor_style: &'a EditorStyle,
) -> impl Iterator<Item = HighlightedChunk<'a>> {
self.chunks(
@@ -1910,7 +1916,10 @@ impl DisplaySnapshot {
let chunks = custom_highlights::CustomHighlightsChunks::new(
multibuffer_range,
- true,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
None,
Some(&self.semantic_token_highlights),
multibuffer,
@@ -1961,7 +1970,14 @@ impl DisplaySnapshot {
let mut line = String::new();
let range = display_row..display_row.next_row();
- for chunk in self.highlighted_chunks(range, false, editor_style) {
+ for chunk in self.highlighted_chunks(
+ range,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ editor_style,
+ ) {
line.push_str(chunk.text);
let text_style = if let Some(style) = chunk.style {
@@ -3388,7 +3404,14 @@ pub mod tests {
let snapshot = map.update(cx, |map, cx| map.snapshot(cx));
let mut chunks = Vec::<(String, Option<lsp::DiagnosticSeverity>, Rgba)>::new();
- for chunk in snapshot.chunks(DisplayRow(0)..DisplayRow(5), true, Default::default()) {
+ for chunk in snapshot.chunks(
+ DisplayRow(0)..DisplayRow(5),
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ Default::default(),
+ ) {
let color = chunk
.highlight_style
.and_then(|style| style.color)
@@ -3940,7 +3963,14 @@ pub mod tests {
) -> Vec<(String, Option<Hsla>, Option<Hsla>)> {
let snapshot = map.update(cx, |map, cx| map.snapshot(cx));
let mut chunks: Vec<(String, Option<Hsla>, Option<Hsla>)> = Vec::new();
- for chunk in snapshot.chunks(rows, true, HighlightStyles::default()) {
+ for chunk in snapshot.chunks(
+ rows,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ HighlightStyles::default(),
+ ) {
let syntax_color = chunk
.syntax_highlight_id
.and_then(|id| theme.get(id)?.color);
@@ -9,7 +9,7 @@ use crate::{
};
use collections::{Bound, HashMap, HashSet};
use gpui::{AnyElement, App, EntityId, Pixels, Window};
-use language::{Patch, Point};
+use language::{LanguageAwareStyling, Patch, Point};
use multi_buffer::{
Anchor, ExcerptBoundaryInfo, MultiBuffer, MultiBufferOffset, MultiBufferPoint, MultiBufferRow,
MultiBufferSnapshot, RowInfo, ToOffset, ToPoint as _,
@@ -2140,7 +2140,10 @@ impl BlockSnapshot {
pub fn text(&self) -> String {
self.chunks(
BlockRow(0)..self.transforms.summary().output_rows,
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
false,
Highlights::default(),
)
@@ -2152,7 +2155,7 @@ impl BlockSnapshot {
pub(crate) fn chunks<'a>(
&'a self,
rows: Range<BlockRow>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
masked: bool,
highlights: Highlights<'a>,
) -> BlockChunks<'a> {
@@ -4300,7 +4303,10 @@ mod tests {
let actual_text = blocks_snapshot
.chunks(
BlockRow(start_row as u32)..BlockRow(end_row as u32),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
false,
Highlights::default(),
)
@@ -1,6 +1,6 @@
use collections::BTreeMap;
use gpui::HighlightStyle;
-use language::Chunk;
+use language::{Chunk, LanguageAwareStyling};
use multi_buffer::{MultiBufferChunks, MultiBufferOffset, MultiBufferSnapshot, ToOffset as _};
use std::{
cmp,
@@ -34,7 +34,7 @@ impl<'a> CustomHighlightsChunks<'a> {
#[ztracing::instrument(skip_all)]
pub fn new(
range: Range<MultiBufferOffset>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
text_highlights: Option<&'a TextHighlights>,
semantic_token_highlights: Option<&'a SemanticTokensHighlights>,
multibuffer_snapshot: &'a MultiBufferSnapshot,
@@ -308,7 +308,10 @@ mod tests {
// Get all chunks and verify their bitmaps
let chunks = CustomHighlightsChunks::new(
MultiBufferOffset(0)..buffer_snapshot.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
None,
None,
&buffer_snapshot,
@@ -5,7 +5,7 @@ use super::{
inlay_map::{InlayBufferRows, InlayChunks, InlayEdit, InlayOffset, InlayPoint, InlaySnapshot},
};
use gpui::{AnyElement, App, ElementId, HighlightStyle, Pixels, SharedString, Stateful, Window};
-use language::{Edit, HighlightId, Point};
+use language::{Edit, HighlightId, LanguageAwareStyling, Point};
use multi_buffer::{
Anchor, AnchorRangeExt, MBTextSummary, MultiBufferOffset, MultiBufferRow, MultiBufferSnapshot,
RowInfo, ToOffset,
@@ -707,7 +707,10 @@ impl FoldSnapshot {
pub fn text(&self) -> String {
self.chunks(
FoldOffset(MultiBufferOffset(0))..self.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
)
.map(|c| c.text)
@@ -909,7 +912,7 @@ impl FoldSnapshot {
pub(crate) fn chunks<'a>(
&'a self,
range: Range<FoldOffset>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
highlights: Highlights<'a>,
) -> FoldChunks<'a> {
let mut transform_cursor = self
@@ -954,7 +957,10 @@ impl FoldSnapshot {
pub fn chars_at(&self, start: FoldPoint) -> impl '_ + Iterator<Item = char> {
self.chunks(
start.to_offset(self)..self.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
)
.flat_map(|chunk| chunk.text.chars())
@@ -964,7 +970,10 @@ impl FoldSnapshot {
pub fn chunks_at(&self, start: FoldPoint) -> FoldChunks<'_> {
self.chunks(
start.to_offset(self)..self.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
)
}
@@ -2131,7 +2140,14 @@ mod tests {
let text = &expected_text[start.0.0..end.0.0];
assert_eq!(
snapshot
- .chunks(start..end, false, Highlights::default())
+ .chunks(
+ start..end,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ Highlights::default()
+ )
.map(|c| c.text)
.collect::<String>(),
text,
@@ -2303,7 +2319,10 @@ mod tests {
// Get all chunks and verify their bitmaps
let chunks = snapshot.chunks(
FoldOffset(MultiBufferOffset(0))..FoldOffset(snapshot.len().0),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
);
@@ -10,7 +10,7 @@ use crate::{
inlays::{Inlay, InlayContent},
};
use collections::BTreeSet;
-use language::{Chunk, Edit, Point, TextSummary};
+use language::{Chunk, Edit, LanguageAwareStyling, Point, TextSummary};
use multi_buffer::{
MBTextSummary, MultiBufferOffset, MultiBufferRow, MultiBufferRows, MultiBufferSnapshot,
RowInfo, ToOffset,
@@ -1200,7 +1200,7 @@ impl InlaySnapshot {
pub(crate) fn chunks<'a>(
&'a self,
range: Range<InlayOffset>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
highlights: Highlights<'a>,
) -> InlayChunks<'a> {
let mut cursor = self
@@ -1234,9 +1234,16 @@ impl InlaySnapshot {
#[cfg(test)]
#[ztracing::instrument(skip_all)]
pub fn text(&self) -> String {
- self.chunks(Default::default()..self.len(), false, Highlights::default())
- .map(|chunk| chunk.chunk.text)
- .collect()
+ self.chunks(
+ Default::default()..self.len(),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ Highlights::default(),
+ )
+ .map(|chunk| chunk.chunk.text)
+ .collect()
}
#[ztracing::instrument(skip_all)]
@@ -1979,7 +1986,10 @@ mod tests {
let actual_text = inlay_snapshot
.chunks(
range,
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights {
text_highlights: Some(&text_highlights),
inlay_highlights: Some(&inlay_highlights),
@@ -2158,7 +2168,10 @@ mod tests {
// Get all chunks and verify their bitmaps
let chunks = snapshot.chunks(
InlayOffset(MultiBufferOffset(0))..snapshot.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
);
@@ -2293,7 +2306,10 @@ mod tests {
let chunks: Vec<_> = inlay_snapshot
.chunks(
InlayOffset(MultiBufferOffset(0))..inlay_snapshot.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
highlights,
)
.collect();
@@ -2408,7 +2424,10 @@ mod tests {
let chunks: Vec<_> = inlay_snapshot
.chunks(
InlayOffset(MultiBufferOffset(0))..inlay_snapshot.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
highlights,
)
.collect();
@@ -3,7 +3,7 @@ use super::{
fold_map::{self, Chunk, FoldChunks, FoldEdit, FoldPoint, FoldSnapshot},
};
-use language::Point;
+use language::{LanguageAwareStyling, Point};
use multi_buffer::MultiBufferSnapshot;
use std::{cmp, num::NonZeroU32, ops::Range};
use sum_tree::Bias;
@@ -101,7 +101,10 @@ impl TabMap {
let mut last_tab_with_changed_expansion_offset = None;
'outer: for chunk in old_snapshot.fold_snapshot.chunks(
fold_edit.old.end..old_end_row_successor_offset,
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
) {
let mut remaining_tabs = chunk.tabs;
@@ -244,7 +247,14 @@ impl TabSnapshot {
self.max_point()
};
let first_line_chars = self
- .chunks(range.start..line_end, false, Highlights::default())
+ .chunks(
+ range.start..line_end,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ Highlights::default(),
+ )
.flat_map(|chunk| chunk.text.chars())
.take_while(|&c| c != '\n')
.count() as u32;
@@ -254,7 +264,10 @@ impl TabSnapshot {
} else {
self.chunks(
TabPoint::new(range.end.row(), 0)..range.end,
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
)
.flat_map(|chunk| chunk.text.chars())
@@ -274,7 +287,7 @@ impl TabSnapshot {
pub(crate) fn chunks<'a>(
&'a self,
range: Range<TabPoint>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
highlights: Highlights<'a>,
) -> TabChunks<'a> {
let (input_start, expanded_char_column, to_next_stop) =
@@ -324,7 +337,10 @@ impl TabSnapshot {
pub fn text(&self) -> String {
self.chunks(
TabPoint::zero()..self.max_point(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
)
.map(|chunk| chunk.text)
@@ -1170,7 +1186,10 @@ mod tests {
tab_snapshot
.chunks(
TabPoint::new(0, ix as u32)..tab_snapshot.max_point(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
)
.map(|c| c.text)
@@ -1246,8 +1265,14 @@ mod tests {
let mut chunks = Vec::new();
let mut was_tab = false;
let mut text = String::new();
- for chunk in snapshot.chunks(start..snapshot.max_point(), false, Highlights::default())
- {
+ for chunk in snapshot.chunks(
+ start..snapshot.max_point(),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ Highlights::default(),
+ ) {
if chunk.is_tab != was_tab {
if !text.is_empty() {
chunks.push((mem::take(&mut text), was_tab));
@@ -1296,7 +1321,14 @@ mod tests {
// This should not panic.
let result: String = tab_snapshot
- .chunks(start..end, false, Highlights::default())
+ .chunks(
+ start..end,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ Highlights::default(),
+ )
.map(|c| c.text)
.collect();
assert!(!result.is_empty());
@@ -1354,7 +1386,14 @@ mod tests {
let expected_summary = TextSummary::from(expected_text.as_str());
assert_eq!(
tabs_snapshot
- .chunks(start..end, false, Highlights::default())
+ .chunks(
+ start..end,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ Highlights::default()
+ )
.map(|c| c.text)
.collect::<String>(),
expected_text,
@@ -1436,7 +1475,10 @@ mod tests {
let (_, fold_snapshot) = FoldMap::new(inlay_snapshot);
let chunks = fold_snapshot.chunks(
FoldOffset(MultiBufferOffset(0))..fold_snapshot.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Default::default(),
);
let mut cursor = TabStopCursor::new(chunks);
@@ -1598,7 +1640,10 @@ mod tests {
let (_, fold_snapshot) = FoldMap::new(inlay_snapshot);
let chunks = fold_snapshot.chunks(
FoldOffset(MultiBufferOffset(0))..fold_snapshot.len(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Default::default(),
);
let mut cursor = TabStopCursor::new(chunks);
@@ -5,7 +5,7 @@ use super::{
tab_map::{self, TabEdit, TabPoint, TabSnapshot},
};
use gpui::{App, AppContext as _, Context, Entity, Font, LineWrapper, Pixels, Task};
-use language::Point;
+use language::{LanguageAwareStyling, Point};
use multi_buffer::{MultiBufferSnapshot, RowInfo};
use smol::future::yield_now;
use std::{cmp, collections::VecDeque, mem, ops::Range, sync::LazyLock, time::Duration};
@@ -513,7 +513,10 @@ impl WrapSnapshot {
let mut remaining = None;
let mut chunks = new_tab_snapshot.chunks(
TabPoint::new(edit.new_rows.start, 0)..new_tab_snapshot.max_point(),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
);
let mut edit_transforms = Vec::<Transform>::new();
@@ -656,7 +659,7 @@ impl WrapSnapshot {
pub(crate) fn chunks<'a>(
&'a self,
rows: Range<WrapRow>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
highlights: Highlights<'a>,
) -> WrapChunks<'a> {
let output_start = WrapPoint::new(rows.start, 0);
@@ -960,7 +963,10 @@ impl WrapSnapshot {
pub fn text_chunks(&self, wrap_row: WrapRow) -> impl Iterator<Item = &str> {
self.chunks(
wrap_row..self.max_point().row() + WrapRow(1),
- false,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
Highlights::default(),
)
.map(|h| h.text)
@@ -1719,7 +1725,10 @@ mod tests {
let actual_text = self
.chunks(
WrapRow(start_row)..WrapRow(end_row),
- true,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
Highlights::default(),
)
.map(|c| c.text)
@@ -132,9 +132,9 @@ use language::{
AutoindentMode, BlockCommentConfig, BracketMatch, BracketPair, Buffer, BufferRow,
BufferSnapshot, Capability, CharClassifier, CharKind, CharScopeContext, CodeLabel, CursorShape,
DiagnosticEntryRef, DiffOptions, EditPredictionsMode, EditPreview, HighlightedText, IndentKind,
- IndentSize, Language, LanguageName, LanguageRegistry, LanguageScope, LocalFile, OffsetRangeExt,
- OutlineItem, Point, Selection, SelectionGoal, TextObject, TransactionId, TreeSitterOptions,
- WordsQuery,
+ IndentSize, Language, LanguageAwareStyling, LanguageName, LanguageRegistry, LanguageScope,
+ LocalFile, OffsetRangeExt, OutlineItem, Point, Selection, SelectionGoal, TextObject,
+ TransactionId, TreeSitterOptions, WordsQuery,
language_settings::{
self, AllLanguageSettings, LanguageSettings, LspInsertMode, RewrapBehavior,
WordsCompletionMode, all_language_settings,
@@ -1265,6 +1265,7 @@ pub struct Editor {
>,
use_autoclose: bool,
use_auto_surround: bool,
+ use_selection_highlight: bool,
auto_replace_emoji_shortcode: bool,
jsx_tag_auto_close_enabled_in_any_buffer: bool,
show_git_blame_gutter: bool,
@@ -2468,6 +2469,7 @@ impl Editor {
read_only: is_minimap,
use_autoclose: true,
use_auto_surround: true,
+ use_selection_highlight: true,
auto_replace_emoji_shortcode: false,
jsx_tag_auto_close_enabled_in_any_buffer: false,
leader_id: None,
@@ -3547,6 +3549,10 @@ impl Editor {
self.use_autoclose = autoclose;
}
+ pub fn set_use_selection_highlight(&mut self, highlight: bool) {
+ self.use_selection_highlight = highlight;
+ }
+
pub fn set_use_auto_surround(&mut self, auto_surround: bool) {
self.use_auto_surround = auto_surround;
}
@@ -7699,7 +7705,7 @@ impl Editor {
if matches!(self.mode, EditorMode::SingleLine) {
return None;
}
- if !EditorSettings::get_global(cx).selection_highlight {
+ if !self.use_selection_highlight || !EditorSettings::get_global(cx).selection_highlight {
return None;
}
if self.selections.count() != 1 || self.selections.line_mode() {
@@ -19147,7 +19153,13 @@ impl Editor {
let range = buffer.anchor_before(rename_start)..buffer.anchor_after(rename_end);
let mut old_highlight_id = None;
let old_name: Arc<str> = buffer
- .chunks(rename_start..rename_end, true)
+ .chunks(
+ rename_start..rename_end,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ )
.map(|chunk| {
if old_highlight_id.is_none() {
old_highlight_id = chunk.syntax_highlight_id;
@@ -25005,7 +25017,13 @@ impl Editor {
selection.range()
};
- let chunks = snapshot.chunks(range, true);
+ let chunks = snapshot.chunks(
+ range,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ );
let mut lines = Vec::new();
let mut line: VecDeque<Chunk> = VecDeque::new();
@@ -51,7 +51,10 @@ use gpui::{
pattern_slash, point, px, quad, relative, size, solid_background, transparent_black,
};
use itertools::Itertools;
-use language::{HighlightedText, IndentGuideSettings, language_settings::ShowWhitespaceSetting};
+use language::{
+ HighlightedText, IndentGuideSettings, LanguageAwareStyling,
+ language_settings::ShowWhitespaceSetting,
+};
use markdown::Markdown;
use multi_buffer::{
Anchor, ExcerptBoundaryInfo, ExpandExcerptDirection, ExpandInfo, MultiBufferPoint,
@@ -3819,7 +3822,11 @@ impl EditorElement {
} else {
let use_tree_sitter = !snapshot.semantic_tokens_enabled
|| snapshot.use_tree_sitter_for_syntax(rows.start, cx);
- let chunks = snapshot.highlighted_chunks(rows.clone(), use_tree_sitter, style);
+ let language_aware = LanguageAwareStyling {
+ tree_sitter: use_tree_sitter,
+ diagnostics: true,
+ };
+ let chunks = snapshot.highlighted_chunks(rows.clone(), language_aware, style);
LineWithInvisibles::from_chunks(
chunks,
style,
@@ -11999,7 +12006,11 @@ pub fn layout_line(
) -> LineWithInvisibles {
let use_tree_sitter =
!snapshot.semantic_tokens_enabled || snapshot.use_tree_sitter_for_syntax(row, cx);
- let chunks = snapshot.highlighted_chunks(row..row + DisplayRow(1), use_tree_sitter, style);
+ let language_aware = LanguageAwareStyling {
+ tree_sitter: use_tree_sitter,
+ diagnostics: true,
+ };
+ let chunks = snapshot.highlighted_chunks(row..row + DisplayRow(1), language_aware, style);
LineWithInvisibles::from_chunks(
chunks,
style,
@@ -475,13 +475,17 @@ mod tests {
use gpui::{
AppContext as _, Entity, Focusable as _, HighlightStyle, TestAppContext, UpdateGlobal as _,
};
- use language::{Language, LanguageConfig, LanguageMatcher};
+ use language::{
+ Diagnostic, DiagnosticEntry, DiagnosticSet, Language, LanguageAwareStyling, LanguageConfig,
+ LanguageMatcher,
+ };
use languages::FakeLspAdapter;
+ use lsp::LanguageServerId;
use multi_buffer::{
AnchorRangeExt, ExpandExcerptDirection, MultiBuffer, MultiBufferOffset, PathKey,
};
use project::Project;
- use rope::Point;
+ use rope::{Point, PointUtf16};
use serde_json::json;
use settings::{
GlobalLspSettingsContent, LanguageSettingsContent, SemanticTokenRule, SemanticTokenRules,
@@ -2088,6 +2092,130 @@ mod tests {
);
}
+ #[gpui::test]
+ async fn test_diagnostics_visible_when_semantic_token_set_to_full(cx: &mut TestAppContext) {
+ init_test(cx, |_| {});
+
+ update_test_language_settings(cx, &|language_settings| {
+ language_settings.languages.0.insert(
+ "Rust".into(),
+ LanguageSettingsContent {
+ semantic_tokens: Some(SemanticTokens::Full),
+ ..LanguageSettingsContent::default()
+ },
+ );
+ });
+
+ let mut cx = EditorLspTestContext::new_rust(
+ lsp::ServerCapabilities {
+ semantic_tokens_provider: Some(
+ lsp::SemanticTokensServerCapabilities::SemanticTokensOptions(
+ lsp::SemanticTokensOptions {
+ legend: lsp::SemanticTokensLegend {
+ token_types: vec!["function".into()],
+ token_modifiers: Vec::new(),
+ },
+ full: Some(lsp::SemanticTokensFullOptions::Delta { delta: None }),
+ ..lsp::SemanticTokensOptions::default()
+ },
+ ),
+ ),
+ ..lsp::ServerCapabilities::default()
+ },
+ cx,
+ )
+ .await;
+
+ let mut full_request = cx
+ .set_request_handler::<lsp::request::SemanticTokensFullRequest, _, _>(
+ move |_, _, _| {
+ async move {
+ Ok(Some(lsp::SemanticTokensResult::Tokens(
+ lsp::SemanticTokens {
+ data: vec![
+ 0, // delta_line
+ 3, // delta_start
+ 4, // length
+ 0, // token_type
+ 0, // token_modifiers_bitset
+ ],
+ result_id: Some("a".into()),
+ },
+ )))
+ }
+ },
+ );
+
+ cx.set_state("Λfn main() {}");
+ assert!(full_request.next().await.is_some());
+
+ let task = cx.update_editor(|e, _, _| e.semantic_token_state.take_update_task());
+ task.await;
+
+ cx.update_buffer(|buffer, cx| {
+ buffer.update_diagnostics(
+ LanguageServerId(0),
+ DiagnosticSet::new(
+ [DiagnosticEntry {
+ range: PointUtf16::new(0, 3)..PointUtf16::new(0, 7),
+ diagnostic: Diagnostic {
+ severity: lsp::DiagnosticSeverity::ERROR,
+ group_id: 1,
+ message: "unused function".into(),
+ ..Default::default()
+ },
+ }],
+ buffer,
+ ),
+ cx,
+ )
+ });
+
+ cx.run_until_parked();
+ let chunks = cx.update_editor(|editor, window, cx| {
+ editor
+ .snapshot(window, cx)
+ .display_snapshot
+ .chunks(
+ crate::display_map::DisplayRow(0)..crate::display_map::DisplayRow(1),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: true,
+ },
+ crate::HighlightStyles::default(),
+ )
+ .map(|chunk| {
+ (
+ chunk.text.to_string(),
+ chunk.diagnostic_severity,
+ chunk.highlight_style,
+ )
+ })
+ .collect::<Vec<_>>()
+ });
+
+ assert_eq!(
+ extract_semantic_highlights(&cx.editor, &cx),
+ vec![MultiBufferOffset(3)..MultiBufferOffset(7)]
+ );
+
+ assert!(
+ chunks.iter().any(
+ |(text, severity, style): &(
+ String,
+ Option<lsp::DiagnosticSeverity>,
+ Option<gpui::HighlightStyle>
+ )| {
+ text == "main"
+ && *severity == Some(lsp::DiagnosticSeverity::ERROR)
+ && style.is_some()
+ }
+ ),
+ "expected 'main' chunk to have both diagnostic and semantic styling: {:?}",
+ chunks
+ );
+ }
+
fn extract_semantic_highlight_styles(
editor: &Entity<Editor>,
cx: &TestAppContext,
@@ -12,4 +12,4 @@ workspace = true
path = "src/env_var.rs"
[dependencies]
-gpui.workspace = true
+gpui_shared_string.workspace = true
@@ -1,4 +1,4 @@
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
#[derive(Clone)]
pub struct EnvVar {
@@ -21,6 +21,7 @@ editor.workspace = true
file_icons.workspace = true
futures.workspace = true
fuzzy.workspace = true
+fuzzy_nucleo.workspace = true
gpui.workspace = true
menu.workspace = true
open_path_prompt.workspace = true
@@ -9,7 +9,8 @@ use client::ChannelId;
use collections::HashMap;
use editor::Editor;
use file_icons::FileIcons;
-use fuzzy::{CharBag, PathMatch, PathMatchCandidate, StringMatch, StringMatchCandidate};
+use fuzzy::{StringMatch, StringMatchCandidate};
+use fuzzy_nucleo::{PathMatch, PathMatchCandidate};
use gpui::{
Action, AnyElement, App, Context, DismissEvent, Entity, EventEmitter, FocusHandle, Focusable,
KeyContext, Modifiers, ModifiersChangedEvent, ParentElement, Render, Styled, Task, WeakEntity,
@@ -663,15 +664,6 @@ impl Matches {
// For file-vs-file matches, use the existing detailed comparison.
if let (Some(a_panel), Some(b_panel)) = (a.panel_match(), b.panel_match()) {
- let a_in_filename = Self::is_filename_match(a_panel);
- let b_in_filename = Self::is_filename_match(b_panel);
-
- match (a_in_filename, b_in_filename) {
- (true, false) => return cmp::Ordering::Greater,
- (false, true) => return cmp::Ordering::Less,
- _ => {}
- }
-
return a_panel.cmp(b_panel);
}
@@ -691,32 +683,6 @@ impl Matches {
Match::CreateNew(_) => 0.0,
}
}
-
- /// Determines if the match occurred within the filename rather than in the path
- fn is_filename_match(panel_match: &ProjectPanelOrdMatch) -> bool {
- if panel_match.0.positions.is_empty() {
- return false;
- }
-
- if let Some(filename) = panel_match.0.path.file_name() {
- let path_str = panel_match.0.path.as_unix_str();
-
- if let Some(filename_pos) = path_str.rfind(filename)
- && panel_match.0.positions[0] >= filename_pos
- {
- let mut prev_position = panel_match.0.positions[0];
- for p in &panel_match.0.positions[1..] {
- if *p != prev_position + 1 {
- return false;
- }
- prev_position = *p;
- }
- return true;
- }
- }
-
- false
- }
}
fn matching_history_items<'a>(
@@ -731,25 +697,16 @@ fn matching_history_items<'a>(
let history_items_by_worktrees = history_items
.into_iter()
.chain(currently_opened)
- .filter_map(|found_path| {
+ .map(|found_path| {
let candidate = PathMatchCandidate {
is_dir: false, // You can't open directories as project items
path: &found_path.project.path,
// Only match history items names, otherwise their paths may match too many queries, producing false positives.
// E.g. `foo` would match both `something/foo/bar.rs` and `something/foo/foo.rs` and if the former is a history item,
// it would be shown first always, despite the latter being a better match.
- char_bag: CharBag::from_iter(
- found_path
- .project
- .path
- .file_name()?
- .to_string()
- .to_lowercase()
- .chars(),
- ),
};
candidates_paths.insert(&found_path.project, found_path);
- Some((found_path.project.worktree_id, candidate))
+ (found_path.project.worktree_id, candidate)
})
.fold(
HashMap::default(),
@@ -767,8 +724,9 @@ fn matching_history_items<'a>(
let worktree_root_name = worktree_name_by_id
.as_ref()
.and_then(|w| w.get(&worktree).cloned());
+
matching_history_paths.extend(
- fuzzy::match_fixed_path_set(
+ fuzzy_nucleo::match_fixed_path_set(
candidates,
worktree.to_usize(),
worktree_root_name,
@@ -778,6 +736,18 @@ fn matching_history_items<'a>(
path_style,
)
.into_iter()
+ // filter matches where at least one matched position is in filename portion, to prevent directory matches, nucleo scores them higher as history items are matched against their full path
+ .filter(|path_match| {
+ if let Some(filename) = path_match.path.file_name() {
+ let filename_start = path_match.path.as_unix_str().len() - filename.len();
+ path_match
+ .positions
+ .iter()
+ .any(|&pos| pos >= filename_start)
+ } else {
+ true
+ }
+ })
.filter_map(|path_match| {
candidates_paths
.remove_entry(&ProjectPath {
@@ -940,7 +910,7 @@ impl FileFinderDelegate {
self.cancel_flag = Arc::new(AtomicBool::new(false));
let cancel_flag = self.cancel_flag.clone();
cx.spawn_in(window, async move |picker, cx| {
- let matches = fuzzy::match_path_sets(
+ let matches = fuzzy_nucleo::match_path_sets(
candidate_sets.as_slice(),
query.path_query(),
&relative_to,
@@ -1452,7 +1422,6 @@ impl PickerDelegate for FileFinderDelegate {
window: &mut Window,
cx: &mut Context<Picker<Self>>,
) -> Task<()> {
- let raw_query = raw_query.replace(' ', "");
let raw_query = raw_query.trim();
let raw_query = match &raw_query.get(0..2) {
@@ -4161,3 +4161,233 @@ async fn test_clear_navigation_history(cx: &mut TestAppContext) {
"Should have no history items after clearing"
);
}
+
+#[gpui::test]
+async fn test_order_independent_search(cx: &mut TestAppContext) {
+ let app_state = init_test(cx);
+ app_state
+ .fs
+ .as_fake()
+ .insert_tree(
+ "/src",
+ json!({
+ "internal": {
+ "auth": {
+ "login.rs": "",
+ }
+ }
+ }),
+ )
+ .await;
+ let project = Project::test(app_state.fs.clone(), ["/src".as_ref()], cx).await;
+ let (picker, _, cx) = build_find_picker(project, cx);
+
+ // forward order
+ picker
+ .update_in(cx, |picker, window, cx| {
+ picker
+ .delegate
+ .spawn_search(test_path_position("auth internal"), window, cx)
+ })
+ .await;
+ picker.update(cx, |picker, _| {
+ let matches = collect_search_matches(picker).search_matches_only();
+ assert_eq!(matches.len(), 1);
+ assert_eq!(matches[0].path.as_unix_str(), "internal/auth/login.rs");
+ });
+
+ // reverse order should give same result
+ picker
+ .update_in(cx, |picker, window, cx| {
+ picker
+ .delegate
+ .spawn_search(test_path_position("internal auth"), window, cx)
+ })
+ .await;
+ picker.update(cx, |picker, _| {
+ let matches = collect_search_matches(picker).search_matches_only();
+ assert_eq!(matches.len(), 1);
+ assert_eq!(matches[0].path.as_unix_str(), "internal/auth/login.rs");
+ });
+}
+
+#[gpui::test]
+async fn test_filename_preferred_over_directory_match(cx: &mut TestAppContext) {
+ let app_state = init_test(cx);
+ app_state
+ .fs
+ .as_fake()
+ .insert_tree(
+ "/src",
+ json!({
+ "crates": {
+ "settings_ui": {
+ "src": {
+ "pages": {
+ "audio_test_window.rs": "",
+ "audio_input_output_setup.rs": "",
+ }
+ }
+ },
+ "audio": {
+ "src": {
+ "audio_settings.rs": "",
+ }
+ }
+ }
+ }),
+ )
+ .await;
+ let project = Project::test(app_state.fs.clone(), ["/src".as_ref()], cx).await;
+ let (picker, _, cx) = build_find_picker(project, cx);
+
+ picker
+ .update_in(cx, |picker, window, cx| {
+ picker
+ .delegate
+ .spawn_search(test_path_position("settings audio"), window, cx)
+ })
+ .await;
+ picker.update(cx, |picker, _| {
+ let matches = collect_search_matches(picker).search_matches_only();
+ assert!(!matches.is_empty(),);
+ assert_eq!(
+ matches[0].path.as_unix_str(),
+ "crates/audio/src/audio_settings.rs"
+ );
+ });
+}
+
+#[gpui::test]
+async fn test_start_of_word_preferred_over_scattered_match(cx: &mut TestAppContext) {
+ let app_state = init_test(cx);
+ app_state
+ .fs
+ .as_fake()
+ .insert_tree(
+ "/src",
+ json!({
+ "crates": {
+ "livekit_client": {
+ "src": {
+ "livekit_client": {
+ "playback.rs": "",
+ }
+ }
+ },
+ "vim": {
+ "test_data": {
+ "test_record_replay_interleaved.json": "",
+ }
+ }
+ }
+ }),
+ )
+ .await;
+ let project = Project::test(app_state.fs.clone(), ["/src".as_ref()], cx).await;
+ let (picker, _, cx) = build_find_picker(project, cx);
+
+ picker
+ .update_in(cx, |picker, window, cx| {
+ picker
+ .delegate
+ .spawn_search(test_path_position("live pla"), window, cx)
+ })
+ .await;
+ picker.update(cx, |picker, _| {
+ let matches = collect_search_matches(picker).search_matches_only();
+ assert!(!matches.is_empty(),);
+ assert_eq!(
+ matches[0].path.as_unix_str(),
+ "crates/livekit_client/src/livekit_client/playback.rs",
+ );
+ });
+}
+
+#[gpui::test]
+async fn test_exact_filename_stem_preferred(cx: &mut TestAppContext) {
+ let app_state = init_test(cx);
+ app_state
+ .fs
+ .as_fake()
+ .insert_tree(
+ "/src",
+ json!({
+ "assets": {
+ "icons": {
+ "file_icons": {
+ "nix.svg": "",
+ }
+ }
+ },
+ "crates": {
+ "zed": {
+ "resources": {
+ "app-icon-nightly@2x.png": "",
+ "app-icon-preview@2x.png": "",
+ }
+ }
+ }
+ }),
+ )
+ .await;
+ let project = Project::test(app_state.fs.clone(), ["/src".as_ref()], cx).await;
+ let (picker, _, cx) = build_find_picker(project, cx);
+
+ picker
+ .update_in(cx, |picker, window, cx| {
+ picker
+ .delegate
+ .spawn_search(test_path_position("nix icon"), window, cx)
+ })
+ .await;
+ picker.update(cx, |picker, _| {
+ let matches = collect_search_matches(picker).search_matches_only();
+ assert!(!matches.is_empty(),);
+ assert_eq!(
+ matches[0].path.as_unix_str(),
+ "assets/icons/file_icons/nix.svg",
+ );
+ });
+}
+
+#[gpui::test]
+async fn test_exact_filename_with_directory_token(cx: &mut TestAppContext) {
+ let app_state = init_test(cx);
+ app_state
+ .fs
+ .as_fake()
+ .insert_tree(
+ "/src",
+ json!({
+ "crates": {
+ "agent_servers": {
+ "src": {
+ "acp.rs": "",
+ "agent_server.rs": "",
+ "custom.rs": "",
+ }
+ }
+ }
+ }),
+ )
+ .await;
+ let project = Project::test(app_state.fs.clone(), ["/src".as_ref()], cx).await;
+ let (picker, _, cx) = build_find_picker(project, cx);
+
+ picker
+ .update_in(cx, |picker, window, cx| {
+ picker
+ .delegate
+ .spawn_search(test_path_position("acp server"), window, cx)
+ })
+ .await;
+ picker.update(cx, |picker, _| {
+ let matches = collect_search_matches(picker).search_matches_only();
+ assert!(!matches.is_empty(),);
+ assert_eq!(
+ matches[0].path.as_unix_str(),
+ "crates/agent_servers/src/acp.rs",
+ );
+ });
+}
@@ -6,9 +6,10 @@ use git::{
Oid, RunHook,
blame::Blame,
repository::{
- AskPassDelegate, Branch, CommitDataReader, CommitDetails, CommitOptions, FetchOptions,
- GRAPH_CHUNK_SIZE, GitRepository, GitRepositoryCheckpoint, InitialGraphCommitData, LogOrder,
- LogSource, PushOptions, Remote, RepoPath, ResetMode, SearchCommitArgs, Worktree,
+ AskPassDelegate, Branch, CommitDataReader, CommitDetails, CommitOptions,
+ CreateWorktreeTarget, FetchOptions, GRAPH_CHUNK_SIZE, GitRepository,
+ GitRepositoryCheckpoint, InitialGraphCommitData, LogOrder, LogSource, PushOptions, Remote,
+ RepoPath, ResetMode, SearchCommitArgs, Worktree,
},
stash::GitStash,
status::{
@@ -60,6 +61,7 @@ pub struct FakeGitRepositoryState {
pub remotes: HashMap<String, String>,
pub simulated_index_write_error_message: Option<String>,
pub simulated_create_worktree_error: Option<String>,
+ pub simulated_graph_error: Option<String>,
pub refs: HashMap<String, String>,
pub graph_commits: Vec<Arc<InitialGraphCommitData>>,
pub stash_entries: GitStash,
@@ -77,6 +79,7 @@ impl FakeGitRepositoryState {
branches: Default::default(),
simulated_index_write_error_message: Default::default(),
simulated_create_worktree_error: Default::default(),
+ simulated_graph_error: None,
refs: HashMap::from_iter([("HEAD".into(), "abc".into())]),
merge_base_contents: Default::default(),
oids: Default::default(),
@@ -540,9 +543,8 @@ impl GitRepository for FakeGitRepository {
fn create_worktree(
&self,
- branch_name: Option<String>,
+ target: CreateWorktreeTarget,
path: PathBuf,
- from_commit: Option<String>,
) -> BoxFuture<'_, Result<()>> {
let fs = self.fs.clone();
let executor = self.executor.clone();
@@ -550,30 +552,82 @@ impl GitRepository for FakeGitRepository {
let common_dir_path = self.common_dir_path.clone();
async move {
executor.simulate_random_delay().await;
- // Check for simulated error and duplicate branch before any side effects.
- fs.with_git_state(&dot_git_path, false, |state| {
- if let Some(message) = &state.simulated_create_worktree_error {
- anyhow::bail!("{message}");
- }
- if let Some(ref name) = branch_name {
- if state.branches.contains(name) {
- bail!("a branch named '{}' already exists", name);
+
+ let branch_name = target.branch_name().map(ToOwned::to_owned);
+ let create_branch_ref = matches!(target, CreateWorktreeTarget::NewBranch { .. });
+
+ // Check for simulated error and validate branch state before any side effects.
+ fs.with_git_state(&dot_git_path, false, {
+ let branch_name = branch_name.clone();
+ move |state| {
+ if let Some(message) = &state.simulated_create_worktree_error {
+ anyhow::bail!("{message}");
+ }
+
+ match (create_branch_ref, branch_name.as_ref()) {
+ (true, Some(branch_name)) => {
+ if state.branches.contains(branch_name) {
+ bail!("a branch named '{}' already exists", branch_name);
+ }
+ }
+ (false, Some(branch_name)) => {
+ if !state.branches.contains(branch_name) {
+ bail!("no branch named '{}' exists", branch_name);
+ }
+ }
+ (false, None) => {}
+ (true, None) => bail!("branch name is required to create a branch"),
}
+
+ Ok(())
}
- Ok(())
})??;
+ let (branch_name, sha, create_branch_ref) = match target {
+ CreateWorktreeTarget::ExistingBranch { branch_name } => {
+ let ref_name = format!("refs/heads/{branch_name}");
+ let sha = fs.with_git_state(&dot_git_path, false, {
+ move |state| {
+ Ok::<_, anyhow::Error>(
+ state
+ .refs
+ .get(&ref_name)
+ .cloned()
+ .unwrap_or_else(|| "fake-sha".to_string()),
+ )
+ }
+ })??;
+ (Some(branch_name), sha, false)
+ }
+ CreateWorktreeTarget::NewBranch {
+ branch_name,
+ base_sha: start_point,
+ } => (
+ Some(branch_name),
+ start_point.unwrap_or_else(|| "fake-sha".to_string()),
+ true,
+ ),
+ CreateWorktreeTarget::Detached {
+ base_sha: start_point,
+ } => (
+ None,
+ start_point.unwrap_or_else(|| "fake-sha".to_string()),
+ false,
+ ),
+ };
+
// Create the worktree checkout directory.
fs.create_dir(&path).await?;
// Create .git/worktrees/<name>/ directory with HEAD, commondir, gitdir.
- let worktree_entry_name = branch_name
- .as_deref()
- .unwrap_or_else(|| path.file_name().unwrap().to_str().unwrap());
+ let worktree_entry_name = branch_name.as_deref().unwrap_or_else(|| {
+ path.file_name()
+ .and_then(|name| name.to_str())
+ .unwrap_or("detached")
+ });
let worktrees_entry_dir = common_dir_path.join("worktrees").join(worktree_entry_name);
fs.create_dir(&worktrees_entry_dir).await?;
- let sha = from_commit.unwrap_or_else(|| "fake-sha".to_string());
let head_content = if let Some(ref branch_name) = branch_name {
let ref_name = format!("refs/heads/{branch_name}");
format!("ref: {ref_name}")
@@ -604,15 +658,22 @@ impl GitRepository for FakeGitRepository {
false,
)?;
- // Update git state: add ref and branch.
- fs.with_git_state(&dot_git_path, true, move |state| {
- if let Some(branch_name) = branch_name {
- let ref_name = format!("refs/heads/{branch_name}");
- state.refs.insert(ref_name, sha);
- state.branches.insert(branch_name);
- }
- Ok::<(), anyhow::Error>(())
- })??;
+ // Update git state for newly created branches.
+ if create_branch_ref {
+ fs.with_git_state(&dot_git_path, true, {
+ let branch_name = branch_name.clone();
+ let sha = sha.clone();
+ move |state| {
+ if let Some(branch_name) = branch_name {
+ let ref_name = format!("refs/heads/{branch_name}");
+ state.refs.insert(ref_name, sha);
+ state.branches.insert(branch_name);
+ }
+ Ok::<(), anyhow::Error>(())
+ }
+ })??;
+ }
+
Ok(())
}
.boxed()
@@ -1268,8 +1329,17 @@ impl GitRepository for FakeGitRepository {
let fs = self.fs.clone();
let dot_git_path = self.dot_git_path.clone();
async move {
- let graph_commits =
- fs.with_git_state(&dot_git_path, false, |state| state.graph_commits.clone())?;
+ let (graph_commits, simulated_error) =
+ fs.with_git_state(&dot_git_path, false, |state| {
+ (
+ state.graph_commits.clone(),
+ state.simulated_graph_error.clone(),
+ )
+ })?;
+
+ if let Some(error) = simulated_error {
+ anyhow::bail!("{}", error);
+ }
for chunk in graph_commits.chunks(GRAPH_CHUNK_SIZE) {
request_tx.send(chunk.to_vec()).await.ok();
@@ -2168,6 +2168,13 @@ impl FakeFs {
.unwrap();
}
+ pub fn set_graph_error(&self, dot_git: &Path, error: Option<String>) {
+ self.with_git_state(dot_git, true, |state| {
+ state.simulated_graph_error = error;
+ })
+ .unwrap();
+ }
+
/// Put the given git repository into a state with the given status,
/// by mutating the head, index, and unmerged state.
pub fn set_status_for_repo(&self, dot_git: &Path, statuses: &[(&str, FileStatus)]) {
@@ -24,9 +24,11 @@ async fn test_fake_worktree_lifecycle(cx: &mut TestAppContext) {
// Create a worktree
let worktree_1_dir = worktrees_dir.join("feature-branch");
repo.create_worktree(
- Some("feature-branch".to_string()),
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: "feature-branch".to_string(),
+ base_sha: Some("abc123".to_string()),
+ },
worktree_1_dir.clone(),
- Some("abc123".to_string()),
)
.await
.unwrap();
@@ -48,9 +50,11 @@ async fn test_fake_worktree_lifecycle(cx: &mut TestAppContext) {
// Create a second worktree (without explicit commit)
let worktree_2_dir = worktrees_dir.join("bugfix-branch");
repo.create_worktree(
- Some("bugfix-branch".to_string()),
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: "bugfix-branch".to_string(),
+ base_sha: None,
+ },
worktree_2_dir.clone(),
- None,
)
.await
.unwrap();
@@ -0,0 +1,21 @@
+[package]
+name = "fuzzy_nucleo"
+version = "0.1.0"
+edition.workspace = true
+publish.workspace = true
+license = "GPL-3.0-or-later"
+
+[lints]
+workspace = true
+
+[lib]
+path = "src/fuzzy_nucleo.rs"
+doctest = false
+
+[dependencies]
+nucleo.workspace = true
+gpui.workspace = true
+util.workspace = true
+
+[dev-dependencies]
+util = {workspace = true, features = ["test-support"]}
@@ -0,0 +1 @@
+../../LICENSE-GPL
@@ -0,0 +1,5 @@
+mod matcher;
+mod paths;
+pub use paths::{
+ PathMatch, PathMatchCandidate, PathMatchCandidateSet, match_fixed_path_set, match_path_sets,
+};
@@ -0,0 +1,39 @@
+use std::sync::Mutex;
+
+static MATCHERS: Mutex<Vec<nucleo::Matcher>> = Mutex::new(Vec::new());
+
+pub const LENGTH_PENALTY: f64 = 0.01;
+
+pub fn get_matcher(config: nucleo::Config) -> nucleo::Matcher {
+ let mut matchers = MATCHERS.lock().unwrap();
+ match matchers.pop() {
+ Some(mut matcher) => {
+ matcher.config = config;
+ matcher
+ }
+ None => nucleo::Matcher::new(config),
+ }
+}
+
+pub fn return_matcher(matcher: nucleo::Matcher) {
+ MATCHERS.lock().unwrap().push(matcher);
+}
+
+pub fn get_matchers(n: usize, config: nucleo::Config) -> Vec<nucleo::Matcher> {
+ let mut matchers: Vec<_> = {
+ let mut pool = MATCHERS.lock().unwrap();
+ let available = pool.len().min(n);
+ pool.drain(..available)
+ .map(|mut matcher| {
+ matcher.config = config.clone();
+ matcher
+ })
+ .collect()
+ };
+ matchers.resize_with(n, || nucleo::Matcher::new(config.clone()));
+ matchers
+}
+
+pub fn return_matchers(mut matchers: Vec<nucleo::Matcher>) {
+ MATCHERS.lock().unwrap().append(&mut matchers);
+}
@@ -0,0 +1,352 @@
+use gpui::BackgroundExecutor;
+use std::{
+ cmp::Ordering,
+ sync::{
+ Arc,
+ atomic::{self, AtomicBool},
+ },
+};
+use util::{paths::PathStyle, rel_path::RelPath};
+
+use nucleo::Utf32Str;
+use nucleo::pattern::{Atom, AtomKind, CaseMatching, Normalization};
+
+use crate::matcher::{self, LENGTH_PENALTY};
+
+#[derive(Clone, Debug)]
+pub struct PathMatchCandidate<'a> {
+ pub is_dir: bool,
+ pub path: &'a RelPath,
+}
+
+#[derive(Clone, Debug)]
+pub struct PathMatch {
+ pub score: f64,
+ pub positions: Vec<usize>,
+ pub worktree_id: usize,
+ pub path: Arc<RelPath>,
+ pub path_prefix: Arc<RelPath>,
+ pub is_dir: bool,
+ /// Number of steps removed from a shared parent with the relative path
+ /// Used to order closer paths first in the search list
+ pub distance_to_relative_ancestor: usize,
+}
+
+pub trait PathMatchCandidateSet<'a>: Send + Sync {
+ type Candidates: Iterator<Item = PathMatchCandidate<'a>>;
+ fn id(&self) -> usize;
+ fn len(&self) -> usize;
+ fn is_empty(&self) -> bool {
+ self.len() == 0
+ }
+ fn root_is_file(&self) -> bool;
+ fn prefix(&self) -> Arc<RelPath>;
+ fn candidates(&'a self, start: usize) -> Self::Candidates;
+ fn path_style(&self) -> PathStyle;
+}
+
+impl PartialEq for PathMatch {
+ fn eq(&self, other: &Self) -> bool {
+ self.cmp(other).is_eq()
+ }
+}
+
+impl Eq for PathMatch {}
+
+impl PartialOrd for PathMatch {
+ fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
+ Some(self.cmp(other))
+ }
+}
+
+impl Ord for PathMatch {
+ fn cmp(&self, other: &Self) -> Ordering {
+ self.score
+ .partial_cmp(&other.score)
+ .unwrap_or(Ordering::Equal)
+ .then_with(|| self.worktree_id.cmp(&other.worktree_id))
+ .then_with(|| {
+ other
+ .distance_to_relative_ancestor
+ .cmp(&self.distance_to_relative_ancestor)
+ })
+ .then_with(|| self.path.cmp(&other.path))
+ }
+}
+
+fn make_atoms(query: &str, smart_case: bool) -> Vec<Atom> {
+ let case = if smart_case {
+ CaseMatching::Smart
+ } else {
+ CaseMatching::Ignore
+ };
+ query
+ .split_whitespace()
+ .map(|word| Atom::new(word, case, Normalization::Smart, AtomKind::Fuzzy, false))
+ .collect()
+}
+
+pub(crate) fn distance_between_paths(path: &RelPath, relative_to: &RelPath) -> usize {
+ let mut path_components = path.components();
+ let mut relative_components = relative_to.components();
+
+ while path_components
+ .next()
+ .zip(relative_components.next())
+ .map(|(path_component, relative_component)| path_component == relative_component)
+ .unwrap_or_default()
+ {}
+ path_components.count() + relative_components.count() + 1
+}
+
+fn get_filename_match_bonus(
+ candidate_buf: &str,
+ query_atoms: &[Atom],
+ matcher: &mut nucleo::Matcher,
+) -> f64 {
+ let filename = match std::path::Path::new(candidate_buf).file_name() {
+ Some(f) => f.to_str().unwrap_or(""),
+ None => return 0.0,
+ };
+ if filename.is_empty() || query_atoms.is_empty() {
+ return 0.0;
+ }
+ let mut buf = Vec::new();
+ let haystack = Utf32Str::new(filename, &mut buf);
+ let mut total_score = 0u32;
+ for atom in query_atoms {
+ if let Some(score) = atom.score(haystack, matcher) {
+ total_score = total_score.saturating_add(score as u32);
+ }
+ }
+ total_score as f64 / filename.len().max(1) as f64
+}
+struct Cancelled;
+
+fn path_match_helper<'a>(
+ matcher: &mut nucleo::Matcher,
+ atoms: &[Atom],
+ candidates: impl Iterator<Item = PathMatchCandidate<'a>>,
+ results: &mut Vec<PathMatch>,
+ worktree_id: usize,
+ path_prefix: &Arc<RelPath>,
+ root_is_file: bool,
+ relative_to: &Option<Arc<RelPath>>,
+ path_style: PathStyle,
+ cancel_flag: &AtomicBool,
+) -> Result<(), Cancelled> {
+ let mut candidate_buf = if !path_prefix.is_empty() && !root_is_file {
+ let mut s = path_prefix.display(path_style).to_string();
+ s.push_str(path_style.primary_separator());
+ s
+ } else {
+ String::new()
+ };
+ let path_prefix_len = candidate_buf.len();
+ let mut buf = Vec::new();
+ let mut matched_chars: Vec<u32> = Vec::new();
+ let mut atom_matched_chars = Vec::new();
+ for candidate in candidates {
+ buf.clear();
+ matched_chars.clear();
+ if cancel_flag.load(atomic::Ordering::Relaxed) {
+ return Err(Cancelled);
+ }
+
+ candidate_buf.truncate(path_prefix_len);
+ if root_is_file {
+ candidate_buf.push_str(path_prefix.as_unix_str());
+ } else {
+ candidate_buf.push_str(candidate.path.as_unix_str());
+ }
+
+ let haystack = Utf32Str::new(&candidate_buf, &mut buf);
+
+ let mut total_score: u32 = 0;
+ let mut all_matched = true;
+
+ for atom in atoms {
+ atom_matched_chars.clear();
+ if let Some(score) = atom.indices(haystack, matcher, &mut atom_matched_chars) {
+ total_score = total_score.saturating_add(score as u32);
+ matched_chars.extend_from_slice(&atom_matched_chars);
+ } else {
+ all_matched = false;
+ break;
+ }
+ }
+
+ if all_matched && !atoms.is_empty() {
+ matched_chars.sort_unstable();
+ matched_chars.dedup();
+
+ let length_penalty = candidate_buf.len() as f64 * LENGTH_PENALTY;
+ let filename_bonus = get_filename_match_bonus(&candidate_buf, atoms, matcher);
+ let adjusted_score = total_score as f64 + filename_bonus - length_penalty;
+ let mut positions: Vec<usize> = candidate_buf
+ .char_indices()
+ .enumerate()
+ .filter_map(|(char_offset, (byte_offset, _))| {
+ matched_chars
+ .contains(&(char_offset as u32))
+ .then_some(byte_offset)
+ })
+ .collect();
+ positions.sort_unstable();
+
+ results.push(PathMatch {
+ score: adjusted_score,
+ positions,
+ worktree_id,
+ path: if root_is_file {
+ Arc::clone(path_prefix)
+ } else {
+ candidate.path.into()
+ },
+ path_prefix: if root_is_file {
+ RelPath::empty().into()
+ } else {
+ Arc::clone(path_prefix)
+ },
+ is_dir: candidate.is_dir,
+ distance_to_relative_ancestor: relative_to
+ .as_ref()
+ .map_or(usize::MAX, |relative_to| {
+ distance_between_paths(candidate.path, relative_to.as_ref())
+ }),
+ });
+ }
+ }
+ Ok(())
+}
+
+pub fn match_fixed_path_set(
+ candidates: Vec<PathMatchCandidate>,
+ worktree_id: usize,
+ worktree_root_name: Option<Arc<RelPath>>,
+ query: &str,
+ smart_case: bool,
+ max_results: usize,
+ path_style: PathStyle,
+) -> Vec<PathMatch> {
+ let mut config = nucleo::Config::DEFAULT;
+ config.set_match_paths();
+ let mut matcher = matcher::get_matcher(config);
+
+ let atoms = make_atoms(query, smart_case);
+
+ let root_is_file = worktree_root_name.is_some() && candidates.iter().all(|c| c.path.is_empty());
+
+ let path_prefix = worktree_root_name.unwrap_or_else(|| RelPath::empty().into());
+
+ let mut results = Vec::new();
+
+ path_match_helper(
+ &mut matcher,
+ &atoms,
+ candidates.into_iter(),
+ &mut results,
+ worktree_id,
+ &path_prefix,
+ root_is_file,
+ &None,
+ path_style,
+ &AtomicBool::new(false),
+ )
+ .ok();
+ util::truncate_to_bottom_n_sorted_by(&mut results, max_results, &|a, b| b.cmp(a));
+ matcher::return_matcher(matcher);
+ results
+}
+
+pub async fn match_path_sets<'a, Set: PathMatchCandidateSet<'a>>(
+ candidate_sets: &'a [Set],
+ query: &str,
+ relative_to: &Option<Arc<RelPath>>,
+ smart_case: bool,
+ max_results: usize,
+ cancel_flag: &AtomicBool,
+ executor: BackgroundExecutor,
+) -> Vec<PathMatch> {
+ let path_count: usize = candidate_sets.iter().map(|s| s.len()).sum();
+ if path_count == 0 {
+ return Vec::new();
+ }
+
+ let path_style = candidate_sets[0].path_style();
+
+ let query = if path_style.is_windows() {
+ query.replace('\\', "/")
+ } else {
+ query.to_owned()
+ };
+
+ let atoms = make_atoms(&query, smart_case);
+
+ let num_cpus = executor.num_cpus().min(path_count);
+ let segment_size = path_count.div_ceil(num_cpus);
+ let mut segment_results = (0..num_cpus)
+ .map(|_| Vec::with_capacity(max_results))
+ .collect::<Vec<_>>();
+ let mut config = nucleo::Config::DEFAULT;
+ config.set_match_paths();
+ let mut matchers = matcher::get_matchers(num_cpus, config);
+ executor
+ .scoped(|scope| {
+ for (segment_idx, (results, matcher)) in segment_results
+ .iter_mut()
+ .zip(matchers.iter_mut())
+ .enumerate()
+ {
+ let atoms = atoms.clone();
+ let relative_to = relative_to.clone();
+ scope.spawn(async move {
+ let segment_start = segment_idx * segment_size;
+ let segment_end = segment_start + segment_size;
+
+ let mut tree_start = 0;
+ for candidate_set in candidate_sets {
+ let tree_end = tree_start + candidate_set.len();
+
+ if tree_start < segment_end && segment_start < tree_end {
+ let start = tree_start.max(segment_start) - tree_start;
+ let end = tree_end.min(segment_end) - tree_start;
+ let candidates = candidate_set.candidates(start).take(end - start);
+
+ if path_match_helper(
+ matcher,
+ &atoms,
+ candidates,
+ results,
+ candidate_set.id(),
+ &candidate_set.prefix(),
+ candidate_set.root_is_file(),
+ &relative_to,
+ path_style,
+ cancel_flag,
+ )
+ .is_err()
+ {
+ break;
+ }
+ }
+
+ if tree_end >= segment_end {
+ break;
+ }
+ tree_start = tree_end;
+ }
+ });
+ }
+ })
+ .await;
+
+ matcher::return_matchers(matchers);
+ if cancel_flag.load(atomic::Ordering::Acquire) {
+ return Vec::new();
+ }
+
+ let mut results = segment_results.concat();
+ util::truncate_to_bottom_n_sorted_by(&mut results, max_results, &|a, b| b.cmp(a));
+ results
+}
@@ -241,20 +241,57 @@ pub struct Worktree {
pub is_main: bool,
}
+/// Describes how a new worktree should choose or create its checked-out HEAD.
+#[derive(Clone, Debug, Hash, PartialEq, Eq)]
+pub enum CreateWorktreeTarget {
+ /// Check out an existing local branch in the new worktree.
+ ExistingBranch {
+ /// The existing local branch to check out.
+ branch_name: String,
+ },
+ /// Create a new local branch for the new worktree.
+ NewBranch {
+ /// The new local branch to create and check out.
+ branch_name: String,
+ /// The commit or ref to create the branch from. Uses `HEAD` when `None`.
+ base_sha: Option<String>,
+ },
+ /// Check out a commit or ref in detached HEAD state.
+ Detached {
+ /// The commit or ref to check out. Uses `HEAD` when `None`.
+ base_sha: Option<String>,
+ },
+}
+
+impl CreateWorktreeTarget {
+ pub fn branch_name(&self) -> Option<&str> {
+ match self {
+ Self::ExistingBranch { branch_name } | Self::NewBranch { branch_name, .. } => {
+ Some(branch_name)
+ }
+ Self::Detached { .. } => None,
+ }
+ }
+}
+
impl Worktree {
+ /// Returns the branch name if the worktree is attached to a branch.
+ pub fn branch_name(&self) -> Option<&str> {
+ self.ref_name.as_ref().map(|ref_name| {
+ ref_name
+ .strip_prefix("refs/heads/")
+ .or_else(|| ref_name.strip_prefix("refs/remotes/"))
+ .unwrap_or(ref_name)
+ })
+ }
+
/// Returns a display name for the worktree, suitable for use in the UI.
///
/// If the worktree is attached to a branch, returns the branch name.
/// Otherwise, returns the short SHA of the worktree's HEAD commit.
pub fn display_name(&self) -> &str {
- match self.ref_name {
- Some(ref ref_name) => ref_name
- .strip_prefix("refs/heads/")
- .or_else(|| ref_name.strip_prefix("refs/remotes/"))
- .unwrap_or(ref_name),
- // Detached HEAD β show the short SHA as a fallback.
- None => &self.sha[..self.sha.len().min(SHORT_SHA_LENGTH)],
- }
+ self.branch_name()
+ .unwrap_or(&self.sha[..self.sha.len().min(SHORT_SHA_LENGTH)])
}
}
@@ -716,9 +753,8 @@ pub trait GitRepository: Send + Sync {
fn create_worktree(
&self,
- branch_name: Option<String>,
+ target: CreateWorktreeTarget,
path: PathBuf,
- from_commit: Option<String>,
) -> BoxFuture<'_, Result<()>>;
fn remove_worktree(&self, path: PathBuf, force: bool) -> BoxFuture<'_, Result<()>>;
@@ -1667,24 +1703,36 @@ impl GitRepository for RealGitRepository {
fn create_worktree(
&self,
- branch_name: Option<String>,
+ target: CreateWorktreeTarget,
path: PathBuf,
- from_commit: Option<String>,
) -> BoxFuture<'_, Result<()>> {
let git_binary = self.git_binary();
let mut args = vec![OsString::from("worktree"), OsString::from("add")];
- if let Some(branch_name) = &branch_name {
- args.push(OsString::from("-b"));
- args.push(OsString::from(branch_name.as_str()));
- } else {
- args.push(OsString::from("--detach"));
- }
- args.push(OsString::from("--"));
- args.push(OsString::from(path.as_os_str()));
- if let Some(from_commit) = from_commit {
- args.push(OsString::from(from_commit));
- } else {
- args.push(OsString::from("HEAD"));
+
+ match &target {
+ CreateWorktreeTarget::ExistingBranch { branch_name } => {
+ args.push(OsString::from("--"));
+ args.push(OsString::from(path.as_os_str()));
+ args.push(OsString::from(branch_name));
+ }
+ CreateWorktreeTarget::NewBranch {
+ branch_name,
+ base_sha: start_point,
+ } => {
+ args.push(OsString::from("-b"));
+ args.push(OsString::from(branch_name));
+ args.push(OsString::from("--"));
+ args.push(OsString::from(path.as_os_str()));
+ args.push(OsString::from(start_point.as_deref().unwrap_or("HEAD")));
+ }
+ CreateWorktreeTarget::Detached {
+ base_sha: start_point,
+ } => {
+ args.push(OsString::from("--detach"));
+ args.push(OsString::from("--"));
+ args.push(OsString::from(path.as_os_str()));
+ args.push(OsString::from(start_point.as_deref().unwrap_or("HEAD")));
+ }
}
self.executor
@@ -2736,10 +2784,11 @@ impl GitRepository for RealGitRepository {
log_source.get_arg()?,
]);
command.stdout(Stdio::piped());
- command.stderr(Stdio::null());
+ command.stderr(Stdio::piped());
let mut child = command.spawn()?;
let stdout = child.stdout.take().context("failed to get stdout")?;
+ let stderr = child.stderr.take().context("failed to get stderr")?;
let mut reader = BufReader::new(stdout);
let mut line_buffer = String::new();
@@ -2774,7 +2823,20 @@ impl GitRepository for RealGitRepository {
}
}
- child.status().await?;
+ let status = child.status().await?;
+ if !status.success() {
+ let mut stderr_output = String::new();
+ BufReader::new(stderr)
+ .read_to_string(&mut stderr_output)
+ .await
+ .log_err();
+
+ if stderr_output.is_empty() {
+ anyhow::bail!("git log command failed with {}", status);
+ } else {
+ anyhow::bail!("git log command failed with {}: {}", status, stderr_output);
+ }
+ }
Ok(())
}
.boxed()
@@ -4054,9 +4116,11 @@ mod tests {
// Create a new worktree
repo.create_worktree(
- Some("test-branch".to_string()),
+ CreateWorktreeTarget::NewBranch {
+ branch_name: "test-branch".to_string(),
+ base_sha: Some("HEAD".to_string()),
+ },
worktree_path.clone(),
- Some("HEAD".to_string()),
)
.await
.unwrap();
@@ -4113,9 +4177,11 @@ mod tests {
// Create a worktree
let worktree_path = worktrees_dir.join("worktree-to-remove");
repo.create_worktree(
- Some("to-remove".to_string()),
+ CreateWorktreeTarget::NewBranch {
+ branch_name: "to-remove".to_string(),
+ base_sha: Some("HEAD".to_string()),
+ },
worktree_path.clone(),
- Some("HEAD".to_string()),
)
.await
.unwrap();
@@ -4137,9 +4203,11 @@ mod tests {
// Create a worktree
let worktree_path = worktrees_dir.join("dirty-wt");
repo.create_worktree(
- Some("dirty-wt".to_string()),
+ CreateWorktreeTarget::NewBranch {
+ branch_name: "dirty-wt".to_string(),
+ base_sha: Some("HEAD".to_string()),
+ },
worktree_path.clone(),
- Some("HEAD".to_string()),
)
.await
.unwrap();
@@ -4207,9 +4275,11 @@ mod tests {
// Create a worktree
let old_path = worktrees_dir.join("old-worktree-name");
repo.create_worktree(
- Some("old-name".to_string()),
+ CreateWorktreeTarget::NewBranch {
+ branch_name: "old-name".to_string(),
+ base_sha: Some("HEAD".to_string()),
+ },
old_path.clone(),
- Some("HEAD".to_string()),
)
.await
.unwrap();
@@ -2536,11 +2536,19 @@ impl Render for GitGraph {
}
};
+ let error = self.get_repository(cx).and_then(|repo| {
+ repo.read(cx)
+ .get_graph_data(self.log_source.clone(), self.log_order)
+ .and_then(|data| data.error.clone())
+ });
+
let content = if commit_count == 0 {
- let message = if is_loading {
- "Loading"
+ let message = if let Some(error) = &error {
+ format!("Error loading: {}", error)
+ } else if is_loading {
+ "Loading".to_string()
} else {
- "No commits found"
+ "No commits found".to_string()
};
let label = Label::new(message)
.color(Color::Muted)
@@ -2552,7 +2560,7 @@ impl Render for GitGraph {
.items_center()
.justify_center()
.child(label)
- .when(is_loading, |this| {
+ .when(is_loading && error.is_none(), |this| {
this.child(self.render_loading_spinner(cx))
})
} else {
@@ -3757,6 +3765,61 @@ mod tests {
);
}
+ #[gpui::test]
+ async fn test_initial_graph_data_propagates_error(cx: &mut TestAppContext) {
+ init_test(cx);
+
+ let fs = FakeFs::new(cx.executor());
+ fs.insert_tree(
+ Path::new("/project"),
+ json!({
+ ".git": {},
+ "file.txt": "content",
+ }),
+ )
+ .await;
+
+ fs.set_graph_error(
+ Path::new("/project/.git"),
+ Some("fatal: bad default revision 'HEAD'".to_string()),
+ );
+
+ let project = Project::test(fs.clone(), [Path::new("/project")], cx).await;
+
+ let repository = project.read_with(cx, |project, cx| {
+ project
+ .active_repository(cx)
+ .expect("should have a repository")
+ });
+
+ repository.update(cx, |repo, cx| {
+ repo.graph_data(
+ crate::LogSource::default(),
+ crate::LogOrder::default(),
+ 0..usize::MAX,
+ cx,
+ );
+ });
+
+ cx.run_until_parked();
+
+ let error = repository.read_with(cx, |repo, _| {
+ repo.get_graph_data(crate::LogSource::default(), crate::LogOrder::default())
+ .and_then(|data| data.error.clone())
+ });
+
+ assert!(
+ error.is_some(),
+ "graph data should contain an error after initial_graph_data fails"
+ );
+ let error_message = error.unwrap();
+ assert!(
+ error_message.contains("bad default revision"),
+ "error should contain the git error message, got: {}",
+ error_message
+ );
+ }
+
#[gpui::test]
async fn test_graph_data_repopulated_from_cache_after_repo_switch(cx: &mut TestAppContext) {
init_test(cx);
@@ -1906,7 +1906,7 @@ mod tests {
assert_eq!(
remotes,
vec![Remote {
- name: SharedString::from("my_new_remote".to_string())
+ name: SharedString::from("my_new_remote")
}]
);
}
@@ -318,8 +318,13 @@ impl WorktreeListDelegate {
.clone();
let new_worktree_path =
repo.path_for_new_linked_worktree(&branch, &worktree_directory_setting)?;
- let receiver =
- repo.create_worktree(branch.clone(), new_worktree_path.clone(), commit);
+ let receiver = repo.create_worktree(
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: branch.clone(),
+ base_sha: commit,
+ },
+ new_worktree_path.clone(),
+ );
anyhow::Ok((receiver, new_worktree_path))
})?;
receiver.await??;
@@ -18,8 +18,10 @@ schemars = ["dep:schemars"]
anyhow.workspace = true
futures.workspace = true
http_client.workspace = true
+language_model_core.workspace = true
+log.workspace = true
schemars = { workspace = true, optional = true }
serde.workspace = true
serde_json.workspace = true
-settings.workspace = true
strum.workspace = true
+tiktoken-rs.workspace = true
@@ -0,0 +1,492 @@
+use anyhow::Result;
+use futures::{Stream, StreamExt};
+use language_model_core::{
+ LanguageModelCompletionError, LanguageModelCompletionEvent, LanguageModelRequest,
+ LanguageModelToolChoice, LanguageModelToolUse, LanguageModelToolUseId, MessageContent, Role,
+ StopReason, TokenUsage,
+};
+use std::pin::Pin;
+use std::sync::Arc;
+use std::sync::atomic::{self, AtomicU64};
+
+use crate::{
+ Content, FunctionCallingConfig, FunctionCallingMode, FunctionDeclaration,
+ GenerateContentResponse, GenerationConfig, GenerativeContentBlob, GoogleModelMode,
+ InlineDataPart, ModelName, Part, SystemInstruction, TextPart, ThinkingConfig, ToolConfig,
+ UsageMetadata,
+};
+
+pub fn into_google(
+ mut request: LanguageModelRequest,
+ model_id: String,
+ mode: GoogleModelMode,
+) -> crate::GenerateContentRequest {
+ fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
+ content
+ .into_iter()
+ .flat_map(|content| match content {
+ MessageContent::Text(text) => {
+ if !text.is_empty() {
+ vec![Part::TextPart(TextPart { text })]
+ } else {
+ vec![]
+ }
+ }
+ MessageContent::Thinking {
+ text: _,
+ signature: Some(signature),
+ } => {
+ if !signature.is_empty() {
+ vec![Part::ThoughtPart(crate::ThoughtPart {
+ thought: true,
+ thought_signature: signature,
+ })]
+ } else {
+ vec![]
+ }
+ }
+ MessageContent::Thinking { .. } => {
+ vec![]
+ }
+ MessageContent::RedactedThinking(_) => vec![],
+ MessageContent::Image(image) => {
+ vec![Part::InlineDataPart(InlineDataPart {
+ inline_data: GenerativeContentBlob {
+ mime_type: "image/png".to_string(),
+ data: image.source.to_string(),
+ },
+ })]
+ }
+ MessageContent::ToolUse(tool_use) => {
+ // Normalize empty string signatures to None
+ let thought_signature = tool_use.thought_signature.filter(|s| !s.is_empty());
+
+ vec![Part::FunctionCallPart(crate::FunctionCallPart {
+ function_call: crate::FunctionCall {
+ name: tool_use.name.to_string(),
+ args: tool_use.input,
+ },
+ thought_signature,
+ })]
+ }
+ MessageContent::ToolResult(tool_result) => {
+ match tool_result.content {
+ language_model_core::LanguageModelToolResultContent::Text(text) => {
+ vec![Part::FunctionResponsePart(crate::FunctionResponsePart {
+ function_response: crate::FunctionResponse {
+ name: tool_result.tool_name.to_string(),
+ // The API expects a valid JSON object
+ response: serde_json::json!({
+ "output": text
+ }),
+ },
+ })]
+ }
+ language_model_core::LanguageModelToolResultContent::Image(image) => {
+ vec![
+ Part::FunctionResponsePart(crate::FunctionResponsePart {
+ function_response: crate::FunctionResponse {
+ name: tool_result.tool_name.to_string(),
+ // The API expects a valid JSON object
+ response: serde_json::json!({
+ "output": "Tool responded with an image"
+ }),
+ },
+ }),
+ Part::InlineDataPart(InlineDataPart {
+ inline_data: GenerativeContentBlob {
+ mime_type: "image/png".to_string(),
+ data: image.source.to_string(),
+ },
+ }),
+ ]
+ }
+ }
+ }
+ })
+ .collect()
+ }
+
+ let system_instructions = if request
+ .messages
+ .first()
+ .is_some_and(|msg| matches!(msg.role, Role::System))
+ {
+ let message = request.messages.remove(0);
+ Some(SystemInstruction {
+ parts: map_content(message.content),
+ })
+ } else {
+ None
+ };
+
+ crate::GenerateContentRequest {
+ model: ModelName { model_id },
+ system_instruction: system_instructions,
+ contents: request
+ .messages
+ .into_iter()
+ .filter_map(|message| {
+ let parts = map_content(message.content);
+ if parts.is_empty() {
+ None
+ } else {
+ Some(Content {
+ parts,
+ role: match message.role {
+ Role::User => crate::Role::User,
+ Role::Assistant => crate::Role::Model,
+ Role::System => crate::Role::User, // Google AI doesn't have a system role
+ },
+ })
+ }
+ })
+ .collect(),
+ generation_config: Some(GenerationConfig {
+ candidate_count: Some(1),
+ stop_sequences: Some(request.stop),
+ max_output_tokens: None,
+ temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
+ thinking_config: match (request.thinking_allowed, mode) {
+ (true, GoogleModelMode::Thinking { budget_tokens }) => {
+ budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
+ }
+ _ => None,
+ },
+ top_p: None,
+ top_k: None,
+ }),
+ safety_settings: None,
+ tools: (!request.tools.is_empty()).then(|| {
+ vec![crate::Tool {
+ function_declarations: request
+ .tools
+ .into_iter()
+ .map(|tool| FunctionDeclaration {
+ name: tool.name,
+ description: tool.description,
+ parameters: tool.input_schema,
+ })
+ .collect(),
+ }]
+ }),
+ tool_config: request.tool_choice.map(|choice| ToolConfig {
+ function_calling_config: FunctionCallingConfig {
+ mode: match choice {
+ LanguageModelToolChoice::Auto => FunctionCallingMode::Auto,
+ LanguageModelToolChoice::Any => FunctionCallingMode::Any,
+ LanguageModelToolChoice::None => FunctionCallingMode::None,
+ },
+ allowed_function_names: None,
+ },
+ }),
+ }
+}
+
+pub struct GoogleEventMapper {
+ usage: UsageMetadata,
+ stop_reason: StopReason,
+}
+
+impl GoogleEventMapper {
+ pub fn new() -> Self {
+ Self {
+ usage: UsageMetadata::default(),
+ stop_reason: StopReason::EndTurn,
+ }
+ }
+
+ pub fn map_stream(
+ mut self,
+ events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
+ ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
+ {
+ events
+ .map(Some)
+ .chain(futures::stream::once(async { None }))
+ .flat_map(move |event| {
+ futures::stream::iter(match event {
+ Some(Ok(event)) => self.map_event(event),
+ Some(Err(error)) => {
+ vec![Err(LanguageModelCompletionError::from(error))]
+ }
+ None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
+ })
+ })
+ }
+
+ pub fn map_event(
+ &mut self,
+ event: GenerateContentResponse,
+ ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
+ static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
+
+ let mut events: Vec<_> = Vec::new();
+ let mut wants_to_use_tool = false;
+ if let Some(usage_metadata) = event.usage_metadata {
+ update_usage(&mut self.usage, &usage_metadata);
+ events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
+ convert_usage(&self.usage),
+ )))
+ }
+
+ if let Some(prompt_feedback) = event.prompt_feedback
+ && let Some(block_reason) = prompt_feedback.block_reason.as_deref()
+ {
+ self.stop_reason = match block_reason {
+ "SAFETY" | "OTHER" | "BLOCKLIST" | "PROHIBITED_CONTENT" | "IMAGE_SAFETY" => {
+ StopReason::Refusal
+ }
+ _ => {
+ log::error!("Unexpected Google block_reason: {block_reason}");
+ StopReason::Refusal
+ }
+ };
+ events.push(Ok(LanguageModelCompletionEvent::Stop(self.stop_reason)));
+
+ return events;
+ }
+
+ if let Some(candidates) = event.candidates {
+ for candidate in candidates {
+ if let Some(finish_reason) = candidate.finish_reason.as_deref() {
+ self.stop_reason = match finish_reason {
+ "STOP" => StopReason::EndTurn,
+ "MAX_TOKENS" => StopReason::MaxTokens,
+ _ => {
+ log::error!("Unexpected google finish_reason: {finish_reason}");
+ StopReason::EndTurn
+ }
+ };
+ }
+ candidate
+ .content
+ .parts
+ .into_iter()
+ .for_each(|part| match part {
+ Part::TextPart(text_part) => {
+ events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
+ }
+ Part::InlineDataPart(_) => {}
+ Part::FunctionCallPart(function_call_part) => {
+ wants_to_use_tool = true;
+ let name: Arc<str> = function_call_part.function_call.name.into();
+ let next_tool_id =
+ TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
+ let id: LanguageModelToolUseId =
+ format!("{}-{}", name, next_tool_id).into();
+
+ // Normalize empty string signatures to None
+ let thought_signature = function_call_part
+ .thought_signature
+ .filter(|s| !s.is_empty());
+
+ events.push(Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id,
+ name,
+ is_input_complete: true,
+ raw_input: function_call_part.function_call.args.to_string(),
+ input: function_call_part.function_call.args,
+ thought_signature,
+ },
+ )));
+ }
+ Part::FunctionResponsePart(_) => {}
+ Part::ThoughtPart(part) => {
+ events.push(Ok(LanguageModelCompletionEvent::Thinking {
+ text: "(Encrypted thought)".to_string(), // TODO: Can we populate this from thought summaries?
+ signature: Some(part.thought_signature),
+ }));
+ }
+ });
+ }
+ }
+
+ // Even when Gemini wants to use a Tool, the API
+ // responds with `finish_reason: STOP`
+ if wants_to_use_tool {
+ self.stop_reason = StopReason::ToolUse;
+ events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
+ }
+ events
+ }
+}
+
+/// Count tokens for a Google AI model using tiktoken. This is synchronous;
+/// callers should spawn it on a background thread if needed.
+pub fn count_google_tokens(request: LanguageModelRequest) -> Result<u64> {
+ let messages = request
+ .messages
+ .into_iter()
+ .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
+ role: match message.role {
+ Role::User => "user".into(),
+ Role::Assistant => "assistant".into(),
+ Role::System => "system".into(),
+ },
+ content: Some(message.string_contents()),
+ name: None,
+ function_call: None,
+ })
+ .collect::<Vec<_>>();
+
+ // Tiktoken doesn't yet support these models, so we manually use the
+ // same tokenizer as GPT-4.
+ tiktoken_rs::num_tokens_from_messages("gpt-4", &messages).map(|tokens| tokens as u64)
+}
+
+fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
+ if let Some(prompt_token_count) = new.prompt_token_count {
+ usage.prompt_token_count = Some(prompt_token_count);
+ }
+ if let Some(cached_content_token_count) = new.cached_content_token_count {
+ usage.cached_content_token_count = Some(cached_content_token_count);
+ }
+ if let Some(candidates_token_count) = new.candidates_token_count {
+ usage.candidates_token_count = Some(candidates_token_count);
+ }
+ if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
+ usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
+ }
+ if let Some(thoughts_token_count) = new.thoughts_token_count {
+ usage.thoughts_token_count = Some(thoughts_token_count);
+ }
+ if let Some(total_token_count) = new.total_token_count {
+ usage.total_token_count = Some(total_token_count);
+ }
+}
+
+fn convert_usage(usage: &UsageMetadata) -> TokenUsage {
+ let prompt_tokens = usage.prompt_token_count.unwrap_or(0);
+ let cached_tokens = usage.cached_content_token_count.unwrap_or(0);
+ let input_tokens = prompt_tokens - cached_tokens;
+ let output_tokens = usage.candidates_token_count.unwrap_or(0);
+
+ TokenUsage {
+ input_tokens,
+ output_tokens,
+ cache_read_input_tokens: cached_tokens,
+ cache_creation_input_tokens: 0,
+ }
+}
+
+#[cfg(test)]
+mod tests {
+ use super::*;
+ use crate::{
+ Content, FunctionCall, FunctionCallPart, GenerateContentCandidate, GenerateContentResponse,
+ Part, Role as GoogleRole,
+ };
+ use serde_json::json;
+
+ #[test]
+ fn test_function_call_with_signature_creates_tool_use_with_signature() {
+ let mut mapper = GoogleEventMapper::new();
+
+ let response = GenerateContentResponse {
+ candidates: Some(vec![GenerateContentCandidate {
+ index: Some(0),
+ content: Content {
+ parts: vec![Part::FunctionCallPart(FunctionCallPart {
+ function_call: FunctionCall {
+ name: "test_function".to_string(),
+ args: json!({"arg": "value"}),
+ },
+ thought_signature: Some("test_signature_123".to_string()),
+ })],
+ role: GoogleRole::Model,
+ },
+ finish_reason: None,
+ finish_message: None,
+ safety_ratings: None,
+ citation_metadata: None,
+ }]),
+ prompt_feedback: None,
+ usage_metadata: None,
+ };
+
+ let events = mapper.map_event(response);
+ assert_eq!(events.len(), 2);
+
+ if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
+ assert_eq!(tool_use.name.as_ref(), "test_function");
+ assert_eq!(
+ tool_use.thought_signature.as_deref(),
+ Some("test_signature_123")
+ );
+ } else {
+ panic!("Expected ToolUse event");
+ }
+ }
+
+ #[test]
+ fn test_function_call_without_signature_has_none() {
+ let mut mapper = GoogleEventMapper::new();
+
+ let response = GenerateContentResponse {
+ candidates: Some(vec![GenerateContentCandidate {
+ index: Some(0),
+ content: Content {
+ parts: vec![Part::FunctionCallPart(FunctionCallPart {
+ function_call: FunctionCall {
+ name: "test_function".to_string(),
+ args: json!({"arg": "value"}),
+ },
+ thought_signature: None,
+ })],
+ role: GoogleRole::Model,
+ },
+ finish_reason: None,
+ finish_message: None,
+ safety_ratings: None,
+ citation_metadata: None,
+ }]),
+ prompt_feedback: None,
+ usage_metadata: None,
+ };
+
+ let events = mapper.map_event(response);
+ assert_eq!(events.len(), 2);
+
+ if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
+ assert!(tool_use.thought_signature.is_none());
+ } else {
+ panic!("Expected ToolUse event");
+ }
+ }
+
+ #[test]
+ fn test_empty_string_signature_normalized_to_none() {
+ let mut mapper = GoogleEventMapper::new();
+
+ let response = GenerateContentResponse {
+ candidates: Some(vec![GenerateContentCandidate {
+ index: Some(0),
+ content: Content {
+ parts: vec![Part::FunctionCallPart(FunctionCallPart {
+ function_call: FunctionCall {
+ name: "test_function".to_string(),
+ args: json!({"arg": "value"}),
+ },
+ thought_signature: Some("".to_string()),
+ })],
+ role: GoogleRole::Model,
+ },
+ finish_reason: None,
+ finish_message: None,
+ safety_ratings: None,
+ citation_metadata: None,
+ }]),
+ prompt_feedback: None,
+ usage_metadata: None,
+ };
+
+ let events = mapper.map_event(response);
+ if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
+ assert!(tool_use.thought_signature.is_none());
+ } else {
+ panic!("Expected ToolUse event");
+ }
+ }
+}
@@ -3,8 +3,9 @@ use std::mem;
use anyhow::{Result, anyhow, bail};
use futures::{AsyncBufReadExt, AsyncReadExt, StreamExt, io::BufReader, stream::BoxStream};
use http_client::{AsyncBody, HttpClient, Method, Request as HttpRequest};
+pub use language_model_core::ModelMode as GoogleModelMode;
use serde::{Deserialize, Deserializer, Serialize, Serializer};
-pub use settings::ModelMode as GoogleModelMode;
+pub mod completion;
pub const API_URL: &str = "https://generativelanguage.googleapis.com";
@@ -56,6 +56,7 @@ etagere = "0.2"
futures.workspace = true
futures-concurrency.workspace = true
gpui_macros.workspace = true
+gpui_shared_string.workspace = true
http_client.workspace = true
image.workspace = true
inventory.workspace = true
@@ -39,7 +39,6 @@ pub mod profiler;
#[expect(missing_docs)]
pub mod queue;
mod scene;
-mod shared_string;
mod shared_uri;
mod style;
mod styled;
@@ -92,6 +91,7 @@ pub use global::*;
pub use gpui_macros::{
AppContext, IntoElement, Render, VisualContext, property_test, register_action, test,
};
+pub use gpui_shared_string::*;
pub use gpui_util::arc_cow::ArcCow;
pub use http_client;
pub use input::*;
@@ -106,7 +106,6 @@ pub use profiler::*;
pub use queue::{PriorityQueueReceiver, PriorityQueueSender};
pub use refineable::*;
pub use scene::*;
-pub use shared_string::*;
pub use shared_uri::*;
use std::{any::Any, future::Future};
pub use style::*;
@@ -105,18 +105,36 @@ pub enum SvgSize {
impl SvgRenderer {
/// Creates a new SVG renderer with the provided asset source.
pub fn new(asset_source: Arc<dyn AssetSource>) -> Self {
- static FONT_DB: LazyLock<Arc<usvg::fontdb::Database>> = LazyLock::new(|| {
+ static SYSTEM_FONT_DB: LazyLock<Arc<usvg::fontdb::Database>> = LazyLock::new(|| {
let mut db = usvg::fontdb::Database::new();
db.load_system_fonts();
Arc::new(db)
});
+
+ let fontdb = {
+ let mut db = (**SYSTEM_FONT_DB).clone();
+ load_bundled_fonts(&*asset_source, &mut db);
+ fix_generic_font_families(&mut db);
+ Arc::new(db)
+ };
+
let default_font_resolver = usvg::FontResolver::default_font_selector();
let font_resolver = Box::new(
move |font: &usvg::Font, db: &mut Arc<usvg::fontdb::Database>| {
if db.is_empty() {
- *db = FONT_DB.clone();
+ *db = fontdb.clone();
+ }
+ if let Some(id) = default_font_resolver(font, db) {
+ return Some(id);
}
- default_font_resolver(font, db)
+ // fontdb doesn't recognize CSS system font keywords like "system-ui"
+ // or "ui-sans-serif", so fall back to sans-serif before any face.
+ let sans_query = usvg::fontdb::Query {
+ families: &[usvg::fontdb::Family::SansSerif],
+ ..Default::default()
+ };
+ db.query(&sans_query)
+ .or_else(|| db.faces().next().map(|f| f.id))
},
);
let default_fallback_selection = usvg::FontResolver::default_fallback_selector();
@@ -226,14 +244,69 @@ impl SvgRenderer {
}
}
+fn load_bundled_fonts(asset_source: &dyn AssetSource, db: &mut usvg::fontdb::Database) {
+ let font_paths = [
+ "fonts/ibm-plex-sans/IBMPlexSans-Regular.ttf",
+ "fonts/lilex/Lilex-Regular.ttf",
+ ];
+ for path in font_paths {
+ match asset_source.load(path) {
+ Ok(Some(data)) => db.load_font_data(data.into_owned()),
+ Ok(None) => log::warn!("Bundled font not found: {path}"),
+ Err(error) => log::warn!("Failed to load bundled font {path}: {error}"),
+ }
+ }
+}
+
+// fontdb defaults generic families to Microsoft fonts ("Arial", "Times New Roman")
+// which aren't installed on most Linux systems. fontconfig normally overrides these,
+// but when it fails the defaults remain and all generic family queries return None.
+fn fix_generic_font_families(db: &mut usvg::fontdb::Database) {
+ use usvg::fontdb::{Family, Query};
+
+ let families_and_fallbacks: &[(Family<'_>, &str)] = &[
+ (Family::SansSerif, "IBM Plex Sans"),
+ // No serif font bundled; use sans-serif as best available fallback.
+ (Family::Serif, "IBM Plex Sans"),
+ (Family::Monospace, "Lilex"),
+ (Family::Cursive, "IBM Plex Sans"),
+ (Family::Fantasy, "IBM Plex Sans"),
+ ];
+
+ for (family, fallback_name) in families_and_fallbacks {
+ let query = Query {
+ families: &[*family],
+ ..Default::default()
+ };
+ if db.query(&query).is_none() {
+ match family {
+ Family::SansSerif => db.set_sans_serif_family(*fallback_name),
+ Family::Serif => db.set_serif_family(*fallback_name),
+ Family::Monospace => db.set_monospace_family(*fallback_name),
+ Family::Cursive => db.set_cursive_family(*fallback_name),
+ Family::Fantasy => db.set_fantasy_family(*fallback_name),
+ _ => {}
+ }
+ }
+ }
+}
+
#[cfg(test)]
mod tests {
use super::*;
+ use usvg::fontdb::{Database, Family, Query};
const IBM_PLEX_REGULAR: &[u8] =
include_bytes!("../../../assets/fonts/ibm-plex-sans/IBMPlexSans-Regular.ttf");
const LILEX_REGULAR: &[u8] = include_bytes!("../../../assets/fonts/lilex/Lilex-Regular.ttf");
+ fn db_with_bundled_fonts() -> Database {
+ let mut db = Database::new();
+ db.load_font_data(IBM_PLEX_REGULAR.to_vec());
+ db.load_font_data(LILEX_REGULAR.to_vec());
+ db
+ }
+
#[test]
fn test_is_emoji_presentation() {
let cases = [
@@ -266,11 +339,33 @@ mod tests {
}
#[test]
- fn test_select_emoji_font_skips_family_without_glyph() {
- let mut db = usvg::fontdb::Database::new();
+ fn fix_generic_font_families_sets_all_families() {
+ let mut db = db_with_bundled_fonts();
+ fix_generic_font_families(&mut db);
+
+ let families = [
+ Family::SansSerif,
+ Family::Serif,
+ Family::Monospace,
+ Family::Cursive,
+ Family::Fantasy,
+ ];
- db.load_font_data(IBM_PLEX_REGULAR.to_vec());
- db.load_font_data(LILEX_REGULAR.to_vec());
+ for family in families {
+ let query = Query {
+ families: &[family],
+ ..Default::default()
+ };
+ assert!(
+ db.query(&query).is_some(),
+ "Expected generic family {family:?} to resolve after fix_generic_font_families"
+ );
+ }
+ }
+
+ #[test]
+ fn test_select_emoji_font_skips_family_without_glyph() {
+ let mut db = db_with_bundled_fonts();
let ibm_plex_sans = db
.query(&usvg::fontdb::Query {
@@ -294,4 +389,22 @@ mod tests {
assert!(!font_has_char(&db, ibm_plex_sans, 'β'));
assert!(font_has_char(&db, selected, 'β'));
}
+
+ #[test]
+ fn fix_generic_font_families_monospace_resolves_to_lilex() {
+ let mut db = db_with_bundled_fonts();
+ fix_generic_font_families(&mut db);
+
+ let query = Query {
+ families: &[Family::Monospace],
+ ..Default::default()
+ };
+ let id = db.query(&query).expect("Monospace should resolve");
+ let face = db.face(id).expect("Face should exist");
+ assert!(
+ face.families.iter().any(|(name, _)| name.contains("Lilex")),
+ "Monospace should map to Lilex, got {:?}",
+ face.families
+ );
+ }
}
@@ -882,7 +882,7 @@ mod tests {
],
len: 6,
}),
- text: SharedString::new("abcdef".to_string()),
+ text: "abcdef".into(),
decoration_runs: SmallVec::new(),
};
@@ -0,0 +1,17 @@
+[package]
+name = "gpui_shared_string"
+version = "0.1.0"
+publish.workspace = true
+edition.workspace = true
+
+[lib]
+path = "gpui_shared_string.rs"
+
+[dependencies]
+derive_more.workspace = true
+gpui_util.workspace = true
+schemars.workspace = true
+serde.workspace = true
+
+[lints]
+workspace = true
@@ -0,0 +1 @@
+../../LICENSE-APACHE
@@ -207,11 +207,7 @@ async fn extract_tar_gz(
from: impl AsyncRead + Unpin,
) -> Result<(), anyhow::Error> {
let decompressed_bytes = GzipDecoder::new(BufReader::new(from));
- let archive = async_tar::Archive::new(decompressed_bytes);
- archive
- .unpack(&destination_path)
- .await
- .with_context(|| format!("extracting {url} to {destination_path:?}"))?;
+ unpack_tar_archive(destination_path, url, decompressed_bytes).await?;
Ok(())
}
@@ -221,7 +217,21 @@ async fn extract_tar_bz2(
from: impl AsyncRead + Unpin,
) -> Result<(), anyhow::Error> {
let decompressed_bytes = BzDecoder::new(BufReader::new(from));
- let archive = async_tar::Archive::new(decompressed_bytes);
+ unpack_tar_archive(destination_path, url, decompressed_bytes).await?;
+ Ok(())
+}
+
+async fn unpack_tar_archive(
+ destination_path: &Path,
+ url: &str,
+ archive_bytes: impl AsyncRead + Unpin,
+) -> Result<(), anyhow::Error> {
+ // We don't need to set the modified time. It's irrelevant to downloaded
+ // archive verification, and some filesystems return errors when asked to
+ // apply it after extraction.
+ let archive = async_tar::ArchiveBuilder::new(archive_bytes)
+ .set_preserve_mtime(false)
+ .build();
archive
.unpack(&destination_path)
.await
@@ -134,7 +134,7 @@ pub enum IconName {
Flame,
Folder,
FolderOpen,
- FolderPlus,
+ FolderOpenAdd,
FolderSearch,
Font,
FontSize,
@@ -184,6 +184,7 @@ pub enum IconName {
NewThread,
Notepad,
OpenFolder,
+ OpenNewWindow,
Option,
PageDown,
PageUp,
@@ -3733,16 +3733,24 @@ impl BufferSnapshot {
/// returned in chunks where each chunk has a single syntax highlighting style and
/// diagnostic status.
#[ztracing::instrument(skip_all)]
- pub fn chunks<T: ToOffset>(&self, range: Range<T>, language_aware: bool) -> BufferChunks<'_> {
+ pub fn chunks<T: ToOffset>(
+ &self,
+ range: Range<T>,
+ language_aware: LanguageAwareStyling,
+ ) -> BufferChunks<'_> {
let range = range.start.to_offset(self)..range.end.to_offset(self);
let mut syntax = None;
- if language_aware {
+ if language_aware.tree_sitter {
syntax = Some(self.get_highlights(range.clone()));
}
- // We want to look at diagnostic spans only when iterating over language-annotated chunks.
- let diagnostics = language_aware;
- BufferChunks::new(self.text.as_rope(), range, syntax, diagnostics, Some(self))
+ BufferChunks::new(
+ self.text.as_rope(),
+ range,
+ syntax,
+ language_aware.diagnostics,
+ Some(self),
+ )
}
pub fn highlighted_text_for_range<T: ToOffset>(
@@ -4477,7 +4485,13 @@ impl BufferSnapshot {
let mut text = String::new();
let mut highlight_ranges = Vec::new();
let mut name_ranges = Vec::new();
- let mut chunks = self.chunks(source_range_for_text.clone(), true);
+ let mut chunks = self.chunks(
+ source_range_for_text.clone(),
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ );
let mut last_buffer_range_end = 0;
for (buffer_range, is_name) in buffer_ranges {
let space_added = !text.is_empty() && buffer_range.start > last_buffer_range_end;
@@ -5402,7 +5416,13 @@ impl BufferSnapshot {
let mut words = BTreeMap::default();
let mut current_word_start_ix = None;
let mut chunk_ix = query.range.start;
- for chunk in self.chunks(query.range, false) {
+ for chunk in self.chunks(
+ query.range,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ ) {
for (i, c) in chunk.text.char_indices() {
let ix = chunk_ix + i;
if classifier.is_word(c) {
@@ -5441,6 +5461,15 @@ impl BufferSnapshot {
}
}
+/// A configuration to use when producing styled text chunks.
+#[derive(Clone, Copy)]
+pub struct LanguageAwareStyling {
+ /// Whether to highlight text chunks using tree-sitter.
+ pub tree_sitter: bool,
+ /// Whether to highlight text chunks based on the diagnostics data.
+ pub diagnostics: bool,
+}
+
pub struct WordsQuery<'a> {
/// Only returns words with all chars from the fuzzy string in them.
pub fuzzy_contents: Option<&'a str>,
@@ -4102,7 +4102,13 @@ fn test_random_chunk_bitmaps(cx: &mut App, mut rng: StdRng) {
let snapshot = buffer.read(cx).snapshot();
// Get all chunks and verify their bitmaps
- let chunks = snapshot.chunks(0..snapshot.len(), false);
+ let chunks = snapshot.chunks(
+ 0..snapshot.len(),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ );
for chunk in chunks {
let chunk_text = chunk.text;
@@ -10,7 +10,7 @@ path = "src/language_core.rs"
[dependencies]
anyhow.workspace = true
collections.workspace = true
-gpui.workspace = true
+gpui_shared_string.workspace = true
log.workspace = true
lsp.workspace = true
parking_lot.workspace = true
@@ -22,8 +22,6 @@ toml.workspace = true
tree-sitter.workspace = true
util.workspace = true
-[dev-dependencies]
-gpui = { workspace = true, features = ["test-support"] }
[features]
test-support = []
@@ -1,4 +1,4 @@
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
use lsp::{DiagnosticSeverity, NumberOrString};
use serde::{Deserialize, Serialize};
use serde_json::Value;
@@ -4,7 +4,7 @@ use crate::{
};
use anyhow::{Context as _, Result};
use collections::HashMap;
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
use lsp::LanguageServerName;
use parking_lot::Mutex;
use std::sync::atomic::{AtomicUsize, Ordering::SeqCst};
@@ -1,6 +1,6 @@
use crate::LanguageName;
use collections::{HashMap, HashSet, IndexSet};
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
use lsp::LanguageServerName;
use regex::Regex;
use schemars::{JsonSchema, SchemaGenerator, json_schema};
@@ -1,4 +1,4 @@
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use std::{
@@ -1,4 +1,4 @@
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
use serde::{Deserialize, Serialize};
/// Converts a value into an LSP position.
@@ -1,6 +1,6 @@
use std::borrow::Borrow;
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
#[derive(Clone, Debug, PartialEq, Eq, Hash, PartialOrd, Ord)]
pub struct ManifestName(SharedString);
@@ -6,7 +6,7 @@
use std::{path::Path, sync::Arc};
-use gpui::SharedString;
+use gpui_shared_string::SharedString;
use util::rel_path::RelPath;
use crate::{LanguageName, ManifestName};
@@ -16,13 +16,9 @@ doctest = false
test-support = []
[dependencies]
-anthropic = { workspace = true, features = ["schemars"] }
anyhow.workspace = true
credentials_provider.workspace = true
base64.workspace = true
-cloud_api_client.workspace = true
-cloud_api_types.workspace = true
-cloud_llm_client.workspace = true
collections.workspace = true
env_var.workspace = true
futures.workspace = true
@@ -30,14 +26,11 @@ gpui.workspace = true
http_client.workspace = true
icons.workspace = true
image.workspace = true
+language_model_core.workspace = true
log.workspace = true
-open_ai = { workspace = true, features = ["schemars"] }
-open_router.workspace = true
parking_lot.workspace = true
-schemars.workspace = true
serde.workspace = true
serde_json.workspace = true
-smol.workspace = true
thiserror.workspace = true
util.workspace = true
@@ -5,11 +5,10 @@ use crate::{
LanguageModelRequest, LanguageModelToolChoice,
};
use anyhow::anyhow;
-use futures::{FutureExt, channel::mpsc, future::BoxFuture, stream::BoxStream};
+use futures::{FutureExt, channel::mpsc, future::BoxFuture, stream::BoxStream, stream::StreamExt};
use gpui::{AnyView, App, AsyncApp, Entity, Task, Window};
use http_client::Result;
use parking_lot::Mutex;
-use smol::stream::StreamExt;
use std::sync::{
Arc,
atomic::{AtomicBool, Ordering::SeqCst},
@@ -1,380 +1,31 @@
mod api_key;
mod model;
-mod provider;
-mod rate_limiter;
mod registry;
mod request;
-mod role;
-pub mod tool_schema;
#[cfg(any(test, feature = "test-support"))]
pub mod fake_provider;
-use anyhow::{Result, anyhow};
-use cloud_llm_client::CompletionRequestStatus;
+pub use language_model_core::*;
+
+use anyhow::Result;
use futures::FutureExt;
use futures::{StreamExt, future::BoxFuture, stream::BoxStream};
-use gpui::{AnyView, App, AsyncApp, SharedString, Task, Window};
-use http_client::{StatusCode, http};
+use gpui::{AnyView, App, AsyncApp, Task, Window};
use icons::IconName;
use parking_lot::Mutex;
-use serde::{Deserialize, Serialize};
-use std::ops::{Add, Sub};
-use std::str::FromStr;
use std::sync::Arc;
-use std::time::Duration;
-use std::{fmt, io};
-use thiserror::Error;
-use util::serde::is_default;
pub use crate::api_key::{ApiKey, ApiKeyState};
pub use crate::model::*;
-pub use crate::rate_limiter::*;
pub use crate::registry::*;
-pub use crate::request::*;
-pub use crate::role::*;
-pub use crate::tool_schema::LanguageModelToolSchemaFormat;
+pub use crate::request::{LanguageModelImageExt, gpui_size_to_image_size, image_size_to_gpui};
pub use env_var::{EnvVar, env_var};
-pub use provider::*;
pub fn init(cx: &mut App) {
registry::init(cx);
}
-#[derive(Clone, Debug)]
-pub struct LanguageModelCacheConfiguration {
- pub max_cache_anchors: usize,
- pub should_speculate: bool,
- pub min_total_token: u64,
-}
-
-/// A completion event from a language model.
-#[derive(Debug, PartialEq, Clone, Serialize, Deserialize)]
-pub enum LanguageModelCompletionEvent {
- Queued {
- position: usize,
- },
- Started,
- Stop(StopReason),
- Text(String),
- Thinking {
- text: String,
- signature: Option<String>,
- },
- RedactedThinking {
- data: String,
- },
- ToolUse(LanguageModelToolUse),
- ToolUseJsonParseError {
- id: LanguageModelToolUseId,
- tool_name: Arc<str>,
- raw_input: Arc<str>,
- json_parse_error: String,
- },
- StartMessage {
- message_id: String,
- },
- ReasoningDetails(serde_json::Value),
- UsageUpdate(TokenUsage),
-}
-
-impl LanguageModelCompletionEvent {
- pub fn from_completion_request_status(
- status: CompletionRequestStatus,
- upstream_provider: LanguageModelProviderName,
- ) -> Result<Option<Self>, LanguageModelCompletionError> {
- match status {
- CompletionRequestStatus::Queued { position } => {
- Ok(Some(LanguageModelCompletionEvent::Queued { position }))
- }
- CompletionRequestStatus::Started => Ok(Some(LanguageModelCompletionEvent::Started)),
- CompletionRequestStatus::Unknown | CompletionRequestStatus::StreamEnded => Ok(None),
- CompletionRequestStatus::Failed {
- code,
- message,
- request_id: _,
- retry_after,
- } => Err(LanguageModelCompletionError::from_cloud_failure(
- upstream_provider,
- code,
- message,
- retry_after.map(Duration::from_secs_f64),
- )),
- }
- }
-}
-
-#[derive(Error, Debug)]
-pub enum LanguageModelCompletionError {
- #[error("prompt too large for context window")]
- PromptTooLarge { tokens: Option<u64> },
- #[error("missing {provider} API key")]
- NoApiKey { provider: LanguageModelProviderName },
- #[error("{provider}'s API rate limit exceeded")]
- RateLimitExceeded {
- provider: LanguageModelProviderName,
- retry_after: Option<Duration>,
- },
- #[error("{provider}'s API servers are overloaded right now")]
- ServerOverloaded {
- provider: LanguageModelProviderName,
- retry_after: Option<Duration>,
- },
- #[error("{provider}'s API server reported an internal server error: {message}")]
- ApiInternalServerError {
- provider: LanguageModelProviderName,
- message: String,
- },
- #[error("{message}")]
- UpstreamProviderError {
- message: String,
- status: StatusCode,
- retry_after: Option<Duration>,
- },
- #[error("HTTP response error from {provider}'s API: status {status_code} - {message:?}")]
- HttpResponseError {
- provider: LanguageModelProviderName,
- status_code: StatusCode,
- message: String,
- },
-
- // Client errors
- #[error("invalid request format to {provider}'s API: {message}")]
- BadRequestFormat {
- provider: LanguageModelProviderName,
- message: String,
- },
- #[error("authentication error with {provider}'s API: {message}")]
- AuthenticationError {
- provider: LanguageModelProviderName,
- message: String,
- },
- #[error("Permission error with {provider}'s API: {message}")]
- PermissionError {
- provider: LanguageModelProviderName,
- message: String,
- },
- #[error("language model provider API endpoint not found")]
- ApiEndpointNotFound { provider: LanguageModelProviderName },
- #[error("I/O error reading response from {provider}'s API")]
- ApiReadResponseError {
- provider: LanguageModelProviderName,
- #[source]
- error: io::Error,
- },
- #[error("error serializing request to {provider} API")]
- SerializeRequest {
- provider: LanguageModelProviderName,
- #[source]
- error: serde_json::Error,
- },
- #[error("error building request body to {provider} API")]
- BuildRequestBody {
- provider: LanguageModelProviderName,
- #[source]
- error: http::Error,
- },
- #[error("error sending HTTP request to {provider} API")]
- HttpSend {
- provider: LanguageModelProviderName,
- #[source]
- error: anyhow::Error,
- },
- #[error("error deserializing {provider} API response")]
- DeserializeResponse {
- provider: LanguageModelProviderName,
- #[source]
- error: serde_json::Error,
- },
-
- #[error("stream from {provider} ended unexpectedly")]
- StreamEndedUnexpectedly { provider: LanguageModelProviderName },
-
- // TODO: Ideally this would be removed in favor of having a comprehensive list of errors.
- #[error(transparent)]
- Other(#[from] anyhow::Error),
-}
-
-impl LanguageModelCompletionError {
- fn parse_upstream_error_json(message: &str) -> Option<(StatusCode, String)> {
- let error_json = serde_json::from_str::<serde_json::Value>(message).ok()?;
- let upstream_status = error_json
- .get("upstream_status")
- .and_then(|v| v.as_u64())
- .and_then(|status| u16::try_from(status).ok())
- .and_then(|status| StatusCode::from_u16(status).ok())?;
- let inner_message = error_json
- .get("message")
- .and_then(|v| v.as_str())
- .unwrap_or(message)
- .to_string();
- Some((upstream_status, inner_message))
- }
-
- pub fn from_cloud_failure(
- upstream_provider: LanguageModelProviderName,
- code: String,
- message: String,
- retry_after: Option<Duration>,
- ) -> Self {
- if let Some(tokens) = parse_prompt_too_long(&message) {
- // TODO: currently Anthropic PAYLOAD_TOO_LARGE response may cause INTERNAL_SERVER_ERROR
- // to be reported. This is a temporary workaround to handle this in the case where the
- // token limit has been exceeded.
- Self::PromptTooLarge {
- tokens: Some(tokens),
- }
- } else if code == "upstream_http_error" {
- if let Some((upstream_status, inner_message)) =
- Self::parse_upstream_error_json(&message)
- {
- return Self::from_http_status(
- upstream_provider,
- upstream_status,
- inner_message,
- retry_after,
- );
- }
- anyhow!("completion request failed, code: {code}, message: {message}").into()
- } else if let Some(status_code) = code
- .strip_prefix("upstream_http_")
- .and_then(|code| StatusCode::from_str(code).ok())
- {
- Self::from_http_status(upstream_provider, status_code, message, retry_after)
- } else if let Some(status_code) = code
- .strip_prefix("http_")
- .and_then(|code| StatusCode::from_str(code).ok())
- {
- Self::from_http_status(ZED_CLOUD_PROVIDER_NAME, status_code, message, retry_after)
- } else {
- anyhow!("completion request failed, code: {code}, message: {message}").into()
- }
- }
-
- pub fn from_http_status(
- provider: LanguageModelProviderName,
- status_code: StatusCode,
- message: String,
- retry_after: Option<Duration>,
- ) -> Self {
- match status_code {
- StatusCode::BAD_REQUEST => Self::BadRequestFormat { provider, message },
- StatusCode::UNAUTHORIZED => Self::AuthenticationError { provider, message },
- StatusCode::FORBIDDEN => Self::PermissionError { provider, message },
- StatusCode::NOT_FOUND => Self::ApiEndpointNotFound { provider },
- StatusCode::PAYLOAD_TOO_LARGE => Self::PromptTooLarge {
- tokens: parse_prompt_too_long(&message),
- },
- StatusCode::TOO_MANY_REQUESTS => Self::RateLimitExceeded {
- provider,
- retry_after,
- },
- StatusCode::INTERNAL_SERVER_ERROR => Self::ApiInternalServerError { provider, message },
- StatusCode::SERVICE_UNAVAILABLE => Self::ServerOverloaded {
- provider,
- retry_after,
- },
- _ if status_code.as_u16() == 529 => Self::ServerOverloaded {
- provider,
- retry_after,
- },
- _ => Self::HttpResponseError {
- provider,
- status_code,
- message,
- },
- }
- }
-}
-
-#[derive(Debug, PartialEq, Clone, Copy, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum StopReason {
- EndTurn,
- MaxTokens,
- ToolUse,
- Refusal,
-}
-
-#[derive(Debug, PartialEq, Clone, Copy, Serialize, Deserialize, Default)]
-pub struct TokenUsage {
- #[serde(default, skip_serializing_if = "is_default")]
- pub input_tokens: u64,
- #[serde(default, skip_serializing_if = "is_default")]
- pub output_tokens: u64,
- #[serde(default, skip_serializing_if = "is_default")]
- pub cache_creation_input_tokens: u64,
- #[serde(default, skip_serializing_if = "is_default")]
- pub cache_read_input_tokens: u64,
-}
-
-impl TokenUsage {
- pub fn total_tokens(&self) -> u64 {
- self.input_tokens
- + self.output_tokens
- + self.cache_read_input_tokens
- + self.cache_creation_input_tokens
- }
-}
-
-impl Add<TokenUsage> for TokenUsage {
- type Output = Self;
-
- fn add(self, other: Self) -> Self {
- Self {
- input_tokens: self.input_tokens + other.input_tokens,
- output_tokens: self.output_tokens + other.output_tokens,
- cache_creation_input_tokens: self.cache_creation_input_tokens
- + other.cache_creation_input_tokens,
- cache_read_input_tokens: self.cache_read_input_tokens + other.cache_read_input_tokens,
- }
- }
-}
-
-impl Sub<TokenUsage> for TokenUsage {
- type Output = Self;
-
- fn sub(self, other: Self) -> Self {
- Self {
- input_tokens: self.input_tokens - other.input_tokens,
- output_tokens: self.output_tokens - other.output_tokens,
- cache_creation_input_tokens: self.cache_creation_input_tokens
- - other.cache_creation_input_tokens,
- cache_read_input_tokens: self.cache_read_input_tokens - other.cache_read_input_tokens,
- }
- }
-}
-
-#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
-pub struct LanguageModelToolUseId(Arc<str>);
-
-impl fmt::Display for LanguageModelToolUseId {
- fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
- write!(f, "{}", self.0)
- }
-}
-
-impl<T> From<T> for LanguageModelToolUseId
-where
- T: Into<Arc<str>>,
-{
- fn from(value: T) -> Self {
- Self(value.into())
- }
-}
-
-#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
-pub struct LanguageModelToolUse {
- pub id: LanguageModelToolUseId,
- pub name: Arc<str>,
- pub raw_input: String,
- pub input: serde_json::Value,
- pub is_input_complete: bool,
- /// Thought signature the model sent us. Some models require that this
- /// signature be preserved and sent back in conversation history for validation.
- pub thought_signature: Option<String>,
-}
-
pub struct LanguageModelTextStream {
pub message_id: Option<String>,
pub stream: BoxStream<'static, Result<String, LanguageModelCompletionError>>,
@@ -392,13 +43,6 @@ impl Default for LanguageModelTextStream {
}
}
-#[derive(Debug, Clone)]
-pub struct LanguageModelEffortLevel {
- pub name: SharedString,
- pub value: SharedString,
- pub is_default: bool,
-}
-
pub trait LanguageModel: Send + Sync {
fn id(&self) -> LanguageModelId;
fn name(&self) -> LanguageModelName;
@@ -605,7 +249,7 @@ pub trait LanguageModel: Send + Sync {
}
impl std::fmt::Debug for dyn LanguageModel {
- fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+ fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("<dyn LanguageModel>")
.field("id", &self.id())
.field("name", &self.name())
@@ -619,17 +263,6 @@ impl std::fmt::Debug for dyn LanguageModel {
}
}
-/// An error that occurred when trying to authenticate the language model provider.
-#[derive(Debug, Error)]
-pub enum AuthenticateError {
- #[error("connection refused")]
- ConnectionRefused,
- #[error("credentials not found")]
- CredentialsNotFound,
- #[error(transparent)]
- Other(#[from] anyhow::Error),
-}
-
/// Either a built-in icon name or a path to an external SVG.
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum IconOrSvg {
@@ -692,18 +325,6 @@ pub trait LanguageModelProviderState: 'static {
}
}
-#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd, Serialize, Deserialize)]
-pub struct LanguageModelId(pub SharedString);
-
-#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
-pub struct LanguageModelName(pub SharedString);
-
-#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
-pub struct LanguageModelProviderId(pub SharedString);
-
-#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
-pub struct LanguageModelProviderName(pub SharedString);
-
#[derive(Clone, Debug, PartialEq)]
pub enum LanguageModelCostInfo {
/// Cost per 1,000 input and output tokens
@@ -741,245 +362,3 @@ impl LanguageModelCostInfo {
}
}
}
-
-impl LanguageModelProviderId {
- pub const fn new(id: &'static str) -> Self {
- Self(SharedString::new_static(id))
- }
-}
-
-impl LanguageModelProviderName {
- pub const fn new(id: &'static str) -> Self {
- Self(SharedString::new_static(id))
- }
-}
-
-impl fmt::Display for LanguageModelProviderId {
- fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
- write!(f, "{}", self.0)
- }
-}
-
-impl fmt::Display for LanguageModelProviderName {
- fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
- write!(f, "{}", self.0)
- }
-}
-
-impl From<String> for LanguageModelId {
- fn from(value: String) -> Self {
- Self(SharedString::from(value))
- }
-}
-
-impl From<String> for LanguageModelName {
- fn from(value: String) -> Self {
- Self(SharedString::from(value))
- }
-}
-
-impl From<String> for LanguageModelProviderId {
- fn from(value: String) -> Self {
- Self(SharedString::from(value))
- }
-}
-
-impl From<String> for LanguageModelProviderName {
- fn from(value: String) -> Self {
- Self(SharedString::from(value))
- }
-}
-
-impl From<Arc<str>> for LanguageModelProviderId {
- fn from(value: Arc<str>) -> Self {
- Self(SharedString::from(value))
- }
-}
-
-impl From<Arc<str>> for LanguageModelProviderName {
- fn from(value: Arc<str>) -> Self {
- Self(SharedString::from(value))
- }
-}
-
-#[cfg(test)]
-mod tests {
- use super::*;
-
- #[test]
- fn test_from_cloud_failure_with_upstream_http_error() {
- let error = LanguageModelCompletionError::from_cloud_failure(
- String::from("anthropic").into(),
- "upstream_http_error".to_string(),
- r#"{"code":"upstream_http_error","message":"Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout","upstream_status":503}"#.to_string(),
- None,
- );
-
- match error {
- LanguageModelCompletionError::ServerOverloaded { provider, .. } => {
- assert_eq!(provider.0, "anthropic");
- }
- _ => panic!(
- "Expected ServerOverloaded error for 503 status, got: {:?}",
- error
- ),
- }
-
- let error = LanguageModelCompletionError::from_cloud_failure(
- String::from("anthropic").into(),
- "upstream_http_error".to_string(),
- r#"{"code":"upstream_http_error","message":"Internal server error","upstream_status":500}"#.to_string(),
- None,
- );
-
- match error {
- LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
- assert_eq!(provider.0, "anthropic");
- assert_eq!(message, "Internal server error");
- }
- _ => panic!(
- "Expected ApiInternalServerError for 500 status, got: {:?}",
- error
- ),
- }
- }
-
- #[test]
- fn test_from_cloud_failure_with_standard_format() {
- let error = LanguageModelCompletionError::from_cloud_failure(
- String::from("anthropic").into(),
- "upstream_http_503".to_string(),
- "Service unavailable".to_string(),
- None,
- );
-
- match error {
- LanguageModelCompletionError::ServerOverloaded { provider, .. } => {
- assert_eq!(provider.0, "anthropic");
- }
- _ => panic!("Expected ServerOverloaded error for upstream_http_503"),
- }
- }
-
- #[test]
- fn test_upstream_http_error_connection_timeout() {
- let error = LanguageModelCompletionError::from_cloud_failure(
- String::from("anthropic").into(),
- "upstream_http_error".to_string(),
- r#"{"code":"upstream_http_error","message":"Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout","upstream_status":503}"#.to_string(),
- None,
- );
-
- match error {
- LanguageModelCompletionError::ServerOverloaded { provider, .. } => {
- assert_eq!(provider.0, "anthropic");
- }
- _ => panic!(
- "Expected ServerOverloaded error for connection timeout with 503 status, got: {:?}",
- error
- ),
- }
-
- let error = LanguageModelCompletionError::from_cloud_failure(
- String::from("anthropic").into(),
- "upstream_http_error".to_string(),
- r#"{"code":"upstream_http_error","message":"Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout","upstream_status":500}"#.to_string(),
- None,
- );
-
- match error {
- LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
- assert_eq!(provider.0, "anthropic");
- assert_eq!(
- message,
- "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout"
- );
- }
- _ => panic!(
- "Expected ApiInternalServerError for connection timeout with 500 status, got: {:?}",
- error
- ),
- }
- }
-
- #[test]
- fn test_language_model_tool_use_serializes_with_signature() {
- use serde_json::json;
-
- let tool_use = LanguageModelToolUse {
- id: LanguageModelToolUseId::from("test_id"),
- name: "test_tool".into(),
- raw_input: json!({"arg": "value"}).to_string(),
- input: json!({"arg": "value"}),
- is_input_complete: true,
- thought_signature: Some("test_signature".to_string()),
- };
-
- let serialized = serde_json::to_value(&tool_use).unwrap();
-
- assert_eq!(serialized["id"], "test_id");
- assert_eq!(serialized["name"], "test_tool");
- assert_eq!(serialized["thought_signature"], "test_signature");
- }
-
- #[test]
- fn test_language_model_tool_use_deserializes_with_missing_signature() {
- use serde_json::json;
-
- let json = json!({
- "id": "test_id",
- "name": "test_tool",
- "raw_input": "{\"arg\":\"value\"}",
- "input": {"arg": "value"},
- "is_input_complete": true
- });
-
- let tool_use: LanguageModelToolUse = serde_json::from_value(json).unwrap();
-
- assert_eq!(tool_use.id, LanguageModelToolUseId::from("test_id"));
- assert_eq!(tool_use.name.as_ref(), "test_tool");
- assert_eq!(tool_use.thought_signature, None);
- }
-
- #[test]
- fn test_language_model_tool_use_round_trip_with_signature() {
- use serde_json::json;
-
- let original = LanguageModelToolUse {
- id: LanguageModelToolUseId::from("round_trip_id"),
- name: "round_trip_tool".into(),
- raw_input: json!({"key": "value"}).to_string(),
- input: json!({"key": "value"}),
- is_input_complete: true,
- thought_signature: Some("round_trip_sig".to_string()),
- };
-
- let serialized = serde_json::to_value(&original).unwrap();
- let deserialized: LanguageModelToolUse = serde_json::from_value(serialized).unwrap();
-
- assert_eq!(deserialized.id, original.id);
- assert_eq!(deserialized.name, original.name);
- assert_eq!(deserialized.thought_signature, original.thought_signature);
- }
-
- #[test]
- fn test_language_model_tool_use_round_trip_without_signature() {
- use serde_json::json;
-
- let original = LanguageModelToolUse {
- id: LanguageModelToolUseId::from("no_sig_id"),
- name: "no_sig_tool".into(),
- raw_input: json!({"arg": "value"}).to_string(),
- input: json!({"arg": "value"}),
- is_input_complete: true,
- thought_signature: None,
- };
-
- let serialized = serde_json::to_value(&original).unwrap();
- let deserialized: LanguageModelToolUse = serde_json::from_value(serialized).unwrap();
-
- assert_eq!(deserialized.id, original.id);
- assert_eq!(deserialized.name, original.name);
- assert_eq!(deserialized.thought_signature, None);
- }
-}
@@ -1,10 +1,5 @@
use std::fmt;
-use std::sync::Arc;
-use cloud_api_client::ClientApiError;
-use cloud_api_client::CloudApiClient;
-use cloud_api_types::OrganizationId;
-use smol::lock::{RwLock, RwLockUpgradableReadGuard, RwLockWriteGuard};
use thiserror::Error;
#[derive(Error, Debug)]
@@ -18,71 +13,3 @@ impl fmt::Display for PaymentRequiredError {
)
}
}
-
-#[derive(Clone, Default)]
-pub struct LlmApiToken(Arc<RwLock<Option<String>>>);
-
-impl LlmApiToken {
- pub async fn acquire(
- &self,
- client: &CloudApiClient,
- system_id: Option<String>,
- organization_id: Option<OrganizationId>,
- ) -> Result<String, ClientApiError> {
- let lock = self.0.upgradable_read().await;
- if let Some(token) = lock.as_ref() {
- Ok(token.to_string())
- } else {
- Self::fetch(
- RwLockUpgradableReadGuard::upgrade(lock).await,
- client,
- system_id,
- organization_id,
- )
- .await
- }
- }
-
- pub async fn refresh(
- &self,
- client: &CloudApiClient,
- system_id: Option<String>,
- organization_id: Option<OrganizationId>,
- ) -> Result<String, ClientApiError> {
- Self::fetch(self.0.write().await, client, system_id, organization_id).await
- }
-
- /// Clears the existing token before attempting to fetch a new one.
- ///
- /// Used when switching organizations so that a failed refresh doesn't
- /// leave a token for the wrong organization.
- pub async fn clear_and_refresh(
- &self,
- client: &CloudApiClient,
- system_id: Option<String>,
- organization_id: Option<OrganizationId>,
- ) -> Result<String, ClientApiError> {
- let mut lock = self.0.write().await;
- *lock = None;
- Self::fetch(lock, client, system_id, organization_id).await
- }
-
- async fn fetch(
- mut lock: RwLockWriteGuard<'_, Option<String>>,
- client: &CloudApiClient,
- system_id: Option<String>,
- organization_id: Option<OrganizationId>,
- ) -> Result<String, ClientApiError> {
- let result = client.create_llm_token(system_id, organization_id).await;
- match result {
- Ok(response) => {
- *lock = Some(response.token.0.clone());
- Ok(response.token.0)
- }
- Err(err) => {
- *lock = None;
- Err(err)
- }
- }
- }
-}
@@ -1,12 +0,0 @@
-pub mod anthropic;
-pub mod google;
-pub mod open_ai;
-pub mod open_router;
-pub mod x_ai;
-pub mod zed;
-
-pub use anthropic::*;
-pub use google::*;
-pub use open_ai::*;
-pub use x_ai::*;
-pub use zed::*;
@@ -1,80 +0,0 @@
-use crate::{LanguageModelCompletionError, LanguageModelProviderId, LanguageModelProviderName};
-use anthropic::AnthropicError;
-pub use anthropic::parse_prompt_too_long;
-
-pub const ANTHROPIC_PROVIDER_ID: LanguageModelProviderId =
- LanguageModelProviderId::new("anthropic");
-pub const ANTHROPIC_PROVIDER_NAME: LanguageModelProviderName =
- LanguageModelProviderName::new("Anthropic");
-
-impl From<AnthropicError> for LanguageModelCompletionError {
- fn from(error: AnthropicError) -> Self {
- let provider = ANTHROPIC_PROVIDER_NAME;
- match error {
- AnthropicError::SerializeRequest(error) => Self::SerializeRequest { provider, error },
- AnthropicError::BuildRequestBody(error) => Self::BuildRequestBody { provider, error },
- AnthropicError::HttpSend(error) => Self::HttpSend { provider, error },
- AnthropicError::DeserializeResponse(error) => {
- Self::DeserializeResponse { provider, error }
- }
- AnthropicError::ReadResponse(error) => Self::ApiReadResponseError { provider, error },
- AnthropicError::HttpResponseError {
- status_code,
- message,
- } => Self::HttpResponseError {
- provider,
- status_code,
- message,
- },
- AnthropicError::RateLimit { retry_after } => Self::RateLimitExceeded {
- provider,
- retry_after: Some(retry_after),
- },
- AnthropicError::ServerOverloaded { retry_after } => Self::ServerOverloaded {
- provider,
- retry_after,
- },
- AnthropicError::ApiError(api_error) => api_error.into(),
- }
- }
-}
-
-impl From<anthropic::ApiError> for LanguageModelCompletionError {
- fn from(error: anthropic::ApiError) -> Self {
- use anthropic::ApiErrorCode::*;
- let provider = ANTHROPIC_PROVIDER_NAME;
- match error.code() {
- Some(code) => match code {
- InvalidRequestError => Self::BadRequestFormat {
- provider,
- message: error.message,
- },
- AuthenticationError => Self::AuthenticationError {
- provider,
- message: error.message,
- },
- PermissionError => Self::PermissionError {
- provider,
- message: error.message,
- },
- NotFoundError => Self::ApiEndpointNotFound { provider },
- RequestTooLarge => Self::PromptTooLarge {
- tokens: parse_prompt_too_long(&error.message),
- },
- RateLimitError => Self::RateLimitExceeded {
- provider,
- retry_after: None,
- },
- ApiError => Self::ApiInternalServerError {
- provider,
- message: error.message,
- },
- OverloadedError => Self::ServerOverloaded {
- provider,
- retry_after: None,
- },
- },
- None => Self::Other(error.into()),
- }
- }
-}
@@ -1,5 +0,0 @@
-use crate::{LanguageModelProviderId, LanguageModelProviderName};
-
-pub const GOOGLE_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("google");
-pub const GOOGLE_PROVIDER_NAME: LanguageModelProviderName =
- LanguageModelProviderName::new("Google AI");
@@ -1,28 +0,0 @@
-use crate::{LanguageModelCompletionError, LanguageModelProviderId, LanguageModelProviderName};
-use http_client::http;
-use std::time::Duration;
-
-pub const OPEN_AI_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("openai");
-pub const OPEN_AI_PROVIDER_NAME: LanguageModelProviderName =
- LanguageModelProviderName::new("OpenAI");
-
-impl From<open_ai::RequestError> for LanguageModelCompletionError {
- fn from(error: open_ai::RequestError) -> Self {
- match error {
- open_ai::RequestError::HttpResponseError {
- provider,
- status_code,
- body,
- headers,
- } => {
- let retry_after = headers
- .get(http::header::RETRY_AFTER)
- .and_then(|val| val.to_str().ok()?.parse::<u64>().ok())
- .map(Duration::from_secs);
-
- Self::from_http_status(provider.into(), status_code, body, retry_after)
- }
- open_ai::RequestError::Other(e) => Self::Other(e),
- }
- }
-}
@@ -1,69 +0,0 @@
-use crate::{LanguageModelCompletionError, LanguageModelProviderName};
-use http_client::StatusCode;
-use open_router::OpenRouterError;
-
-impl From<OpenRouterError> for LanguageModelCompletionError {
- fn from(error: OpenRouterError) -> Self {
- let provider = LanguageModelProviderName::new("OpenRouter");
- match error {
- OpenRouterError::SerializeRequest(error) => Self::SerializeRequest { provider, error },
- OpenRouterError::BuildRequestBody(error) => Self::BuildRequestBody { provider, error },
- OpenRouterError::HttpSend(error) => Self::HttpSend { provider, error },
- OpenRouterError::DeserializeResponse(error) => {
- Self::DeserializeResponse { provider, error }
- }
- OpenRouterError::ReadResponse(error) => Self::ApiReadResponseError { provider, error },
- OpenRouterError::RateLimit { retry_after } => Self::RateLimitExceeded {
- provider,
- retry_after: Some(retry_after),
- },
- OpenRouterError::ServerOverloaded { retry_after } => Self::ServerOverloaded {
- provider,
- retry_after,
- },
- OpenRouterError::ApiError(api_error) => api_error.into(),
- }
- }
-}
-
-impl From<open_router::ApiError> for LanguageModelCompletionError {
- fn from(error: open_router::ApiError) -> Self {
- use open_router::ApiErrorCode::*;
- let provider = LanguageModelProviderName::new("OpenRouter");
- match error.code {
- InvalidRequestError => Self::BadRequestFormat {
- provider,
- message: error.message,
- },
- AuthenticationError => Self::AuthenticationError {
- provider,
- message: error.message,
- },
- PaymentRequiredError => Self::AuthenticationError {
- provider,
- message: format!("Payment required: {}", error.message),
- },
- PermissionError => Self::PermissionError {
- provider,
- message: error.message,
- },
- RequestTimedOut => Self::HttpResponseError {
- provider,
- status_code: StatusCode::REQUEST_TIMEOUT,
- message: error.message,
- },
- RateLimitError => Self::RateLimitExceeded {
- provider,
- retry_after: None,
- },
- ApiError => Self::ApiInternalServerError {
- provider,
- message: error.message,
- },
- OverloadedError => Self::ServerOverloaded {
- provider,
- retry_after: None,
- },
- }
- }
-}
@@ -1,4 +0,0 @@
-use crate::{LanguageModelProviderId, LanguageModelProviderName};
-
-pub const X_AI_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("x_ai");
-pub const X_AI_PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("xAI");
@@ -1,5 +0,0 @@
-use crate::{LanguageModelProviderId, LanguageModelProviderName};
-
-pub const ZED_CLOUD_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("zed.dev");
-pub const ZED_CLOUD_PROVIDER_NAME: LanguageModelProviderName =
- LanguageModelProviderName::new("Zed");
@@ -1,6 +1,6 @@
use crate::{
LanguageModel, LanguageModelId, LanguageModelProvider, LanguageModelProviderId,
- LanguageModelProviderState,
+ LanguageModelProviderState, ZED_CLOUD_PROVIDER_ID,
};
use collections::{BTreeMap, HashSet};
use gpui::{App, Context, Entity, EventEmitter, Global, prelude::*};
@@ -101,7 +101,7 @@ impl ConfiguredModel {
}
pub fn is_provided_by_zed(&self) -> bool {
- self.provider.id() == crate::provider::ZED_CLOUD_PROVIDER_ID
+ self.provider.id() == ZED_CLOUD_PROVIDER_ID
}
}
@@ -4,78 +4,13 @@ use std::sync::Arc;
use anyhow::Result;
use base64::write::EncoderWriter;
use gpui::{
- App, AppContext as _, DevicePixels, Image, ImageFormat, ObjectFit, SharedString, Size, Task,
- point, px, size,
+ App, AppContext as _, DevicePixels, Image, ImageFormat, ObjectFit, Size, Task, point, px, size,
};
use image::GenericImageView as _;
use image::codecs::png::PngEncoder;
-use serde::{Deserialize, Serialize};
use util::ResultExt;
-use crate::role::Role;
-use crate::{LanguageModelToolUse, LanguageModelToolUseId};
-
-#[derive(Clone, PartialEq, Eq, Serialize, Deserialize, Hash)]
-pub struct LanguageModelImage {
- /// A base64-encoded PNG image.
- pub source: SharedString,
- #[serde(default, skip_serializing_if = "Option::is_none")]
- pub size: Option<Size<DevicePixels>>,
-}
-
-impl LanguageModelImage {
- pub fn len(&self) -> usize {
- self.source.len()
- }
-
- pub fn is_empty(&self) -> bool {
- self.source.is_empty()
- }
-
- // Parse Self from a JSON object with case-insensitive field names
- pub fn from_json(obj: &serde_json::Map<String, serde_json::Value>) -> Option<Self> {
- let mut source = None;
- let mut size_obj = None;
-
- // Find source and size fields (case-insensitive)
- for (k, v) in obj.iter() {
- match k.to_lowercase().as_str() {
- "source" => source = v.as_str(),
- "size" => size_obj = v.as_object(),
- _ => {}
- }
- }
-
- let source = source?;
- let size_obj = size_obj?;
-
- let mut width = None;
- let mut height = None;
-
- // Find width and height in size object (case-insensitive)
- for (k, v) in size_obj.iter() {
- match k.to_lowercase().as_str() {
- "width" => width = v.as_i64().map(|w| w as i32),
- "height" => height = v.as_i64().map(|h| h as i32),
- _ => {}
- }
- }
-
- Some(Self {
- size: Some(size(DevicePixels(width?), DevicePixels(height?))),
- source: SharedString::from(source.to_string()),
- })
- }
-}
-
-impl std::fmt::Debug for LanguageModelImage {
- fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
- f.debug_struct("LanguageModelImage")
- .field("source", &format!("<{} bytes>", self.source.len()))
- .field("size", &self.size)
- .finish()
- }
-}
+use language_model_core::{ImageSize, LanguageModelImage};
/// Anthropic wants uploaded images to be smaller than this in both dimensions.
const ANTHROPIC_SIZE_LIMIT: f32 = 1568.;
@@ -90,18 +25,16 @@ const DEFAULT_IMAGE_MAX_BYTES: usize = 5 * 1024 * 1024;
/// `DEFAULT_IMAGE_MAX_BYTES`.
const MAX_IMAGE_DOWNSCALE_PASSES: usize = 8;
-impl LanguageModelImage {
- // All language model images are encoded as PNGs.
- pub const FORMAT: ImageFormat = ImageFormat::Png;
+/// Extension trait for `LanguageModelImage` that provides GPUI-dependent functionality.
+pub trait LanguageModelImageExt {
+ const FORMAT: ImageFormat;
+ fn from_image(data: Arc<Image>, cx: &mut App) -> Task<Option<LanguageModelImage>>;
+}
- pub fn empty() -> Self {
- Self {
- source: "".into(),
- size: None,
- }
- }
+impl LanguageModelImageExt for LanguageModelImage {
+ const FORMAT: ImageFormat = ImageFormat::Png;
- pub fn from_image(data: Arc<Image>, cx: &mut App) -> Task<Option<Self>> {
+ fn from_image(data: Arc<Image>, cx: &mut App) -> Task<Option<LanguageModelImage>> {
cx.background_spawn(async move {
let image_bytes = Cursor::new(data.bytes());
let dynamic_image = match data.format() {
@@ -186,28 +119,14 @@ impl LanguageModelImage {
let source = unsafe { String::from_utf8_unchecked(base64_image) };
Some(LanguageModelImage {
- size: Some(image_size),
+ size: Some(ImageSize {
+ width: width as i32,
+ height: height as i32,
+ }),
source: source.into(),
})
})
}
-
- pub fn estimate_tokens(&self) -> usize {
- let Some(size) = self.size.as_ref() else {
- return 0;
- };
- let width = size.width.0.unsigned_abs() as usize;
- let height = size.height.0.unsigned_abs() as usize;
-
- // From: https://docs.anthropic.com/en/docs/build-with-claude/vision#calculate-image-costs
- // Note that are a lot of conditions on Anthropic's API, and OpenAI doesn't use this,
- // so this method is more of a rough guess.
- (width * height) / 750
- }
-
- pub fn to_base64_url(&self) -> String {
- format!("data:image/png;base64,{}", self.source)
- }
}
fn encode_png_bytes(image: &image::DynamicImage) -> Result<Vec<u8>> {
@@ -228,512 +147,85 @@ fn encode_bytes_as_base64(bytes: &[u8]) -> Result<Vec<u8>> {
Ok(base64_image)
}
-#[derive(Debug, Clone, Serialize, Deserialize, Eq, PartialEq, Hash)]
-pub struct LanguageModelToolResult {
- pub tool_use_id: LanguageModelToolUseId,
- pub tool_name: Arc<str>,
- pub is_error: bool,
- /// The tool output formatted for presenting to the model
- pub content: LanguageModelToolResultContent,
- /// The raw tool output, if available, often for debugging or extra state for replay
- pub output: Option<serde_json::Value>,
-}
-
-#[derive(Debug, Clone, Serialize, Eq, PartialEq, Hash)]
-pub enum LanguageModelToolResultContent {
- Text(Arc<str>),
- Image(LanguageModelImage),
-}
-
-impl<'de> Deserialize<'de> for LanguageModelToolResultContent {
- fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
- where
- D: serde::Deserializer<'de>,
- {
- use serde::de::Error;
-
- let value = serde_json::Value::deserialize(deserializer)?;
-
- // Models can provide these responses in several styles. Try each in order.
-
- // 1. Try as plain string
- if let Ok(text) = serde_json::from_value::<String>(value.clone()) {
- return Ok(Self::Text(Arc::from(text)));
- }
-
- // 2. Try as object
- if let Some(obj) = value.as_object() {
- // get a JSON field case-insensitively
- fn get_field<'a>(
- obj: &'a serde_json::Map<String, serde_json::Value>,
- field: &str,
- ) -> Option<&'a serde_json::Value> {
- obj.iter()
- .find(|(k, _)| k.to_lowercase() == field.to_lowercase())
- .map(|(_, v)| v)
- }
-
- // Accept wrapped text format: { "type": "text", "text": "..." }
- if let (Some(type_value), Some(text_value)) =
- (get_field(obj, "type"), get_field(obj, "text"))
- && let Some(type_str) = type_value.as_str()
- && type_str.to_lowercase() == "text"
- && let Some(text) = text_value.as_str()
- {
- return Ok(Self::Text(Arc::from(text)));
- }
-
- // Check for wrapped Text variant: { "text": "..." }
- if let Some((_key, value)) = obj.iter().find(|(k, _)| k.to_lowercase() == "text")
- && obj.len() == 1
- {
- // Only one field, and it's "text" (case-insensitive)
- if let Some(text) = value.as_str() {
- return Ok(Self::Text(Arc::from(text)));
- }
- }
-
- // Check for wrapped Image variant: { "image": { "source": "...", "size": ... } }
- if let Some((_key, value)) = obj.iter().find(|(k, _)| k.to_lowercase() == "image")
- && obj.len() == 1
- {
- // Only one field, and it's "image" (case-insensitive)
- // Try to parse the nested image object
- if let Some(image_obj) = value.as_object()
- && let Some(image) = LanguageModelImage::from_json(image_obj)
- {
- return Ok(Self::Image(image));
- }
- }
-
- // Try as direct Image (object with "source" and "size" fields)
- if let Some(image) = LanguageModelImage::from_json(obj) {
- return Ok(Self::Image(image));
- }
- }
-
- // If none of the variants match, return an error with the problematic JSON
- Err(D::Error::custom(format!(
- "data did not match any variant of LanguageModelToolResultContent. Expected either a string, \
- an object with 'type': 'text', a wrapped variant like {{\"Text\": \"...\"}}, or an image object. Got: {}",
- serde_json::to_string_pretty(&value).unwrap_or_else(|_| value.to_string())
- )))
- }
-}
-
-impl LanguageModelToolResultContent {
- pub fn to_str(&self) -> Option<&str> {
- match self {
- Self::Text(text) => Some(text),
- Self::Image(_) => None,
- }
- }
-
- pub fn is_empty(&self) -> bool {
- match self {
- Self::Text(text) => text.chars().all(|c| c.is_whitespace()),
- Self::Image(_) => false,
- }
- }
-}
-
-impl From<&str> for LanguageModelToolResultContent {
- fn from(value: &str) -> Self {
- Self::Text(Arc::from(value))
- }
-}
-
-impl From<String> for LanguageModelToolResultContent {
- fn from(value: String) -> Self {
- Self::Text(Arc::from(value))
- }
-}
-
-impl From<LanguageModelImage> for LanguageModelToolResultContent {
- fn from(image: LanguageModelImage) -> Self {
- Self::Image(image)
- }
-}
-
-#[derive(Debug, Clone, Serialize, Deserialize, Eq, PartialEq, Hash)]
-pub enum MessageContent {
- Text(String),
- Thinking {
- text: String,
- signature: Option<String>,
- },
- RedactedThinking(String),
- Image(LanguageModelImage),
- ToolUse(LanguageModelToolUse),
- ToolResult(LanguageModelToolResult),
-}
-
-impl MessageContent {
- pub fn to_str(&self) -> Option<&str> {
- match self {
- MessageContent::Text(text) => Some(text.as_str()),
- MessageContent::Thinking { text, .. } => Some(text.as_str()),
- MessageContent::RedactedThinking(_) => None,
- MessageContent::ToolResult(tool_result) => tool_result.content.to_str(),
- MessageContent::ToolUse(_) | MessageContent::Image(_) => None,
- }
- }
-
- pub fn is_empty(&self) -> bool {
- match self {
- MessageContent::Text(text) => text.chars().all(|c| c.is_whitespace()),
- MessageContent::Thinking { text, .. } => text.chars().all(|c| c.is_whitespace()),
- MessageContent::ToolResult(tool_result) => tool_result.content.is_empty(),
- MessageContent::RedactedThinking(_)
- | MessageContent::ToolUse(_)
- | MessageContent::Image(_) => false,
- }
- }
-}
-
-impl From<String> for MessageContent {
- fn from(value: String) -> Self {
- MessageContent::Text(value)
- }
-}
-
-impl From<&str> for MessageContent {
- fn from(value: &str) -> Self {
- MessageContent::Text(value.to_string())
- }
-}
-
-#[derive(Clone, Serialize, Deserialize, Debug, PartialEq, Hash)]
-pub struct LanguageModelRequestMessage {
- pub role: Role,
- pub content: Vec<MessageContent>,
- pub cache: bool,
- #[serde(default, skip_serializing_if = "Option::is_none")]
- pub reasoning_details: Option<serde_json::Value>,
-}
-
-impl LanguageModelRequestMessage {
- pub fn string_contents(&self) -> String {
- let mut buffer = String::new();
- for string in self.content.iter().filter_map(|content| content.to_str()) {
- buffer.push_str(string);
- }
-
- buffer
- }
-
- pub fn contents_empty(&self) -> bool {
- self.content.iter().all(|content| content.is_empty())
- }
-}
-
-#[derive(Debug, PartialEq, Hash, Clone, Serialize, Deserialize)]
-pub struct LanguageModelRequestTool {
- pub name: String,
- pub description: String,
- pub input_schema: serde_json::Value,
- pub use_input_streaming: bool,
-}
-
-#[derive(Debug, PartialEq, Hash, Clone, Serialize, Deserialize)]
-pub enum LanguageModelToolChoice {
- Auto,
- Any,
- None,
-}
-
-#[derive(Debug, PartialEq, Eq, PartialOrd, Ord, Hash, Clone, Copy, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum CompletionIntent {
- UserPrompt,
- Subagent,
- ToolResults,
- ThreadSummarization,
- ThreadContextSummarization,
- CreateFile,
- EditFile,
- InlineAssist,
- TerminalInlineAssist,
- GenerateGitCommitMessage,
-}
-
-#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq)]
-pub struct LanguageModelRequest {
- pub thread_id: Option<String>,
- pub prompt_id: Option<String>,
- pub intent: Option<CompletionIntent>,
- pub messages: Vec<LanguageModelRequestMessage>,
- pub tools: Vec<LanguageModelRequestTool>,
- pub tool_choice: Option<LanguageModelToolChoice>,
- pub stop: Vec<String>,
- pub temperature: Option<f32>,
- pub thinking_allowed: bool,
- pub thinking_effort: Option<String>,
- pub speed: Option<Speed>,
-}
-
-#[derive(Clone, Copy, Default, Debug, Serialize, Deserialize, PartialEq, Eq)]
-#[serde(rename_all = "snake_case")]
-pub enum Speed {
- #[default]
- Standard,
- Fast,
-}
-
-impl Speed {
- pub fn toggle(self) -> Self {
- match self {
- Speed::Standard => Speed::Fast,
- Speed::Fast => Speed::Standard,
- }
+/// Convert a core `ImageSize` to a gpui `Size<DevicePixels>`.
+pub fn image_size_to_gpui(size: ImageSize) -> Size<DevicePixels> {
+ Size {
+ width: DevicePixels(size.width),
+ height: DevicePixels(size.height),
}
}
-impl From<Speed> for anthropic::Speed {
- fn from(speed: Speed) -> Self {
- match speed {
- Speed::Standard => anthropic::Speed::Standard,
- Speed::Fast => anthropic::Speed::Fast,
- }
+/// Convert a gpui `Size<DevicePixels>` to a core `ImageSize`.
+pub fn gpui_size_to_image_size(size: Size<DevicePixels>) -> ImageSize {
+ ImageSize {
+ width: size.width.0,
+ height: size.height.0,
}
}
-#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
-pub struct LanguageModelResponseMessage {
- pub role: Option<Role>,
- pub content: Option<String>,
-}
-
#[cfg(test)]
mod tests {
use super::*;
use base64::Engine as _;
use gpui::TestAppContext;
- use image::ImageDecoder as _;
- fn base64_to_png_bytes(base64_png: &str) -> Vec<u8> {
+ fn base64_to_png_bytes(base64: &str) -> Vec<u8> {
base64::engine::general_purpose::STANDARD
- .decode(base64_png.as_bytes())
- .expect("base64 should decode")
+ .decode(base64)
+ .expect("valid base64")
}
fn png_dimensions(png_bytes: &[u8]) -> (u32, u32) {
- let decoder =
- image::codecs::png::PngDecoder::new(Cursor::new(png_bytes)).expect("png should decode");
- decoder.dimensions()
+ let img = image::load_from_memory(png_bytes).expect("valid png");
+ (img.width(), img.height())
}
fn make_noisy_png_bytes(width: u32, height: u32) -> Vec<u8> {
- // Create an RGBA image with per-pixel variance to avoid PNG compressing too well.
- let mut img = image::RgbaImage::new(width, height);
- for y in 0..height {
- for x in 0..width {
- let r = ((x ^ y) & 0xFF) as u8;
- let g = ((x.wrapping_mul(31) ^ y.wrapping_mul(17)) & 0xFF) as u8;
- let b = ((x.wrapping_mul(131) ^ y.wrapping_mul(7)) & 0xFF) as u8;
- img.put_pixel(x, y, image::Rgba([r, g, b, 0xFF]));
- }
- }
+ use image::{ImageBuffer, Rgba};
+ use std::hash::{Hash, Hasher};
+
+ let img = ImageBuffer::from_fn(width, height, |x, y| {
+ let mut hasher = std::hash::DefaultHasher::new();
+ (x, y, width, height).hash(&mut hasher);
+ let h = hasher.finish();
+ Rgba([h as u8, (h >> 8) as u8, (h >> 16) as u8, 255])
+ });
- let mut out = Vec::new();
- image::DynamicImage::ImageRgba8(img)
- .write_with_encoder(PngEncoder::new(&mut out))
- .expect("png encoding should succeed");
- out
+ let mut buf = Cursor::new(Vec::new());
+ img.write_with_encoder(PngEncoder::new(&mut buf))
+ .expect("encode");
+ buf.into_inner()
}
#[gpui::test]
async fn test_from_image_downscales_to_default_5mb_limit(cx: &mut TestAppContext) {
- // Pick a size that reliably produces a PNG > 5MB when filled with noise.
- // If this fails (image is too small), bump dimensions.
- let original_png = make_noisy_png_bytes(4096, 4096);
+ let raw_png = make_noisy_png_bytes(4096, 4096);
assert!(
- original_png.len() > DEFAULT_IMAGE_MAX_BYTES,
- "precondition failed: noisy PNG must exceed DEFAULT_IMAGE_MAX_BYTES"
+ raw_png.len() > DEFAULT_IMAGE_MAX_BYTES,
+ "Test image should exceed the 5 MB limit (actual: {} bytes)",
+ raw_png.len()
);
- let image = gpui::Image::from_bytes(ImageFormat::Png, original_png);
+ let image = Arc::new(gpui::Image::from_bytes(ImageFormat::Png, raw_png));
let lm_image = cx
- .update(|cx| LanguageModelImage::from_image(Arc::new(image), cx))
+ .update(|cx| LanguageModelImage::from_image(Arc::clone(&image), cx))
.await
- .expect("image conversion should succeed");
+ .expect("from_image should succeed");
- let encoded_png = base64_to_png_bytes(lm_image.source.as_ref());
+ let decoded_png = base64_to_png_bytes(lm_image.source.as_ref());
assert!(
- encoded_png.len() <= DEFAULT_IMAGE_MAX_BYTES,
- "expected encoded PNG <= DEFAULT_IMAGE_MAX_BYTES, got {} bytes",
- encoded_png.len()
+ decoded_png.len() <= DEFAULT_IMAGE_MAX_BYTES,
+ "Encoded PNG should be β€ {} bytes after downscale, but was {} bytes",
+ DEFAULT_IMAGE_MAX_BYTES,
+ decoded_png.len()
);
- // Ensure we actually downscaled in pixels (not just re-encoded).
- let (w, h) = png_dimensions(&encoded_png);
+ let (w, h) = png_dimensions(&decoded_png);
assert!(
- w < 4096 || h < 4096,
- "expected image to be downscaled in at least one dimension; got {w}x{h}"
- );
- }
-
- #[test]
- fn test_language_model_tool_result_content_deserialization() {
- let json = r#""This is plain text""#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(
- result,
- LanguageModelToolResultContent::Text("This is plain text".into())
- );
-
- let json = r#"{"type": "text", "text": "This is wrapped text"}"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(
- result,
- LanguageModelToolResultContent::Text("This is wrapped text".into())
- );
-
- let json = r#"{"Type": "TEXT", "TEXT": "Case insensitive"}"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(
- result,
- LanguageModelToolResultContent::Text("Case insensitive".into())
- );
-
- let json = r#"{"Text": "Wrapped variant"}"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(
- result,
- LanguageModelToolResultContent::Text("Wrapped variant".into())
- );
-
- let json = r#"{"text": "Lowercase wrapped"}"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(
- result,
- LanguageModelToolResultContent::Text("Lowercase wrapped".into())
+ w < 4096 && h < 4096,
+ "Dimensions should have shrunk: got {}Γ{}",
+ w,
+ h
);
-
- // Test image deserialization
- let json = r#"{
- "source": "base64encodedimagedata",
- "size": {
- "width": 100,
- "height": 200
- }
- }"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- match result {
- LanguageModelToolResultContent::Image(image) => {
- assert_eq!(image.source.as_ref(), "base64encodedimagedata");
- let size = image.size.expect("size");
- assert_eq!(size.width.0, 100);
- assert_eq!(size.height.0, 200);
- }
- _ => panic!("Expected Image variant"),
- }
-
- // Test wrapped Image variant
- let json = r#"{
- "Image": {
- "source": "wrappedimagedata",
- "size": {
- "width": 50,
- "height": 75
- }
- }
- }"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- match result {
- LanguageModelToolResultContent::Image(image) => {
- assert_eq!(image.source.as_ref(), "wrappedimagedata");
- let size = image.size.expect("size");
- assert_eq!(size.width.0, 50);
- assert_eq!(size.height.0, 75);
- }
- _ => panic!("Expected Image variant"),
- }
-
- // Test wrapped Image variant with case insensitive
- let json = r#"{
- "image": {
- "Source": "caseinsensitive",
- "SIZE": {
- "width": 30,
- "height": 40
- }
- }
- }"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- match result {
- LanguageModelToolResultContent::Image(image) => {
- assert_eq!(image.source.as_ref(), "caseinsensitive");
- let size = image.size.expect("size");
- assert_eq!(size.width.0, 30);
- assert_eq!(size.height.0, 40);
- }
- _ => panic!("Expected Image variant"),
- }
-
- // Test that wrapped text with wrong type fails
- let json = r#"{"type": "blahblah", "text": "This should fail"}"#;
- let result: Result<LanguageModelToolResultContent, _> = serde_json::from_str(json);
- assert!(result.is_err());
-
- // Test that malformed JSON fails
- let json = r#"{"invalid": "structure"}"#;
- let result: Result<LanguageModelToolResultContent, _> = serde_json::from_str(json);
- assert!(result.is_err());
-
- // Test edge cases
- let json = r#""""#; // Empty string
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(result, LanguageModelToolResultContent::Text("".into()));
-
- // Test with extra fields in wrapped text (should be ignored)
- let json = r#"{"type": "text", "text": "Hello", "extra": "field"}"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(result, LanguageModelToolResultContent::Text("Hello".into()));
-
- // Test direct image with case-insensitive fields
- let json = r#"{
- "SOURCE": "directimage",
- "Size": {
- "width": 200,
- "height": 300
- }
- }"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- match result {
- LanguageModelToolResultContent::Image(image) => {
- assert_eq!(image.source.as_ref(), "directimage");
- let size = image.size.expect("size");
- assert_eq!(size.width.0, 200);
- assert_eq!(size.height.0, 300);
- }
- _ => panic!("Expected Image variant"),
- }
-
- // Test that multiple fields prevent wrapped variant interpretation
- let json = r#"{"Text": "not wrapped", "extra": "field"}"#;
- let result: Result<LanguageModelToolResultContent, _> = serde_json::from_str(json);
- assert!(result.is_err());
-
- // Test wrapped text with uppercase TEXT variant
- let json = r#"{"TEXT": "Uppercase variant"}"#;
- let result: LanguageModelToolResultContent = serde_json::from_str(json).unwrap();
- assert_eq!(
- result,
- LanguageModelToolResultContent::Text("Uppercase variant".into())
- );
-
- // Test that numbers and other JSON values fail gracefully
- let json = r#"123"#;
- let result: Result<LanguageModelToolResultContent, _> = serde_json::from_str(json);
- assert!(result.is_err());
-
- let json = r#"null"#;
- let result: Result<LanguageModelToolResultContent, _> = serde_json::from_str(json);
- assert!(result.is_err());
-
- let json = r#"[1, 2, 3]"#;
- let result: Result<LanguageModelToolResultContent, _> = serde_json::from_str(json);
- assert!(result.is_err());
}
}
@@ -0,0 +1,27 @@
+[package]
+name = "language_model_core"
+version = "0.1.0"
+edition.workspace = true
+publish.workspace = true
+license = "GPL-3.0-or-later"
+
+[lints]
+workspace = true
+
+[lib]
+path = "src/language_model_core.rs"
+doctest = false
+
+[dependencies]
+anyhow.workspace = true
+cloud_llm_client.workspace = true
+futures.workspace = true
+gpui_shared_string.workspace = true
+http_client.workspace = true
+partial-json-fixer.workspace = true
+schemars.workspace = true
+serde.workspace = true
+serde_json.workspace = true
+smol.workspace = true
+strum.workspace = true
+thiserror.workspace = true
@@ -0,0 +1 @@
+../../LICENSE-GPL
@@ -0,0 +1,658 @@
+mod provider;
+mod rate_limiter;
+mod request;
+mod role;
+pub mod tool_schema;
+pub mod util;
+
+use anyhow::{Result, anyhow};
+use cloud_llm_client::CompletionRequestStatus;
+use http_client::{StatusCode, http};
+use schemars::JsonSchema;
+use serde::{Deserialize, Serialize};
+use std::ops::{Add, Sub};
+use std::str::FromStr;
+use std::sync::Arc;
+use std::time::Duration;
+use std::{fmt, io};
+use thiserror::Error;
+fn is_default<T: Default + PartialEq>(value: &T) -> bool {
+ *value == T::default()
+}
+
+pub use crate::provider::*;
+pub use crate::rate_limiter::*;
+pub use crate::request::*;
+pub use crate::role::*;
+pub use crate::tool_schema::LanguageModelToolSchemaFormat;
+pub use crate::util::{fix_streamed_json, parse_prompt_too_long, parse_tool_arguments};
+pub use gpui_shared_string::SharedString;
+
+#[derive(Clone, Debug)]
+pub struct LanguageModelCacheConfiguration {
+ pub max_cache_anchors: usize,
+ pub should_speculate: bool,
+ pub min_total_token: u64,
+}
+
+/// A completion event from a language model.
+#[derive(Debug, PartialEq, Clone, Serialize, Deserialize)]
+pub enum LanguageModelCompletionEvent {
+ Queued {
+ position: usize,
+ },
+ Started,
+ Stop(StopReason),
+ Text(String),
+ Thinking {
+ text: String,
+ signature: Option<String>,
+ },
+ RedactedThinking {
+ data: String,
+ },
+ ToolUse(LanguageModelToolUse),
+ ToolUseJsonParseError {
+ id: LanguageModelToolUseId,
+ tool_name: Arc<str>,
+ raw_input: Arc<str>,
+ json_parse_error: String,
+ },
+ StartMessage {
+ message_id: String,
+ },
+ ReasoningDetails(serde_json::Value),
+ UsageUpdate(TokenUsage),
+}
+
+impl LanguageModelCompletionEvent {
+ pub fn from_completion_request_status(
+ status: CompletionRequestStatus,
+ upstream_provider: LanguageModelProviderName,
+ ) -> Result<Option<Self>, LanguageModelCompletionError> {
+ match status {
+ CompletionRequestStatus::Queued { position } => {
+ Ok(Some(LanguageModelCompletionEvent::Queued { position }))
+ }
+ CompletionRequestStatus::Started => Ok(Some(LanguageModelCompletionEvent::Started)),
+ CompletionRequestStatus::Unknown | CompletionRequestStatus::StreamEnded => Ok(None),
+ CompletionRequestStatus::Failed {
+ code,
+ message,
+ request_id: _,
+ retry_after,
+ } => Err(LanguageModelCompletionError::from_cloud_failure(
+ upstream_provider,
+ code,
+ message,
+ retry_after.map(Duration::from_secs_f64),
+ )),
+ }
+ }
+}
+
+#[derive(Error, Debug)]
+pub enum LanguageModelCompletionError {
+ #[error("prompt too large for context window")]
+ PromptTooLarge { tokens: Option<u64> },
+ #[error("missing {provider} API key")]
+ NoApiKey { provider: LanguageModelProviderName },
+ #[error("{provider}'s API rate limit exceeded")]
+ RateLimitExceeded {
+ provider: LanguageModelProviderName,
+ retry_after: Option<Duration>,
+ },
+ #[error("{provider}'s API servers are overloaded right now")]
+ ServerOverloaded {
+ provider: LanguageModelProviderName,
+ retry_after: Option<Duration>,
+ },
+ #[error("{provider}'s API server reported an internal server error: {message}")]
+ ApiInternalServerError {
+ provider: LanguageModelProviderName,
+ message: String,
+ },
+ #[error("{message}")]
+ UpstreamProviderError {
+ message: String,
+ status: StatusCode,
+ retry_after: Option<Duration>,
+ },
+ #[error("HTTP response error from {provider}'s API: status {status_code} - {message:?}")]
+ HttpResponseError {
+ provider: LanguageModelProviderName,
+ status_code: StatusCode,
+ message: String,
+ },
+ #[error("invalid request format to {provider}'s API: {message}")]
+ BadRequestFormat {
+ provider: LanguageModelProviderName,
+ message: String,
+ },
+ #[error("authentication error with {provider}'s API: {message}")]
+ AuthenticationError {
+ provider: LanguageModelProviderName,
+ message: String,
+ },
+ #[error("Permission error with {provider}'s API: {message}")]
+ PermissionError {
+ provider: LanguageModelProviderName,
+ message: String,
+ },
+ #[error("language model provider API endpoint not found")]
+ ApiEndpointNotFound { provider: LanguageModelProviderName },
+ #[error("I/O error reading response from {provider}'s API")]
+ ApiReadResponseError {
+ provider: LanguageModelProviderName,
+ #[source]
+ error: io::Error,
+ },
+ #[error("error serializing request to {provider} API")]
+ SerializeRequest {
+ provider: LanguageModelProviderName,
+ #[source]
+ error: serde_json::Error,
+ },
+ #[error("error building request body to {provider} API")]
+ BuildRequestBody {
+ provider: LanguageModelProviderName,
+ #[source]
+ error: http::Error,
+ },
+ #[error("error sending HTTP request to {provider} API")]
+ HttpSend {
+ provider: LanguageModelProviderName,
+ #[source]
+ error: anyhow::Error,
+ },
+ #[error("error deserializing {provider} API response")]
+ DeserializeResponse {
+ provider: LanguageModelProviderName,
+ #[source]
+ error: serde_json::Error,
+ },
+ #[error("stream from {provider} ended unexpectedly")]
+ StreamEndedUnexpectedly { provider: LanguageModelProviderName },
+ #[error(transparent)]
+ Other(#[from] anyhow::Error),
+}
+
+impl LanguageModelCompletionError {
+ fn parse_upstream_error_json(message: &str) -> Option<(StatusCode, String)> {
+ let error_json = serde_json::from_str::<serde_json::Value>(message).ok()?;
+ let upstream_status = error_json
+ .get("upstream_status")
+ .and_then(|v| v.as_u64())
+ .and_then(|status| u16::try_from(status).ok())
+ .and_then(|status| StatusCode::from_u16(status).ok())?;
+ let inner_message = error_json
+ .get("message")
+ .and_then(|v| v.as_str())
+ .unwrap_or(message)
+ .to_string();
+ Some((upstream_status, inner_message))
+ }
+
+ pub fn from_cloud_failure(
+ upstream_provider: LanguageModelProviderName,
+ code: String,
+ message: String,
+ retry_after: Option<Duration>,
+ ) -> Self {
+ if let Some(tokens) = parse_prompt_too_long(&message) {
+ Self::PromptTooLarge {
+ tokens: Some(tokens),
+ }
+ } else if code == "upstream_http_error" {
+ if let Some((upstream_status, inner_message)) =
+ Self::parse_upstream_error_json(&message)
+ {
+ return Self::from_http_status(
+ upstream_provider,
+ upstream_status,
+ inner_message,
+ retry_after,
+ );
+ }
+ anyhow!("completion request failed, code: {code}, message: {message}").into()
+ } else if let Some(status_code) = code
+ .strip_prefix("upstream_http_")
+ .and_then(|code| StatusCode::from_str(code).ok())
+ {
+ Self::from_http_status(upstream_provider, status_code, message, retry_after)
+ } else if let Some(status_code) = code
+ .strip_prefix("http_")
+ .and_then(|code| StatusCode::from_str(code).ok())
+ {
+ Self::from_http_status(ZED_CLOUD_PROVIDER_NAME, status_code, message, retry_after)
+ } else {
+ anyhow!("completion request failed, code: {code}, message: {message}").into()
+ }
+ }
+
+ pub fn from_http_status(
+ provider: LanguageModelProviderName,
+ status_code: StatusCode,
+ message: String,
+ retry_after: Option<Duration>,
+ ) -> Self {
+ match status_code {
+ StatusCode::BAD_REQUEST => Self::BadRequestFormat { provider, message },
+ StatusCode::UNAUTHORIZED => Self::AuthenticationError { provider, message },
+ StatusCode::FORBIDDEN => Self::PermissionError { provider, message },
+ StatusCode::NOT_FOUND => Self::ApiEndpointNotFound { provider },
+ StatusCode::PAYLOAD_TOO_LARGE => Self::PromptTooLarge {
+ tokens: parse_prompt_too_long(&message),
+ },
+ StatusCode::TOO_MANY_REQUESTS => Self::RateLimitExceeded {
+ provider,
+ retry_after,
+ },
+ StatusCode::INTERNAL_SERVER_ERROR => Self::ApiInternalServerError { provider, message },
+ StatusCode::SERVICE_UNAVAILABLE => Self::ServerOverloaded {
+ provider,
+ retry_after,
+ },
+ _ if status_code.as_u16() == 529 => Self::ServerOverloaded {
+ provider,
+ retry_after,
+ },
+ _ => Self::HttpResponseError {
+ provider,
+ status_code,
+ message,
+ },
+ }
+ }
+}
+
+#[derive(Debug, PartialEq, Clone, Copy, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum StopReason {
+ EndTurn,
+ MaxTokens,
+ ToolUse,
+ Refusal,
+}
+
+#[derive(Debug, PartialEq, Clone, Copy, Serialize, Deserialize, Default)]
+pub struct TokenUsage {
+ #[serde(default, skip_serializing_if = "is_default")]
+ pub input_tokens: u64,
+ #[serde(default, skip_serializing_if = "is_default")]
+ pub output_tokens: u64,
+ #[serde(default, skip_serializing_if = "is_default")]
+ pub cache_creation_input_tokens: u64,
+ #[serde(default, skip_serializing_if = "is_default")]
+ pub cache_read_input_tokens: u64,
+}
+
+impl TokenUsage {
+ pub fn total_tokens(&self) -> u64 {
+ self.input_tokens
+ + self.output_tokens
+ + self.cache_read_input_tokens
+ + self.cache_creation_input_tokens
+ }
+}
+
+impl Add<TokenUsage> for TokenUsage {
+ type Output = Self;
+
+ fn add(self, other: Self) -> Self {
+ Self {
+ input_tokens: self.input_tokens + other.input_tokens,
+ output_tokens: self.output_tokens + other.output_tokens,
+ cache_creation_input_tokens: self.cache_creation_input_tokens
+ + other.cache_creation_input_tokens,
+ cache_read_input_tokens: self.cache_read_input_tokens + other.cache_read_input_tokens,
+ }
+ }
+}
+
+impl Sub<TokenUsage> for TokenUsage {
+ type Output = Self;
+
+ fn sub(self, other: Self) -> Self {
+ Self {
+ input_tokens: self.input_tokens - other.input_tokens,
+ output_tokens: self.output_tokens - other.output_tokens,
+ cache_creation_input_tokens: self.cache_creation_input_tokens
+ - other.cache_creation_input_tokens,
+ cache_read_input_tokens: self.cache_read_input_tokens - other.cache_read_input_tokens,
+ }
+ }
+}
+
+#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
+pub struct LanguageModelToolUseId(Arc<str>);
+
+impl fmt::Display for LanguageModelToolUseId {
+ fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+ write!(f, "{}", self.0)
+ }
+}
+
+impl<T> From<T> for LanguageModelToolUseId
+where
+ T: Into<Arc<str>>,
+{
+ fn from(value: T) -> Self {
+ Self(value.into())
+ }
+}
+
+#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
+pub struct LanguageModelToolUse {
+ pub id: LanguageModelToolUseId,
+ pub name: Arc<str>,
+ pub raw_input: String,
+ pub input: serde_json::Value,
+ pub is_input_complete: bool,
+ /// Thought signature the model sent us. Some models require that this
+ /// signature be preserved and sent back in conversation history for validation.
+ pub thought_signature: Option<String>,
+}
+
+#[derive(Debug, Clone)]
+pub struct LanguageModelEffortLevel {
+ pub name: SharedString,
+ pub value: SharedString,
+ pub is_default: bool,
+}
+
+/// An error that occurred when trying to authenticate the language model provider.
+#[derive(Debug, Error)]
+pub enum AuthenticateError {
+ #[error("connection refused")]
+ ConnectionRefused,
+ #[error("credentials not found")]
+ CredentialsNotFound,
+ #[error(transparent)]
+ Other(#[from] anyhow::Error),
+}
+
+#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd, Serialize, Deserialize)]
+pub struct LanguageModelId(pub SharedString);
+
+#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
+pub struct LanguageModelName(pub SharedString);
+
+#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
+pub struct LanguageModelProviderId(pub SharedString);
+
+#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
+pub struct LanguageModelProviderName(pub SharedString);
+
+impl LanguageModelProviderId {
+ pub const fn new(id: &'static str) -> Self {
+ Self(SharedString::new_static(id))
+ }
+}
+
+impl LanguageModelProviderName {
+ pub const fn new(id: &'static str) -> Self {
+ Self(SharedString::new_static(id))
+ }
+}
+
+impl fmt::Display for LanguageModelProviderId {
+ fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+ write!(f, "{}", self.0)
+ }
+}
+
+impl fmt::Display for LanguageModelProviderName {
+ fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+ write!(f, "{}", self.0)
+ }
+}
+
+impl From<String> for LanguageModelId {
+ fn from(value: String) -> Self {
+ Self(SharedString::from(value))
+ }
+}
+
+impl From<String> for LanguageModelName {
+ fn from(value: String) -> Self {
+ Self(SharedString::from(value))
+ }
+}
+
+impl From<String> for LanguageModelProviderId {
+ fn from(value: String) -> Self {
+ Self(SharedString::from(value))
+ }
+}
+
+impl From<String> for LanguageModelProviderName {
+ fn from(value: String) -> Self {
+ Self(SharedString::from(value))
+ }
+}
+
+impl From<Arc<str>> for LanguageModelProviderId {
+ fn from(value: Arc<str>) -> Self {
+ Self(SharedString::from(value))
+ }
+}
+
+impl From<Arc<str>> for LanguageModelProviderName {
+ fn from(value: Arc<str>) -> Self {
+ Self(SharedString::from(value))
+ }
+}
+
+/// Settings-layerβfree model mode enum.
+///
+/// Mirrors the shape of `settings_content::ModelMode` but lives here so that
+/// crates below the settings layer can reference it.
+#[derive(Copy, Clone, Debug, Default, PartialEq, Eq, Serialize, Deserialize, JsonSchema)]
+#[serde(tag = "type", rename_all = "lowercase")]
+pub enum ModelMode {
+ #[default]
+ Default,
+ Thinking {
+ budget_tokens: Option<u32>,
+ },
+}
+
+/// Settings-layerβfree reasoning-effort enum.
+///
+/// Mirrors the shape of `settings_content::OpenAiReasoningEffort` but lives
+/// here so that crates below the settings layer can reference it.
+#[derive(
+ Debug, Copy, Clone, PartialEq, Eq, Serialize, Deserialize, JsonSchema, strum::EnumString,
+)]
+#[serde(rename_all = "lowercase")]
+#[strum(serialize_all = "lowercase")]
+pub enum ReasoningEffort {
+ Minimal,
+ Low,
+ Medium,
+ High,
+ XHigh,
+}
+
+#[cfg(test)]
+mod tests {
+ use super::*;
+
+ #[test]
+ fn test_from_cloud_failure_with_upstream_http_error() {
+ let error = LanguageModelCompletionError::from_cloud_failure(
+ String::from("anthropic").into(),
+ "upstream_http_error".to_string(),
+ r#"{"code":"upstream_http_error","message":"Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout","upstream_status":503}"#.to_string(),
+ None,
+ );
+
+ match error {
+ LanguageModelCompletionError::ServerOverloaded { provider, .. } => {
+ assert_eq!(provider.0, "anthropic");
+ }
+ _ => panic!(
+ "Expected ServerOverloaded error for 503 status, got: {:?}",
+ error
+ ),
+ }
+
+ let error = LanguageModelCompletionError::from_cloud_failure(
+ String::from("anthropic").into(),
+ "upstream_http_error".to_string(),
+ r#"{"code":"upstream_http_error","message":"Internal server error","upstream_status":500}"#.to_string(),
+ None,
+ );
+
+ match error {
+ LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
+ assert_eq!(provider.0, "anthropic");
+ assert_eq!(message, "Internal server error");
+ }
+ _ => panic!(
+ "Expected ApiInternalServerError for 500 status, got: {:?}",
+ error
+ ),
+ }
+ }
+
+ #[test]
+ fn test_from_cloud_failure_with_standard_format() {
+ let error = LanguageModelCompletionError::from_cloud_failure(
+ String::from("anthropic").into(),
+ "upstream_http_503".to_string(),
+ "Service unavailable".to_string(),
+ None,
+ );
+
+ match error {
+ LanguageModelCompletionError::ServerOverloaded { provider, .. } => {
+ assert_eq!(provider.0, "anthropic");
+ }
+ _ => panic!("Expected ServerOverloaded error for upstream_http_503"),
+ }
+ }
+
+ #[test]
+ fn test_upstream_http_error_connection_timeout() {
+ let error = LanguageModelCompletionError::from_cloud_failure(
+ String::from("anthropic").into(),
+ "upstream_http_error".to_string(),
+ r#"{"code":"upstream_http_error","message":"Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout","upstream_status":503}"#.to_string(),
+ None,
+ );
+
+ match error {
+ LanguageModelCompletionError::ServerOverloaded { provider, .. } => {
+ assert_eq!(provider.0, "anthropic");
+ }
+ _ => panic!(
+ "Expected ServerOverloaded error for connection timeout with 503 status, got: {:?}",
+ error
+ ),
+ }
+
+ let error = LanguageModelCompletionError::from_cloud_failure(
+ String::from("anthropic").into(),
+ "upstream_http_error".to_string(),
+ r#"{"code":"upstream_http_error","message":"Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout","upstream_status":500}"#.to_string(),
+ None,
+ );
+
+ match error {
+ LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
+ assert_eq!(provider.0, "anthropic");
+ assert_eq!(
+ message,
+ "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers. reset reason: connection timeout"
+ );
+ }
+ _ => panic!(
+ "Expected ApiInternalServerError for connection timeout with 500 status, got: {:?}",
+ error
+ ),
+ }
+ }
+
+ #[test]
+ fn test_language_model_tool_use_serializes_with_signature() {
+ use serde_json::json;
+
+ let tool_use = LanguageModelToolUse {
+ id: LanguageModelToolUseId::from("test_id"),
+ name: "test_tool".into(),
+ raw_input: json!({"arg": "value"}).to_string(),
+ input: json!({"arg": "value"}),
+ is_input_complete: true,
+ thought_signature: Some("test_signature".to_string()),
+ };
+
+ let serialized = serde_json::to_value(&tool_use).unwrap();
+
+ assert_eq!(serialized["id"], "test_id");
+ assert_eq!(serialized["name"], "test_tool");
+ assert_eq!(serialized["thought_signature"], "test_signature");
+ }
+
+ #[test]
+ fn test_language_model_tool_use_deserializes_with_missing_signature() {
+ use serde_json::json;
+
+ let json = json!({
+ "id": "test_id",
+ "name": "test_tool",
+ "raw_input": "{\"arg\":\"value\"}",
+ "input": {"arg": "value"},
+ "is_input_complete": true
+ });
+
+ let tool_use: LanguageModelToolUse = serde_json::from_value(json).unwrap();
+
+ assert_eq!(tool_use.id, LanguageModelToolUseId::from("test_id"));
+ assert_eq!(tool_use.name.as_ref(), "test_tool");
+ assert_eq!(tool_use.thought_signature, None);
+ }
+
+ #[test]
+ fn test_language_model_tool_use_round_trip_with_signature() {
+ use serde_json::json;
+
+ let original = LanguageModelToolUse {
+ id: LanguageModelToolUseId::from("round_trip_id"),
+ name: "round_trip_tool".into(),
+ raw_input: json!({"key": "value"}).to_string(),
+ input: json!({"key": "value"}),
+ is_input_complete: true,
+ thought_signature: Some("round_trip_sig".to_string()),
+ };
+
+ let serialized = serde_json::to_value(&original).unwrap();
+ let deserialized: LanguageModelToolUse = serde_json::from_value(serialized).unwrap();
+
+ assert_eq!(deserialized.id, original.id);
+ assert_eq!(deserialized.name, original.name);
+ assert_eq!(deserialized.thought_signature, original.thought_signature);
+ }
+
+ #[test]
+ fn test_language_model_tool_use_round_trip_without_signature() {
+ use serde_json::json;
+
+ let original = LanguageModelToolUse {
+ id: LanguageModelToolUseId::from("no_sig_id"),
+ name: "no_sig_tool".into(),
+ raw_input: json!({"arg": "value"}).to_string(),
+ input: json!({"arg": "value"}),
+ is_input_complete: true,
+ thought_signature: None,
+ };
+
+ let serialized = serde_json::to_value(&original).unwrap();
+ let deserialized: LanguageModelToolUse = serde_json::from_value(serialized).unwrap();
+
+ assert_eq!(deserialized.id, original.id);
+ assert_eq!(deserialized.name, original.name);
+ assert_eq!(deserialized.thought_signature, None);
+ }
+}
@@ -0,0 +1,21 @@
+use crate::{LanguageModelProviderId, LanguageModelProviderName};
+
+pub const ANTHROPIC_PROVIDER_ID: LanguageModelProviderId =
+ LanguageModelProviderId::new("anthropic");
+pub const ANTHROPIC_PROVIDER_NAME: LanguageModelProviderName =
+ LanguageModelProviderName::new("Anthropic");
+
+pub const OPEN_AI_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("openai");
+pub const OPEN_AI_PROVIDER_NAME: LanguageModelProviderName =
+ LanguageModelProviderName::new("OpenAI");
+
+pub const GOOGLE_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("google");
+pub const GOOGLE_PROVIDER_NAME: LanguageModelProviderName =
+ LanguageModelProviderName::new("Google AI");
+
+pub const X_AI_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("x_ai");
+pub const X_AI_PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("xAI");
+
+pub const ZED_CLOUD_PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("zed.dev");
+pub const ZED_CLOUD_PROVIDER_NAME: LanguageModelProviderName =
+ LanguageModelProviderName::new("Zed");
@@ -0,0 +1,463 @@
+use std::sync::Arc;
+
+use serde::{Deserialize, Serialize};
+
+use crate::role::Role;
+use crate::{LanguageModelToolUse, LanguageModelToolUseId, SharedString};
+
+/// Dimensions of a `LanguageModelImage`
+#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, Serialize, Deserialize)]
+pub struct ImageSize {
+ pub width: i32,
+ pub height: i32,
+}
+
+#[derive(Clone, PartialEq, Eq, Serialize, Deserialize, Hash)]
+pub struct LanguageModelImage {
+ /// A base64-encoded PNG image.
+ pub source: SharedString,
+ #[serde(default, skip_serializing_if = "Option::is_none")]
+ pub size: Option<ImageSize>,
+}
+
+impl LanguageModelImage {
+ pub fn len(&self) -> usize {
+ self.source.len()
+ }
+
+ pub fn is_empty(&self) -> bool {
+ self.source.is_empty()
+ }
+
+ pub fn empty() -> Self {
+ Self {
+ source: "".into(),
+ size: None,
+ }
+ }
+
+ /// Parse Self from a JSON object with case-insensitive field names
+ pub fn from_json(obj: &serde_json::Map<String, serde_json::Value>) -> Option<Self> {
+ let mut source = None;
+ let mut size_obj = None;
+
+ for (k, v) in obj.iter() {
+ match k.to_lowercase().as_str() {
+ "source" => source = v.as_str(),
+ "size" => size_obj = v.as_object(),
+ _ => {}
+ }
+ }
+
+ let source = source?;
+ let size_obj = size_obj?;
+
+ let mut width = None;
+ let mut height = None;
+
+ for (k, v) in size_obj.iter() {
+ match k.to_lowercase().as_str() {
+ "width" => width = v.as_i64().map(|w| w as i32),
+ "height" => height = v.as_i64().map(|h| h as i32),
+ _ => {}
+ }
+ }
+
+ Some(Self {
+ size: Some(ImageSize {
+ width: width?,
+ height: height?,
+ }),
+ source: SharedString::from(source.to_string()),
+ })
+ }
+
+ pub fn estimate_tokens(&self) -> usize {
+ let Some(size) = self.size.as_ref() else {
+ return 0;
+ };
+ let width = size.width.unsigned_abs() as usize;
+ let height = size.height.unsigned_abs() as usize;
+
+ // From: https://docs.anthropic.com/en/docs/build-with-claude/vision#calculate-image-costs
+ (width * height) / 750
+ }
+
+ pub fn to_base64_url(&self) -> String {
+ format!("data:image/png;base64,{}", self.source)
+ }
+}
+
+impl std::fmt::Debug for LanguageModelImage {
+ fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+ f.debug_struct("LanguageModelImage")
+ .field("source", &format!("<{} bytes>", self.source.len()))
+ .field("size", &self.size)
+ .finish()
+ }
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize, Eq, PartialEq, Hash)]
+pub struct LanguageModelToolResult {
+ pub tool_use_id: LanguageModelToolUseId,
+ pub tool_name: Arc<str>,
+ pub is_error: bool,
+ /// The tool output formatted for presenting to the model
+ pub content: LanguageModelToolResultContent,
+ /// The raw tool output, if available, often for debugging or extra state for replay
+ pub output: Option<serde_json::Value>,
+}
+
+#[derive(Debug, Clone, Serialize, Eq, PartialEq, Hash)]
+pub enum LanguageModelToolResultContent {
+ Text(Arc<str>),
+ Image(LanguageModelImage),
+}
+
+impl<'de> Deserialize<'de> for LanguageModelToolResultContent {
+ fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
+ where
+ D: serde::Deserializer<'de>,
+ {
+ use serde::de::Error;
+
+ let value = serde_json::Value::deserialize(deserializer)?;
+
+ // 1. Try as plain string
+ if let Ok(text) = serde_json::from_value::<String>(value.clone()) {
+ return Ok(Self::Text(Arc::from(text)));
+ }
+
+ // 2. Try as object
+ if let Some(obj) = value.as_object() {
+ fn get_field<'a>(
+ obj: &'a serde_json::Map<String, serde_json::Value>,
+ field: &str,
+ ) -> Option<&'a serde_json::Value> {
+ obj.iter()
+ .find(|(k, _)| k.to_lowercase() == field.to_lowercase())
+ .map(|(_, v)| v)
+ }
+
+ // Accept wrapped text format: { "type": "text", "text": "..." }
+ if let (Some(type_value), Some(text_value)) =
+ (get_field(obj, "type"), get_field(obj, "text"))
+ && let Some(type_str) = type_value.as_str()
+ && type_str.to_lowercase() == "text"
+ && let Some(text) = text_value.as_str()
+ {
+ return Ok(Self::Text(Arc::from(text)));
+ }
+
+ // Check for wrapped Text variant: { "text": "..." }
+ if let Some((_key, value)) = obj.iter().find(|(k, _)| k.to_lowercase() == "text")
+ && obj.len() == 1
+ {
+ if let Some(text) = value.as_str() {
+ return Ok(Self::Text(Arc::from(text)));
+ }
+ }
+
+ // Check for wrapped Image variant: { "image": { "source": "...", "size": ... } }
+ if let Some((_key, value)) = obj.iter().find(|(k, _)| k.to_lowercase() == "image")
+ && obj.len() == 1
+ {
+ if let Some(image_obj) = value.as_object()
+ && let Some(image) = LanguageModelImage::from_json(image_obj)
+ {
+ return Ok(Self::Image(image));
+ }
+ }
+
+ // Try as direct Image
+ if let Some(image) = LanguageModelImage::from_json(obj) {
+ return Ok(Self::Image(image));
+ }
+ }
+
+ Err(D::Error::custom(format!(
+ "data did not match any variant of LanguageModelToolResultContent. Expected either a string, \
+ an object with 'type': 'text', a wrapped variant like {{\"Text\": \"...\"}}, or an image object. Got: {}",
+ serde_json::to_string_pretty(&value).unwrap_or_else(|_| value.to_string())
+ )))
+ }
+}
+
+impl LanguageModelToolResultContent {
+ pub fn to_str(&self) -> Option<&str> {
+ match self {
+ Self::Text(text) => Some(text),
+ Self::Image(_) => None,
+ }
+ }
+
+ pub fn is_empty(&self) -> bool {
+ match self {
+ Self::Text(text) => text.chars().all(|c| c.is_whitespace()),
+ Self::Image(_) => false,
+ }
+ }
+}
+
+impl From<&str> for LanguageModelToolResultContent {
+ fn from(value: &str) -> Self {
+ Self::Text(Arc::from(value))
+ }
+}
+
+impl From<String> for LanguageModelToolResultContent {
+ fn from(value: String) -> Self {
+ Self::Text(Arc::from(value))
+ }
+}
+
+impl From<LanguageModelImage> for LanguageModelToolResultContent {
+ fn from(image: LanguageModelImage) -> Self {
+ Self::Image(image)
+ }
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize, Eq, PartialEq, Hash)]
+pub enum MessageContent {
+ Text(String),
+ Thinking {
+ text: String,
+ signature: Option<String>,
+ },
+ RedactedThinking(String),
+ Image(LanguageModelImage),
+ ToolUse(LanguageModelToolUse),
+ ToolResult(LanguageModelToolResult),
+}
+
+impl MessageContent {
+ pub fn to_str(&self) -> Option<&str> {
+ match self {
+ MessageContent::Text(text) => Some(text.as_str()),
+ MessageContent::Thinking { text, .. } => Some(text.as_str()),
+ MessageContent::RedactedThinking(_) => None,
+ MessageContent::ToolResult(tool_result) => tool_result.content.to_str(),
+ MessageContent::ToolUse(_) | MessageContent::Image(_) => None,
+ }
+ }
+
+ pub fn is_empty(&self) -> bool {
+ match self {
+ MessageContent::Text(text) => text.chars().all(|c| c.is_whitespace()),
+ MessageContent::Thinking { text, .. } => text.chars().all(|c| c.is_whitespace()),
+ MessageContent::ToolResult(tool_result) => tool_result.content.is_empty(),
+ MessageContent::RedactedThinking(_)
+ | MessageContent::ToolUse(_)
+ | MessageContent::Image(_) => false,
+ }
+ }
+}
+
+impl From<String> for MessageContent {
+ fn from(value: String) -> Self {
+ MessageContent::Text(value)
+ }
+}
+
+impl From<&str> for MessageContent {
+ fn from(value: &str) -> Self {
+ MessageContent::Text(value.to_string())
+ }
+}
+
+#[derive(Clone, Serialize, Deserialize, Debug, PartialEq, Hash)]
+pub struct LanguageModelRequestMessage {
+ pub role: Role,
+ pub content: Vec<MessageContent>,
+ pub cache: bool,
+ #[serde(default, skip_serializing_if = "Option::is_none")]
+ pub reasoning_details: Option<serde_json::Value>,
+}
+
+impl LanguageModelRequestMessage {
+ pub fn string_contents(&self) -> String {
+ let mut buffer = String::new();
+ for string in self.content.iter().filter_map(|content| content.to_str()) {
+ buffer.push_str(string);
+ }
+ buffer
+ }
+
+ pub fn contents_empty(&self) -> bool {
+ self.content.iter().all(|content| content.is_empty())
+ }
+}
+
+#[derive(Debug, PartialEq, Hash, Clone, Serialize, Deserialize)]
+pub struct LanguageModelRequestTool {
+ pub name: String,
+ pub description: String,
+ pub input_schema: serde_json::Value,
+ pub use_input_streaming: bool,
+}
+
+#[derive(Debug, PartialEq, Hash, Clone, Serialize, Deserialize)]
+pub enum LanguageModelToolChoice {
+ Auto,
+ Any,
+ None,
+}
+
+#[derive(Debug, PartialEq, Eq, PartialOrd, Ord, Hash, Clone, Copy, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum CompletionIntent {
+ UserPrompt,
+ Subagent,
+ ToolResults,
+ ThreadSummarization,
+ ThreadContextSummarization,
+ CreateFile,
+ EditFile,
+ InlineAssist,
+ TerminalInlineAssist,
+ GenerateGitCommitMessage,
+}
+
+#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq)]
+pub struct LanguageModelRequest {
+ pub thread_id: Option<String>,
+ pub prompt_id: Option<String>,
+ pub intent: Option<CompletionIntent>,
+ pub messages: Vec<LanguageModelRequestMessage>,
+ pub tools: Vec<LanguageModelRequestTool>,
+ pub tool_choice: Option<LanguageModelToolChoice>,
+ pub stop: Vec<String>,
+ pub temperature: Option<f32>,
+ pub thinking_allowed: bool,
+ pub thinking_effort: Option<String>,
+ pub speed: Option<Speed>,
+}
+
+#[derive(Clone, Copy, Default, Debug, Serialize, Deserialize, PartialEq, Eq)]
+#[serde(rename_all = "snake_case")]
+pub enum Speed {
+ #[default]
+ Standard,
+ Fast,
+}
+
+impl Speed {
+ pub fn toggle(self) -> Self {
+ match self {
+ Speed::Standard => Speed::Fast,
+ Speed::Fast => Speed::Standard,
+ }
+ }
+}
+
+#[derive(Serialize, Deserialize, Debug, Eq, PartialEq)]
+pub struct LanguageModelResponseMessage {
+ pub role: Option<Role>,
+ pub content: Option<String>,
+}
+
+#[cfg(test)]
+mod tests {
+ use super::*;
+
+ #[test]
+ fn test_language_model_tool_result_content_deserialization() {
+ // Test plain string
+ let json = serde_json::json!("hello world");
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ assert_eq!(
+ content,
+ LanguageModelToolResultContent::Text(Arc::from("hello world"))
+ );
+
+ // Test wrapped text format: { "type": "text", "text": "..." }
+ let json = serde_json::json!({"type": "text", "text": "hello"});
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ assert_eq!(
+ content,
+ LanguageModelToolResultContent::Text(Arc::from("hello"))
+ );
+
+ // Test single-field text object: { "text": "..." }
+ let json = serde_json::json!({"text": "hello"});
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ assert_eq!(
+ content,
+ LanguageModelToolResultContent::Text(Arc::from("hello"))
+ );
+
+ // Test case-insensitive type field
+ let json = serde_json::json!({"Type": "Text", "Text": "hello"});
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ assert_eq!(
+ content,
+ LanguageModelToolResultContent::Text(Arc::from("hello"))
+ );
+
+ // Test image object
+ let json = serde_json::json!({
+ "source": "base64encodedimagedata",
+ "size": {"width": 100, "height": 200}
+ });
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ match content {
+ LanguageModelToolResultContent::Image(image) => {
+ assert_eq!(image.source.as_ref(), "base64encodedimagedata");
+ let size = image.size.expect("size");
+ assert_eq!(size.width, 100);
+ assert_eq!(size.height, 200);
+ }
+ _ => panic!("Expected Image variant"),
+ }
+
+ // Test wrapped image: { "image": { "source": "...", "size": ... } }
+ let json = serde_json::json!({
+ "image": {
+ "source": "wrappedimagedata",
+ "size": {"width": 50, "height": 75}
+ }
+ });
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ match content {
+ LanguageModelToolResultContent::Image(image) => {
+ assert_eq!(image.source.as_ref(), "wrappedimagedata");
+ let size = image.size.expect("size");
+ assert_eq!(size.width, 50);
+ assert_eq!(size.height, 75);
+ }
+ _ => panic!("Expected Image variant"),
+ }
+
+ // Test case insensitive
+ let json = serde_json::json!({
+ "Source": "caseinsensitive",
+ "Size": {"Width": 30, "Height": 40}
+ });
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ match content {
+ LanguageModelToolResultContent::Image(image) => {
+ assert_eq!(image.source.as_ref(), "caseinsensitive");
+ let size = image.size.expect("size");
+ assert_eq!(size.width, 30);
+ assert_eq!(size.height, 40);
+ }
+ _ => panic!("Expected Image variant"),
+ }
+
+ // Test direct image object
+ let json = serde_json::json!({
+ "source": "directimage",
+ "size": {"width": 200, "height": 300}
+ });
+ let content: LanguageModelToolResultContent = serde_json::from_value(json).unwrap();
+ match content {
+ LanguageModelToolResultContent::Image(image) => {
+ assert_eq!(image.source.as_ref(), "directimage");
+ let size = image.size.expect("size");
+ assert_eq!(size.width, 200);
+ assert_eq!(size.height, 300);
+ }
+ _ => panic!("Expected Image variant"),
+ }
+ }
+}
@@ -77,8 +77,6 @@ pub fn adapt_schema_to_format(
}
fn preprocess_json_schema(json: &mut Value) -> Result<()> {
- // `additionalProperties` defaults to `false` unless explicitly specified.
- // This prevents models from hallucinating tool parameters.
if let Value::Object(obj) = json
&& matches!(obj.get("type"), Some(Value::String(s)) if s == "object")
{
@@ -86,7 +84,6 @@ fn preprocess_json_schema(json: &mut Value) -> Result<()> {
obj.insert("additionalProperties".to_string(), Value::Bool(false));
}
- // OpenAI API requires non-missing `properties`
if !obj.contains_key("properties") {
obj.insert("properties".to_string(), Value::Object(Default::default()));
}
@@ -94,7 +91,6 @@ fn preprocess_json_schema(json: &mut Value) -> Result<()> {
Ok(())
}
-/// Tries to adapt the json schema so that it is compatible with https://ai.google.dev/api/caching#Schema
fn adapt_to_json_schema_subset(json: &mut Value) -> Result<()> {
if let Value::Object(obj) = json {
const UNSUPPORTED_KEYS: [&str; 4] = ["if", "then", "else", "$ref"];
@@ -108,9 +104,7 @@ fn adapt_to_json_schema_subset(json: &mut Value) -> Result<()> {
const KEYS_TO_REMOVE: [(&str, fn(&Value) -> bool); 6] = [
("format", |value| value.is_string()),
- // Gemini doesn't support `additionalProperties` in any form (boolean or schema object)
("additionalProperties", |_| true),
- // Gemini doesn't support `propertyNames`
("propertyNames", |_| true),
("exclusiveMinimum", |value| value.is_number()),
("exclusiveMaximum", |value| value.is_number()),
@@ -124,7 +118,6 @@ fn adapt_to_json_schema_subset(json: &mut Value) -> Result<()> {
}
}
- // If a type is not specified for an input parameter, add a default type
if matches!(obj.get("description"), Some(Value::String(_)))
&& !obj.contains_key("type")
&& !(obj.contains_key("anyOf")
@@ -134,7 +127,6 @@ fn adapt_to_json_schema_subset(json: &mut Value) -> Result<()> {
obj.insert("type".to_string(), Value::String("string".to_string()));
}
- // Handle oneOf -> anyOf conversion
if let Some(subschemas) = obj.get_mut("oneOf")
&& subschemas.is_array()
{
@@ -143,7 +135,6 @@ fn adapt_to_json_schema_subset(json: &mut Value) -> Result<()> {
obj.insert("anyOf".to_string(), subschemas_clone);
}
- // Recursively process all nested objects and arrays
for (_, value) in obj.iter_mut() {
if let Value::Object(_) | Value::Array(_) = value {
adapt_to_json_schema_subset(value)?;
@@ -178,7 +169,6 @@ mod tests {
})
);
- // Ensure that we do not add a type if it is an object
let mut json = json!({
"description": {
"value": "abc",
@@ -221,7 +211,6 @@ mod tests {
})
);
- // Ensure that we do not remove keys that are actually supported (e.g. "format" can just be used as another property)
let mut json = json!({
"description": "A test field",
"type": "integer",
@@ -239,7 +228,6 @@ mod tests {
})
);
- // additionalProperties as an object schema is also unsupported by Gemini
let mut json = json!({
"type": "object",
"properties": {
@@ -38,13 +38,22 @@ fn strip_trailing_incomplete_escape(json: &str) -> &str {
}
}
+/// Parses a "prompt is too long: N tokens ..." message and extracts the token count.
+pub fn parse_prompt_too_long(message: &str) -> Option<u64> {
+ message
+ .strip_prefix("prompt is too long: ")?
+ .split_once(" tokens")?
+ .0
+ .parse()
+ .ok()
+}
+
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_fix_streamed_json_strips_incomplete_escape() {
- // Trailing `\` inside a string β incomplete escape sequence
let fixed = fix_streamed_json(r#"{"text": "hello\"#);
let parsed: serde_json::Value = serde_json::from_str(&fixed).expect("valid json");
assert_eq!(parsed["text"], "hello");
@@ -52,7 +61,6 @@ mod tests {
#[test]
fn test_fix_streamed_json_preserves_complete_escape() {
- // `\\` is a complete escape (literal backslash)
let fixed = fix_streamed_json(r#"{"text": "hello\\"#);
let parsed: serde_json::Value = serde_json::from_str(&fixed).expect("valid json");
assert_eq!(parsed["text"], "hello\\");
@@ -60,7 +68,6 @@ mod tests {
#[test]
fn test_fix_streamed_json_strips_escape_after_complete_escape() {
- // `\\\` = complete `\\` (literal backslash) + incomplete `\`
let fixed = fix_streamed_json(r#"{"text": "hello\\\"#);
let parsed: serde_json::Value = serde_json::from_str(&fixed).expect("valid json");
assert_eq!(parsed["text"], "hello\\");
@@ -75,12 +82,10 @@ mod tests {
#[test]
fn test_fix_streamed_json_newline_escape_boundary() {
- // Simulates a stream boundary landing between `\` and `n`
let fixed = fix_streamed_json(r#"{"text": "line1\"#);
let parsed: serde_json::Value = serde_json::from_str(&fixed).expect("valid json");
assert_eq!(parsed["text"], "line1");
- // Next chunk completes the escape
let fixed = fix_streamed_json(r#"{"text": "line1\nline2"#);
let parsed: serde_json::Value = serde_json::from_str(&fixed).expect("valid json");
assert_eq!(parsed["text"], "line1\nline2");
@@ -88,8 +93,6 @@ mod tests {
#[test]
fn test_fix_streamed_json_incremental_delta_correctness() {
- // This is the actual scenario that causes the bug:
- // chunk 1 ends mid-escape, chunk 2 completes it.
let chunk1 = r#"{"replacement_text": "fn foo() {\"#;
let fixed1 = fix_streamed_json(chunk1);
let parsed1: serde_json::Value = serde_json::from_str(&fixed1).expect("valid json");
@@ -102,7 +105,6 @@ mod tests {
let text2 = parsed2["replacement_text"].as_str().expect("string");
assert_eq!(text2, "fn foo() {\n return bar;\n}");
- // The delta should be the newline + rest, with no spurious backslash
let delta = &text2[text1.len()..];
assert_eq!(delta, "\n return bar;\n}");
}
@@ -21,8 +21,8 @@ aws_http_client.workspace = true
base64.workspace = true
bedrock = { workspace = true, features = ["schemars"] }
client.workspace = true
+cloud_api_client.workspace = true
cloud_api_types.workspace = true
-cloud_llm_client.workspace = true
collections.workspace = true
component.workspace = true
convert_case.workspace = true
@@ -41,6 +41,7 @@ gpui_tokio.workspace = true
http_client.workspace = true
language.workspace = true
language_model.workspace = true
+language_models_cloud.workspace = true
lmstudio = { workspace = true, features = ["schemars"] }
log.workspace = true
menu.workspace = true
@@ -49,18 +50,15 @@ ollama = { workspace = true, features = ["schemars"] }
open_ai = { workspace = true, features = ["schemars"] }
opencode = { workspace = true, features = ["schemars"] }
open_router = { workspace = true, features = ["schemars"] }
-partial-json-fixer.workspace = true
rand.workspace = true
release_channel.workspace = true
schemars.workspace = true
sha2.workspace = true
-semver.workspace = true
serde.workspace = true
serde_json.workspace = true
settings.workspace = true
smol.workspace = true
strum.workspace = true
-thiserror.workspace = true
tiktoken-rs.workspace = true
tokio = { workspace = true, features = ["rt", "rt-multi-thread"] }
ui.workspace = true
@@ -76,4 +74,3 @@ http_client = { workspace = true, features = ["test-support"] }
language_model = { workspace = true, features = ["test-support"] }
parking_lot.workspace = true
pretty_assertions.workspace = true
-
@@ -12,7 +12,7 @@ pub mod open_ai_compatible;
pub mod open_router;
pub mod openai_subscribed;
pub mod opencode;
-mod util;
+
pub mod vercel;
pub mod vercel_ai_gateway;
pub mod x_ai;
@@ -1,13 +1,10 @@
pub mod telemetry;
-use anthropic::{
- ANTHROPIC_API_URL, AnthropicError, AnthropicModelMode, ContentDelta, CountTokensRequest, Event,
- ResponseContent, ToolResultContent, ToolResultPart, Usage,
-};
+use anthropic::{ANTHROPIC_API_URL, AnthropicError, AnthropicModelMode};
use anyhow::Result;
-use collections::{BTreeMap, HashMap};
+use collections::BTreeMap;
use credentials_provider::CredentialsProvider;
-use futures::{FutureExt, Stream, StreamExt, future::BoxFuture, stream::BoxStream};
+use futures::{FutureExt, StreamExt, future::BoxFuture, stream::BoxStream};
use gpui::{AnyView, App, AsyncApp, Context, Entity, Task};
use http_client::HttpClient;
use language_model::{
@@ -16,20 +13,19 @@ use language_model::{
LanguageModelCacheConfiguration, LanguageModelCompletionError, LanguageModelCompletionEvent,
LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
- LanguageModelToolChoice, LanguageModelToolResultContent, LanguageModelToolUse, MessageContent,
- RateLimiter, Role, StopReason, env_var,
+ LanguageModelToolChoice, RateLimiter, env_var,
};
use settings::{Settings, SettingsStore};
-use std::pin::Pin;
-use std::str::FromStr;
use std::sync::{Arc, LazyLock};
use strum::IntoEnumIterator;
use ui::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
use ui_input::InputField;
use util::ResultExt;
-use crate::provider::util::{fix_streamed_json, parse_tool_arguments};
-
+pub use anthropic::completion::{
+ AnthropicEventMapper, count_anthropic_tokens_with_tiktoken, into_anthropic,
+ into_anthropic_count_tokens_request,
+};
pub use settings::AnthropicAvailableModel as AvailableModel;
const PROVIDER_ID: LanguageModelProviderId = ANTHROPIC_PROVIDER_ID;
@@ -249,228 +245,6 @@ pub struct AnthropicModel {
request_limiter: RateLimiter,
}
-fn to_anthropic_content(content: MessageContent) -> Option<anthropic::RequestContent> {
- match content {
- MessageContent::Text(text) => {
- let text = if text.chars().last().is_some_and(|c| c.is_whitespace()) {
- text.trim_end().to_string()
- } else {
- text
- };
- if !text.is_empty() {
- Some(anthropic::RequestContent::Text {
- text,
- cache_control: None,
- })
- } else {
- None
- }
- }
- MessageContent::Thinking {
- text: thinking,
- signature,
- } => {
- if let Some(signature) = signature
- && !thinking.is_empty()
- {
- Some(anthropic::RequestContent::Thinking {
- thinking,
- signature,
- cache_control: None,
- })
- } else {
- None
- }
- }
- MessageContent::RedactedThinking(data) => {
- if !data.is_empty() {
- Some(anthropic::RequestContent::RedactedThinking { data })
- } else {
- None
- }
- }
- MessageContent::Image(image) => Some(anthropic::RequestContent::Image {
- source: anthropic::ImageSource {
- source_type: "base64".to_string(),
- media_type: "image/png".to_string(),
- data: image.source.to_string(),
- },
- cache_control: None,
- }),
- MessageContent::ToolUse(tool_use) => Some(anthropic::RequestContent::ToolUse {
- id: tool_use.id.to_string(),
- name: tool_use.name.to_string(),
- input: tool_use.input,
- cache_control: None,
- }),
- MessageContent::ToolResult(tool_result) => Some(anthropic::RequestContent::ToolResult {
- tool_use_id: tool_result.tool_use_id.to_string(),
- is_error: tool_result.is_error,
- content: match tool_result.content {
- LanguageModelToolResultContent::Text(text) => {
- ToolResultContent::Plain(text.to_string())
- }
- LanguageModelToolResultContent::Image(image) => {
- ToolResultContent::Multipart(vec![ToolResultPart::Image {
- source: anthropic::ImageSource {
- source_type: "base64".to_string(),
- media_type: "image/png".to_string(),
- data: image.source.to_string(),
- },
- }])
- }
- },
- cache_control: None,
- }),
- }
-}
-
-/// Convert a LanguageModelRequest to an Anthropic CountTokensRequest.
-pub fn into_anthropic_count_tokens_request(
- request: LanguageModelRequest,
- model: String,
- mode: AnthropicModelMode,
-) -> CountTokensRequest {
- let mut new_messages: Vec<anthropic::Message> = Vec::new();
- let mut system_message = String::new();
-
- for message in request.messages {
- if message.contents_empty() {
- continue;
- }
-
- match message.role {
- Role::User | Role::Assistant => {
- let anthropic_message_content: Vec<anthropic::RequestContent> = message
- .content
- .into_iter()
- .filter_map(to_anthropic_content)
- .collect();
- let anthropic_role = match message.role {
- Role::User => anthropic::Role::User,
- Role::Assistant => anthropic::Role::Assistant,
- Role::System => unreachable!("System role should never occur here"),
- };
- if anthropic_message_content.is_empty() {
- continue;
- }
-
- if let Some(last_message) = new_messages.last_mut()
- && last_message.role == anthropic_role
- {
- last_message.content.extend(anthropic_message_content);
- continue;
- }
-
- new_messages.push(anthropic::Message {
- role: anthropic_role,
- content: anthropic_message_content,
- });
- }
- Role::System => {
- if !system_message.is_empty() {
- system_message.push_str("\n\n");
- }
- system_message.push_str(&message.string_contents());
- }
- }
- }
-
- CountTokensRequest {
- model,
- messages: new_messages,
- system: if system_message.is_empty() {
- None
- } else {
- Some(anthropic::StringOrContents::String(system_message))
- },
- thinking: if request.thinking_allowed {
- match mode {
- AnthropicModelMode::Thinking { budget_tokens } => {
- Some(anthropic::Thinking::Enabled { budget_tokens })
- }
- AnthropicModelMode::AdaptiveThinking => Some(anthropic::Thinking::Adaptive),
- AnthropicModelMode::Default => None,
- }
- } else {
- None
- },
- tools: request
- .tools
- .into_iter()
- .map(|tool| anthropic::Tool {
- name: tool.name,
- description: tool.description,
- input_schema: tool.input_schema,
- eager_input_streaming: tool.use_input_streaming,
- })
- .collect(),
- tool_choice: request.tool_choice.map(|choice| match choice {
- LanguageModelToolChoice::Auto => anthropic::ToolChoice::Auto,
- LanguageModelToolChoice::Any => anthropic::ToolChoice::Any,
- LanguageModelToolChoice::None => anthropic::ToolChoice::None,
- }),
- }
-}
-
-/// Estimate tokens using tiktoken. Used as a fallback when the API is unavailable,
-/// or by providers (like Zed Cloud) that don't have direct Anthropic API access.
-pub fn count_anthropic_tokens_with_tiktoken(request: LanguageModelRequest) -> Result<u64> {
- let messages = request.messages;
- let mut tokens_from_images = 0;
- let mut string_messages = Vec::with_capacity(messages.len());
-
- for message in messages {
- let mut string_contents = String::new();
-
- for content in message.content {
- match content {
- MessageContent::Text(text) => {
- string_contents.push_str(&text);
- }
- MessageContent::Thinking { .. } => {
- // Thinking blocks are not included in the input token count.
- }
- MessageContent::RedactedThinking(_) => {
- // Thinking blocks are not included in the input token count.
- }
- MessageContent::Image(image) => {
- tokens_from_images += image.estimate_tokens();
- }
- MessageContent::ToolUse(_tool_use) => {
- // TODO: Estimate token usage from tool uses.
- }
- MessageContent::ToolResult(tool_result) => match &tool_result.content {
- LanguageModelToolResultContent::Text(text) => {
- string_contents.push_str(text);
- }
- LanguageModelToolResultContent::Image(image) => {
- tokens_from_images += image.estimate_tokens();
- }
- },
- }
- }
-
- if !string_contents.is_empty() {
- string_messages.push(tiktoken_rs::ChatCompletionRequestMessage {
- role: match message.role {
- Role::User => "user".into(),
- Role::Assistant => "assistant".into(),
- Role::System => "system".into(),
- },
- content: Some(string_contents),
- name: None,
- function_call: None,
- });
- }
- }
-
- // Tiktoken doesn't yet support these models, so we manually use the
- // same tokenizer as GPT-4.
- tiktoken_rs::num_tokens_from_messages("gpt-4", &string_messages)
- .map(|tokens| (tokens + tokens_from_images) as u64)
-}
-
impl AnthropicModel {
fn stream_completion(
&self,
@@ -617,10 +391,13 @@ impl LanguageModel for AnthropicModel {
)
});
+ let background = cx.background_executor().clone();
async move {
// If no API key, fall back to tiktoken estimation
let Some(api_key) = api_key else {
- return count_anthropic_tokens_with_tiktoken(request);
+ return background
+ .spawn(async move { count_anthropic_tokens_with_tiktoken(request) })
+ .await;
};
let count_request =
@@ -634,7 +411,9 @@ impl LanguageModel for AnthropicModel {
log::error!(
"Anthropic count_tokens API failed, falling back to tiktoken: {err:?}"
);
- count_anthropic_tokens_with_tiktoken(request)
+ background
+ .spawn(async move { count_anthropic_tokens_with_tiktoken(request) })
+ .await
}
}
}
@@ -678,345 +457,6 @@ impl LanguageModel for AnthropicModel {
}
}
-pub fn into_anthropic(
- request: LanguageModelRequest,
- model: String,
- default_temperature: f32,
- max_output_tokens: u64,
- mode: AnthropicModelMode,
-) -> anthropic::Request {
- let mut new_messages: Vec<anthropic::Message> = Vec::new();
- let mut system_message = String::new();
-
- for message in request.messages {
- if message.contents_empty() {
- continue;
- }
-
- match message.role {
- Role::User | Role::Assistant => {
- let mut anthropic_message_content: Vec<anthropic::RequestContent> = message
- .content
- .into_iter()
- .filter_map(to_anthropic_content)
- .collect();
- let anthropic_role = match message.role {
- Role::User => anthropic::Role::User,
- Role::Assistant => anthropic::Role::Assistant,
- Role::System => unreachable!("System role should never occur here"),
- };
- if anthropic_message_content.is_empty() {
- continue;
- }
-
- if let Some(last_message) = new_messages.last_mut()
- && last_message.role == anthropic_role
- {
- last_message.content.extend(anthropic_message_content);
- continue;
- }
-
- // Mark the last segment of the message as cached
- if message.cache {
- let cache_control_value = Some(anthropic::CacheControl {
- cache_type: anthropic::CacheControlType::Ephemeral,
- });
- for message_content in anthropic_message_content.iter_mut().rev() {
- match message_content {
- anthropic::RequestContent::RedactedThinking { .. } => {
- // Caching is not possible, fallback to next message
- }
- anthropic::RequestContent::Text { cache_control, .. }
- | anthropic::RequestContent::Thinking { cache_control, .. }
- | anthropic::RequestContent::Image { cache_control, .. }
- | anthropic::RequestContent::ToolUse { cache_control, .. }
- | anthropic::RequestContent::ToolResult { cache_control, .. } => {
- *cache_control = cache_control_value;
- break;
- }
- }
- }
- }
-
- new_messages.push(anthropic::Message {
- role: anthropic_role,
- content: anthropic_message_content,
- });
- }
- Role::System => {
- if !system_message.is_empty() {
- system_message.push_str("\n\n");
- }
- system_message.push_str(&message.string_contents());
- }
- }
- }
-
- anthropic::Request {
- model,
- messages: new_messages,
- max_tokens: max_output_tokens,
- system: if system_message.is_empty() {
- None
- } else {
- Some(anthropic::StringOrContents::String(system_message))
- },
- thinking: if request.thinking_allowed {
- match mode {
- AnthropicModelMode::Thinking { budget_tokens } => {
- Some(anthropic::Thinking::Enabled { budget_tokens })
- }
- AnthropicModelMode::AdaptiveThinking => Some(anthropic::Thinking::Adaptive),
- AnthropicModelMode::Default => None,
- }
- } else {
- None
- },
- tools: request
- .tools
- .into_iter()
- .map(|tool| anthropic::Tool {
- name: tool.name,
- description: tool.description,
- input_schema: tool.input_schema,
- eager_input_streaming: tool.use_input_streaming,
- })
- .collect(),
- tool_choice: request.tool_choice.map(|choice| match choice {
- LanguageModelToolChoice::Auto => anthropic::ToolChoice::Auto,
- LanguageModelToolChoice::Any => anthropic::ToolChoice::Any,
- LanguageModelToolChoice::None => anthropic::ToolChoice::None,
- }),
- metadata: None,
- output_config: if request.thinking_allowed
- && matches!(mode, AnthropicModelMode::AdaptiveThinking)
- {
- request.thinking_effort.as_deref().and_then(|effort| {
- let effort = match effort {
- "low" => Some(anthropic::Effort::Low),
- "medium" => Some(anthropic::Effort::Medium),
- "high" => Some(anthropic::Effort::High),
- "max" => Some(anthropic::Effort::Max),
- _ => None,
- };
- effort.map(|effort| anthropic::OutputConfig {
- effort: Some(effort),
- })
- })
- } else {
- None
- },
- stop_sequences: Vec::new(),
- speed: request.speed.map(From::from),
- temperature: request.temperature.or(Some(default_temperature)),
- top_k: None,
- top_p: None,
- }
-}
-
-pub struct AnthropicEventMapper {
- tool_uses_by_index: HashMap<usize, RawToolUse>,
- usage: Usage,
- stop_reason: StopReason,
-}
-
-impl AnthropicEventMapper {
- pub fn new() -> Self {
- Self {
- tool_uses_by_index: HashMap::default(),
- usage: Usage::default(),
- stop_reason: StopReason::EndTurn,
- }
- }
-
- pub fn map_stream(
- mut self,
- events: Pin<Box<dyn Send + Stream<Item = Result<Event, AnthropicError>>>>,
- ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
- {
- events.flat_map(move |event| {
- futures::stream::iter(match event {
- Ok(event) => self.map_event(event),
- Err(error) => vec![Err(error.into())],
- })
- })
- }
-
- pub fn map_event(
- &mut self,
- event: Event,
- ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
- match event {
- Event::ContentBlockStart {
- index,
- content_block,
- } => match content_block {
- ResponseContent::Text { text } => {
- vec![Ok(LanguageModelCompletionEvent::Text(text))]
- }
- ResponseContent::Thinking { thinking } => {
- vec![Ok(LanguageModelCompletionEvent::Thinking {
- text: thinking,
- signature: None,
- })]
- }
- ResponseContent::RedactedThinking { data } => {
- vec![Ok(LanguageModelCompletionEvent::RedactedThinking { data })]
- }
- ResponseContent::ToolUse { id, name, .. } => {
- self.tool_uses_by_index.insert(
- index,
- RawToolUse {
- id,
- name,
- input_json: String::new(),
- },
- );
- Vec::new()
- }
- },
- Event::ContentBlockDelta { index, delta } => match delta {
- ContentDelta::TextDelta { text } => {
- vec![Ok(LanguageModelCompletionEvent::Text(text))]
- }
- ContentDelta::ThinkingDelta { thinking } => {
- vec![Ok(LanguageModelCompletionEvent::Thinking {
- text: thinking,
- signature: None,
- })]
- }
- ContentDelta::SignatureDelta { signature } => {
- vec![Ok(LanguageModelCompletionEvent::Thinking {
- text: "".to_string(),
- signature: Some(signature),
- })]
- }
- ContentDelta::InputJsonDelta { partial_json } => {
- if let Some(tool_use) = self.tool_uses_by_index.get_mut(&index) {
- tool_use.input_json.push_str(&partial_json);
-
- // Try to convert invalid (incomplete) JSON into
- // valid JSON that serde can accept, e.g. by closing
- // unclosed delimiters. This way, we can update the
- // UI with whatever has been streamed back so far.
- if let Ok(input) =
- serde_json::Value::from_str(&fix_streamed_json(&tool_use.input_json))
- {
- return vec![Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id: tool_use.id.clone().into(),
- name: tool_use.name.clone().into(),
- is_input_complete: false,
- raw_input: tool_use.input_json.clone(),
- input,
- thought_signature: None,
- },
- ))];
- }
- }
- vec![]
- }
- },
- Event::ContentBlockStop { index } => {
- if let Some(tool_use) = self.tool_uses_by_index.remove(&index) {
- let input_json = tool_use.input_json.trim();
- let event_result = match parse_tool_arguments(input_json) {
- Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id: tool_use.id.into(),
- name: tool_use.name.into(),
- is_input_complete: true,
- input,
- raw_input: tool_use.input_json.clone(),
- thought_signature: None,
- },
- )),
- Err(json_parse_err) => {
- Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
- id: tool_use.id.into(),
- tool_name: tool_use.name.into(),
- raw_input: input_json.into(),
- json_parse_error: json_parse_err.to_string(),
- })
- }
- };
-
- vec![event_result]
- } else {
- Vec::new()
- }
- }
- Event::MessageStart { message } => {
- update_usage(&mut self.usage, &message.usage);
- vec![
- Ok(LanguageModelCompletionEvent::UsageUpdate(convert_usage(
- &self.usage,
- ))),
- Ok(LanguageModelCompletionEvent::StartMessage {
- message_id: message.id,
- }),
- ]
- }
- Event::MessageDelta { delta, usage } => {
- update_usage(&mut self.usage, &usage);
- if let Some(stop_reason) = delta.stop_reason.as_deref() {
- self.stop_reason = match stop_reason {
- "end_turn" => StopReason::EndTurn,
- "max_tokens" => StopReason::MaxTokens,
- "tool_use" => StopReason::ToolUse,
- "refusal" => StopReason::Refusal,
- _ => {
- log::error!("Unexpected anthropic stop_reason: {stop_reason}");
- StopReason::EndTurn
- }
- };
- }
- vec![Ok(LanguageModelCompletionEvent::UsageUpdate(
- convert_usage(&self.usage),
- ))]
- }
- Event::MessageStop => {
- vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))]
- }
- Event::Error { error } => {
- vec![Err(error.into())]
- }
- _ => Vec::new(),
- }
- }
-}
-
-struct RawToolUse {
- id: String,
- name: String,
- input_json: String,
-}
-
-/// Updates usage data by preferring counts from `new`.
-fn update_usage(usage: &mut Usage, new: &Usage) {
- if let Some(input_tokens) = new.input_tokens {
- usage.input_tokens = Some(input_tokens);
- }
- if let Some(output_tokens) = new.output_tokens {
- usage.output_tokens = Some(output_tokens);
- }
- if let Some(cache_creation_input_tokens) = new.cache_creation_input_tokens {
- usage.cache_creation_input_tokens = Some(cache_creation_input_tokens);
- }
- if let Some(cache_read_input_tokens) = new.cache_read_input_tokens {
- usage.cache_read_input_tokens = Some(cache_read_input_tokens);
- }
-}
-
-fn convert_usage(usage: &Usage) -> language_model::TokenUsage {
- language_model::TokenUsage {
- input_tokens: usage.input_tokens.unwrap_or(0),
- output_tokens: usage.output_tokens.unwrap_or(0),
- cache_creation_input_tokens: usage.cache_creation_input_tokens.unwrap_or(0),
- cache_read_input_tokens: usage.cache_read_input_tokens.unwrap_or(0),
- }
-}
-
struct ConfigurationView {
api_key_editor: Entity<InputField>,
state: Entity<State>,
@@ -1157,192 +597,3 @@ impl Render for ConfigurationView {
}
}
}
-
-#[cfg(test)]
-mod tests {
- use super::*;
- use anthropic::AnthropicModelMode;
- use language_model::{LanguageModelRequestMessage, MessageContent};
-
- #[test]
- fn test_cache_control_only_on_last_segment() {
- let request = LanguageModelRequest {
- messages: vec![LanguageModelRequestMessage {
- role: Role::User,
- content: vec![
- MessageContent::Text("Some prompt".to_string()),
- MessageContent::Image(language_model::LanguageModelImage::empty()),
- MessageContent::Image(language_model::LanguageModelImage::empty()),
- MessageContent::Image(language_model::LanguageModelImage::empty()),
- MessageContent::Image(language_model::LanguageModelImage::empty()),
- ],
- cache: true,
- reasoning_details: None,
- }],
- thread_id: None,
- prompt_id: None,
- intent: None,
- stop: vec![],
- temperature: None,
- tools: vec![],
- tool_choice: None,
- thinking_allowed: true,
- thinking_effort: None,
- speed: None,
- };
-
- let anthropic_request = into_anthropic(
- request,
- "claude-3-5-sonnet".to_string(),
- 0.7,
- 4096,
- AnthropicModelMode::Default,
- );
-
- assert_eq!(anthropic_request.messages.len(), 1);
-
- let message = &anthropic_request.messages[0];
- assert_eq!(message.content.len(), 5);
-
- assert!(matches!(
- message.content[0],
- anthropic::RequestContent::Text {
- cache_control: None,
- ..
- }
- ));
- for i in 1..3 {
- assert!(matches!(
- message.content[i],
- anthropic::RequestContent::Image {
- cache_control: None,
- ..
- }
- ));
- }
-
- assert!(matches!(
- message.content[4],
- anthropic::RequestContent::Image {
- cache_control: Some(anthropic::CacheControl {
- cache_type: anthropic::CacheControlType::Ephemeral,
- }),
- ..
- }
- ));
- }
-
- fn request_with_assistant_content(
- assistant_content: Vec<MessageContent>,
- ) -> anthropic::Request {
- let mut request = LanguageModelRequest {
- messages: vec![LanguageModelRequestMessage {
- role: Role::User,
- content: vec![MessageContent::Text("Hello".to_string())],
- cache: false,
- reasoning_details: None,
- }],
- thinking_effort: None,
- thread_id: None,
- prompt_id: None,
- intent: None,
- stop: vec![],
- temperature: None,
- tools: vec![],
- tool_choice: None,
- thinking_allowed: true,
- speed: None,
- };
- request.messages.push(LanguageModelRequestMessage {
- role: Role::Assistant,
- content: assistant_content,
- cache: false,
- reasoning_details: None,
- });
- into_anthropic(
- request,
- "claude-sonnet-4-5".to_string(),
- 1.0,
- 16000,
- AnthropicModelMode::Thinking {
- budget_tokens: Some(10000),
- },
- )
- }
-
- #[test]
- fn test_unsigned_thinking_blocks_stripped() {
- let result = request_with_assistant_content(vec![
- MessageContent::Thinking {
- text: "Cancelled mid-think, no signature".to_string(),
- signature: None,
- },
- MessageContent::Text("Some response text".to_string()),
- ]);
-
- let assistant_message = result
- .messages
- .iter()
- .find(|m| m.role == anthropic::Role::Assistant)
- .expect("assistant message should still exist");
-
- assert_eq!(
- assistant_message.content.len(),
- 1,
- "Only the text content should remain; unsigned thinking block should be stripped"
- );
- assert!(matches!(
- &assistant_message.content[0],
- anthropic::RequestContent::Text { text, .. } if text == "Some response text"
- ));
- }
-
- #[test]
- fn test_signed_thinking_blocks_preserved() {
- let result = request_with_assistant_content(vec![
- MessageContent::Thinking {
- text: "Completed thinking".to_string(),
- signature: Some("valid-signature".to_string()),
- },
- MessageContent::Text("Response".to_string()),
- ]);
-
- let assistant_message = result
- .messages
- .iter()
- .find(|m| m.role == anthropic::Role::Assistant)
- .expect("assistant message should exist");
-
- assert_eq!(
- assistant_message.content.len(),
- 2,
- "Both the signed thinking block and text should be preserved"
- );
- assert!(matches!(
- &assistant_message.content[0],
- anthropic::RequestContent::Thinking { thinking, signature, .. }
- if thinking == "Completed thinking" && signature == "valid-signature"
- ));
- }
-
- #[test]
- fn test_only_unsigned_thinking_block_omits_entire_message() {
- let result = request_with_assistant_content(vec![MessageContent::Thinking {
- text: "Cancelled before any text or signature".to_string(),
- signature: None,
- }]);
-
- let assistant_messages: Vec<_> = result
- .messages
- .iter()
- .filter(|m| m.role == anthropic::Role::Assistant)
- .collect();
-
- assert_eq!(
- assistant_messages.len(),
- 0,
- "An assistant message whose only content was an unsigned thinking block \
- should be omitted entirely"
- );
- }
-}
@@ -48,7 +48,7 @@ use ui_input::InputField;
use util::ResultExt;
use crate::AllLanguageModelSettings;
-use crate::provider::util::{fix_streamed_json, parse_tool_arguments};
+use language_model::util::{fix_streamed_json, parse_tool_arguments};
actions!(bedrock, [Tab, TabPrev]);
@@ -1,107 +1,93 @@
use ai_onboarding::YoungAccountBanner;
-use anthropic::AnthropicModelMode;
-use anyhow::{Context as _, Result, anyhow};
-use client::{
- Client, NeedsLlmTokenRefresh, RefreshLlmTokenListener, UserStore, global_llm_token, zed_urls,
-};
-use cloud_api_types::{OrganizationId, Plan};
-use cloud_llm_client::{
- CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, CLIENT_SUPPORTS_STATUS_STREAM_ENDED_HEADER_NAME,
- CLIENT_SUPPORTS_X_AI_HEADER_NAME, CompletionBody, CompletionEvent, CompletionRequestStatus,
- CountTokensBody, CountTokensResponse, ListModelsResponse,
- SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, ZED_VERSION_HEADER_NAME,
-};
-use futures::{
- AsyncBufReadExt, FutureExt, Stream, StreamExt,
- future::BoxFuture,
- stream::{self, BoxStream},
-};
-use google_ai::GoogleModelMode;
-use gpui::{AnyElement, AnyView, App, AsyncApp, Context, Entity, Subscription, Task};
-use http_client::http::{HeaderMap, HeaderValue};
-use http_client::{AsyncBody, HttpClient, HttpRequestExt, Method, Response, StatusCode};
+use anyhow::Result;
+use client::{Client, RefreshLlmTokenListener, UserStore, global_llm_token, zed_urls};
+use cloud_api_client::LlmApiToken;
+use cloud_api_types::OrganizationId;
+use cloud_api_types::Plan;
+use futures::StreamExt;
+use futures::future::BoxFuture;
+use gpui::AsyncApp;
+use gpui::{AnyElement, AnyView, App, Context, Entity, Subscription, Task};
use language_model::{
- ANTHROPIC_PROVIDER_ID, ANTHROPIC_PROVIDER_NAME, AuthenticateError, GOOGLE_PROVIDER_ID,
- GOOGLE_PROVIDER_NAME, IconOrSvg, LanguageModel, LanguageModelCacheConfiguration,
- LanguageModelCompletionError, LanguageModelCompletionEvent, LanguageModelEffortLevel,
- LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
- LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
- LanguageModelToolChoice, LanguageModelToolSchemaFormat, LlmApiToken, OPEN_AI_PROVIDER_ID,
- OPEN_AI_PROVIDER_NAME, PaymentRequiredError, RateLimiter, X_AI_PROVIDER_ID, X_AI_PROVIDER_NAME,
- ZED_CLOUD_PROVIDER_ID, ZED_CLOUD_PROVIDER_NAME,
+ AuthenticateError, IconOrSvg, LanguageModel, LanguageModelProvider, LanguageModelProviderId,
+ LanguageModelProviderName, LanguageModelProviderState, ZED_CLOUD_PROVIDER_ID,
+ ZED_CLOUD_PROVIDER_NAME,
};
+use language_models_cloud::{CloudLlmTokenProvider, CloudModelProvider};
use release_channel::AppVersion;
-use schemars::JsonSchema;
-use semver::Version;
-use serde::{Deserialize, Serialize, de::DeserializeOwned};
+
use settings::SettingsStore;
pub use settings::ZedDotDevAvailableModel as AvailableModel;
pub use settings::ZedDotDevAvailableProvider as AvailableProvider;
-use smol::io::{AsyncReadExt, BufReader};
-use std::collections::VecDeque;
-use std::pin::Pin;
-use std::str::FromStr;
use std::sync::Arc;
-use std::task::Poll;
-use std::time::Duration;
-use thiserror::Error;
use ui::{TintColor, prelude::*};
-use crate::provider::anthropic::{
- AnthropicEventMapper, count_anthropic_tokens_with_tiktoken, into_anthropic,
-};
-use crate::provider::google::{GoogleEventMapper, into_google};
-use crate::provider::open_ai::{
- OpenAiEventMapper, OpenAiResponseEventMapper, count_open_ai_tokens, into_open_ai,
- into_open_ai_response,
-};
-use crate::provider::x_ai::count_xai_tokens;
-
const PROVIDER_ID: LanguageModelProviderId = ZED_CLOUD_PROVIDER_ID;
const PROVIDER_NAME: LanguageModelProviderName = ZED_CLOUD_PROVIDER_NAME;
-#[derive(Default, Clone, Debug, PartialEq)]
-pub struct ZedDotDevSettings {
- pub available_models: Vec<AvailableModel>,
-}
-#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
-#[serde(tag = "type", rename_all = "lowercase")]
-pub enum ModelMode {
- #[default]
- Default,
- Thinking {
- /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
- budget_tokens: Option<u32>,
- },
+struct ClientTokenProvider {
+ client: Arc<Client>,
+ llm_api_token: LlmApiToken,
+ user_store: Entity<UserStore>,
}
-impl From<ModelMode> for AnthropicModelMode {
- fn from(value: ModelMode) -> Self {
- match value {
- ModelMode::Default => AnthropicModelMode::Default,
- ModelMode::Thinking { budget_tokens } => AnthropicModelMode::Thinking { budget_tokens },
- }
+impl CloudLlmTokenProvider for ClientTokenProvider {
+ type AuthContext = Option<OrganizationId>;
+
+ fn auth_context(&self, cx: &AsyncApp) -> Self::AuthContext {
+ self.user_store.read_with(cx, |user_store, _| {
+ user_store
+ .current_organization()
+ .map(|organization| organization.id.clone())
+ })
}
+
+ fn acquire_token(
+ &self,
+ organization_id: Self::AuthContext,
+ ) -> BoxFuture<'static, Result<String>> {
+ let client = self.client.clone();
+ let llm_api_token = self.llm_api_token.clone();
+ Box::pin(async move {
+ client
+ .acquire_llm_token(&llm_api_token, organization_id)
+ .await
+ })
+ }
+
+ fn refresh_token(
+ &self,
+ organization_id: Self::AuthContext,
+ ) -> BoxFuture<'static, Result<String>> {
+ let client = self.client.clone();
+ let llm_api_token = self.llm_api_token.clone();
+ Box::pin(async move {
+ client
+ .refresh_llm_token(&llm_api_token, organization_id)
+ .await
+ })
+ }
+}
+
+#[derive(Default, Clone, Debug, PartialEq)]
+pub struct ZedDotDevSettings {
+ pub available_models: Vec<AvailableModel>,
}
pub struct CloudLanguageModelProvider {
- client: Arc<Client>,
state: Entity<State>,
_maintain_client_status: Task<()>,
}
pub struct State {
client: Arc<Client>,
- llm_api_token: LlmApiToken,
user_store: Entity<UserStore>,
status: client::Status,
- models: Vec<Arc<cloud_llm_client::LanguageModel>>,
- default_model: Option<Arc<cloud_llm_client::LanguageModel>>,
- default_fast_model: Option<Arc<cloud_llm_client::LanguageModel>>,
- recommended_models: Vec<Arc<cloud_llm_client::LanguageModel>>,
+ provider: Entity<CloudModelProvider<ClientTokenProvider>>,
_user_store_subscription: Subscription,
_settings_subscription: Subscription,
_llm_token_subscription: Subscription,
+ _provider_subscription: Subscription,
}
impl State {
@@ -112,16 +98,26 @@ impl State {
cx: &mut Context<Self>,
) -> Self {
let refresh_llm_token_listener = RefreshLlmTokenListener::global(cx);
- let llm_api_token = global_llm_token(cx);
+ let token_provider = Arc::new(ClientTokenProvider {
+ client: client.clone(),
+ llm_api_token: global_llm_token(cx),
+ user_store: user_store.clone(),
+ });
+
+ let provider = cx.new(|cx| {
+ CloudModelProvider::new(
+ token_provider.clone(),
+ client.http_client(),
+ Some(AppVersion::global(cx)),
+ )
+ });
+
Self {
client: client.clone(),
- llm_api_token,
user_store: user_store.clone(),
status,
- models: Vec::new(),
- default_model: None,
- default_fast_model: None,
- recommended_models: Vec::new(),
+ _provider_subscription: cx.observe(&provider, |_, _, cx| cx.notify()),
+ provider,
_user_store_subscription: cx.subscribe(
&user_store,
move |this, _user_store, event, cx| match event {
@@ -131,19 +127,7 @@ impl State {
return;
}
- let client = this.client.clone();
- let llm_api_token = this.llm_api_token.clone();
- let organization_id = this
- .user_store
- .read(cx)
- .current_organization()
- .map(|organization| organization.id.clone());
- cx.spawn(async move |this, cx| {
- let response =
- Self::fetch_models(client, llm_api_token, organization_id).await?;
- this.update(cx, |this, cx| this.update_models(response, cx))
- })
- .detach_and_log_err(cx);
+ this.refresh_models(cx);
}
_ => {}
},
@@ -154,21 +138,7 @@ impl State {
_llm_token_subscription: cx.subscribe(
&refresh_llm_token_listener,
move |this, _listener, _event, cx| {
- let client = this.client.clone();
- let llm_api_token = this.llm_api_token.clone();
- let organization_id = this
- .user_store
- .read(cx)
- .current_organization()
- .map(|organization| organization.id.clone());
- cx.spawn(async move |this, cx| {
- let response =
- Self::fetch_models(client, llm_api_token, organization_id).await?;
- this.update(cx, |this, cx| {
- this.update_models(response, cx);
- })
- })
- .detach_and_log_err(cx);
+ this.refresh_models(cx);
},
),
}
@@ -186,74 +156,10 @@ impl State {
})
}
- fn update_models(&mut self, response: ListModelsResponse, cx: &mut Context<Self>) {
- let mut models = Vec::new();
-
- for model in response.models {
- models.push(Arc::new(model.clone()));
- }
-
- self.default_model = models
- .iter()
- .find(|model| {
- response
- .default_model
- .as_ref()
- .is_some_and(|default_model_id| &model.id == default_model_id)
- })
- .cloned();
- self.default_fast_model = models
- .iter()
- .find(|model| {
- response
- .default_fast_model
- .as_ref()
- .is_some_and(|default_fast_model_id| &model.id == default_fast_model_id)
- })
- .cloned();
- self.recommended_models = response
- .recommended_models
- .iter()
- .filter_map(|id| models.iter().find(|model| &model.id == id))
- .cloned()
- .collect();
- self.models = models;
- cx.notify();
- }
-
- async fn fetch_models(
- client: Arc<Client>,
- llm_api_token: LlmApiToken,
- organization_id: Option<OrganizationId>,
- ) -> Result<ListModelsResponse> {
- let http_client = &client.http_client();
- let token = client
- .acquire_llm_token(&llm_api_token, organization_id)
- .await?;
-
- let request = http_client::Request::builder()
- .method(Method::GET)
- .header(CLIENT_SUPPORTS_X_AI_HEADER_NAME, "true")
- .uri(http_client.build_zed_llm_url("/models", &[])?.as_ref())
- .header("Authorization", format!("Bearer {token}"))
- .body(AsyncBody::empty())?;
- let mut response = http_client
- .send(request)
- .await
- .context("failed to send list models request")?;
-
- if response.status().is_success() {
- let mut body = String::new();
- response.body_mut().read_to_string(&mut body).await?;
- Ok(serde_json::from_str(&body)?)
- } else {
- let mut body = String::new();
- response.body_mut().read_to_string(&mut body).await?;
- anyhow::bail!(
- "error listing models.\nStatus: {:?}\nBody: {body}",
- response.status(),
- );
- }
+ fn refresh_models(&mut self, cx: &mut Context<Self>) {
+ self.provider.update(cx, |provider, cx| {
+ provider.refresh_models(cx).detach_and_log_err(cx);
+ });
}
}
@@ -281,27 +187,10 @@ impl CloudLanguageModelProvider {
});
Self {
- client,
state,
_maintain_client_status: maintain_client_status,
}
}
-
- fn create_language_model(
- &self,
- model: Arc<cloud_llm_client::LanguageModel>,
- llm_api_token: LlmApiToken,
- user_store: Entity<UserStore>,
- ) -> Arc<dyn LanguageModel> {
- Arc::new(CloudLanguageModel {
- id: LanguageModelId(SharedString::from(model.id.0.clone())),
- model,
- llm_api_token,
- user_store,
- client: self.client.clone(),
- request_limiter: RateLimiter::new(4),
- })
- }
}
impl LanguageModelProviderState for CloudLanguageModelProvider {
@@ -327,45 +216,35 @@ impl LanguageModelProvider for CloudLanguageModelProvider {
fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
let state = self.state.read(cx);
- let default_model = state.default_model.clone()?;
- let llm_api_token = state.llm_api_token.clone();
- let user_store = state.user_store.clone();
- Some(self.create_language_model(default_model, llm_api_token, user_store))
+ let provider = state.provider.read(cx);
+ let model = provider.default_model()?;
+ Some(provider.create_model(model))
}
fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
let state = self.state.read(cx);
- let default_fast_model = state.default_fast_model.clone()?;
- let llm_api_token = state.llm_api_token.clone();
- let user_store = state.user_store.clone();
- Some(self.create_language_model(default_fast_model, llm_api_token, user_store))
+ let provider = state.provider.read(cx);
+ let model = provider.default_fast_model()?;
+ Some(provider.create_model(model))
}
fn recommended_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
let state = self.state.read(cx);
- let llm_api_token = state.llm_api_token.clone();
- let user_store = state.user_store.clone();
- state
- .recommended_models
+ let provider = state.provider.read(cx);
+ provider
+ .recommended_models()
.iter()
- .cloned()
- .map(|model| {
- self.create_language_model(model, llm_api_token.clone(), user_store.clone())
- })
+ .map(|model| provider.create_model(model))
.collect()
}
fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
let state = self.state.read(cx);
- let llm_api_token = state.llm_api_token.clone();
- let user_store = state.user_store.clone();
- state
- .models
+ let provider = state.provider.read(cx);
+ provider
+ .models()
.iter()
- .cloned()
- .map(|model| {
- self.create_language_model(model, llm_api_token.clone(), user_store.clone())
- })
+ .map(|model| provider.create_model(model))
.collect()
}
@@ -393,700 +272,6 @@ impl LanguageModelProvider for CloudLanguageModelProvider {
}
}
-pub struct CloudLanguageModel {
- id: LanguageModelId,
- model: Arc<cloud_llm_client::LanguageModel>,
- llm_api_token: LlmApiToken,
- user_store: Entity<UserStore>,
- client: Arc<Client>,
- request_limiter: RateLimiter,
-}
-
-struct PerformLlmCompletionResponse {
- response: Response<AsyncBody>,
- includes_status_messages: bool,
-}
-
-impl CloudLanguageModel {
- async fn perform_llm_completion(
- client: Arc<Client>,
- llm_api_token: LlmApiToken,
- organization_id: Option<OrganizationId>,
- app_version: Option<Version>,
- body: CompletionBody,
- ) -> Result<PerformLlmCompletionResponse> {
- let http_client = &client.http_client();
-
- let mut token = client
- .acquire_llm_token(&llm_api_token, organization_id.clone())
- .await?;
- let mut refreshed_token = false;
-
- loop {
- let request = http_client::Request::builder()
- .method(Method::POST)
- .uri(http_client.build_zed_llm_url("/completions", &[])?.as_ref())
- .when_some(app_version.as_ref(), |builder, app_version| {
- builder.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
- })
- .header("Content-Type", "application/json")
- .header("Authorization", format!("Bearer {token}"))
- .header(CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, "true")
- .header(CLIENT_SUPPORTS_STATUS_STREAM_ENDED_HEADER_NAME, "true")
- .body(serde_json::to_string(&body)?.into())?;
-
- let mut response = http_client.send(request).await?;
- let status = response.status();
- if status.is_success() {
- let includes_status_messages = response
- .headers()
- .get(SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME)
- .is_some();
-
- return Ok(PerformLlmCompletionResponse {
- response,
- includes_status_messages,
- });
- }
-
- if !refreshed_token && response.needs_llm_token_refresh() {
- token = client
- .refresh_llm_token(&llm_api_token, organization_id.clone())
- .await?;
- refreshed_token = true;
- continue;
- }
-
- if status == StatusCode::PAYMENT_REQUIRED {
- return Err(anyhow!(PaymentRequiredError));
- }
-
- let mut body = String::new();
- let headers = response.headers().clone();
- response.body_mut().read_to_string(&mut body).await?;
- return Err(anyhow!(ApiError {
- status,
- body,
- headers
- }));
- }
- }
-}
-
-#[derive(Debug, Error)]
-#[error("cloud language model request failed with status {status}: {body}")]
-struct ApiError {
- status: StatusCode,
- body: String,
- headers: HeaderMap<HeaderValue>,
-}
-
-/// Represents error responses from Zed's cloud API.
-///
-/// Example JSON for an upstream HTTP error:
-/// ```json
-/// {
-/// "code": "upstream_http_error",
-/// "message": "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout",
-/// "upstream_status": 503
-/// }
-/// ```
-#[derive(Debug, serde::Deserialize)]
-struct CloudApiError {
- code: String,
- message: String,
- #[serde(default)]
- #[serde(deserialize_with = "deserialize_optional_status_code")]
- upstream_status: Option<StatusCode>,
- #[serde(default)]
- retry_after: Option<f64>,
-}
-
-fn deserialize_optional_status_code<'de, D>(deserializer: D) -> Result<Option<StatusCode>, D::Error>
-where
- D: serde::Deserializer<'de>,
-{
- let opt: Option<u16> = Option::deserialize(deserializer)?;
- Ok(opt.and_then(|code| StatusCode::from_u16(code).ok()))
-}
-
-impl From<ApiError> for LanguageModelCompletionError {
- fn from(error: ApiError) -> Self {
- if let Ok(cloud_error) = serde_json::from_str::<CloudApiError>(&error.body) {
- if cloud_error.code.starts_with("upstream_http_") {
- let status = if let Some(status) = cloud_error.upstream_status {
- status
- } else if cloud_error.code.ends_with("_error") {
- error.status
- } else {
- // If there's a status code in the code string (e.g. "upstream_http_429")
- // then use that; otherwise, see if the JSON contains a status code.
- cloud_error
- .code
- .strip_prefix("upstream_http_")
- .and_then(|code_str| code_str.parse::<u16>().ok())
- .and_then(|code| StatusCode::from_u16(code).ok())
- .unwrap_or(error.status)
- };
-
- return LanguageModelCompletionError::UpstreamProviderError {
- message: cloud_error.message,
- status,
- retry_after: cloud_error.retry_after.map(Duration::from_secs_f64),
- };
- }
-
- return LanguageModelCompletionError::from_http_status(
- PROVIDER_NAME,
- error.status,
- cloud_error.message,
- None,
- );
- }
-
- let retry_after = None;
- LanguageModelCompletionError::from_http_status(
- PROVIDER_NAME,
- error.status,
- error.body,
- retry_after,
- )
- }
-}
-
-impl LanguageModel for CloudLanguageModel {
- fn id(&self) -> LanguageModelId {
- self.id.clone()
- }
-
- fn name(&self) -> LanguageModelName {
- LanguageModelName::from(self.model.display_name.clone())
- }
-
- fn provider_id(&self) -> LanguageModelProviderId {
- PROVIDER_ID
- }
-
- fn provider_name(&self) -> LanguageModelProviderName {
- PROVIDER_NAME
- }
-
- fn upstream_provider_id(&self) -> LanguageModelProviderId {
- use cloud_llm_client::LanguageModelProvider::*;
- match self.model.provider {
- Anthropic => ANTHROPIC_PROVIDER_ID,
- OpenAi => OPEN_AI_PROVIDER_ID,
- Google => GOOGLE_PROVIDER_ID,
- XAi => X_AI_PROVIDER_ID,
- }
- }
-
- fn upstream_provider_name(&self) -> LanguageModelProviderName {
- use cloud_llm_client::LanguageModelProvider::*;
- match self.model.provider {
- Anthropic => ANTHROPIC_PROVIDER_NAME,
- OpenAi => OPEN_AI_PROVIDER_NAME,
- Google => GOOGLE_PROVIDER_NAME,
- XAi => X_AI_PROVIDER_NAME,
- }
- }
-
- fn is_latest(&self) -> bool {
- self.model.is_latest
- }
-
- fn supports_tools(&self) -> bool {
- self.model.supports_tools
- }
-
- fn supports_images(&self) -> bool {
- self.model.supports_images
- }
-
- fn supports_thinking(&self) -> bool {
- self.model.supports_thinking
- }
-
- fn supports_fast_mode(&self) -> bool {
- self.model.supports_fast_mode
- }
-
- fn supported_effort_levels(&self) -> Vec<LanguageModelEffortLevel> {
- self.model
- .supported_effort_levels
- .iter()
- .map(|effort_level| LanguageModelEffortLevel {
- name: effort_level.name.clone().into(),
- value: effort_level.value.clone().into(),
- is_default: effort_level.is_default.unwrap_or(false),
- })
- .collect()
- }
-
- fn supports_streaming_tools(&self) -> bool {
- self.model.supports_streaming_tools
- }
-
- fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
- match choice {
- LanguageModelToolChoice::Auto
- | LanguageModelToolChoice::Any
- | LanguageModelToolChoice::None => true,
- }
- }
-
- fn supports_split_token_display(&self) -> bool {
- use cloud_llm_client::LanguageModelProvider::*;
- matches!(self.model.provider, OpenAi | XAi)
- }
-
- fn telemetry_id(&self) -> String {
- format!("zed.dev/{}", self.model.id)
- }
-
- fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
- match self.model.provider {
- cloud_llm_client::LanguageModelProvider::Anthropic
- | cloud_llm_client::LanguageModelProvider::OpenAi => {
- LanguageModelToolSchemaFormat::JsonSchema
- }
- cloud_llm_client::LanguageModelProvider::Google
- | cloud_llm_client::LanguageModelProvider::XAi => {
- LanguageModelToolSchemaFormat::JsonSchemaSubset
- }
- }
- }
-
- fn max_token_count(&self) -> u64 {
- self.model.max_token_count as u64
- }
-
- fn max_output_tokens(&self) -> Option<u64> {
- Some(self.model.max_output_tokens as u64)
- }
-
- fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
- match &self.model.provider {
- cloud_llm_client::LanguageModelProvider::Anthropic => {
- Some(LanguageModelCacheConfiguration {
- min_total_token: 2_048,
- should_speculate: true,
- max_cache_anchors: 4,
- })
- }
- cloud_llm_client::LanguageModelProvider::OpenAi
- | cloud_llm_client::LanguageModelProvider::XAi
- | cloud_llm_client::LanguageModelProvider::Google => None,
- }
- }
-
- fn count_tokens(
- &self,
- request: LanguageModelRequest,
- cx: &App,
- ) -> BoxFuture<'static, Result<u64>> {
- match self.model.provider {
- cloud_llm_client::LanguageModelProvider::Anthropic => cx
- .background_spawn(async move { count_anthropic_tokens_with_tiktoken(request) })
- .boxed(),
- cloud_llm_client::LanguageModelProvider::OpenAi => {
- let model = match open_ai::Model::from_id(&self.model.id.0) {
- Ok(model) => model,
- Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
- };
- count_open_ai_tokens(request, model, cx)
- }
- cloud_llm_client::LanguageModelProvider::XAi => {
- let model = match x_ai::Model::from_id(&self.model.id.0) {
- Ok(model) => model,
- Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
- };
- count_xai_tokens(request, model, cx)
- }
- cloud_llm_client::LanguageModelProvider::Google => {
- let client = self.client.clone();
- let llm_api_token = self.llm_api_token.clone();
- let organization_id = self
- .user_store
- .read(cx)
- .current_organization()
- .map(|organization| organization.id.clone());
- let model_id = self.model.id.to_string();
- let generate_content_request =
- into_google(request, model_id.clone(), GoogleModelMode::Default);
- async move {
- let http_client = &client.http_client();
- let token = client
- .acquire_llm_token(&llm_api_token, organization_id)
- .await?;
-
- let request_body = CountTokensBody {
- provider: cloud_llm_client::LanguageModelProvider::Google,
- model: model_id,
- provider_request: serde_json::to_value(&google_ai::CountTokensRequest {
- generate_content_request,
- })?,
- };
- let request = http_client::Request::builder()
- .method(Method::POST)
- .uri(
- http_client
- .build_zed_llm_url("/count_tokens", &[])?
- .as_ref(),
- )
- .header("Content-Type", "application/json")
- .header("Authorization", format!("Bearer {token}"))
- .body(serde_json::to_string(&request_body)?.into())?;
- let mut response = http_client.send(request).await?;
- let status = response.status();
- let headers = response.headers().clone();
- let mut response_body = String::new();
- response
- .body_mut()
- .read_to_string(&mut response_body)
- .await?;
-
- if status.is_success() {
- let response_body: CountTokensResponse =
- serde_json::from_str(&response_body)?;
-
- Ok(response_body.tokens as u64)
- } else {
- Err(anyhow!(ApiError {
- status,
- body: response_body,
- headers
- }))
- }
- }
- .boxed()
- }
- }
- }
-
- fn stream_completion(
- &self,
- request: LanguageModelRequest,
- cx: &AsyncApp,
- ) -> BoxFuture<
- 'static,
- Result<
- BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
- LanguageModelCompletionError,
- >,
- > {
- let thread_id = request.thread_id.clone();
- let prompt_id = request.prompt_id.clone();
- let app_version = Some(cx.update(|cx| AppVersion::global(cx)));
- let user_store = self.user_store.clone();
- let organization_id = cx.update(|cx| {
- user_store
- .read(cx)
- .current_organization()
- .map(|organization| organization.id.clone())
- });
- let thinking_allowed = request.thinking_allowed;
- let enable_thinking = thinking_allowed && self.model.supports_thinking;
- let provider_name = provider_name(&self.model.provider);
- match self.model.provider {
- cloud_llm_client::LanguageModelProvider::Anthropic => {
- let effort = request
- .thinking_effort
- .as_ref()
- .and_then(|effort| anthropic::Effort::from_str(effort).ok());
-
- let mut request = into_anthropic(
- request,
- self.model.id.to_string(),
- 1.0,
- self.model.max_output_tokens as u64,
- if enable_thinking {
- AnthropicModelMode::Thinking {
- budget_tokens: Some(4_096),
- }
- } else {
- AnthropicModelMode::Default
- },
- );
-
- if enable_thinking && effort.is_some() {
- request.thinking = Some(anthropic::Thinking::Adaptive);
- request.output_config = Some(anthropic::OutputConfig { effort });
- }
-
- let client = self.client.clone();
- let llm_api_token = self.llm_api_token.clone();
- let organization_id = organization_id.clone();
- let future = self.request_limiter.stream(async move {
- let PerformLlmCompletionResponse {
- response,
- includes_status_messages,
- } = Self::perform_llm_completion(
- client.clone(),
- llm_api_token,
- organization_id,
- app_version,
- CompletionBody {
- thread_id,
- prompt_id,
- provider: cloud_llm_client::LanguageModelProvider::Anthropic,
- model: request.model.clone(),
- provider_request: serde_json::to_value(&request)
- .map_err(|e| anyhow!(e))?,
- },
- )
- .await
- .map_err(|err| match err.downcast::<ApiError>() {
- Ok(api_err) => anyhow!(LanguageModelCompletionError::from(api_err)),
- Err(err) => anyhow!(err),
- })?;
-
- let mut mapper = AnthropicEventMapper::new();
- Ok(map_cloud_completion_events(
- Box::pin(response_lines(response, includes_status_messages)),
- &provider_name,
- move |event| mapper.map_event(event),
- ))
- });
- async move { Ok(future.await?.boxed()) }.boxed()
- }
- cloud_llm_client::LanguageModelProvider::OpenAi => {
- let client = self.client.clone();
- let llm_api_token = self.llm_api_token.clone();
- let organization_id = organization_id.clone();
- let effort = request
- .thinking_effort
- .as_ref()
- .and_then(|effort| open_ai::ReasoningEffort::from_str(effort).ok());
-
- let mut request = into_open_ai_response(
- request,
- &self.model.id.0,
- self.model.supports_parallel_tool_calls,
- true,
- None,
- None,
- );
-
- if enable_thinking && let Some(effort) = effort {
- request.reasoning = Some(open_ai::responses::ReasoningConfig {
- effort,
- summary: Some(open_ai::responses::ReasoningSummaryMode::Auto),
- });
- }
-
- let future = self.request_limiter.stream(async move {
- let PerformLlmCompletionResponse {
- response,
- includes_status_messages,
- } = Self::perform_llm_completion(
- client.clone(),
- llm_api_token,
- organization_id,
- app_version,
- CompletionBody {
- thread_id,
- prompt_id,
- provider: cloud_llm_client::LanguageModelProvider::OpenAi,
- model: request.model.clone(),
- provider_request: serde_json::to_value(&request)
- .map_err(|e| anyhow!(e))?,
- },
- )
- .await?;
-
- let mut mapper = OpenAiResponseEventMapper::new();
- Ok(map_cloud_completion_events(
- Box::pin(response_lines(response, includes_status_messages)),
- &provider_name,
- move |event| mapper.map_event(event),
- ))
- });
- async move { Ok(future.await?.boxed()) }.boxed()
- }
- cloud_llm_client::LanguageModelProvider::XAi => {
- let client = self.client.clone();
- let request = into_open_ai(
- request,
- &self.model.id.0,
- self.model.supports_parallel_tool_calls,
- false,
- None,
- None,
- );
- let llm_api_token = self.llm_api_token.clone();
- let organization_id = organization_id.clone();
- let future = self.request_limiter.stream(async move {
- let PerformLlmCompletionResponse {
- response,
- includes_status_messages,
- } = Self::perform_llm_completion(
- client.clone(),
- llm_api_token,
- organization_id,
- app_version,
- CompletionBody {
- thread_id,
- prompt_id,
- provider: cloud_llm_client::LanguageModelProvider::XAi,
- model: request.model.clone(),
- provider_request: serde_json::to_value(&request)
- .map_err(|e| anyhow!(e))?,
- },
- )
- .await?;
-
- let mut mapper = OpenAiEventMapper::new();
- Ok(map_cloud_completion_events(
- Box::pin(response_lines(response, includes_status_messages)),
- &provider_name,
- move |event| mapper.map_event(event),
- ))
- });
- async move { Ok(future.await?.boxed()) }.boxed()
- }
- cloud_llm_client::LanguageModelProvider::Google => {
- let client = self.client.clone();
- let request =
- into_google(request, self.model.id.to_string(), GoogleModelMode::Default);
- let llm_api_token = self.llm_api_token.clone();
- let future = self.request_limiter.stream(async move {
- let PerformLlmCompletionResponse {
- response,
- includes_status_messages,
- } = Self::perform_llm_completion(
- client.clone(),
- llm_api_token,
- organization_id,
- app_version,
- CompletionBody {
- thread_id,
- prompt_id,
- provider: cloud_llm_client::LanguageModelProvider::Google,
- model: request.model.model_id.clone(),
- provider_request: serde_json::to_value(&request)
- .map_err(|e| anyhow!(e))?,
- },
- )
- .await?;
-
- let mut mapper = GoogleEventMapper::new();
- Ok(map_cloud_completion_events(
- Box::pin(response_lines(response, includes_status_messages)),
- &provider_name,
- move |event| mapper.map_event(event),
- ))
- });
- async move { Ok(future.await?.boxed()) }.boxed()
- }
- }
- }
-}
-
-fn map_cloud_completion_events<T, F>(
- stream: Pin<Box<dyn Stream<Item = Result<CompletionEvent<T>>> + Send>>,
- provider: &LanguageModelProviderName,
- mut map_callback: F,
-) -> BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
-where
- T: DeserializeOwned + 'static,
- F: FnMut(T) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
- + Send
- + 'static,
-{
- let provider = provider.clone();
- let mut stream = stream.fuse();
-
- let mut saw_stream_ended = false;
-
- let mut done = false;
- let mut pending = VecDeque::new();
-
- stream::poll_fn(move |cx| {
- loop {
- if let Some(item) = pending.pop_front() {
- return Poll::Ready(Some(item));
- }
-
- if done {
- return Poll::Ready(None);
- }
-
- match stream.poll_next_unpin(cx) {
- Poll::Ready(Some(event)) => {
- let items = match event {
- Err(error) => {
- vec![Err(LanguageModelCompletionError::from(error))]
- }
- Ok(CompletionEvent::Status(CompletionRequestStatus::StreamEnded)) => {
- saw_stream_ended = true;
- vec![]
- }
- Ok(CompletionEvent::Status(status)) => {
- LanguageModelCompletionEvent::from_completion_request_status(
- status,
- provider.clone(),
- )
- .transpose()
- .map(|event| vec![event])
- .unwrap_or_default()
- }
- Ok(CompletionEvent::Event(event)) => map_callback(event),
- };
- pending.extend(items);
- }
- Poll::Ready(None) => {
- done = true;
-
- if !saw_stream_ended {
- return Poll::Ready(Some(Err(
- LanguageModelCompletionError::StreamEndedUnexpectedly {
- provider: provider.clone(),
- },
- )));
- }
- }
- Poll::Pending => return Poll::Pending,
- }
- }
- })
- .boxed()
-}
-
-fn provider_name(provider: &cloud_llm_client::LanguageModelProvider) -> LanguageModelProviderName {
- match provider {
- cloud_llm_client::LanguageModelProvider::Anthropic => ANTHROPIC_PROVIDER_NAME,
- cloud_llm_client::LanguageModelProvider::OpenAi => OPEN_AI_PROVIDER_NAME,
- cloud_llm_client::LanguageModelProvider::Google => GOOGLE_PROVIDER_NAME,
- cloud_llm_client::LanguageModelProvider::XAi => X_AI_PROVIDER_NAME,
- }
-}
-
-fn response_lines<T: DeserializeOwned>(
- response: Response<AsyncBody>,
- includes_status_messages: bool,
-) -> impl Stream<Item = Result<CompletionEvent<T>>> {
- futures::stream::try_unfold(
- (String::new(), BufReader::new(response.into_body())),
- move |(mut line, mut body)| async move {
- match body.read_line(&mut line).await {
- Ok(0) => Ok(None),
- Ok(_) => {
- let event = if includes_status_messages {
- serde_json::from_str::<CompletionEvent<T>>(&line)?
- } else {
- CompletionEvent::Event(serde_json::from_str::<T>(&line)?)
- };
-
- line.clear();
- Ok(Some((event, (line, body))))
- }
- Err(e) => Err(e.into()),
- }
- },
- )
-}
-
#[derive(IntoElement, RegisterComponent)]
struct ZedAiConfiguration {
is_connected: bool,
@@ -32,7 +32,7 @@ use ui::prelude::*;
use util::debug_panic;
use crate::provider::anthropic::{AnthropicEventMapper, into_anthropic};
-use crate::provider::util::{fix_streamed_json, parse_tool_arguments};
+use language_model::util::{fix_streamed_json, parse_tool_arguments};
const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("copilot_chat");
const PROVIDER_NAME: LanguageModelProviderName =
@@ -268,15 +268,15 @@ impl LanguageModel for CopilotChatLanguageModel {
levels
.iter()
.map(|level| {
- let name: SharedString = match level.as_str() {
+ let name = match level.as_str() {
"low" => "Low".into(),
"medium" => "Medium".into(),
"high" => "High".into(),
- _ => SharedString::from(level.clone()),
+ _ => language_model::SharedString::from(level.clone()),
};
LanguageModelEffortLevel {
name,
- value: SharedString::from(level.clone()),
+ value: language_model::SharedString::from(level.clone()),
is_default: level == "high",
}
})
@@ -23,7 +23,7 @@ use ui::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
use ui_input::InputField;
use util::ResultExt;
-use crate::provider::util::{fix_streamed_json, parse_tool_arguments};
+use language_model::util::{fix_streamed_json, parse_tool_arguments};
const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("deepseek");
const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("DeepSeek");
@@ -1,32 +1,25 @@
use anyhow::{Context as _, Result};
use collections::BTreeMap;
use credentials_provider::CredentialsProvider;
-use futures::{FutureExt, Stream, StreamExt, future::BoxFuture};
-use google_ai::{
- FunctionDeclaration, GenerateContentResponse, GoogleModelMode, Part, SystemInstruction,
- ThinkingConfig, UsageMetadata,
-};
+use futures::{FutureExt, StreamExt, future::BoxFuture};
+pub use google_ai::completion::{GoogleEventMapper, count_google_tokens, into_google};
+use google_ai::{GenerateContentResponse, GoogleModelMode};
use gpui::{AnyView, App, AsyncApp, Context, Entity, SharedString, Task, Window};
use http_client::HttpClient;
use language_model::{
AuthenticateError, ConfigurationViewTargetAgent, EnvVar, LanguageModelCompletionError,
LanguageModelCompletionEvent, LanguageModelToolChoice, LanguageModelToolSchemaFormat,
- LanguageModelToolUse, LanguageModelToolUseId, MessageContent, StopReason,
};
use language_model::{
GOOGLE_PROVIDER_ID, GOOGLE_PROVIDER_NAME, IconOrSvg, LanguageModel, LanguageModelId,
LanguageModelName, LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
- LanguageModelProviderState, LanguageModelRequest, RateLimiter, Role,
+ LanguageModelProviderState, LanguageModelRequest, RateLimiter,
};
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
pub use settings::GoogleAvailableModel as AvailableModel;
use settings::{Settings, SettingsStore};
-use std::pin::Pin;
-use std::sync::{
- Arc, LazyLock,
- atomic::{self, AtomicU64},
-};
+use std::sync::{Arc, LazyLock};
use strum::IntoEnumIterator;
use ui::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
use ui_input::InputField;
@@ -394,369 +387,6 @@ impl LanguageModel for GoogleLanguageModel {
}
}
-pub fn into_google(
- mut request: LanguageModelRequest,
- model_id: String,
- mode: GoogleModelMode,
-) -> google_ai::GenerateContentRequest {
- fn map_content(content: Vec<MessageContent>) -> Vec<Part> {
- content
- .into_iter()
- .flat_map(|content| match content {
- language_model::MessageContent::Text(text) => {
- if !text.is_empty() {
- vec![Part::TextPart(google_ai::TextPart { text })]
- } else {
- vec![]
- }
- }
- language_model::MessageContent::Thinking {
- text: _,
- signature: Some(signature),
- } => {
- if !signature.is_empty() {
- vec![Part::ThoughtPart(google_ai::ThoughtPart {
- thought: true,
- thought_signature: signature,
- })]
- } else {
- vec![]
- }
- }
- language_model::MessageContent::Thinking { .. } => {
- vec![]
- }
- language_model::MessageContent::RedactedThinking(_) => vec![],
- language_model::MessageContent::Image(image) => {
- vec![Part::InlineDataPart(google_ai::InlineDataPart {
- inline_data: google_ai::GenerativeContentBlob {
- mime_type: "image/png".to_string(),
- data: image.source.to_string(),
- },
- })]
- }
- language_model::MessageContent::ToolUse(tool_use) => {
- // Normalize empty string signatures to None
- let thought_signature = tool_use.thought_signature.filter(|s| !s.is_empty());
-
- vec![Part::FunctionCallPart(google_ai::FunctionCallPart {
- function_call: google_ai::FunctionCall {
- name: tool_use.name.to_string(),
- args: tool_use.input,
- },
- thought_signature,
- })]
- }
- language_model::MessageContent::ToolResult(tool_result) => {
- match tool_result.content {
- language_model::LanguageModelToolResultContent::Text(text) => {
- vec![Part::FunctionResponsePart(
- google_ai::FunctionResponsePart {
- function_response: google_ai::FunctionResponse {
- name: tool_result.tool_name.to_string(),
- // The API expects a valid JSON object
- response: serde_json::json!({
- "output": text
- }),
- },
- },
- )]
- }
- language_model::LanguageModelToolResultContent::Image(image) => {
- vec![
- Part::FunctionResponsePart(google_ai::FunctionResponsePart {
- function_response: google_ai::FunctionResponse {
- name: tool_result.tool_name.to_string(),
- // The API expects a valid JSON object
- response: serde_json::json!({
- "output": "Tool responded with an image"
- }),
- },
- }),
- Part::InlineDataPart(google_ai::InlineDataPart {
- inline_data: google_ai::GenerativeContentBlob {
- mime_type: "image/png".to_string(),
- data: image.source.to_string(),
- },
- }),
- ]
- }
- }
- }
- })
- .collect()
- }
-
- let system_instructions = if request
- .messages
- .first()
- .is_some_and(|msg| matches!(msg.role, Role::System))
- {
- let message = request.messages.remove(0);
- Some(SystemInstruction {
- parts: map_content(message.content),
- })
- } else {
- None
- };
-
- google_ai::GenerateContentRequest {
- model: google_ai::ModelName { model_id },
- system_instruction: system_instructions,
- contents: request
- .messages
- .into_iter()
- .filter_map(|message| {
- let parts = map_content(message.content);
- if parts.is_empty() {
- None
- } else {
- Some(google_ai::Content {
- parts,
- role: match message.role {
- Role::User => google_ai::Role::User,
- Role::Assistant => google_ai::Role::Model,
- Role::System => google_ai::Role::User, // Google AI doesn't have a system role
- },
- })
- }
- })
- .collect(),
- generation_config: Some(google_ai::GenerationConfig {
- candidate_count: Some(1),
- stop_sequences: Some(request.stop),
- max_output_tokens: None,
- temperature: request.temperature.map(|t| t as f64).or(Some(1.0)),
- thinking_config: match (request.thinking_allowed, mode) {
- (true, GoogleModelMode::Thinking { budget_tokens }) => {
- budget_tokens.map(|thinking_budget| ThinkingConfig { thinking_budget })
- }
- _ => None,
- },
- top_p: None,
- top_k: None,
- }),
- safety_settings: None,
- tools: (!request.tools.is_empty()).then(|| {
- vec![google_ai::Tool {
- function_declarations: request
- .tools
- .into_iter()
- .map(|tool| FunctionDeclaration {
- name: tool.name,
- description: tool.description,
- parameters: tool.input_schema,
- })
- .collect(),
- }]
- }),
- tool_config: request.tool_choice.map(|choice| google_ai::ToolConfig {
- function_calling_config: google_ai::FunctionCallingConfig {
- mode: match choice {
- LanguageModelToolChoice::Auto => google_ai::FunctionCallingMode::Auto,
- LanguageModelToolChoice::Any => google_ai::FunctionCallingMode::Any,
- LanguageModelToolChoice::None => google_ai::FunctionCallingMode::None,
- },
- allowed_function_names: None,
- },
- }),
- }
-}
-
-pub struct GoogleEventMapper {
- usage: UsageMetadata,
- stop_reason: StopReason,
-}
-
-impl GoogleEventMapper {
- pub fn new() -> Self {
- Self {
- usage: UsageMetadata::default(),
- stop_reason: StopReason::EndTurn,
- }
- }
-
- pub fn map_stream(
- mut self,
- events: Pin<Box<dyn Send + Stream<Item = Result<GenerateContentResponse>>>>,
- ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
- {
- events
- .map(Some)
- .chain(futures::stream::once(async { None }))
- .flat_map(move |event| {
- futures::stream::iter(match event {
- Some(Ok(event)) => self.map_event(event),
- Some(Err(error)) => {
- vec![Err(LanguageModelCompletionError::from(error))]
- }
- None => vec![Ok(LanguageModelCompletionEvent::Stop(self.stop_reason))],
- })
- })
- }
-
- pub fn map_event(
- &mut self,
- event: GenerateContentResponse,
- ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
- static TOOL_CALL_COUNTER: AtomicU64 = AtomicU64::new(0);
-
- let mut events: Vec<_> = Vec::new();
- let mut wants_to_use_tool = false;
- if let Some(usage_metadata) = event.usage_metadata {
- update_usage(&mut self.usage, &usage_metadata);
- events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
- convert_usage(&self.usage),
- )))
- }
-
- if let Some(prompt_feedback) = event.prompt_feedback
- && let Some(block_reason) = prompt_feedback.block_reason.as_deref()
- {
- self.stop_reason = match block_reason {
- "SAFETY" | "OTHER" | "BLOCKLIST" | "PROHIBITED_CONTENT" | "IMAGE_SAFETY" => {
- StopReason::Refusal
- }
- _ => {
- log::error!("Unexpected Google block_reason: {block_reason}");
- StopReason::Refusal
- }
- };
- events.push(Ok(LanguageModelCompletionEvent::Stop(self.stop_reason)));
-
- return events;
- }
-
- if let Some(candidates) = event.candidates {
- for candidate in candidates {
- if let Some(finish_reason) = candidate.finish_reason.as_deref() {
- self.stop_reason = match finish_reason {
- "STOP" => StopReason::EndTurn,
- "MAX_TOKENS" => StopReason::MaxTokens,
- _ => {
- log::error!("Unexpected google finish_reason: {finish_reason}");
- StopReason::EndTurn
- }
- };
- }
- candidate
- .content
- .parts
- .into_iter()
- .for_each(|part| match part {
- Part::TextPart(text_part) => {
- events.push(Ok(LanguageModelCompletionEvent::Text(text_part.text)))
- }
- Part::InlineDataPart(_) => {}
- Part::FunctionCallPart(function_call_part) => {
- wants_to_use_tool = true;
- let name: Arc<str> = function_call_part.function_call.name.into();
- let next_tool_id =
- TOOL_CALL_COUNTER.fetch_add(1, atomic::Ordering::SeqCst);
- let id: LanguageModelToolUseId =
- format!("{}-{}", name, next_tool_id).into();
-
- // Normalize empty string signatures to None
- let thought_signature = function_call_part
- .thought_signature
- .filter(|s| !s.is_empty());
-
- events.push(Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id,
- name,
- is_input_complete: true,
- raw_input: function_call_part.function_call.args.to_string(),
- input: function_call_part.function_call.args,
- thought_signature,
- },
- )));
- }
- Part::FunctionResponsePart(_) => {}
- Part::ThoughtPart(part) => {
- events.push(Ok(LanguageModelCompletionEvent::Thinking {
- text: "(Encrypted thought)".to_string(), // TODO: Can we populate this from thought summaries?
- signature: Some(part.thought_signature),
- }));
- }
- });
- }
- }
-
- // Even when Gemini wants to use a Tool, the API
- // responds with `finish_reason: STOP`
- if wants_to_use_tool {
- self.stop_reason = StopReason::ToolUse;
- events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
- }
- events
- }
-}
-
-pub fn count_google_tokens(
- request: LanguageModelRequest,
- cx: &App,
-) -> BoxFuture<'static, Result<u64>> {
- // We couldn't use the GoogleLanguageModelProvider to count tokens because the github copilot doesn't have the access to google_ai directly.
- // So we have to use tokenizer from tiktoken_rs to count tokens.
- cx.background_spawn(async move {
- let messages = request
- .messages
- .into_iter()
- .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
- role: match message.role {
- Role::User => "user".into(),
- Role::Assistant => "assistant".into(),
- Role::System => "system".into(),
- },
- content: Some(message.string_contents()),
- name: None,
- function_call: None,
- })
- .collect::<Vec<_>>();
-
- // Tiktoken doesn't yet support these models, so we manually use the
- // same tokenizer as GPT-4.
- tiktoken_rs::num_tokens_from_messages("gpt-4", &messages).map(|tokens| tokens as u64)
- })
- .boxed()
-}
-
-fn update_usage(usage: &mut UsageMetadata, new: &UsageMetadata) {
- if let Some(prompt_token_count) = new.prompt_token_count {
- usage.prompt_token_count = Some(prompt_token_count);
- }
- if let Some(cached_content_token_count) = new.cached_content_token_count {
- usage.cached_content_token_count = Some(cached_content_token_count);
- }
- if let Some(candidates_token_count) = new.candidates_token_count {
- usage.candidates_token_count = Some(candidates_token_count);
- }
- if let Some(tool_use_prompt_token_count) = new.tool_use_prompt_token_count {
- usage.tool_use_prompt_token_count = Some(tool_use_prompt_token_count);
- }
- if let Some(thoughts_token_count) = new.thoughts_token_count {
- usage.thoughts_token_count = Some(thoughts_token_count);
- }
- if let Some(total_token_count) = new.total_token_count {
- usage.total_token_count = Some(total_token_count);
- }
-}
-
-fn convert_usage(usage: &UsageMetadata) -> language_model::TokenUsage {
- let prompt_tokens = usage.prompt_token_count.unwrap_or(0);
- let cached_tokens = usage.cached_content_token_count.unwrap_or(0);
- let input_tokens = prompt_tokens - cached_tokens;
- let output_tokens = usage.candidates_token_count.unwrap_or(0);
-
- language_model::TokenUsage {
- input_tokens,
- output_tokens,
- cache_read_input_tokens: cached_tokens,
- cache_creation_input_tokens: 0,
- }
-}
-
struct ConfigurationView {
api_key_editor: Entity<InputField>,
state: Entity<State>,
@@ -895,428 +525,3 @@ impl Render for ConfigurationView {
}
}
}
-
-#[cfg(test)]
-mod tests {
- use super::*;
- use google_ai::{
- Content, FunctionCall, FunctionCallPart, GenerateContentCandidate, GenerateContentResponse,
- Part, Role as GoogleRole, TextPart,
- };
- use language_model::{LanguageModelToolUseId, MessageContent, Role};
- use serde_json::json;
-
- #[test]
- fn test_function_call_with_signature_creates_tool_use_with_signature() {
- let mut mapper = GoogleEventMapper::new();
-
- let response = GenerateContentResponse {
- candidates: Some(vec![GenerateContentCandidate {
- index: Some(0),
- content: Content {
- parts: vec![Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "test_function".to_string(),
- args: json!({"arg": "value"}),
- },
- thought_signature: Some("test_signature_123".to_string()),
- })],
- role: GoogleRole::Model,
- },
- finish_reason: None,
- finish_message: None,
- safety_ratings: None,
- citation_metadata: None,
- }]),
- prompt_feedback: None,
- usage_metadata: None,
- };
-
- let events = mapper.map_event(response);
-
- assert_eq!(events.len(), 2); // ToolUse event + Stop event
-
- if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
- assert_eq!(tool_use.name.as_ref(), "test_function");
- assert_eq!(
- tool_use.thought_signature.as_deref(),
- Some("test_signature_123")
- );
- } else {
- panic!("Expected ToolUse event");
- }
- }
-
- #[test]
- fn test_function_call_without_signature_has_none() {
- let mut mapper = GoogleEventMapper::new();
-
- let response = GenerateContentResponse {
- candidates: Some(vec![GenerateContentCandidate {
- index: Some(0),
- content: Content {
- parts: vec![Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "test_function".to_string(),
- args: json!({"arg": "value"}),
- },
- thought_signature: None,
- })],
- role: GoogleRole::Model,
- },
- finish_reason: None,
- finish_message: None,
- safety_ratings: None,
- citation_metadata: None,
- }]),
- prompt_feedback: None,
- usage_metadata: None,
- };
-
- let events = mapper.map_event(response);
-
- if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
- assert_eq!(tool_use.thought_signature, None);
- } else {
- panic!("Expected ToolUse event");
- }
- }
-
- #[test]
- fn test_empty_string_signature_normalized_to_none() {
- let mut mapper = GoogleEventMapper::new();
-
- let response = GenerateContentResponse {
- candidates: Some(vec![GenerateContentCandidate {
- index: Some(0),
- content: Content {
- parts: vec![Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "test_function".to_string(),
- args: json!({"arg": "value"}),
- },
- thought_signature: Some("".to_string()),
- })],
- role: GoogleRole::Model,
- },
- finish_reason: None,
- finish_message: None,
- safety_ratings: None,
- citation_metadata: None,
- }]),
- prompt_feedback: None,
- usage_metadata: None,
- };
-
- let events = mapper.map_event(response);
-
- if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
- assert_eq!(tool_use.thought_signature, None);
- } else {
- panic!("Expected ToolUse event");
- }
- }
-
- #[test]
- fn test_parallel_function_calls_preserve_signatures() {
- let mut mapper = GoogleEventMapper::new();
-
- let response = GenerateContentResponse {
- candidates: Some(vec![GenerateContentCandidate {
- index: Some(0),
- content: Content {
- parts: vec![
- Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "function_1".to_string(),
- args: json!({"arg": "value1"}),
- },
- thought_signature: Some("signature_1".to_string()),
- }),
- Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "function_2".to_string(),
- args: json!({"arg": "value2"}),
- },
- thought_signature: None,
- }),
- ],
- role: GoogleRole::Model,
- },
- finish_reason: None,
- finish_message: None,
- safety_ratings: None,
- citation_metadata: None,
- }]),
- prompt_feedback: None,
- usage_metadata: None,
- };
-
- let events = mapper.map_event(response);
-
- assert_eq!(events.len(), 3); // 2 ToolUse events + Stop event
-
- if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
- assert_eq!(tool_use.name.as_ref(), "function_1");
- assert_eq!(tool_use.thought_signature.as_deref(), Some("signature_1"));
- } else {
- panic!("Expected ToolUse event for function_1");
- }
-
- if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[1] {
- assert_eq!(tool_use.name.as_ref(), "function_2");
- assert_eq!(tool_use.thought_signature, None);
- } else {
- panic!("Expected ToolUse event for function_2");
- }
- }
-
- #[test]
- fn test_tool_use_with_signature_converts_to_function_call_part() {
- let tool_use = language_model::LanguageModelToolUse {
- id: LanguageModelToolUseId::from("test_id"),
- name: "test_function".into(),
- raw_input: json!({"arg": "value"}).to_string(),
- input: json!({"arg": "value"}),
- is_input_complete: true,
- thought_signature: Some("test_signature_456".to_string()),
- };
-
- let request = super::into_google(
- LanguageModelRequest {
- messages: vec![language_model::LanguageModelRequestMessage {
- role: Role::Assistant,
- content: vec![MessageContent::ToolUse(tool_use)],
- cache: false,
- reasoning_details: None,
- }],
- ..Default::default()
- },
- "gemini-2.5-flash".to_string(),
- GoogleModelMode::Default,
- );
-
- assert_eq!(request.contents[0].parts.len(), 1);
- if let Part::FunctionCallPart(fc_part) = &request.contents[0].parts[0] {
- assert_eq!(fc_part.function_call.name, "test_function");
- assert_eq!(
- fc_part.thought_signature.as_deref(),
- Some("test_signature_456")
- );
- } else {
- panic!("Expected FunctionCallPart");
- }
- }
-
- #[test]
- fn test_tool_use_without_signature_omits_field() {
- let tool_use = language_model::LanguageModelToolUse {
- id: LanguageModelToolUseId::from("test_id"),
- name: "test_function".into(),
- raw_input: json!({"arg": "value"}).to_string(),
- input: json!({"arg": "value"}),
- is_input_complete: true,
- thought_signature: None,
- };
-
- let request = super::into_google(
- LanguageModelRequest {
- messages: vec![language_model::LanguageModelRequestMessage {
- role: Role::Assistant,
- content: vec![MessageContent::ToolUse(tool_use)],
- cache: false,
- reasoning_details: None,
- }],
- ..Default::default()
- },
- "gemini-2.5-flash".to_string(),
- GoogleModelMode::Default,
- );
-
- assert_eq!(request.contents[0].parts.len(), 1);
- if let Part::FunctionCallPart(fc_part) = &request.contents[0].parts[0] {
- assert_eq!(fc_part.thought_signature, None);
- } else {
- panic!("Expected FunctionCallPart");
- }
- }
-
- #[test]
- fn test_empty_signature_in_tool_use_normalized_to_none() {
- let tool_use = language_model::LanguageModelToolUse {
- id: LanguageModelToolUseId::from("test_id"),
- name: "test_function".into(),
- raw_input: json!({"arg": "value"}).to_string(),
- input: json!({"arg": "value"}),
- is_input_complete: true,
- thought_signature: Some("".to_string()),
- };
-
- let request = super::into_google(
- LanguageModelRequest {
- messages: vec![language_model::LanguageModelRequestMessage {
- role: Role::Assistant,
- content: vec![MessageContent::ToolUse(tool_use)],
- cache: false,
- reasoning_details: None,
- }],
- ..Default::default()
- },
- "gemini-2.5-flash".to_string(),
- GoogleModelMode::Default,
- );
-
- if let Part::FunctionCallPart(fc_part) = &request.contents[0].parts[0] {
- assert_eq!(fc_part.thought_signature, None);
- } else {
- panic!("Expected FunctionCallPart");
- }
- }
-
- #[test]
- fn test_round_trip_preserves_signature() {
- let mut mapper = GoogleEventMapper::new();
-
- // Simulate receiving a response from Google with a signature
- let response = GenerateContentResponse {
- candidates: Some(vec![GenerateContentCandidate {
- index: Some(0),
- content: Content {
- parts: vec![Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "test_function".to_string(),
- args: json!({"arg": "value"}),
- },
- thought_signature: Some("round_trip_sig".to_string()),
- })],
- role: GoogleRole::Model,
- },
- finish_reason: None,
- finish_message: None,
- safety_ratings: None,
- citation_metadata: None,
- }]),
- prompt_feedback: None,
- usage_metadata: None,
- };
-
- let events = mapper.map_event(response);
-
- let tool_use = if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
- tool_use.clone()
- } else {
- panic!("Expected ToolUse event");
- };
-
- // Convert back to Google format
- let request = super::into_google(
- LanguageModelRequest {
- messages: vec![language_model::LanguageModelRequestMessage {
- role: Role::Assistant,
- content: vec![MessageContent::ToolUse(tool_use)],
- cache: false,
- reasoning_details: None,
- }],
- ..Default::default()
- },
- "gemini-2.5-flash".to_string(),
- GoogleModelMode::Default,
- );
-
- // Verify signature is preserved
- if let Part::FunctionCallPart(fc_part) = &request.contents[0].parts[0] {
- assert_eq!(fc_part.thought_signature.as_deref(), Some("round_trip_sig"));
- } else {
- panic!("Expected FunctionCallPart");
- }
- }
-
- #[test]
- fn test_mixed_text_and_function_call_with_signature() {
- let mut mapper = GoogleEventMapper::new();
-
- let response = GenerateContentResponse {
- candidates: Some(vec![GenerateContentCandidate {
- index: Some(0),
- content: Content {
- parts: vec![
- Part::TextPart(TextPart {
- text: "I'll help with that.".to_string(),
- }),
- Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "helper_function".to_string(),
- args: json!({"query": "help"}),
- },
- thought_signature: Some("mixed_sig".to_string()),
- }),
- ],
- role: GoogleRole::Model,
- },
- finish_reason: None,
- finish_message: None,
- safety_ratings: None,
- citation_metadata: None,
- }]),
- prompt_feedback: None,
- usage_metadata: None,
- };
-
- let events = mapper.map_event(response);
-
- assert_eq!(events.len(), 3); // Text event + ToolUse event + Stop event
-
- if let Ok(LanguageModelCompletionEvent::Text(text)) = &events[0] {
- assert_eq!(text, "I'll help with that.");
- } else {
- panic!("Expected Text event");
- }
-
- if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[1] {
- assert_eq!(tool_use.name.as_ref(), "helper_function");
- assert_eq!(tool_use.thought_signature.as_deref(), Some("mixed_sig"));
- } else {
- panic!("Expected ToolUse event");
- }
- }
-
- #[test]
- fn test_special_characters_in_signature_preserved() {
- let mut mapper = GoogleEventMapper::new();
-
- let signature_with_special_chars = "sig<>\"'&%$#@!{}[]".to_string();
-
- let response = GenerateContentResponse {
- candidates: Some(vec![GenerateContentCandidate {
- index: Some(0),
- content: Content {
- parts: vec![Part::FunctionCallPart(FunctionCallPart {
- function_call: FunctionCall {
- name: "test_function".to_string(),
- args: json!({"arg": "value"}),
- },
- thought_signature: Some(signature_with_special_chars.clone()),
- })],
- role: GoogleRole::Model,
- },
- finish_reason: None,
- finish_message: None,
- safety_ratings: None,
- citation_metadata: None,
- }]),
- prompt_feedback: None,
- usage_metadata: None,
- };
-
- let events = mapper.map_event(response);
-
- if let Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) = &events[0] {
- assert_eq!(
- tool_use.thought_signature.as_deref(),
- Some(signature_with_special_chars.as_str())
- );
- } else {
- panic!("Expected ToolUse event");
- }
- }
-}
@@ -28,7 +28,7 @@ use ui::{
use ui_input::InputField;
use crate::AllLanguageModelSettings;
-use crate::provider::util::parse_tool_arguments;
+use language_model::util::parse_tool_arguments;
const LMSTUDIO_DOWNLOAD_URL: &str = "https://lmstudio.ai/download";
const LMSTUDIO_CATALOG_URL: &str = "https://lmstudio.ai/models";
@@ -23,7 +23,7 @@ use ui::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
use ui_input::InputField;
use util::ResultExt;
-use crate::provider::util::{fix_streamed_json, parse_tool_arguments};
+use language_model::util::{fix_streamed_json, parse_tool_arguments};
const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("mistral");
const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("Mistral");
@@ -1,41 +1,33 @@
-use anyhow::{Result, anyhow};
-use collections::{BTreeMap, HashMap};
+use anyhow::Result;
+use collections::BTreeMap;
use credentials_provider::CredentialsProvider;
-use futures::Stream;
use futures::{FutureExt, StreamExt, future::BoxFuture};
use gpui::{AnyView, App, AsyncApp, Context, Entity, SharedString, Task, Window};
use http_client::HttpClient;
use language_model::{
ApiKeyState, AuthenticateError, EnvVar, IconOrSvg, LanguageModel, LanguageModelCompletionError,
- LanguageModelCompletionEvent, LanguageModelId, LanguageModelImage, LanguageModelName,
- LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
- LanguageModelProviderState, LanguageModelRequest, LanguageModelRequestMessage,
- LanguageModelToolChoice, LanguageModelToolResultContent, LanguageModelToolUse,
- LanguageModelToolUseId, MessageContent, OPEN_AI_PROVIDER_ID, OPEN_AI_PROVIDER_NAME,
- RateLimiter, Role, StopReason, TokenUsage, env_var,
+ LanguageModelCompletionEvent, LanguageModelId, LanguageModelName, LanguageModelProvider,
+ LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
+ LanguageModelRequest, LanguageModelToolChoice, OPEN_AI_PROVIDER_ID, OPEN_AI_PROVIDER_NAME,
+ RateLimiter, env_var,
};
use menu;
-use open_ai::responses::{
- ResponseFunctionCallItem, ResponseFunctionCallOutputContent, ResponseFunctionCallOutputItem,
- ResponseInputContent, ResponseInputItem, ResponseMessageItem,
-};
use open_ai::{
- ImageUrl, Model, OPEN_AI_API_URL, ReasoningEffort, ResponseStreamEvent,
- responses::{
- Request as ResponseRequest, ResponseOutputItem, ResponseSummary as ResponsesSummary,
- ResponseUsage as ResponsesUsage, StreamEvent as ResponsesStreamEvent, stream_response,
- },
+ OPEN_AI_API_URL, ResponseStreamEvent,
+ responses::{Request as ResponseRequest, StreamEvent as ResponsesStreamEvent, stream_response},
stream_completion,
};
use settings::{OpenAiAvailableModel as AvailableModel, Settings, SettingsStore};
-use std::pin::Pin;
use std::sync::{Arc, LazyLock};
use strum::IntoEnumIterator;
use ui::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
use ui_input::InputField;
use util::ResultExt;
-use crate::provider::util::{fix_streamed_json, parse_tool_arguments};
+pub use open_ai::completion::{
+ OpenAiEventMapper, OpenAiResponseEventMapper, collect_tiktoken_messages, count_open_ai_tokens,
+ into_open_ai, into_open_ai_response,
+};
const PROVIDER_ID: LanguageModelProviderId = OPEN_AI_PROVIDER_ID;
const PROVIDER_NAME: LanguageModelProviderName = OPEN_AI_PROVIDER_NAME;
@@ -189,7 +181,7 @@ impl LanguageModelProvider for OpenAiLanguageModelProvider {
max_tokens: model.max_tokens,
max_output_tokens: model.max_output_tokens,
max_completion_tokens: model.max_completion_tokens,
- reasoning_effort: model.reasoning_effort.clone(),
+ reasoning_effort: model.reasoning_effort,
supports_chat_completions: model.capabilities.chat_completions,
},
);
@@ -384,7 +376,9 @@ impl LanguageModel for OpenAiLanguageModel {
request: LanguageModelRequest,
cx: &App,
) -> BoxFuture<'static, Result<u64>> {
- count_open_ai_tokens(request, self.model.clone(), cx)
+ let model = self.model.clone();
+ cx.background_spawn(async move { count_open_ai_tokens(request, model) })
+ .boxed()
}
fn stream_completion(
@@ -435,856 +429,6 @@ impl LanguageModel for OpenAiLanguageModel {
}
}
-pub fn into_open_ai(
- request: LanguageModelRequest,
- model_id: &str,
- supports_parallel_tool_calls: bool,
- supports_prompt_cache_key: bool,
- max_output_tokens: Option<u64>,
- reasoning_effort: Option<ReasoningEffort>,
-) -> open_ai::Request {
- let stream = !model_id.starts_with("o1-");
-
- let mut messages = Vec::new();
- for message in request.messages {
- for content in message.content {
- match content {
- MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
- let should_add = if message.role == Role::User {
- // Including whitespace-only user messages can cause error with OpenAI compatible APIs
- // See https://github.com/zed-industries/zed/issues/40097
- !text.trim().is_empty()
- } else {
- !text.is_empty()
- };
- if should_add {
- add_message_content_part(
- open_ai::MessagePart::Text { text },
- message.role,
- &mut messages,
- );
- }
- }
- MessageContent::RedactedThinking(_) => {}
- MessageContent::Image(image) => {
- add_message_content_part(
- open_ai::MessagePart::Image {
- image_url: ImageUrl {
- url: image.to_base64_url(),
- detail: None,
- },
- },
- message.role,
- &mut messages,
- );
- }
- MessageContent::ToolUse(tool_use) => {
- let tool_call = open_ai::ToolCall {
- id: tool_use.id.to_string(),
- content: open_ai::ToolCallContent::Function {
- function: open_ai::FunctionContent {
- name: tool_use.name.to_string(),
- arguments: serde_json::to_string(&tool_use.input)
- .unwrap_or_default(),
- },
- },
- };
-
- if let Some(open_ai::RequestMessage::Assistant { tool_calls, .. }) =
- messages.last_mut()
- {
- tool_calls.push(tool_call);
- } else {
- messages.push(open_ai::RequestMessage::Assistant {
- content: None,
- tool_calls: vec![tool_call],
- });
- }
- }
- MessageContent::ToolResult(tool_result) => {
- let content = match &tool_result.content {
- LanguageModelToolResultContent::Text(text) => {
- vec![open_ai::MessagePart::Text {
- text: text.to_string(),
- }]
- }
- LanguageModelToolResultContent::Image(image) => {
- vec![open_ai::MessagePart::Image {
- image_url: ImageUrl {
- url: image.to_base64_url(),
- detail: None,
- },
- }]
- }
- };
-
- messages.push(open_ai::RequestMessage::Tool {
- content: content.into(),
- tool_call_id: tool_result.tool_use_id.to_string(),
- });
- }
- }
- }
- }
-
- open_ai::Request {
- model: model_id.into(),
- messages,
- stream,
- stream_options: if stream {
- Some(open_ai::StreamOptions::default())
- } else {
- None
- },
- stop: request.stop,
- temperature: request.temperature.or(Some(1.0)),
- max_completion_tokens: max_output_tokens,
- parallel_tool_calls: if supports_parallel_tool_calls && !request.tools.is_empty() {
- Some(supports_parallel_tool_calls)
- } else {
- None
- },
- prompt_cache_key: if supports_prompt_cache_key {
- request.thread_id
- } else {
- None
- },
- tools: request
- .tools
- .into_iter()
- .map(|tool| open_ai::ToolDefinition::Function {
- function: open_ai::FunctionDefinition {
- name: tool.name,
- description: Some(tool.description),
- parameters: Some(tool.input_schema),
- },
- })
- .collect(),
- tool_choice: request.tool_choice.map(|choice| match choice {
- LanguageModelToolChoice::Auto => open_ai::ToolChoice::Auto,
- LanguageModelToolChoice::Any => open_ai::ToolChoice::Required,
- LanguageModelToolChoice::None => open_ai::ToolChoice::None,
- }),
- reasoning_effort,
- }
-}
-
-pub fn into_open_ai_response(
- request: LanguageModelRequest,
- model_id: &str,
- supports_parallel_tool_calls: bool,
- supports_prompt_cache_key: bool,
- max_output_tokens: Option<u64>,
- reasoning_effort: Option<ReasoningEffort>,
-) -> ResponseRequest {
- let stream = !model_id.starts_with("o1-");
-
- let LanguageModelRequest {
- thread_id,
- prompt_id: _,
- intent: _,
- messages,
- tools,
- tool_choice,
- stop: _,
- temperature,
- thinking_allowed: _,
- thinking_effort: _,
- speed: _,
- } = request;
-
- let mut input_items = Vec::new();
- for (index, message) in messages.into_iter().enumerate() {
- append_message_to_response_items(message, index, &mut input_items);
- }
-
- let tools: Vec<_> = tools
- .into_iter()
- .map(|tool| open_ai::responses::ToolDefinition::Function {
- name: tool.name,
- description: Some(tool.description),
- parameters: Some(tool.input_schema),
- strict: None,
- })
- .collect();
-
- ResponseRequest {
- model: model_id.into(),
- instructions: None,
- input: input_items,
- stream,
- temperature,
- top_p: None,
- max_output_tokens,
- parallel_tool_calls: if tools.is_empty() {
- None
- } else {
- Some(supports_parallel_tool_calls)
- },
- tool_choice: tool_choice.map(|choice| match choice {
- LanguageModelToolChoice::Auto => open_ai::ToolChoice::Auto,
- LanguageModelToolChoice::Any => open_ai::ToolChoice::Required,
- LanguageModelToolChoice::None => open_ai::ToolChoice::None,
- }),
- tools,
- prompt_cache_key: if supports_prompt_cache_key {
- thread_id
- } else {
- None
- },
- reasoning: reasoning_effort.map(|effort| open_ai::responses::ReasoningConfig {
- effort,
- summary: Some(open_ai::responses::ReasoningSummaryMode::Auto),
- }),
- store: None,
- }
-}
-
-fn append_message_to_response_items(
- message: LanguageModelRequestMessage,
- index: usize,
- input_items: &mut Vec<ResponseInputItem>,
-) {
- let mut content_parts: Vec<ResponseInputContent> = Vec::new();
-
- for content in message.content {
- match content {
- MessageContent::Text(text) => {
- push_response_text_part(&message.role, text, &mut content_parts);
- }
- MessageContent::Thinking { text, .. } => {
- push_response_text_part(&message.role, text, &mut content_parts);
- }
- MessageContent::RedactedThinking(_) => {}
- MessageContent::Image(image) => {
- push_response_image_part(&message.role, image, &mut content_parts);
- }
- MessageContent::ToolUse(tool_use) => {
- flush_response_parts(&message.role, index, &mut content_parts, input_items);
- let call_id = tool_use.id.to_string();
- input_items.push(ResponseInputItem::FunctionCall(ResponseFunctionCallItem {
- call_id,
- name: tool_use.name.to_string(),
- arguments: tool_use.raw_input,
- }));
- }
- MessageContent::ToolResult(tool_result) => {
- flush_response_parts(&message.role, index, &mut content_parts, input_items);
- input_items.push(ResponseInputItem::FunctionCallOutput(
- ResponseFunctionCallOutputItem {
- call_id: tool_result.tool_use_id.to_string(),
- output: match tool_result.content {
- LanguageModelToolResultContent::Text(text) => {
- ResponseFunctionCallOutputContent::Text(text.to_string())
- }
- LanguageModelToolResultContent::Image(image) => {
- ResponseFunctionCallOutputContent::List(vec![
- ResponseInputContent::Image {
- image_url: image.to_base64_url(),
- },
- ])
- }
- },
- },
- ));
- }
- }
- }
-
- flush_response_parts(&message.role, index, &mut content_parts, input_items);
-}
-
-fn push_response_text_part(
- role: &Role,
- text: impl Into<String>,
- parts: &mut Vec<ResponseInputContent>,
-) {
- let text = text.into();
- if text.trim().is_empty() {
- return;
- }
-
- match role {
- Role::Assistant => parts.push(ResponseInputContent::OutputText {
- text,
- annotations: Vec::new(),
- }),
- _ => parts.push(ResponseInputContent::Text { text }),
- }
-}
-
-fn push_response_image_part(
- role: &Role,
- image: LanguageModelImage,
- parts: &mut Vec<ResponseInputContent>,
-) {
- match role {
- Role::Assistant => parts.push(ResponseInputContent::OutputText {
- text: "[image omitted]".to_string(),
- annotations: Vec::new(),
- }),
- _ => parts.push(ResponseInputContent::Image {
- image_url: image.to_base64_url(),
- }),
- }
-}
-
-fn flush_response_parts(
- role: &Role,
- _index: usize,
- parts: &mut Vec<ResponseInputContent>,
- input_items: &mut Vec<ResponseInputItem>,
-) {
- if parts.is_empty() {
- return;
- }
-
- let item = ResponseInputItem::Message(ResponseMessageItem {
- role: match role {
- Role::User => open_ai::Role::User,
- Role::Assistant => open_ai::Role::Assistant,
- Role::System => open_ai::Role::System,
- },
- content: parts.clone(),
- });
-
- input_items.push(item);
- parts.clear();
-}
-
-fn add_message_content_part(
- new_part: open_ai::MessagePart,
- role: Role,
- messages: &mut Vec<open_ai::RequestMessage>,
-) {
- match (role, messages.last_mut()) {
- (Role::User, Some(open_ai::RequestMessage::User { content }))
- | (
- Role::Assistant,
- Some(open_ai::RequestMessage::Assistant {
- content: Some(content),
- ..
- }),
- )
- | (Role::System, Some(open_ai::RequestMessage::System { content, .. })) => {
- content.push_part(new_part);
- }
- _ => {
- messages.push(match role {
- Role::User => open_ai::RequestMessage::User {
- content: open_ai::MessageContent::from(vec![new_part]),
- },
- Role::Assistant => open_ai::RequestMessage::Assistant {
- content: Some(open_ai::MessageContent::from(vec![new_part])),
- tool_calls: Vec::new(),
- },
- Role::System => open_ai::RequestMessage::System {
- content: open_ai::MessageContent::from(vec![new_part]),
- },
- });
- }
- }
-}
-
-pub struct OpenAiEventMapper {
- tool_calls_by_index: HashMap<usize, RawToolCall>,
-}
-
-impl OpenAiEventMapper {
- pub fn new() -> Self {
- Self {
- tool_calls_by_index: HashMap::default(),
- }
- }
-
- pub fn map_stream(
- mut self,
- events: Pin<Box<dyn Send + Stream<Item = Result<ResponseStreamEvent>>>>,
- ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
- {
- events.flat_map(move |event| {
- futures::stream::iter(match event {
- Ok(event) => self.map_event(event),
- Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
- })
- })
- }
-
- pub fn map_event(
- &mut self,
- event: ResponseStreamEvent,
- ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
- let mut events = Vec::new();
- if let Some(usage) = event.usage {
- events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
- input_tokens: usage.prompt_tokens,
- output_tokens: usage.completion_tokens,
- cache_creation_input_tokens: 0,
- cache_read_input_tokens: 0,
- })));
- }
-
- let Some(choice) = event.choices.first() else {
- return events;
- };
-
- if let Some(delta) = choice.delta.as_ref() {
- if let Some(reasoning_content) = delta.reasoning_content.clone() {
- if !reasoning_content.is_empty() {
- events.push(Ok(LanguageModelCompletionEvent::Thinking {
- text: reasoning_content,
- signature: None,
- }));
- }
- }
- if let Some(content) = delta.content.clone() {
- if !content.is_empty() {
- events.push(Ok(LanguageModelCompletionEvent::Text(content)));
- }
- }
-
- if let Some(tool_calls) = delta.tool_calls.as_ref() {
- for tool_call in tool_calls {
- let entry = self.tool_calls_by_index.entry(tool_call.index).or_default();
-
- if let Some(tool_id) = tool_call.id.clone() {
- entry.id = tool_id;
- }
-
- if let Some(function) = tool_call.function.as_ref() {
- if let Some(name) = function.name.clone() {
- entry.name = name;
- }
-
- if let Some(arguments) = function.arguments.clone() {
- entry.arguments.push_str(&arguments);
- }
- }
-
- if !entry.id.is_empty() && !entry.name.is_empty() {
- if let Ok(input) = serde_json::from_str::<serde_json::Value>(
- &fix_streamed_json(&entry.arguments),
- ) {
- events.push(Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id: entry.id.clone().into(),
- name: entry.name.as_str().into(),
- is_input_complete: false,
- input,
- raw_input: entry.arguments.clone(),
- thought_signature: None,
- },
- )));
- }
- }
- }
- }
- }
-
- match choice.finish_reason.as_deref() {
- Some("stop") => {
- events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
- }
- Some("tool_calls") => {
- events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
- match parse_tool_arguments(&tool_call.arguments) {
- Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id: tool_call.id.clone().into(),
- name: tool_call.name.as_str().into(),
- is_input_complete: true,
- input,
- raw_input: tool_call.arguments.clone(),
- thought_signature: None,
- },
- )),
- Err(error) => Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
- id: tool_call.id.into(),
- tool_name: tool_call.name.into(),
- raw_input: tool_call.arguments.clone().into(),
- json_parse_error: error.to_string(),
- }),
- }
- }));
-
- events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
- }
- Some(stop_reason) => {
- log::error!("Unexpected OpenAI stop_reason: {stop_reason:?}",);
- events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
- }
- None => {}
- }
-
- events
- }
-}
-
-#[derive(Default)]
-struct RawToolCall {
- id: String,
- name: String,
- arguments: String,
-}
-
-pub struct OpenAiResponseEventMapper {
- function_calls_by_item: HashMap<String, PendingResponseFunctionCall>,
- pending_stop_reason: Option<StopReason>,
-}
-
-#[derive(Default)]
-struct PendingResponseFunctionCall {
- call_id: String,
- name: Arc<str>,
- arguments: String,
-}
-
-impl OpenAiResponseEventMapper {
- pub fn new() -> Self {
- Self {
- function_calls_by_item: HashMap::default(),
- pending_stop_reason: None,
- }
- }
-
- pub fn map_stream(
- mut self,
- events: Pin<Box<dyn Send + Stream<Item = Result<ResponsesStreamEvent>>>>,
- ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
- {
- events.flat_map(move |event| {
- futures::stream::iter(match event {
- Ok(event) => self.map_event(event),
- Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
- })
- })
- }
-
- pub fn map_event(
- &mut self,
- event: ResponsesStreamEvent,
- ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
- match event {
- ResponsesStreamEvent::OutputItemAdded { item, .. } => {
- let mut events = Vec::new();
-
- match &item {
- ResponseOutputItem::Message(message) => {
- if let Some(id) = &message.id {
- events.push(Ok(LanguageModelCompletionEvent::StartMessage {
- message_id: id.clone(),
- }));
- }
- }
- ResponseOutputItem::FunctionCall(function_call) => {
- if let Some(item_id) = function_call.id.clone() {
- let call_id = function_call
- .call_id
- .clone()
- .or_else(|| function_call.id.clone())
- .unwrap_or_else(|| item_id.clone());
- let entry = PendingResponseFunctionCall {
- call_id,
- name: Arc::<str>::from(
- function_call.name.clone().unwrap_or_default(),
- ),
- arguments: function_call.arguments.clone(),
- };
- self.function_calls_by_item.insert(item_id, entry);
- }
- }
- ResponseOutputItem::Reasoning(_) | ResponseOutputItem::Unknown => {}
- }
- events
- }
- ResponsesStreamEvent::ReasoningSummaryTextDelta { delta, .. } => {
- if delta.is_empty() {
- Vec::new()
- } else {
- vec![Ok(LanguageModelCompletionEvent::Thinking {
- text: delta,
- signature: None,
- })]
- }
- }
- ResponsesStreamEvent::OutputTextDelta { delta, .. } => {
- if delta.is_empty() {
- Vec::new()
- } else {
- vec![Ok(LanguageModelCompletionEvent::Text(delta))]
- }
- }
- ResponsesStreamEvent::FunctionCallArgumentsDelta { item_id, delta, .. } => {
- if let Some(entry) = self.function_calls_by_item.get_mut(&item_id) {
- entry.arguments.push_str(&delta);
- if let Ok(input) = serde_json::from_str::<serde_json::Value>(
- &fix_streamed_json(&entry.arguments),
- ) {
- return vec![Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id: LanguageModelToolUseId::from(entry.call_id.clone()),
- name: entry.name.clone(),
- is_input_complete: false,
- input,
- raw_input: entry.arguments.clone(),
- thought_signature: None,
- },
- ))];
- }
- }
- Vec::new()
- }
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id, arguments, ..
- } => {
- if let Some(mut entry) = self.function_calls_by_item.remove(&item_id) {
- if !arguments.is_empty() {
- entry.arguments = arguments;
- }
- let raw_input = entry.arguments.clone();
- self.pending_stop_reason = Some(StopReason::ToolUse);
- match parse_tool_arguments(&entry.arguments) {
- Ok(input) => {
- vec![Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id: LanguageModelToolUseId::from(entry.call_id.clone()),
- name: entry.name.clone(),
- is_input_complete: true,
- input,
- raw_input,
- thought_signature: None,
- },
- ))]
- }
- Err(error) => {
- vec![Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
- id: LanguageModelToolUseId::from(entry.call_id.clone()),
- tool_name: entry.name.clone(),
- raw_input: Arc::<str>::from(raw_input),
- json_parse_error: error.to_string(),
- })]
- }
- }
- } else {
- Vec::new()
- }
- }
- ResponsesStreamEvent::Completed { response } => {
- self.handle_completion(response, StopReason::EndTurn)
- }
- ResponsesStreamEvent::Incomplete { response } => {
- let reason = response
- .status_details
- .as_ref()
- .and_then(|details| details.reason.as_deref());
- let stop_reason = match reason {
- Some("max_output_tokens") => StopReason::MaxTokens,
- Some("content_filter") => {
- self.pending_stop_reason = Some(StopReason::Refusal);
- StopReason::Refusal
- }
- _ => self
- .pending_stop_reason
- .take()
- .unwrap_or(StopReason::EndTurn),
- };
-
- let mut events = Vec::new();
- if self.pending_stop_reason.is_none() {
- events.extend(self.emit_tool_calls_from_output(&response.output));
- }
- if let Some(usage) = response.usage.as_ref() {
- events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
- token_usage_from_response_usage(usage),
- )));
- }
- events.push(Ok(LanguageModelCompletionEvent::Stop(stop_reason)));
- events
- }
- ResponsesStreamEvent::Failed { response } => {
- let message = response
- .status_details
- .and_then(|details| details.error)
- .map(|error| error.to_string())
- .unwrap_or_else(|| "response failed".to_string());
- vec![Err(LanguageModelCompletionError::Other(anyhow!(message)))]
- }
- ResponsesStreamEvent::Error { error }
- | ResponsesStreamEvent::GenericError { error } => {
- vec![Err(LanguageModelCompletionError::Other(anyhow!(
- error.message
- )))]
- }
- ResponsesStreamEvent::ReasoningSummaryPartAdded { summary_index, .. } => {
- if summary_index > 0 {
- vec![Ok(LanguageModelCompletionEvent::Thinking {
- text: "\n\n".to_string(),
- signature: None,
- })]
- } else {
- Vec::new()
- }
- }
- ResponsesStreamEvent::OutputTextDone { .. }
- | ResponsesStreamEvent::OutputItemDone { .. }
- | ResponsesStreamEvent::ContentPartAdded { .. }
- | ResponsesStreamEvent::ContentPartDone { .. }
- | ResponsesStreamEvent::ReasoningSummaryTextDone { .. }
- | ResponsesStreamEvent::ReasoningSummaryPartDone { .. }
- | ResponsesStreamEvent::Created { .. }
- | ResponsesStreamEvent::InProgress { .. }
- | ResponsesStreamEvent::Unknown => Vec::new(),
- }
- }
-
- fn handle_completion(
- &mut self,
- response: ResponsesSummary,
- default_reason: StopReason,
- ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
- let mut events = Vec::new();
-
- if self.pending_stop_reason.is_none() {
- events.extend(self.emit_tool_calls_from_output(&response.output));
- }
-
- if let Some(usage) = response.usage.as_ref() {
- events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
- token_usage_from_response_usage(usage),
- )));
- }
-
- let stop_reason = self.pending_stop_reason.take().unwrap_or(default_reason);
- events.push(Ok(LanguageModelCompletionEvent::Stop(stop_reason)));
- events
- }
-
- fn emit_tool_calls_from_output(
- &mut self,
- output: &[ResponseOutputItem],
- ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
- let mut events = Vec::new();
- for item in output {
- if let ResponseOutputItem::FunctionCall(function_call) = item {
- let Some(call_id) = function_call
- .call_id
- .clone()
- .or_else(|| function_call.id.clone())
- else {
- log::error!(
- "Function call item missing both call_id and id: {:?}",
- function_call
- );
- continue;
- };
- let name: Arc<str> = Arc::from(function_call.name.clone().unwrap_or_default());
- let arguments = &function_call.arguments;
- self.pending_stop_reason = Some(StopReason::ToolUse);
- match parse_tool_arguments(arguments) {
- Ok(input) => {
- events.push(Ok(LanguageModelCompletionEvent::ToolUse(
- LanguageModelToolUse {
- id: LanguageModelToolUseId::from(call_id.clone()),
- name: name.clone(),
- is_input_complete: true,
- input,
- raw_input: arguments.clone(),
- thought_signature: None,
- },
- )));
- }
- Err(error) => {
- events.push(Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
- id: LanguageModelToolUseId::from(call_id.clone()),
- tool_name: name.clone(),
- raw_input: Arc::<str>::from(arguments.clone()),
- json_parse_error: error.to_string(),
- }));
- }
- }
- }
- }
- events
- }
-}
-
-fn token_usage_from_response_usage(usage: &ResponsesUsage) -> TokenUsage {
- TokenUsage {
- input_tokens: usage.input_tokens.unwrap_or_default(),
- output_tokens: usage.output_tokens.unwrap_or_default(),
- cache_creation_input_tokens: 0,
- cache_read_input_tokens: 0,
- }
-}
-
-pub(crate) fn collect_tiktoken_messages(
- request: LanguageModelRequest,
-) -> Vec<tiktoken_rs::ChatCompletionRequestMessage> {
- request
- .messages
- .into_iter()
- .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
- role: match message.role {
- Role::User => "user".into(),
- Role::Assistant => "assistant".into(),
- Role::System => "system".into(),
- },
- content: Some(message.string_contents()),
- name: None,
- function_call: None,
- })
- .collect::<Vec<_>>()
-}
-
-pub fn count_open_ai_tokens(
- request: LanguageModelRequest,
- model: Model,
- cx: &App,
-) -> BoxFuture<'static, Result<u64>> {
- cx.background_spawn(async move {
- let messages = collect_tiktoken_messages(request);
- match model {
- Model::Custom { max_tokens, .. } => {
- let model = if max_tokens >= 100_000 {
- // If the max tokens is 100k or more, it likely uses the o200k_base tokenizer
- "gpt-4o"
- } else {
- // Otherwise fallback to gpt-4, since only cl100k_base and o200k_base are
- // supported with this tiktoken method
- "gpt-4"
- };
- tiktoken_rs::num_tokens_from_messages(model, &messages)
- }
- // Currently supported by tiktoken_rs
- // Sometimes tiktoken-rs is behind on model support. If that is the case, make a new branch
- // arm with an override. We enumerate all supported models here so that we can check if new
- // models are supported yet or not.
- Model::ThreePointFiveTurbo
- | Model::Four
- | Model::FourTurbo
- | Model::FourOmniMini
- | Model::FourPointOneNano
- | Model::O1
- | Model::O3
- | Model::O3Mini
- | Model::O4Mini
- | Model::Five
- | Model::FiveCodex
- | Model::FiveMini
- | Model::FiveNano => tiktoken_rs::num_tokens_from_messages(model.id(), &messages),
- // GPT-5.1, 5.2, 5.2-codex, 5.3-codex, 5.4, and 5.4-pro don't have dedicated tiktoken support; use gpt-5 tokenizer
- Model::FivePointOne
- | Model::FivePointTwo
- | Model::FivePointTwoCodex
- | Model::FivePointThreeCodex
- | Model::FivePointFour
- | Model::FivePointFourPro => tiktoken_rs::num_tokens_from_messages("gpt-5", &messages),
- }
- .map(|tokens| tokens as u64)
- })
- .boxed()
-}
-
struct ConfigurationView {
api_key_editor: Entity<InputField>,
state: Entity<State>,
@@ -1464,874 +608,3 @@ impl Render for ConfigurationView {
}
}
}
-
-#[cfg(test)]
-mod tests {
- use futures::{StreamExt, executor::block_on};
- use gpui::TestAppContext;
- use language_model::{
- LanguageModelRequestMessage, LanguageModelRequestTool, LanguageModelToolResult,
- };
- use open_ai::responses::{
- ReasoningSummaryPart, ResponseFunctionToolCall, ResponseOutputItem, ResponseOutputMessage,
- ResponseReasoningItem, ResponseStatusDetails, ResponseSummary, ResponseUsage,
- StreamEvent as ResponsesStreamEvent,
- };
- use pretty_assertions::assert_eq;
- use serde_json::json;
-
- use super::*;
-
- fn map_response_events(events: Vec<ResponsesStreamEvent>) -> Vec<LanguageModelCompletionEvent> {
- block_on(async {
- OpenAiResponseEventMapper::new()
- .map_stream(Box::pin(futures::stream::iter(events.into_iter().map(Ok))))
- .collect::<Vec<_>>()
- .await
- .into_iter()
- .map(Result::unwrap)
- .collect()
- })
- }
-
- fn response_item_message(id: &str) -> ResponseOutputItem {
- ResponseOutputItem::Message(ResponseOutputMessage {
- id: Some(id.to_string()),
- role: Some("assistant".to_string()),
- status: Some("in_progress".to_string()),
- content: vec![],
- })
- }
-
- fn response_item_function_call(id: &str, args: Option<&str>) -> ResponseOutputItem {
- ResponseOutputItem::FunctionCall(ResponseFunctionToolCall {
- id: Some(id.to_string()),
- status: Some("in_progress".to_string()),
- name: Some("get_weather".to_string()),
- call_id: Some("call_123".to_string()),
- arguments: args.map(|s| s.to_string()).unwrap_or_default(),
- })
- }
-
- #[gpui::test]
- fn tiktoken_rs_support(cx: &TestAppContext) {
- let request = LanguageModelRequest {
- thread_id: None,
- prompt_id: None,
- intent: None,
- messages: vec![LanguageModelRequestMessage {
- role: Role::User,
- content: vec![MessageContent::Text("message".into())],
- cache: false,
- reasoning_details: None,
- }],
- tools: vec![],
- tool_choice: None,
- stop: vec![],
- temperature: None,
- thinking_allowed: true,
- thinking_effort: None,
- speed: None,
- };
-
- // Validate that all models are supported by tiktoken-rs
- for model in Model::iter() {
- let count = cx
- .foreground_executor()
- .block_on(count_open_ai_tokens(
- request.clone(),
- model,
- &cx.app.borrow(),
- ))
- .unwrap();
- assert!(count > 0);
- }
- }
-
- #[test]
- fn responses_stream_maps_text_and_usage() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_message("msg_123"),
- },
- ResponsesStreamEvent::OutputTextDelta {
- item_id: "msg_123".into(),
- output_index: 0,
- content_index: Some(0),
- delta: "Hello".into(),
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary {
- usage: Some(ResponseUsage {
- input_tokens: Some(5),
- output_tokens: Some(3),
- total_tokens: Some(8),
- }),
- ..Default::default()
- },
- },
- ];
-
- let mapped = map_response_events(events);
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::StartMessage { ref message_id } if message_id == "msg_123"
- ));
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::Text(ref text) if text == "Hello"
- ));
- assert!(matches!(
- mapped[2],
- LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
- input_tokens: 5,
- output_tokens: 3,
- ..
- })
- ));
- assert!(matches!(
- mapped[3],
- LanguageModelCompletionEvent::Stop(StopReason::EndTurn)
- ));
- }
-
- #[test]
- fn into_open_ai_response_builds_complete_payload() {
- let tool_call_id = LanguageModelToolUseId::from("call-42");
- let tool_input = json!({ "city": "Boston" });
- let tool_arguments = serde_json::to_string(&tool_input).unwrap();
- let tool_use = LanguageModelToolUse {
- id: tool_call_id.clone(),
- name: Arc::from("get_weather"),
- raw_input: tool_arguments.clone(),
- input: tool_input,
- is_input_complete: true,
- thought_signature: None,
- };
- let tool_result = LanguageModelToolResult {
- tool_use_id: tool_call_id,
- tool_name: Arc::from("get_weather"),
- is_error: false,
- content: LanguageModelToolResultContent::Text(Arc::from("Sunny")),
- output: Some(json!({ "forecast": "Sunny" })),
- };
- let user_image = LanguageModelImage {
- source: SharedString::from("aGVsbG8="),
- size: None,
- };
- let expected_image_url = user_image.to_base64_url();
-
- let request = LanguageModelRequest {
- thread_id: Some("thread-123".into()),
- prompt_id: None,
- intent: None,
- messages: vec![
- LanguageModelRequestMessage {
- role: Role::System,
- content: vec![MessageContent::Text("System context".into())],
- cache: false,
- reasoning_details: None,
- },
- LanguageModelRequestMessage {
- role: Role::User,
- content: vec![
- MessageContent::Text("Please check the weather.".into()),
- MessageContent::Image(user_image),
- ],
- cache: false,
- reasoning_details: None,
- },
- LanguageModelRequestMessage {
- role: Role::Assistant,
- content: vec![
- MessageContent::Text("Looking that up.".into()),
- MessageContent::ToolUse(tool_use),
- ],
- cache: false,
- reasoning_details: None,
- },
- LanguageModelRequestMessage {
- role: Role::Assistant,
- content: vec![MessageContent::ToolResult(tool_result)],
- cache: false,
- reasoning_details: None,
- },
- ],
- tools: vec![LanguageModelRequestTool {
- name: "get_weather".into(),
- description: "Fetches the weather".into(),
- input_schema: json!({ "type": "object" }),
- use_input_streaming: false,
- }],
- tool_choice: Some(LanguageModelToolChoice::Any),
- stop: vec!["<STOP>".into()],
- temperature: None,
- thinking_allowed: false,
- thinking_effort: None,
- speed: None,
- };
-
- let response = into_open_ai_response(
- request,
- "custom-model",
- true,
- true,
- Some(2048),
- Some(ReasoningEffort::Low),
- );
-
- let serialized = serde_json::to_value(&response).unwrap();
- let expected = json!({
- "model": "custom-model",
- "input": [
- {
- "type": "message",
- "role": "system",
- "content": [
- { "type": "input_text", "text": "System context" }
- ]
- },
- {
- "type": "message",
- "role": "user",
- "content": [
- { "type": "input_text", "text": "Please check the weather." },
- { "type": "input_image", "image_url": expected_image_url }
- ]
- },
- {
- "type": "message",
- "role": "assistant",
- "content": [
- { "type": "output_text", "text": "Looking that up.", "annotations": [] }
- ]
- },
- {
- "type": "function_call",
- "call_id": "call-42",
- "name": "get_weather",
- "arguments": tool_arguments
- },
- {
- "type": "function_call_output",
- "call_id": "call-42",
- "output": "Sunny"
- }
- ],
- "stream": true,
- "max_output_tokens": 2048,
- "parallel_tool_calls": true,
- "tool_choice": "required",
- "tools": [
- {
- "type": "function",
- "name": "get_weather",
- "description": "Fetches the weather",
- "parameters": { "type": "object" }
- }
- ],
- "prompt_cache_key": "thread-123",
- "reasoning": { "effort": "low", "summary": "auto" }
- });
-
- assert_eq!(serialized, expected);
- }
-
- #[test]
- fn responses_stream_maps_tool_calls() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_function_call("item_fn", Some("{\"city\":\"Bos")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDelta {
- item_id: "item_fn".into(),
- output_index: 0,
- delta: "ton\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn".into(),
- output_index: 0,
- arguments: "{\"city\":\"Boston\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
- assert_eq!(mapped.len(), 3);
- // First event is the partial tool use (from FunctionCallArgumentsDelta)
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
- is_input_complete: false,
- ..
- })
- ));
- // Second event is the complete tool use (from FunctionCallArgumentsDone)
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
- ref id,
- ref name,
- ref raw_input,
- is_input_complete: true,
- ..
- }) if id.to_string() == "call_123"
- && name.as_ref() == "get_weather"
- && raw_input == "{\"city\":\"Boston\"}"
- ));
- assert!(matches!(
- mapped[2],
- LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
- ));
- }
-
- #[test]
- fn responses_stream_uses_max_tokens_stop_reason() {
- let events = vec![ResponsesStreamEvent::Incomplete {
- response: ResponseSummary {
- status_details: Some(ResponseStatusDetails {
- reason: Some("max_output_tokens".into()),
- r#type: Some("incomplete".into()),
- error: None,
- }),
- usage: Some(ResponseUsage {
- input_tokens: Some(10),
- output_tokens: Some(20),
- total_tokens: Some(30),
- }),
- ..Default::default()
- },
- }];
-
- let mapped = map_response_events(events);
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
- input_tokens: 10,
- output_tokens: 20,
- ..
- })
- ));
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
- ));
- }
-
- #[test]
- fn responses_stream_handles_multiple_tool_calls() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_function_call("item_fn1", Some("{\"city\":\"NYC\"}")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn1".into(),
- output_index: 0,
- arguments: "{\"city\":\"NYC\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 1,
- sequence_number: None,
- item: response_item_function_call("item_fn2", Some("{\"city\":\"LA\"}")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn2".into(),
- output_index: 1,
- arguments: "{\"city\":\"LA\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
- assert_eq!(mapped.len(), 3);
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. })
- if raw_input == "{\"city\":\"NYC\"}"
- ));
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. })
- if raw_input == "{\"city\":\"LA\"}"
- ));
- assert!(matches!(
- mapped[2],
- LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
- ));
- }
-
- #[test]
- fn responses_stream_handles_mixed_text_and_tool_calls() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_message("msg_123"),
- },
- ResponsesStreamEvent::OutputTextDelta {
- item_id: "msg_123".into(),
- output_index: 0,
- content_index: Some(0),
- delta: "Let me check that".into(),
- },
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 1,
- sequence_number: None,
- item: response_item_function_call("item_fn", Some("{\"query\":\"test\"}")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn".into(),
- output_index: 1,
- arguments: "{\"query\":\"test\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::StartMessage { .. }
- ));
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::Text(ref text) if text == "Let me check that"
- ));
- assert!(matches!(
- mapped[2],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. })
- if raw_input == "{\"query\":\"test\"}"
- ));
- assert!(matches!(
- mapped[3],
- LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
- ));
- }
-
- #[test]
- fn responses_stream_handles_json_parse_error() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_function_call("item_fn", Some("{invalid json")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn".into(),
- output_index: 0,
- arguments: "{invalid json".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::ToolUseJsonParseError {
- ref raw_input,
- ..
- } if raw_input.as_ref() == "{invalid json"
- ));
- }
-
- #[test]
- fn responses_stream_handles_incomplete_function_call() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_function_call("item_fn", Some("{\"city\":")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDelta {
- item_id: "item_fn".into(),
- output_index: 0,
- delta: "\"Boston\"".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Incomplete {
- response: ResponseSummary {
- status_details: Some(ResponseStatusDetails {
- reason: Some("max_output_tokens".into()),
- r#type: Some("incomplete".into()),
- error: None,
- }),
- output: vec![response_item_function_call(
- "item_fn",
- Some("{\"city\":\"Boston\"}"),
- )],
- ..Default::default()
- },
- },
- ];
-
- let mapped = map_response_events(events);
- assert_eq!(mapped.len(), 3);
- // First event is the partial tool use (from FunctionCallArgumentsDelta)
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
- is_input_complete: false,
- ..
- })
- ));
- // Second event is the complete tool use (from the Incomplete response output)
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
- ref raw_input,
- is_input_complete: true,
- ..
- })
- if raw_input == "{\"city\":\"Boston\"}"
- ));
- assert!(matches!(
- mapped[2],
- LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
- ));
- }
-
- #[test]
- fn responses_stream_incomplete_does_not_duplicate_tool_calls() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_function_call("item_fn", Some("{\"city\":\"Boston\"}")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn".into(),
- output_index: 0,
- arguments: "{\"city\":\"Boston\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Incomplete {
- response: ResponseSummary {
- status_details: Some(ResponseStatusDetails {
- reason: Some("max_output_tokens".into()),
- r#type: Some("incomplete".into()),
- error: None,
- }),
- output: vec![response_item_function_call(
- "item_fn",
- Some("{\"city\":\"Boston\"}"),
- )],
- ..Default::default()
- },
- },
- ];
-
- let mapped = map_response_events(events);
- assert_eq!(mapped.len(), 2);
- assert!(matches!(
- mapped[0],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. })
- if raw_input == "{\"city\":\"Boston\"}"
- ));
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
- ));
- }
-
- #[test]
- fn responses_stream_handles_empty_tool_arguments() {
- // Test that tools with no arguments (empty string) are handled correctly
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: response_item_function_call("item_fn", Some("")),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn".into(),
- output_index: 0,
- arguments: "".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
- assert_eq!(mapped.len(), 2);
-
- // Should produce a ToolUse event with an empty object
- assert!(matches!(
- &mapped[0],
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
- id,
- name,
- raw_input,
- input,
- ..
- }) if id.to_string() == "call_123"
- && name.as_ref() == "get_weather"
- && raw_input == ""
- && input.is_object()
- && input.as_object().unwrap().is_empty()
- ));
-
- assert!(matches!(
- mapped[1],
- LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
- ));
- }
-
- #[test]
- fn responses_stream_emits_partial_tool_use_events() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: ResponseOutputItem::FunctionCall(ResponseFunctionToolCall {
- id: Some("item_fn".to_string()),
- status: Some("in_progress".to_string()),
- name: Some("get_weather".to_string()),
- call_id: Some("call_abc".to_string()),
- arguments: String::new(),
- }),
- },
- ResponsesStreamEvent::FunctionCallArgumentsDelta {
- item_id: "item_fn".into(),
- output_index: 0,
- delta: "{\"city\":\"Bos".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::FunctionCallArgumentsDelta {
- item_id: "item_fn".into(),
- output_index: 0,
- delta: "ton\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::FunctionCallArgumentsDone {
- item_id: "item_fn".into(),
- output_index: 0,
- arguments: "{\"city\":\"Boston\"}".into(),
- sequence_number: None,
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
- // Two partial events + one complete event + Stop
- assert!(mapped.len() >= 3);
-
- // The last complete ToolUse event should have is_input_complete: true
- let complete_tool_use = mapped.iter().find(|e| {
- matches!(
- e,
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
- is_input_complete: true,
- ..
- })
- )
- });
- assert!(
- complete_tool_use.is_some(),
- "should have a complete tool use event"
- );
-
- // All ToolUse events before the final one should have is_input_complete: false
- let tool_uses: Vec<_> = mapped
- .iter()
- .filter(|e| matches!(e, LanguageModelCompletionEvent::ToolUse(_)))
- .collect();
- assert!(
- tool_uses.len() >= 2,
- "should have at least one partial and one complete event"
- );
-
- let last = tool_uses.last().unwrap();
- assert!(matches!(
- last,
- LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
- is_input_complete: true,
- ..
- })
- ));
- }
-
- #[test]
- fn responses_stream_maps_reasoning_summary_deltas() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
- id: Some("rs_123".into()),
- summary: vec![],
- }),
- },
- ResponsesStreamEvent::ReasoningSummaryPartAdded {
- item_id: "rs_123".into(),
- output_index: 0,
- summary_index: 0,
- },
- ResponsesStreamEvent::ReasoningSummaryTextDelta {
- item_id: "rs_123".into(),
- output_index: 0,
- delta: "Thinking about".into(),
- },
- ResponsesStreamEvent::ReasoningSummaryTextDelta {
- item_id: "rs_123".into(),
- output_index: 0,
- delta: " the answer".into(),
- },
- ResponsesStreamEvent::ReasoningSummaryTextDone {
- item_id: "rs_123".into(),
- output_index: 0,
- text: "Thinking about the answer".into(),
- },
- ResponsesStreamEvent::ReasoningSummaryPartDone {
- item_id: "rs_123".into(),
- output_index: 0,
- summary_index: 0,
- },
- ResponsesStreamEvent::ReasoningSummaryPartAdded {
- item_id: "rs_123".into(),
- output_index: 0,
- summary_index: 1,
- },
- ResponsesStreamEvent::ReasoningSummaryTextDelta {
- item_id: "rs_123".into(),
- output_index: 0,
- delta: "Second part".into(),
- },
- ResponsesStreamEvent::ReasoningSummaryTextDone {
- item_id: "rs_123".into(),
- output_index: 0,
- text: "Second part".into(),
- },
- ResponsesStreamEvent::ReasoningSummaryPartDone {
- item_id: "rs_123".into(),
- output_index: 0,
- summary_index: 1,
- },
- ResponsesStreamEvent::OutputItemDone {
- output_index: 0,
- sequence_number: None,
- item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
- id: Some("rs_123".into()),
- summary: vec![
- ReasoningSummaryPart::SummaryText {
- text: "Thinking about the answer".into(),
- },
- ReasoningSummaryPart::SummaryText {
- text: "Second part".into(),
- },
- ],
- }),
- },
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 1,
- sequence_number: None,
- item: response_item_message("msg_456"),
- },
- ResponsesStreamEvent::OutputTextDelta {
- item_id: "msg_456".into(),
- output_index: 1,
- content_index: Some(0),
- delta: "The answer is 42".into(),
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
-
- let thinking_events: Vec<_> = mapped
- .iter()
- .filter(|e| matches!(e, LanguageModelCompletionEvent::Thinking { .. }))
- .collect();
- assert_eq!(
- thinking_events.len(),
- 4,
- "expected 4 thinking events (2 deltas + separator + second delta), got {:?}",
- thinking_events,
- );
-
- assert!(matches!(
- &thinking_events[0],
- LanguageModelCompletionEvent::Thinking { text, .. } if text == "Thinking about"
- ));
- assert!(matches!(
- &thinking_events[1],
- LanguageModelCompletionEvent::Thinking { text, .. } if text == " the answer"
- ));
- assert!(
- matches!(
- &thinking_events[2],
- LanguageModelCompletionEvent::Thinking { text, .. } if text == "\n\n"
- ),
- "expected separator between summary parts"
- );
- assert!(matches!(
- &thinking_events[3],
- LanguageModelCompletionEvent::Thinking { text, .. } if text == "Second part"
- ));
-
- assert!(mapped.iter().any(|e| matches!(
- e,
- LanguageModelCompletionEvent::Text(t) if t == "The answer is 42"
- )));
- }
-
- #[test]
- fn responses_stream_maps_reasoning_from_done_only() {
- let events = vec![
- ResponsesStreamEvent::OutputItemAdded {
- output_index: 0,
- sequence_number: None,
- item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
- id: Some("rs_789".into()),
- summary: vec![],
- }),
- },
- ResponsesStreamEvent::OutputItemDone {
- output_index: 0,
- sequence_number: None,
- item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
- id: Some("rs_789".into()),
- summary: vec![ReasoningSummaryPart::SummaryText {
- text: "Summary without deltas".into(),
- }],
- }),
- },
- ResponsesStreamEvent::Completed {
- response: ResponseSummary::default(),
- },
- ];
-
- let mapped = map_response_events(events);
-
- assert!(
- !mapped
- .iter()
- .any(|e| matches!(e, LanguageModelCompletionEvent::Thinking { .. })),
- "OutputItemDone reasoning should not produce Thinking events (no delta/done text events)"
- );
- }
-}
@@ -403,7 +403,7 @@ impl LanguageModel for OpenAiCompatibleLanguageModel {
self.model.capabilities.parallel_tool_calls,
self.model.capabilities.prompt_cache_key,
self.max_output_tokens(),
- self.model.reasoning_effort.clone(),
+ self.model.reasoning_effort,
);
let completions = self.stream_completion(request, cx);
async move {
@@ -418,7 +418,7 @@ impl LanguageModel for OpenAiCompatibleLanguageModel {
self.model.capabilities.parallel_tool_calls,
self.model.capabilities.prompt_cache_key,
self.max_output_tokens(),
- self.model.reasoning_effort.clone(),
+ self.model.reasoning_effort,
);
let completions = self.stream_response(request, cx);
async move {
@@ -22,7 +22,7 @@ use ui::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
use ui_input::InputField;
use util::ResultExt;
-use crate::provider::util::{fix_streamed_json, parse_tool_arguments};
+use language_model::util::{fix_streamed_json, parse_tool_arguments};
const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("openrouter");
const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("OpenRouter");
@@ -9,7 +9,7 @@ use language_model::{
LanguageModelCompletionEvent, LanguageModelId, LanguageModelName, LanguageModelProvider,
LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
LanguageModelRequest, LanguageModelToolChoice, LanguageModelToolSchemaFormat, RateLimiter,
- Role, env_var,
+ env_var,
};
use open_ai::ResponseStreamEvent;
pub use settings::XaiAvailableModel as AvailableModel;
@@ -19,7 +19,8 @@ use strum::IntoEnumIterator;
use ui::{ButtonLink, ConfiguredApiCard, List, ListBulletItem, prelude::*};
use ui_input::InputField;
use util::ResultExt;
-use x_ai::{Model, XAI_API_URL};
+use x_ai::XAI_API_URL;
+pub use x_ai::completion::count_xai_tokens;
const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("x_ai");
const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("xAI");
@@ -320,7 +321,9 @@ impl LanguageModel for XAiLanguageModel {
request: LanguageModelRequest,
cx: &App,
) -> BoxFuture<'static, Result<u64>> {
- count_xai_tokens(request, self.model.clone(), cx)
+ let model = self.model.clone();
+ cx.background_spawn(async move { count_xai_tokens(request, model) })
+ .boxed()
}
fn stream_completion(
@@ -354,37 +357,6 @@ impl LanguageModel for XAiLanguageModel {
}
}
-pub fn count_xai_tokens(
- request: LanguageModelRequest,
- model: Model,
- cx: &App,
-) -> BoxFuture<'static, Result<u64>> {
- cx.background_spawn(async move {
- let messages = request
- .messages
- .into_iter()
- .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
- role: match message.role {
- Role::User => "user".into(),
- Role::Assistant => "assistant".into(),
- Role::System => "system".into(),
- },
- content: Some(message.string_contents()),
- name: None,
- function_call: None,
- })
- .collect::<Vec<_>>();
-
- let model_name = if model.max_token_count() >= 100_000 {
- "gpt-4o"
- } else {
- "gpt-4"
- };
- tiktoken_rs::num_tokens_from_messages(model_name, &messages).map(|tokens| tokens as u64)
- })
- .boxed()
-}
-
struct ConfigurationView {
api_key_editor: Entity<InputField>,
state: Entity<State>,
@@ -0,0 +1,33 @@
+[package]
+name = "language_models_cloud"
+version = "0.1.0"
+edition.workspace = true
+publish.workspace = true
+license = "GPL-3.0-or-later"
+
+[lints]
+workspace = true
+
+[lib]
+path = "src/language_models_cloud.rs"
+
+[dependencies]
+anthropic = { workspace = true, features = ["schemars"] }
+anyhow.workspace = true
+cloud_llm_client.workspace = true
+futures.workspace = true
+google_ai = { workspace = true, features = ["schemars"] }
+gpui.workspace = true
+http_client.workspace = true
+language_model.workspace = true
+open_ai = { workspace = true, features = ["schemars"] }
+schemars.workspace = true
+semver.workspace = true
+serde.workspace = true
+serde_json.workspace = true
+smol.workspace = true
+thiserror.workspace = true
+x_ai = { workspace = true, features = ["schemars"] }
+
+[dev-dependencies]
+language_model = { workspace = true, features = ["test-support"] }
@@ -0,0 +1 @@
+../../LICENSE-GPL
@@ -0,0 +1,1059 @@
+use anthropic::AnthropicModelMode;
+use anyhow::{Context as _, Result, anyhow};
+use cloud_llm_client::{
+ CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, CLIENT_SUPPORTS_STATUS_STREAM_ENDED_HEADER_NAME,
+ CLIENT_SUPPORTS_X_AI_HEADER_NAME, CompletionBody, CompletionEvent, CompletionRequestStatus,
+ CountTokensBody, CountTokensResponse, EXPIRED_LLM_TOKEN_HEADER_NAME, ListModelsResponse,
+ OUTDATED_LLM_TOKEN_HEADER_NAME, SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME,
+ ZED_VERSION_HEADER_NAME,
+};
+use futures::{
+ AsyncBufReadExt, FutureExt, Stream, StreamExt,
+ future::BoxFuture,
+ stream::{self, BoxStream},
+};
+use google_ai::GoogleModelMode;
+use gpui::{App, AppContext, AsyncApp, Context, Task};
+use http_client::http::{HeaderMap, HeaderValue};
+use http_client::{
+ AsyncBody, HttpClient, HttpClientWithUrl, HttpRequestExt, Method, Response, StatusCode,
+};
+use language_model::{
+ ANTHROPIC_PROVIDER_ID, ANTHROPIC_PROVIDER_NAME, GOOGLE_PROVIDER_ID, GOOGLE_PROVIDER_NAME,
+ LanguageModel, LanguageModelCacheConfiguration, LanguageModelCompletionError,
+ LanguageModelCompletionEvent, LanguageModelEffortLevel, LanguageModelId, LanguageModelName,
+ LanguageModelProviderId, LanguageModelProviderName, LanguageModelRequest,
+ LanguageModelToolChoice, LanguageModelToolSchemaFormat, OPEN_AI_PROVIDER_ID,
+ OPEN_AI_PROVIDER_NAME, PaymentRequiredError, RateLimiter, X_AI_PROVIDER_ID, X_AI_PROVIDER_NAME,
+ ZED_CLOUD_PROVIDER_ID, ZED_CLOUD_PROVIDER_NAME,
+};
+
+use schemars::JsonSchema;
+use semver::Version;
+use serde::{Deserialize, Serialize, de::DeserializeOwned};
+use smol::io::{AsyncReadExt, BufReader};
+use std::collections::VecDeque;
+use std::pin::Pin;
+use std::str::FromStr;
+use std::sync::Arc;
+use std::task::Poll;
+use std::time::Duration;
+use thiserror::Error;
+
+use anthropic::completion::{
+ AnthropicEventMapper, count_anthropic_tokens_with_tiktoken, into_anthropic,
+};
+use google_ai::completion::{GoogleEventMapper, into_google};
+use open_ai::completion::{
+ OpenAiEventMapper, OpenAiResponseEventMapper, count_open_ai_tokens, into_open_ai,
+ into_open_ai_response,
+};
+use x_ai::completion::count_xai_tokens;
+
+const PROVIDER_ID: LanguageModelProviderId = ZED_CLOUD_PROVIDER_ID;
+const PROVIDER_NAME: LanguageModelProviderName = ZED_CLOUD_PROVIDER_NAME;
+
+/// Trait for acquiring and refreshing LLM authentication tokens.
+pub trait CloudLlmTokenProvider: Send + Sync {
+ type AuthContext: Clone + Send + 'static;
+
+ fn auth_context(&self, cx: &AsyncApp) -> Self::AuthContext;
+ fn acquire_token(&self, auth_context: Self::AuthContext) -> BoxFuture<'static, Result<String>>;
+ fn refresh_token(&self, auth_context: Self::AuthContext) -> BoxFuture<'static, Result<String>>;
+}
+
+#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
+#[serde(tag = "type", rename_all = "lowercase")]
+pub enum ModelMode {
+ #[default]
+ Default,
+ Thinking {
+ /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
+ budget_tokens: Option<u32>,
+ },
+}
+
+impl From<ModelMode> for AnthropicModelMode {
+ fn from(value: ModelMode) -> Self {
+ match value {
+ ModelMode::Default => AnthropicModelMode::Default,
+ ModelMode::Thinking { budget_tokens } => AnthropicModelMode::Thinking { budget_tokens },
+ }
+ }
+}
+
+pub struct CloudLanguageModel<TP: CloudLlmTokenProvider> {
+ pub id: LanguageModelId,
+ pub model: Arc<cloud_llm_client::LanguageModel>,
+ pub token_provider: Arc<TP>,
+ pub http_client: Arc<HttpClientWithUrl>,
+ pub app_version: Option<Version>,
+ pub request_limiter: RateLimiter,
+}
+
+pub struct PerformLlmCompletionResponse {
+ pub response: Response<AsyncBody>,
+ pub includes_status_messages: bool,
+}
+
+impl<TP: CloudLlmTokenProvider> CloudLanguageModel<TP> {
+ pub async fn perform_llm_completion(
+ http_client: &HttpClientWithUrl,
+ token_provider: &TP,
+ auth_context: TP::AuthContext,
+ app_version: Option<Version>,
+ body: CompletionBody,
+ ) -> Result<PerformLlmCompletionResponse> {
+ let mut token = token_provider.acquire_token(auth_context.clone()).await?;
+ let mut refreshed_token = false;
+
+ loop {
+ let request = http_client::Request::builder()
+ .method(Method::POST)
+ .uri(http_client.build_zed_llm_url("/completions", &[])?.as_ref())
+ .when_some(app_version.as_ref(), |builder, app_version| {
+ builder.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
+ })
+ .header("Content-Type", "application/json")
+ .header("Authorization", format!("Bearer {token}"))
+ .header(CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, "true")
+ .header(CLIENT_SUPPORTS_STATUS_STREAM_ENDED_HEADER_NAME, "true")
+ .body(serde_json::to_string(&body)?.into())?;
+
+ let mut response = http_client.send(request).await?;
+ let status = response.status();
+ if status.is_success() {
+ let includes_status_messages = response
+ .headers()
+ .get(SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME)
+ .is_some();
+
+ return Ok(PerformLlmCompletionResponse {
+ response,
+ includes_status_messages,
+ });
+ }
+
+ if !refreshed_token && needs_llm_token_refresh(&response) {
+ token = token_provider.refresh_token(auth_context.clone()).await?;
+ refreshed_token = true;
+ continue;
+ }
+
+ if status == StatusCode::PAYMENT_REQUIRED {
+ return Err(anyhow!(PaymentRequiredError));
+ }
+
+ let mut body = String::new();
+ let headers = response.headers().clone();
+ response.body_mut().read_to_string(&mut body).await?;
+ return Err(anyhow!(ApiError {
+ status,
+ body,
+ headers
+ }));
+ }
+ }
+}
+
+fn needs_llm_token_refresh(response: &Response<AsyncBody>) -> bool {
+ response
+ .headers()
+ .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
+ .is_some()
+ || response
+ .headers()
+ .get(OUTDATED_LLM_TOKEN_HEADER_NAME)
+ .is_some()
+}
+
+#[derive(Debug, Error)]
+#[error("cloud language model request failed with status {status}: {body}")]
+struct ApiError {
+ status: StatusCode,
+ body: String,
+ headers: HeaderMap<HeaderValue>,
+}
+
+/// Represents error responses from Zed's cloud API.
+///
+/// Example JSON for an upstream HTTP error:
+/// ```json
+/// {
+/// "code": "upstream_http_error",
+/// "message": "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout",
+/// "upstream_status": 503
+/// }
+/// ```
+#[derive(Debug, serde::Deserialize)]
+struct CloudApiError {
+ code: String,
+ message: String,
+ #[serde(default)]
+ #[serde(deserialize_with = "deserialize_optional_status_code")]
+ upstream_status: Option<StatusCode>,
+ #[serde(default)]
+ retry_after: Option<f64>,
+}
+
+fn deserialize_optional_status_code<'de, D>(deserializer: D) -> Result<Option<StatusCode>, D::Error>
+where
+ D: serde::Deserializer<'de>,
+{
+ let opt: Option<u16> = Option::deserialize(deserializer)?;
+ Ok(opt.and_then(|code| StatusCode::from_u16(code).ok()))
+}
+
+impl From<ApiError> for LanguageModelCompletionError {
+ fn from(error: ApiError) -> Self {
+ if let Ok(cloud_error) = serde_json::from_str::<CloudApiError>(&error.body) {
+ if cloud_error.code.starts_with("upstream_http_") {
+ let status = if let Some(status) = cloud_error.upstream_status {
+ status
+ } else if cloud_error.code.ends_with("_error") {
+ error.status
+ } else {
+ // If there's a status code in the code string (e.g. "upstream_http_429")
+ // then use that; otherwise, see if the JSON contains a status code.
+ cloud_error
+ .code
+ .strip_prefix("upstream_http_")
+ .and_then(|code_str| code_str.parse::<u16>().ok())
+ .and_then(|code| StatusCode::from_u16(code).ok())
+ .unwrap_or(error.status)
+ };
+
+ return LanguageModelCompletionError::UpstreamProviderError {
+ message: cloud_error.message,
+ status,
+ retry_after: cloud_error.retry_after.map(Duration::from_secs_f64),
+ };
+ }
+
+ return LanguageModelCompletionError::from_http_status(
+ PROVIDER_NAME,
+ error.status,
+ cloud_error.message,
+ None,
+ );
+ }
+
+ let retry_after = None;
+ LanguageModelCompletionError::from_http_status(
+ PROVIDER_NAME,
+ error.status,
+ error.body,
+ retry_after,
+ )
+ }
+}
+
+impl<TP: CloudLlmTokenProvider + 'static> LanguageModel for CloudLanguageModel<TP> {
+ fn id(&self) -> LanguageModelId {
+ self.id.clone()
+ }
+
+ fn name(&self) -> LanguageModelName {
+ LanguageModelName::from(self.model.display_name.clone())
+ }
+
+ fn provider_id(&self) -> LanguageModelProviderId {
+ PROVIDER_ID
+ }
+
+ fn provider_name(&self) -> LanguageModelProviderName {
+ PROVIDER_NAME
+ }
+
+ fn upstream_provider_id(&self) -> LanguageModelProviderId {
+ use cloud_llm_client::LanguageModelProvider::*;
+ match self.model.provider {
+ Anthropic => ANTHROPIC_PROVIDER_ID,
+ OpenAi => OPEN_AI_PROVIDER_ID,
+ Google => GOOGLE_PROVIDER_ID,
+ XAi => X_AI_PROVIDER_ID,
+ }
+ }
+
+ fn upstream_provider_name(&self) -> LanguageModelProviderName {
+ use cloud_llm_client::LanguageModelProvider::*;
+ match self.model.provider {
+ Anthropic => ANTHROPIC_PROVIDER_NAME,
+ OpenAi => OPEN_AI_PROVIDER_NAME,
+ Google => GOOGLE_PROVIDER_NAME,
+ XAi => X_AI_PROVIDER_NAME,
+ }
+ }
+
+ fn is_latest(&self) -> bool {
+ self.model.is_latest
+ }
+
+ fn supports_tools(&self) -> bool {
+ self.model.supports_tools
+ }
+
+ fn supports_images(&self) -> bool {
+ self.model.supports_images
+ }
+
+ fn supports_thinking(&self) -> bool {
+ self.model.supports_thinking
+ }
+
+ fn supports_fast_mode(&self) -> bool {
+ self.model.supports_fast_mode
+ }
+
+ fn supported_effort_levels(&self) -> Vec<LanguageModelEffortLevel> {
+ self.model
+ .supported_effort_levels
+ .iter()
+ .map(|effort_level| LanguageModelEffortLevel {
+ name: effort_level.name.clone().into(),
+ value: effort_level.value.clone().into(),
+ is_default: effort_level.is_default.unwrap_or(false),
+ })
+ .collect()
+ }
+
+ fn supports_streaming_tools(&self) -> bool {
+ self.model.supports_streaming_tools
+ }
+
+ fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
+ match choice {
+ LanguageModelToolChoice::Auto
+ | LanguageModelToolChoice::Any
+ | LanguageModelToolChoice::None => true,
+ }
+ }
+
+ fn supports_split_token_display(&self) -> bool {
+ use cloud_llm_client::LanguageModelProvider::*;
+ matches!(self.model.provider, OpenAi | XAi)
+ }
+
+ fn telemetry_id(&self) -> String {
+ format!("zed.dev/{}", self.model.id)
+ }
+
+ fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
+ match self.model.provider {
+ cloud_llm_client::LanguageModelProvider::Anthropic
+ | cloud_llm_client::LanguageModelProvider::OpenAi => {
+ LanguageModelToolSchemaFormat::JsonSchema
+ }
+ cloud_llm_client::LanguageModelProvider::Google
+ | cloud_llm_client::LanguageModelProvider::XAi => {
+ LanguageModelToolSchemaFormat::JsonSchemaSubset
+ }
+ }
+ }
+
+ fn max_token_count(&self) -> u64 {
+ self.model.max_token_count as u64
+ }
+
+ fn max_output_tokens(&self) -> Option<u64> {
+ Some(self.model.max_output_tokens as u64)
+ }
+
+ fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
+ match &self.model.provider {
+ cloud_llm_client::LanguageModelProvider::Anthropic => {
+ Some(LanguageModelCacheConfiguration {
+ min_total_token: 2_048,
+ should_speculate: true,
+ max_cache_anchors: 4,
+ })
+ }
+ cloud_llm_client::LanguageModelProvider::OpenAi
+ | cloud_llm_client::LanguageModelProvider::XAi
+ | cloud_llm_client::LanguageModelProvider::Google => None,
+ }
+ }
+
+ fn count_tokens(
+ &self,
+ request: LanguageModelRequest,
+ cx: &App,
+ ) -> BoxFuture<'static, Result<u64>> {
+ match self.model.provider {
+ cloud_llm_client::LanguageModelProvider::Anthropic => cx
+ .background_spawn(async move { count_anthropic_tokens_with_tiktoken(request) })
+ .boxed(),
+ cloud_llm_client::LanguageModelProvider::OpenAi => {
+ let model = match open_ai::Model::from_id(&self.model.id.0) {
+ Ok(model) => model,
+ Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
+ };
+ cx.background_spawn(async move { count_open_ai_tokens(request, model) })
+ .boxed()
+ }
+ cloud_llm_client::LanguageModelProvider::XAi => {
+ let model = match x_ai::Model::from_id(&self.model.id.0) {
+ Ok(model) => model,
+ Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
+ };
+ cx.background_spawn(async move { count_xai_tokens(request, model) })
+ .boxed()
+ }
+ cloud_llm_client::LanguageModelProvider::Google => {
+ let http_client = self.http_client.clone();
+ let token_provider = self.token_provider.clone();
+ let model_id = self.model.id.to_string();
+ let generate_content_request =
+ into_google(request, model_id.clone(), GoogleModelMode::Default);
+ let auth_context = token_provider.auth_context(&cx.to_async());
+ async move {
+ let token = token_provider.acquire_token(auth_context).await?;
+
+ let request_body = CountTokensBody {
+ provider: cloud_llm_client::LanguageModelProvider::Google,
+ model: model_id,
+ provider_request: serde_json::to_value(&google_ai::CountTokensRequest {
+ generate_content_request,
+ })?,
+ };
+ let request = http_client::Request::builder()
+ .method(Method::POST)
+ .uri(
+ http_client
+ .build_zed_llm_url("/count_tokens", &[])?
+ .as_ref(),
+ )
+ .header("Content-Type", "application/json")
+ .header("Authorization", format!("Bearer {token}"))
+ .body(serde_json::to_string(&request_body)?.into())?;
+ let mut response = http_client.send(request).await?;
+ let status = response.status();
+ let headers = response.headers().clone();
+ let mut response_body = String::new();
+ response
+ .body_mut()
+ .read_to_string(&mut response_body)
+ .await?;
+
+ if status.is_success() {
+ let response_body: CountTokensResponse =
+ serde_json::from_str(&response_body)?;
+
+ Ok(response_body.tokens as u64)
+ } else {
+ Err(anyhow!(ApiError {
+ status,
+ body: response_body,
+ headers
+ }))
+ }
+ }
+ .boxed()
+ }
+ }
+ }
+
+ fn stream_completion(
+ &self,
+ request: LanguageModelRequest,
+ cx: &AsyncApp,
+ ) -> BoxFuture<
+ 'static,
+ Result<
+ BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
+ LanguageModelCompletionError,
+ >,
+ > {
+ let thread_id = request.thread_id.clone();
+ let prompt_id = request.prompt_id.clone();
+ let app_version = self.app_version.clone();
+ let thinking_allowed = request.thinking_allowed;
+ let enable_thinking = thinking_allowed && self.model.supports_thinking;
+ let provider_name = provider_name(&self.model.provider);
+ match self.model.provider {
+ cloud_llm_client::LanguageModelProvider::Anthropic => {
+ let effort = request
+ .thinking_effort
+ .as_ref()
+ .and_then(|effort| anthropic::Effort::from_str(effort).ok());
+
+ let mut request = into_anthropic(
+ request,
+ self.model.id.to_string(),
+ 1.0,
+ self.model.max_output_tokens as u64,
+ if enable_thinking {
+ AnthropicModelMode::Thinking {
+ budget_tokens: Some(4_096),
+ }
+ } else {
+ AnthropicModelMode::Default
+ },
+ );
+
+ if enable_thinking && effort.is_some() {
+ request.thinking = Some(anthropic::Thinking::Adaptive);
+ request.output_config = Some(anthropic::OutputConfig { effort });
+ }
+
+ let http_client = self.http_client.clone();
+ let token_provider = self.token_provider.clone();
+ let auth_context = token_provider.auth_context(cx);
+ let future = self.request_limiter.stream(async move {
+ let PerformLlmCompletionResponse {
+ response,
+ includes_status_messages,
+ } = Self::perform_llm_completion(
+ &http_client,
+ &*token_provider,
+ auth_context,
+ app_version,
+ CompletionBody {
+ thread_id,
+ prompt_id,
+ provider: cloud_llm_client::LanguageModelProvider::Anthropic,
+ model: request.model.clone(),
+ provider_request: serde_json::to_value(&request)
+ .map_err(|e| anyhow!(e))?,
+ },
+ )
+ .await
+ .map_err(|err| match err.downcast::<ApiError>() {
+ Ok(api_err) => anyhow!(LanguageModelCompletionError::from(api_err)),
+ Err(err) => anyhow!(err),
+ })?;
+
+ let mut mapper = AnthropicEventMapper::new();
+ Ok(map_cloud_completion_events(
+ Box::pin(response_lines(response, includes_status_messages)),
+ &provider_name,
+ move |event| mapper.map_event(event),
+ ))
+ });
+ async move { Ok(future.await?.boxed()) }.boxed()
+ }
+ cloud_llm_client::LanguageModelProvider::OpenAi => {
+ let http_client = self.http_client.clone();
+ let token_provider = self.token_provider.clone();
+ let effort = request
+ .thinking_effort
+ .as_ref()
+ .and_then(|effort| open_ai::ReasoningEffort::from_str(effort).ok());
+
+ let mut request = into_open_ai_response(
+ request,
+ &self.model.id.0,
+ self.model.supports_parallel_tool_calls,
+ true,
+ None,
+ None,
+ );
+
+ if enable_thinking && let Some(effort) = effort {
+ request.reasoning = Some(open_ai::responses::ReasoningConfig {
+ effort,
+ summary: Some(open_ai::responses::ReasoningSummaryMode::Auto),
+ });
+ }
+
+ let auth_context = token_provider.auth_context(cx);
+ let future = self.request_limiter.stream(async move {
+ let PerformLlmCompletionResponse {
+ response,
+ includes_status_messages,
+ } = Self::perform_llm_completion(
+ &http_client,
+ &*token_provider,
+ auth_context,
+ app_version,
+ CompletionBody {
+ thread_id,
+ prompt_id,
+ provider: cloud_llm_client::LanguageModelProvider::OpenAi,
+ model: request.model.clone(),
+ provider_request: serde_json::to_value(&request)
+ .map_err(|e| anyhow!(e))?,
+ },
+ )
+ .await?;
+
+ let mut mapper = OpenAiResponseEventMapper::new();
+ Ok(map_cloud_completion_events(
+ Box::pin(response_lines(response, includes_status_messages)),
+ &provider_name,
+ move |event| mapper.map_event(event),
+ ))
+ });
+ async move { Ok(future.await?.boxed()) }.boxed()
+ }
+ cloud_llm_client::LanguageModelProvider::XAi => {
+ let http_client = self.http_client.clone();
+ let token_provider = self.token_provider.clone();
+ let request = into_open_ai(
+ request,
+ &self.model.id.0,
+ self.model.supports_parallel_tool_calls,
+ false,
+ None,
+ None,
+ );
+ let auth_context = token_provider.auth_context(cx);
+ let future = self.request_limiter.stream(async move {
+ let PerformLlmCompletionResponse {
+ response,
+ includes_status_messages,
+ } = Self::perform_llm_completion(
+ &http_client,
+ &*token_provider,
+ auth_context,
+ app_version,
+ CompletionBody {
+ thread_id,
+ prompt_id,
+ provider: cloud_llm_client::LanguageModelProvider::XAi,
+ model: request.model.clone(),
+ provider_request: serde_json::to_value(&request)
+ .map_err(|e| anyhow!(e))?,
+ },
+ )
+ .await?;
+
+ let mut mapper = OpenAiEventMapper::new();
+ Ok(map_cloud_completion_events(
+ Box::pin(response_lines(response, includes_status_messages)),
+ &provider_name,
+ move |event| mapper.map_event(event),
+ ))
+ });
+ async move { Ok(future.await?.boxed()) }.boxed()
+ }
+ cloud_llm_client::LanguageModelProvider::Google => {
+ let http_client = self.http_client.clone();
+ let token_provider = self.token_provider.clone();
+ let request =
+ into_google(request, self.model.id.to_string(), GoogleModelMode::Default);
+ let auth_context = token_provider.auth_context(cx);
+ let future = self.request_limiter.stream(async move {
+ let PerformLlmCompletionResponse {
+ response,
+ includes_status_messages,
+ } = Self::perform_llm_completion(
+ &http_client,
+ &*token_provider,
+ auth_context,
+ app_version,
+ CompletionBody {
+ thread_id,
+ prompt_id,
+ provider: cloud_llm_client::LanguageModelProvider::Google,
+ model: request.model.model_id.clone(),
+ provider_request: serde_json::to_value(&request)
+ .map_err(|e| anyhow!(e))?,
+ },
+ )
+ .await?;
+
+ let mut mapper = GoogleEventMapper::new();
+ Ok(map_cloud_completion_events(
+ Box::pin(response_lines(response, includes_status_messages)),
+ &provider_name,
+ move |event| mapper.map_event(event),
+ ))
+ });
+ async move { Ok(future.await?.boxed()) }.boxed()
+ }
+ }
+ }
+}
+
+pub struct CloudModelProvider<TP: CloudLlmTokenProvider> {
+ token_provider: Arc<TP>,
+ http_client: Arc<HttpClientWithUrl>,
+ app_version: Option<Version>,
+ models: Vec<Arc<cloud_llm_client::LanguageModel>>,
+ default_model: Option<Arc<cloud_llm_client::LanguageModel>>,
+ default_fast_model: Option<Arc<cloud_llm_client::LanguageModel>>,
+ recommended_models: Vec<Arc<cloud_llm_client::LanguageModel>>,
+}
+
+impl<TP: CloudLlmTokenProvider + 'static> CloudModelProvider<TP> {
+ pub fn new(
+ token_provider: Arc<TP>,
+ http_client: Arc<HttpClientWithUrl>,
+ app_version: Option<Version>,
+ ) -> Self {
+ Self {
+ token_provider,
+ http_client,
+ app_version,
+ models: Vec::new(),
+ default_model: None,
+ default_fast_model: None,
+ recommended_models: Vec::new(),
+ }
+ }
+
+ pub fn refresh_models(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
+ let http_client = self.http_client.clone();
+ let token_provider = self.token_provider.clone();
+ cx.spawn(async move |this, cx| {
+ let auth_context = token_provider.auth_context(cx);
+ let response =
+ Self::fetch_models_request(&http_client, &*token_provider, auth_context).await?;
+ this.update(cx, |this, cx| {
+ this.update_models(response);
+ cx.notify();
+ })
+ })
+ }
+
+ async fn fetch_models_request(
+ http_client: &HttpClientWithUrl,
+ token_provider: &TP,
+ auth_context: TP::AuthContext,
+ ) -> Result<ListModelsResponse> {
+ let token = token_provider.acquire_token(auth_context).await?;
+
+ let request = http_client::Request::builder()
+ .method(Method::GET)
+ .header(CLIENT_SUPPORTS_X_AI_HEADER_NAME, "true")
+ .uri(http_client.build_zed_llm_url("/models", &[])?.as_ref())
+ .header("Authorization", format!("Bearer {token}"))
+ .body(AsyncBody::empty())?;
+ let mut response = http_client
+ .send(request)
+ .await
+ .context("failed to send list models request")?;
+
+ if response.status().is_success() {
+ let mut body = String::new();
+ response.body_mut().read_to_string(&mut body).await?;
+ Ok(serde_json::from_str(&body)?)
+ } else {
+ let mut body = String::new();
+ response.body_mut().read_to_string(&mut body).await?;
+ anyhow::bail!(
+ "error listing models.\nStatus: {:?}\nBody: {body}",
+ response.status(),
+ );
+ }
+ }
+
+ pub fn update_models(&mut self, response: ListModelsResponse) {
+ let models: Vec<_> = response.models.into_iter().map(Arc::new).collect();
+
+ self.default_model = models
+ .iter()
+ .find(|model| {
+ response
+ .default_model
+ .as_ref()
+ .is_some_and(|default_model_id| &model.id == default_model_id)
+ })
+ .cloned();
+ self.default_fast_model = models
+ .iter()
+ .find(|model| {
+ response
+ .default_fast_model
+ .as_ref()
+ .is_some_and(|default_fast_model_id| &model.id == default_fast_model_id)
+ })
+ .cloned();
+ self.recommended_models = response
+ .recommended_models
+ .iter()
+ .filter_map(|id| models.iter().find(|model| &model.id == id))
+ .cloned()
+ .collect();
+ self.models = models;
+ }
+
+ pub fn create_model(
+ &self,
+ model: &Arc<cloud_llm_client::LanguageModel>,
+ ) -> Arc<dyn LanguageModel> {
+ Arc::new(CloudLanguageModel::<TP> {
+ id: LanguageModelId::from(model.id.0.to_string()),
+ model: model.clone(),
+ token_provider: self.token_provider.clone(),
+ http_client: self.http_client.clone(),
+ app_version: self.app_version.clone(),
+ request_limiter: RateLimiter::new(4),
+ })
+ }
+
+ pub fn models(&self) -> &[Arc<cloud_llm_client::LanguageModel>] {
+ &self.models
+ }
+
+ pub fn default_model(&self) -> Option<&Arc<cloud_llm_client::LanguageModel>> {
+ self.default_model.as_ref()
+ }
+
+ pub fn default_fast_model(&self) -> Option<&Arc<cloud_llm_client::LanguageModel>> {
+ self.default_fast_model.as_ref()
+ }
+
+ pub fn recommended_models(&self) -> &[Arc<cloud_llm_client::LanguageModel>] {
+ &self.recommended_models
+ }
+}
+
+pub fn map_cloud_completion_events<T, F>(
+ stream: Pin<Box<dyn Stream<Item = Result<CompletionEvent<T>>> + Send>>,
+ provider: &LanguageModelProviderName,
+ mut map_callback: F,
+) -> BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
+where
+ T: DeserializeOwned + 'static,
+ F: FnMut(T) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
+ + Send
+ + 'static,
+{
+ let provider = provider.clone();
+ let mut stream = stream.fuse();
+
+ let mut saw_stream_ended = false;
+
+ let mut done = false;
+ let mut pending = VecDeque::new();
+
+ stream::poll_fn(move |cx| {
+ loop {
+ if let Some(item) = pending.pop_front() {
+ return Poll::Ready(Some(item));
+ }
+
+ if done {
+ return Poll::Ready(None);
+ }
+
+ match stream.poll_next_unpin(cx) {
+ Poll::Ready(Some(event)) => {
+ let items = match event {
+ Err(error) => {
+ vec![Err(LanguageModelCompletionError::from(error))]
+ }
+ Ok(CompletionEvent::Status(CompletionRequestStatus::StreamEnded)) => {
+ saw_stream_ended = true;
+ vec![]
+ }
+ Ok(CompletionEvent::Status(status)) => {
+ LanguageModelCompletionEvent::from_completion_request_status(
+ status,
+ provider.clone(),
+ )
+ .transpose()
+ .map(|event| vec![event])
+ .unwrap_or_default()
+ }
+ Ok(CompletionEvent::Event(event)) => map_callback(event),
+ };
+ pending.extend(items);
+ }
+ Poll::Ready(None) => {
+ done = true;
+
+ if !saw_stream_ended {
+ return Poll::Ready(Some(Err(
+ LanguageModelCompletionError::StreamEndedUnexpectedly {
+ provider: provider.clone(),
+ },
+ )));
+ }
+ }
+ Poll::Pending => return Poll::Pending,
+ }
+ }
+ })
+ .boxed()
+}
+
+pub fn provider_name(
+ provider: &cloud_llm_client::LanguageModelProvider,
+) -> LanguageModelProviderName {
+ match provider {
+ cloud_llm_client::LanguageModelProvider::Anthropic => ANTHROPIC_PROVIDER_NAME,
+ cloud_llm_client::LanguageModelProvider::OpenAi => OPEN_AI_PROVIDER_NAME,
+ cloud_llm_client::LanguageModelProvider::Google => GOOGLE_PROVIDER_NAME,
+ cloud_llm_client::LanguageModelProvider::XAi => X_AI_PROVIDER_NAME,
+ }
+}
+
+pub fn response_lines<T: DeserializeOwned>(
+ response: Response<AsyncBody>,
+ includes_status_messages: bool,
+) -> impl Stream<Item = Result<CompletionEvent<T>>> {
+ futures::stream::try_unfold(
+ (String::new(), BufReader::new(response.into_body())),
+ move |(mut line, mut body)| async move {
+ match body.read_line(&mut line).await {
+ Ok(0) => Ok(None),
+ Ok(_) => {
+ let event = if includes_status_messages {
+ serde_json::from_str::<CompletionEvent<T>>(&line)?
+ } else {
+ CompletionEvent::Event(serde_json::from_str::<T>(&line)?)
+ };
+
+ line.clear();
+ Ok(Some((event, (line, body))))
+ }
+ Err(e) => Err(e.into()),
+ }
+ },
+ )
+}
+
+#[cfg(test)]
+mod tests {
+ use super::*;
+ use http_client::http::{HeaderMap, StatusCode};
+ use language_model::LanguageModelCompletionError;
+
+ #[test]
+ fn test_api_error_conversion_with_upstream_http_error() {
+ // upstream_http_error with 503 status should become ServerOverloaded
+ let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout","upstream_status":503}"#;
+
+ let api_error = ApiError {
+ status: StatusCode::INTERNAL_SERVER_ERROR,
+ body: error_body.to_string(),
+ headers: HeaderMap::new(),
+ };
+
+ let completion_error: LanguageModelCompletionError = api_error.into();
+
+ match completion_error {
+ LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
+ assert_eq!(
+ message,
+ "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout"
+ );
+ }
+ _ => panic!(
+ "Expected UpstreamProviderError for upstream 503, got: {:?}",
+ completion_error
+ ),
+ }
+
+ // upstream_http_error with 500 status should become ApiInternalServerError
+ let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the OpenAI API: internal server error","upstream_status":500}"#;
+
+ let api_error = ApiError {
+ status: StatusCode::INTERNAL_SERVER_ERROR,
+ body: error_body.to_string(),
+ headers: HeaderMap::new(),
+ };
+
+ let completion_error: LanguageModelCompletionError = api_error.into();
+
+ match completion_error {
+ LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
+ assert_eq!(
+ message,
+ "Received an error from the OpenAI API: internal server error"
+ );
+ }
+ _ => panic!(
+ "Expected UpstreamProviderError for upstream 500, got: {:?}",
+ completion_error
+ ),
+ }
+
+ // upstream_http_error with 429 status should become RateLimitExceeded
+ let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the Google API: rate limit exceeded","upstream_status":429}"#;
+
+ let api_error = ApiError {
+ status: StatusCode::INTERNAL_SERVER_ERROR,
+ body: error_body.to_string(),
+ headers: HeaderMap::new(),
+ };
+
+ let completion_error: LanguageModelCompletionError = api_error.into();
+
+ match completion_error {
+ LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
+ assert_eq!(
+ message,
+ "Received an error from the Google API: rate limit exceeded"
+ );
+ }
+ _ => panic!(
+ "Expected UpstreamProviderError for upstream 429, got: {:?}",
+ completion_error
+ ),
+ }
+
+ // Regular 500 error without upstream_http_error should remain ApiInternalServerError for Zed
+ let error_body = "Regular internal server error";
+
+ let api_error = ApiError {
+ status: StatusCode::INTERNAL_SERVER_ERROR,
+ body: error_body.to_string(),
+ headers: HeaderMap::new(),
+ };
+
+ let completion_error: LanguageModelCompletionError = api_error.into();
+
+ match completion_error {
+ LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
+ assert_eq!(provider, PROVIDER_NAME);
+ assert_eq!(message, "Regular internal server error");
+ }
+ _ => panic!(
+ "Expected ApiInternalServerError for regular 500, got: {:?}",
+ completion_error
+ ),
+ }
+
+ // upstream_http_429 format should be converted to UpstreamProviderError
+ let error_body = r#"{"code":"upstream_http_429","message":"Upstream Anthropic rate limit exceeded.","retry_after":30.5}"#;
+
+ let api_error = ApiError {
+ status: StatusCode::INTERNAL_SERVER_ERROR,
+ body: error_body.to_string(),
+ headers: HeaderMap::new(),
+ };
+
+ let completion_error: LanguageModelCompletionError = api_error.into();
+
+ match completion_error {
+ LanguageModelCompletionError::UpstreamProviderError {
+ message,
+ status,
+ retry_after,
+ } => {
+ assert_eq!(message, "Upstream Anthropic rate limit exceeded.");
+ assert_eq!(status, StatusCode::TOO_MANY_REQUESTS);
+ assert_eq!(retry_after, Some(Duration::from_secs_f64(30.5)));
+ }
+ _ => panic!(
+ "Expected UpstreamProviderError for upstream_http_429, got: {:?}",
+ completion_error
+ ),
+ }
+
+ // Invalid JSON in error body should fall back to regular error handling
+ let error_body = "Not JSON at all";
+
+ let api_error = ApiError {
+ status: StatusCode::INTERNAL_SERVER_ERROR,
+ body: error_body.to_string(),
+ headers: HeaderMap::new(),
+ };
+
+ let completion_error: LanguageModelCompletionError = api_error.into();
+
+ match completion_error {
+ LanguageModelCompletionError::ApiInternalServerError { provider, .. } => {
+ assert_eq!(provider, PROVIDER_NAME);
+ }
+ _ => panic!(
+ "Expected ApiInternalServerError for invalid JSON, got: {:?}",
+ completion_error
+ ),
+ }
+ }
+}
@@ -1,6 +1,6 @@
use std::{cell::RefCell, collections::HashMap, mem, ops::Range};
-use gpui::{DefiniteLength, FontWeight, SharedString, px, relative};
+use gpui::{DefiniteLength, FontWeight, SharedString, TextAlign, px, relative};
use html5ever::{
Attribute, LocalName, ParseOpts, local_name, parse_document, tendril::TendrilSink,
};
@@ -24,10 +24,17 @@ pub(crate) enum ParsedHtmlElement {
List(ParsedHtmlList),
Table(ParsedHtmlTable),
BlockQuote(ParsedHtmlBlockQuote),
- Paragraph(HtmlParagraph),
+ Paragraph(ParsedHtmlParagraph),
Image(HtmlImage),
}
+#[derive(Debug, Clone)]
+#[cfg_attr(test, derive(PartialEq))]
+pub(crate) struct ParsedHtmlParagraph {
+ pub text_align: Option<TextAlign>,
+ pub contents: HtmlParagraph,
+}
+
impl ParsedHtmlElement {
pub fn source_range(&self) -> Option<Range<usize>> {
Some(match self {
@@ -35,7 +42,7 @@ impl ParsedHtmlElement {
Self::List(list) => list.source_range.clone(),
Self::Table(table) => table.source_range.clone(),
Self::BlockQuote(block_quote) => block_quote.source_range.clone(),
- Self::Paragraph(text) => match text.first()? {
+ Self::Paragraph(paragraph) => match paragraph.contents.first()? {
HtmlParagraphChunk::Text(text) => text.source_range.clone(),
HtmlParagraphChunk::Image(image) => image.source_range.clone(),
},
@@ -83,6 +90,7 @@ pub(crate) struct ParsedHtmlHeading {
pub source_range: Range<usize>,
pub level: HeadingLevel,
pub contents: HtmlParagraph,
+ pub text_align: Option<TextAlign>,
}
#[derive(Debug, Clone)]
@@ -236,20 +244,21 @@ fn parse_html_node(
consume_children(source_range, node, elements, context);
}
NodeData::Text { contents } => {
- elements.push(ParsedHtmlElement::Paragraph(vec![
- HtmlParagraphChunk::Text(ParsedHtmlText {
+ elements.push(ParsedHtmlElement::Paragraph(ParsedHtmlParagraph {
+ text_align: None,
+ contents: vec![HtmlParagraphChunk::Text(ParsedHtmlText {
source_range,
highlights: Vec::default(),
links: Vec::default(),
contents: contents.borrow().to_string().into(),
- }),
- ]));
+ })],
+ }));
}
NodeData::Comment { .. } => {}
NodeData::Element { name, attrs, .. } => {
- let mut styles = if let Some(styles) =
- html_style_from_html_styles(extract_styles_from_attributes(attrs))
- {
+ let styles_map = extract_styles_from_attributes(attrs);
+ let text_align = text_align_from_attributes(attrs, &styles_map);
+ let mut styles = if let Some(styles) = html_style_from_html_styles(styles_map) {
vec![styles]
} else {
Vec::default()
@@ -270,7 +279,10 @@ fn parse_html_node(
);
if !paragraph.is_empty() {
- elements.push(ParsedHtmlElement::Paragraph(paragraph));
+ elements.push(ParsedHtmlElement::Paragraph(ParsedHtmlParagraph {
+ text_align,
+ contents: paragraph,
+ }));
}
} else if matches!(
name.local,
@@ -303,6 +315,7 @@ fn parse_html_node(
_ => unreachable!(),
},
contents: paragraph,
+ text_align,
}));
}
} else if name.local == local_name!("ul") || name.local == local_name!("ol") {
@@ -589,6 +602,30 @@ fn html_style_from_html_styles(styles: HashMap<String, String>) -> Option<HtmlHi
}
}
+fn parse_text_align(value: &str) -> Option<TextAlign> {
+ match value.trim().to_ascii_lowercase().as_str() {
+ "left" => Some(TextAlign::Left),
+ "center" => Some(TextAlign::Center),
+ "right" => Some(TextAlign::Right),
+ _ => None,
+ }
+}
+
+fn text_align_from_styles(styles: &HashMap<String, String>) -> Option<TextAlign> {
+ styles
+ .get("text-align")
+ .and_then(|value| parse_text_align(value))
+}
+
+fn text_align_from_attributes(
+ attrs: &RefCell<Vec<Attribute>>,
+ styles: &HashMap<String, String>,
+) -> Option<TextAlign> {
+ text_align_from_styles(styles).or_else(|| {
+ attr_value(attrs, local_name!("align")).and_then(|value| parse_text_align(&value))
+ })
+}
+
fn extract_styles_from_attributes(attrs: &RefCell<Vec<Attribute>>) -> HashMap<String, String> {
let mut styles = HashMap::new();
@@ -770,6 +807,7 @@ fn extract_html_table(node: &Node, source_range: Range<usize>) -> Option<ParsedH
#[cfg(test)]
mod tests {
use super::*;
+ use gpui::TextAlign;
#[test]
fn parses_html_styled_text() {
@@ -783,7 +821,7 @@ mod tests {
let ParsedHtmlElement::Paragraph(paragraph) = &parsed.children[0] else {
panic!("expected paragraph");
};
- let HtmlParagraphChunk::Text(text) = ¶graph[0] else {
+ let HtmlParagraphChunk::Text(text) = ¶graph.contents[0] else {
panic!("expected text chunk");
};
@@ -851,7 +889,7 @@ mod tests {
let ParsedHtmlElement::Paragraph(paragraph) = &first_item.content[0] else {
panic!("expected first item paragraph");
};
- let HtmlParagraphChunk::Text(text) = ¶graph[0] else {
+ let HtmlParagraphChunk::Text(text) = ¶graph.contents[0] else {
panic!("expected first item text");
};
assert_eq!(text.contents.as_ref(), "parent");
@@ -866,7 +904,7 @@ mod tests {
else {
panic!("expected nested item paragraph");
};
- let HtmlParagraphChunk::Text(nested_text) = &nested_paragraph[0] else {
+ let HtmlParagraphChunk::Text(nested_text) = &nested_paragraph.contents[0] else {
panic!("expected nested item text");
};
assert_eq!(nested_text.contents.as_ref(), "child");
@@ -875,9 +913,58 @@ mod tests {
let ParsedHtmlElement::Paragraph(second_paragraph) = &second_item.content[0] else {
panic!("expected second item paragraph");
};
- let HtmlParagraphChunk::Text(second_text) = &second_paragraph[0] else {
+ let HtmlParagraphChunk::Text(second_text) = &second_paragraph.contents[0] else {
panic!("expected second item text");
};
assert_eq!(second_text.contents.as_ref(), "sibling");
}
+
+ #[test]
+ fn parses_paragraph_text_align_from_style() {
+ let parsed = parse_html_block("<p style=\"text-align: center\">x</p>", 0..40).unwrap();
+ let ParsedHtmlElement::Paragraph(paragraph) = &parsed.children[0] else {
+ panic!("expected paragraph");
+ };
+ assert_eq!(paragraph.text_align, Some(TextAlign::Center));
+ }
+
+ #[test]
+ fn parses_heading_text_align_from_style() {
+ let parsed = parse_html_block("<h2 style=\"text-align: right\">Title</h2>", 0..45).unwrap();
+ let ParsedHtmlElement::Heading(heading) = &parsed.children[0] else {
+ panic!("expected heading");
+ };
+ assert_eq!(heading.text_align, Some(TextAlign::Right));
+ }
+
+ #[test]
+ fn parses_paragraph_text_align_from_align_attribute() {
+ let parsed = parse_html_block("<p align=\"center\">x</p>", 0..24).unwrap();
+ let ParsedHtmlElement::Paragraph(paragraph) = &parsed.children[0] else {
+ panic!("expected paragraph");
+ };
+ assert_eq!(paragraph.text_align, Some(TextAlign::Center));
+ }
+
+ #[test]
+ fn parses_heading_text_align_from_align_attribute() {
+ let parsed = parse_html_block("<h2 align=\"right\">Title</h2>", 0..30).unwrap();
+ let ParsedHtmlElement::Heading(heading) = &parsed.children[0] else {
+ panic!("expected heading");
+ };
+ assert_eq!(heading.text_align, Some(TextAlign::Right));
+ }
+
+ #[test]
+ fn prefers_style_text_align_over_align_attribute() {
+ let parsed = parse_html_block(
+ "<p align=\"left\" style=\"text-align: center\">x</p>",
+ 0..50,
+ )
+ .unwrap();
+ let ParsedHtmlElement::Paragraph(paragraph) = &parsed.children[0] else {
+ panic!("expected paragraph");
+ };
+ assert_eq!(paragraph.text_align, Some(TextAlign::Center));
+ }
}
@@ -79,9 +79,20 @@ impl MarkdownElement {
match element {
ParsedHtmlElement::Paragraph(paragraph) => {
- self.push_markdown_paragraph(builder, &source_range, markdown_end);
- self.render_html_paragraph(paragraph, source_allocator, builder, cx, markdown_end);
- builder.pop_div();
+ self.push_markdown_paragraph(
+ builder,
+ &source_range,
+ markdown_end,
+ paragraph.text_align,
+ );
+ self.render_html_paragraph(
+ ¶graph.contents,
+ source_allocator,
+ builder,
+ cx,
+ markdown_end,
+ );
+ self.pop_markdown_paragraph(builder);
}
ParsedHtmlElement::Heading(heading) => {
self.push_markdown_heading(
@@ -89,6 +100,7 @@ impl MarkdownElement {
heading.level,
&heading.source_range,
markdown_end,
+ heading.text_align,
);
self.render_html_paragraph(
&heading.contents,
@@ -36,8 +36,8 @@ use gpui::{
FocusHandle, Focusable, FontStyle, FontWeight, GlobalElementId, Hitbox, Hsla, Image,
ImageFormat, ImageSource, KeyContext, Length, MouseButton, MouseDownEvent, MouseEvent,
MouseMoveEvent, MouseUpEvent, Point, ScrollHandle, Stateful, StrikethroughStyle,
- StyleRefinement, StyledText, Task, TextLayout, TextRun, TextStyle, TextStyleRefinement,
- actions, img, point, quad,
+ StyleRefinement, StyledText, Task, TextAlign, TextLayout, TextRun, TextStyle,
+ TextStyleRefinement, actions, img, point, quad,
};
use language::{CharClassifier, Language, LanguageRegistry, Rope};
use parser::CodeBlockMetadata;
@@ -1025,8 +1025,17 @@ impl MarkdownElement {
width: Option<DefiniteLength>,
height: Option<DefiniteLength>,
) {
+ let align = builder.text_style().text_align;
builder.modify_current_div(|el| {
- el.items_center().flex().flex_row().child(
+ let mut image_container = el.flex().flex_row().items_center();
+
+ image_container = match align {
+ TextAlign::Left => image_container.justify_start(),
+ TextAlign::Center => image_container.justify_center(),
+ TextAlign::Right => image_container.justify_end(),
+ };
+
+ image_container.child(
img(source)
.max_w_full()
.when_some(height, |this, height| this.h(height))
@@ -1041,14 +1050,29 @@ impl MarkdownElement {
builder: &mut MarkdownElementBuilder,
range: &Range<usize>,
markdown_end: usize,
+ text_align_override: Option<TextAlign>,
) {
- builder.push_div(
- div().when(!self.style.height_is_multiple_of_line_height, |el| {
- el.mb_2().line_height(rems(1.3))
- }),
- range,
- markdown_end,
- );
+ let align = text_align_override.unwrap_or(self.style.base_text_style.text_align);
+ let mut paragraph = div().when(!self.style.height_is_multiple_of_line_height, |el| {
+ el.mb_2().line_height(rems(1.3))
+ });
+
+ paragraph = match align {
+ TextAlign::Center => paragraph.text_center(),
+ TextAlign::Left => paragraph.text_left(),
+ TextAlign::Right => paragraph.text_right(),
+ };
+
+ builder.push_text_style(TextStyleRefinement {
+ text_align: Some(align),
+ ..Default::default()
+ });
+ builder.push_div(paragraph, range, markdown_end);
+ }
+
+ fn pop_markdown_paragraph(&self, builder: &mut MarkdownElementBuilder) {
+ builder.pop_div();
+ builder.pop_text_style();
}
fn push_markdown_heading(
@@ -1057,15 +1081,26 @@ impl MarkdownElement {
level: pulldown_cmark::HeadingLevel,
range: &Range<usize>,
markdown_end: usize,
+ text_align_override: Option<TextAlign>,
) {
+ let align = text_align_override.unwrap_or(self.style.base_text_style.text_align);
let mut heading = div().mb_2();
heading = apply_heading_style(heading, level, self.style.heading_level_styles.as_ref());
+ heading = match align {
+ TextAlign::Center => heading.text_center(),
+ TextAlign::Left => heading.text_left(),
+ TextAlign::Right => heading.text_right(),
+ };
+
let mut heading_style = self.style.heading.clone();
let heading_text_style = heading_style.text_style().clone();
heading.style().refine(&heading_style);
- builder.push_text_style(heading_text_style);
+ builder.push_text_style(TextStyleRefinement {
+ text_align: Some(align),
+ ..heading_text_style
+ });
builder.push_div(heading, range, markdown_end);
}
@@ -1571,10 +1606,16 @@ impl Element for MarkdownElement {
}
}
MarkdownTag::Paragraph => {
- self.push_markdown_paragraph(&mut builder, range, markdown_end);
+ self.push_markdown_paragraph(&mut builder, range, markdown_end, None);
}
MarkdownTag::Heading { level, .. } => {
- self.push_markdown_heading(&mut builder, *level, range, markdown_end);
+ self.push_markdown_heading(
+ &mut builder,
+ *level,
+ range,
+ markdown_end,
+ None,
+ );
}
MarkdownTag::BlockQuote => {
self.push_markdown_block_quote(&mut builder, range, markdown_end);
@@ -1826,7 +1867,7 @@ impl Element for MarkdownElement {
current_img_block_range.take();
}
MarkdownTagEnd::Paragraph => {
- builder.pop_div();
+ self.pop_markdown_paragraph(&mut builder);
}
MarkdownTagEnd::Heading(_) => {
self.pop_markdown_heading(&mut builder);
@@ -21,9 +21,9 @@ use itertools::Itertools;
use language::{
AutoindentMode, Buffer, BufferChunks, BufferRow, BufferSnapshot, Capability, CharClassifier,
CharKind, CharScopeContext, Chunk, CursorShape, DiagnosticEntryRef, File, IndentGuideSettings,
- IndentSize, Language, LanguageScope, OffsetRangeExt, OffsetUtf16, Outline, OutlineItem, Point,
- PointUtf16, Selection, TextDimension, TextObject, ToOffset as _, ToPoint as _, TransactionId,
- TreeSitterOptions, Unclipped,
+ IndentSize, Language, LanguageAwareStyling, LanguageScope, OffsetRangeExt, OffsetUtf16,
+ Outline, OutlineItem, Point, PointUtf16, Selection, TextDimension, TextObject, ToOffset as _,
+ ToPoint as _, TransactionId, TreeSitterOptions, Unclipped,
language_settings::{AllLanguageSettings, LanguageSettings},
};
@@ -1072,7 +1072,7 @@ pub struct MultiBufferChunks<'a> {
range: Range<MultiBufferOffset>,
excerpt_offset_range: Range<ExcerptOffset>,
excerpt_chunks: Option<ExcerptChunks<'a>>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
snapshot: &'a MultiBufferSnapshot,
}
@@ -3340,9 +3340,15 @@ impl EventEmitter<Event> for MultiBuffer {}
impl MultiBufferSnapshot {
pub fn text(&self) -> String {
- self.chunks(MultiBufferOffset::ZERO..self.len(), false)
- .map(|chunk| chunk.text)
- .collect()
+ self.chunks(
+ MultiBufferOffset::ZERO..self.len(),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ )
+ .map(|chunk| chunk.text)
+ .collect()
}
pub fn reversed_chars_at<T: ToOffset>(&self, position: T) -> impl Iterator<Item = char> + '_ {
@@ -3378,7 +3384,14 @@ impl MultiBufferSnapshot {
}
pub fn text_for_range<T: ToOffset>(&self, range: Range<T>) -> impl Iterator<Item = &str> + '_ {
- self.chunks(range, false).map(|chunk| chunk.text)
+ self.chunks(
+ range,
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ )
+ .map(|chunk| chunk.text)
}
pub fn is_line_blank(&self, row: MultiBufferRow) -> bool {
@@ -4178,7 +4191,7 @@ impl MultiBufferSnapshot {
pub fn chunks<T: ToOffset>(
&self,
range: Range<T>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
) -> MultiBufferChunks<'_> {
let mut chunks = MultiBufferChunks {
excerpt_offset_range: ExcerptDimension(MultiBufferOffset::ZERO)
@@ -7227,7 +7240,7 @@ impl Excerpt {
fn chunks_in_range<'a>(
&'a self,
range: Range<usize>,
- language_aware: bool,
+ language_aware: LanguageAwareStyling,
snapshot: &'a MultiBufferSnapshot,
) -> ExcerptChunks<'a> {
let buffer = self.buffer_snapshot(snapshot);
@@ -5039,7 +5039,13 @@ fn check_edits(
fn assert_chunks_in_ranges(snapshot: &MultiBufferSnapshot) {
let full_text = snapshot.text();
for ix in 0..full_text.len() {
- let mut chunks = snapshot.chunks(MultiBufferOffset(0)..snapshot.len(), false);
+ let mut chunks = snapshot.chunks(
+ MultiBufferOffset(0)..snapshot.len(),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ );
chunks.seek(MultiBufferOffset(ix)..snapshot.len());
let tail = chunks.map(|chunk| chunk.text).collect::<String>();
assert_eq!(tail, &full_text[ix..], "seek to range: {:?}", ix..);
@@ -5300,7 +5306,13 @@ fn test_random_chunk_bitmaps(cx: &mut App, mut rng: StdRng) {
let snapshot = multibuffer.read(cx).snapshot(cx);
- let chunks = snapshot.chunks(MultiBufferOffset(0)..snapshot.len(), false);
+ let chunks = snapshot.chunks(
+ MultiBufferOffset(0)..snapshot.len(),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ );
for chunk in chunks {
let chunk_text = chunk.text;
@@ -5466,7 +5478,13 @@ fn test_random_chunk_bitmaps_with_diffs(cx: &mut App, mut rng: StdRng) {
let snapshot = multibuffer.read(cx).snapshot(cx);
- let chunks = snapshot.chunks(MultiBufferOffset(0)..snapshot.len(), false);
+ let chunks = snapshot.chunks(
+ MultiBufferOffset(0)..snapshot.len(),
+ LanguageAwareStyling {
+ tree_sitter: false,
+ diagnostics: false,
+ },
+ );
for chunk in chunks {
let chunk_text = chunk.text;
@@ -17,13 +17,18 @@ schemars = ["dep:schemars"]
[dependencies]
anyhow.workspace = true
+collections.workspace = true
futures.workspace = true
http_client.workspace = true
+language_model_core.workspace = true
rand.workspace = true
schemars = { workspace = true, optional = true }
log.workspace = true
serde.workspace = true
serde_json.workspace = true
-settings.workspace = true
strum.workspace = true
thiserror.workspace = true
+tiktoken-rs.workspace = true
+
+[dev-dependencies]
+pretty_assertions.workspace = true
@@ -0,0 +1,1696 @@
+use anyhow::{Result, anyhow};
+use collections::HashMap;
+use futures::{Stream, StreamExt};
+use language_model_core::{
+ LanguageModelCompletionError, LanguageModelCompletionEvent, LanguageModelImage,
+ LanguageModelRequest, LanguageModelRequestMessage, LanguageModelToolChoice,
+ LanguageModelToolResultContent, LanguageModelToolUse, LanguageModelToolUseId, MessageContent,
+ Role, StopReason, TokenUsage,
+ util::{fix_streamed_json, parse_tool_arguments},
+};
+use std::pin::Pin;
+use std::sync::Arc;
+
+use crate::responses::{
+ Request as ResponseRequest, ResponseFunctionCallItem, ResponseFunctionCallOutputContent,
+ ResponseFunctionCallOutputItem, ResponseInputContent, ResponseInputItem, ResponseMessageItem,
+ ResponseOutputItem, ResponseSummary as ResponsesSummary, ResponseUsage as ResponsesUsage,
+ StreamEvent as ResponsesStreamEvent,
+};
+use crate::{
+ FunctionContent, FunctionDefinition, ImageUrl, MessagePart, Model, ReasoningEffort,
+ ResponseStreamEvent, ToolCall, ToolCallContent,
+};
+
+pub fn into_open_ai(
+ request: LanguageModelRequest,
+ model_id: &str,
+ supports_parallel_tool_calls: bool,
+ supports_prompt_cache_key: bool,
+ max_output_tokens: Option<u64>,
+ reasoning_effort: Option<ReasoningEffort>,
+) -> crate::Request {
+ let stream = !model_id.starts_with("o1-");
+
+ let mut messages = Vec::new();
+ for message in request.messages {
+ for content in message.content {
+ match content {
+ MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
+ let should_add = if message.role == Role::User {
+ // Including whitespace-only user messages can cause error with OpenAI compatible APIs
+ // See https://github.com/zed-industries/zed/issues/40097
+ !text.trim().is_empty()
+ } else {
+ !text.is_empty()
+ };
+ if should_add {
+ add_message_content_part(
+ MessagePart::Text { text },
+ message.role,
+ &mut messages,
+ );
+ }
+ }
+ MessageContent::RedactedThinking(_) => {}
+ MessageContent::Image(image) => {
+ add_message_content_part(
+ MessagePart::Image {
+ image_url: ImageUrl {
+ url: image.to_base64_url(),
+ detail: None,
+ },
+ },
+ message.role,
+ &mut messages,
+ );
+ }
+ MessageContent::ToolUse(tool_use) => {
+ let tool_call = ToolCall {
+ id: tool_use.id.to_string(),
+ content: ToolCallContent::Function {
+ function: FunctionContent {
+ name: tool_use.name.to_string(),
+ arguments: serde_json::to_string(&tool_use.input)
+ .unwrap_or_default(),
+ },
+ },
+ };
+
+ if let Some(crate::RequestMessage::Assistant { tool_calls, .. }) =
+ messages.last_mut()
+ {
+ tool_calls.push(tool_call);
+ } else {
+ messages.push(crate::RequestMessage::Assistant {
+ content: None,
+ tool_calls: vec![tool_call],
+ });
+ }
+ }
+ MessageContent::ToolResult(tool_result) => {
+ let content = match &tool_result.content {
+ LanguageModelToolResultContent::Text(text) => {
+ vec![MessagePart::Text {
+ text: text.to_string(),
+ }]
+ }
+ LanguageModelToolResultContent::Image(image) => {
+ vec![MessagePart::Image {
+ image_url: ImageUrl {
+ url: image.to_base64_url(),
+ detail: None,
+ },
+ }]
+ }
+ };
+
+ messages.push(crate::RequestMessage::Tool {
+ content: content.into(),
+ tool_call_id: tool_result.tool_use_id.to_string(),
+ });
+ }
+ }
+ }
+ }
+
+ crate::Request {
+ model: model_id.into(),
+ messages,
+ stream,
+ stream_options: if stream {
+ Some(crate::StreamOptions::default())
+ } else {
+ None
+ },
+ stop: request.stop,
+ temperature: request.temperature.or(Some(1.0)),
+ max_completion_tokens: max_output_tokens,
+ parallel_tool_calls: if supports_parallel_tool_calls && !request.tools.is_empty() {
+ Some(supports_parallel_tool_calls)
+ } else {
+ None
+ },
+ prompt_cache_key: if supports_prompt_cache_key {
+ request.thread_id
+ } else {
+ None
+ },
+ tools: request
+ .tools
+ .into_iter()
+ .map(|tool| crate::ToolDefinition::Function {
+ function: FunctionDefinition {
+ name: tool.name,
+ description: Some(tool.description),
+ parameters: Some(tool.input_schema),
+ },
+ })
+ .collect(),
+ tool_choice: request.tool_choice.map(|choice| match choice {
+ LanguageModelToolChoice::Auto => crate::ToolChoice::Auto,
+ LanguageModelToolChoice::Any => crate::ToolChoice::Required,
+ LanguageModelToolChoice::None => crate::ToolChoice::None,
+ }),
+ reasoning_effort,
+ }
+}
+
+pub fn into_open_ai_response(
+ request: LanguageModelRequest,
+ model_id: &str,
+ supports_parallel_tool_calls: bool,
+ supports_prompt_cache_key: bool,
+ max_output_tokens: Option<u64>,
+ reasoning_effort: Option<ReasoningEffort>,
+) -> ResponseRequest {
+ let stream = !model_id.starts_with("o1-");
+
+ let LanguageModelRequest {
+ thread_id,
+ prompt_id: _,
+ intent: _,
+ messages,
+ tools,
+ tool_choice,
+ stop: _,
+ temperature,
+ thinking_allowed: _,
+ thinking_effort: _,
+ speed: _,
+ } = request;
+
+ let mut input_items = Vec::new();
+ for (index, message) in messages.into_iter().enumerate() {
+ append_message_to_response_items(message, index, &mut input_items);
+ }
+
+ let tools: Vec<_> = tools
+ .into_iter()
+ .map(|tool| crate::responses::ToolDefinition::Function {
+ name: tool.name,
+ description: Some(tool.description),
+ parameters: Some(tool.input_schema),
+ strict: None,
+ })
+ .collect();
+
+ ResponseRequest {
+ model: model_id.into(),
+ instructions: None,
+ input: input_items,
+ stream,
+ temperature,
+ top_p: None,
+ max_output_tokens,
+ parallel_tool_calls: if tools.is_empty() {
+ None
+ } else {
+ Some(supports_parallel_tool_calls)
+ },
+ tool_choice: tool_choice.map(|choice| match choice {
+ LanguageModelToolChoice::Auto => crate::ToolChoice::Auto,
+ LanguageModelToolChoice::Any => crate::ToolChoice::Required,
+ LanguageModelToolChoice::None => crate::ToolChoice::None,
+ }),
+ tools,
+ prompt_cache_key: if supports_prompt_cache_key {
+ thread_id
+ } else {
+ None
+ },
+ reasoning: reasoning_effort.map(|effort| crate::responses::ReasoningConfig {
+ effort,
+ summary: Some(crate::responses::ReasoningSummaryMode::Auto),
+ }),
+ store: None,
+ }
+}
+
+fn append_message_to_response_items(
+ message: LanguageModelRequestMessage,
+ index: usize,
+ input_items: &mut Vec<ResponseInputItem>,
+) {
+ let mut content_parts: Vec<ResponseInputContent> = Vec::new();
+
+ for content in message.content {
+ match content {
+ MessageContent::Text(text) => {
+ push_response_text_part(&message.role, text, &mut content_parts);
+ }
+ MessageContent::Thinking { text, .. } => {
+ push_response_text_part(&message.role, text, &mut content_parts);
+ }
+ MessageContent::RedactedThinking(_) => {}
+ MessageContent::Image(image) => {
+ push_response_image_part(&message.role, image, &mut content_parts);
+ }
+ MessageContent::ToolUse(tool_use) => {
+ flush_response_parts(&message.role, index, &mut content_parts, input_items);
+ let call_id = tool_use.id.to_string();
+ input_items.push(ResponseInputItem::FunctionCall(ResponseFunctionCallItem {
+ call_id,
+ name: tool_use.name.to_string(),
+ arguments: tool_use.raw_input,
+ }));
+ }
+ MessageContent::ToolResult(tool_result) => {
+ flush_response_parts(&message.role, index, &mut content_parts, input_items);
+ input_items.push(ResponseInputItem::FunctionCallOutput(
+ ResponseFunctionCallOutputItem {
+ call_id: tool_result.tool_use_id.to_string(),
+ output: match tool_result.content {
+ LanguageModelToolResultContent::Text(text) => {
+ ResponseFunctionCallOutputContent::Text(text.to_string())
+ }
+ LanguageModelToolResultContent::Image(image) => {
+ ResponseFunctionCallOutputContent::List(vec![
+ ResponseInputContent::Image {
+ image_url: image.to_base64_url(),
+ },
+ ])
+ }
+ },
+ },
+ ));
+ }
+ }
+ }
+
+ flush_response_parts(&message.role, index, &mut content_parts, input_items);
+}
+
+fn push_response_text_part(
+ role: &Role,
+ text: impl Into<String>,
+ parts: &mut Vec<ResponseInputContent>,
+) {
+ let text = text.into();
+ if text.trim().is_empty() {
+ return;
+ }
+
+ match role {
+ Role::Assistant => parts.push(ResponseInputContent::OutputText {
+ text,
+ annotations: Vec::new(),
+ }),
+ _ => parts.push(ResponseInputContent::Text { text }),
+ }
+}
+
+fn push_response_image_part(
+ role: &Role,
+ image: LanguageModelImage,
+ parts: &mut Vec<ResponseInputContent>,
+) {
+ match role {
+ Role::Assistant => parts.push(ResponseInputContent::OutputText {
+ text: "[image omitted]".to_string(),
+ annotations: Vec::new(),
+ }),
+ _ => parts.push(ResponseInputContent::Image {
+ image_url: image.to_base64_url(),
+ }),
+ }
+}
+
+fn flush_response_parts(
+ role: &Role,
+ _index: usize,
+ parts: &mut Vec<ResponseInputContent>,
+ input_items: &mut Vec<ResponseInputItem>,
+) {
+ if parts.is_empty() {
+ return;
+ }
+
+ let item = ResponseInputItem::Message(ResponseMessageItem {
+ role: match role {
+ Role::User => crate::Role::User,
+ Role::Assistant => crate::Role::Assistant,
+ Role::System => crate::Role::System,
+ },
+ content: parts.clone(),
+ });
+
+ input_items.push(item);
+ parts.clear();
+}
+
+fn add_message_content_part(
+ new_part: MessagePart,
+ role: Role,
+ messages: &mut Vec<crate::RequestMessage>,
+) {
+ match (role, messages.last_mut()) {
+ (Role::User, Some(crate::RequestMessage::User { content }))
+ | (
+ Role::Assistant,
+ Some(crate::RequestMessage::Assistant {
+ content: Some(content),
+ ..
+ }),
+ )
+ | (Role::System, Some(crate::RequestMessage::System { content, .. })) => {
+ content.push_part(new_part);
+ }
+ _ => {
+ messages.push(match role {
+ Role::User => crate::RequestMessage::User {
+ content: crate::MessageContent::from(vec![new_part]),
+ },
+ Role::Assistant => crate::RequestMessage::Assistant {
+ content: Some(crate::MessageContent::from(vec![new_part])),
+ tool_calls: Vec::new(),
+ },
+ Role::System => crate::RequestMessage::System {
+ content: crate::MessageContent::from(vec![new_part]),
+ },
+ });
+ }
+ }
+}
+
+pub struct OpenAiEventMapper {
+ tool_calls_by_index: HashMap<usize, RawToolCall>,
+}
+
+impl OpenAiEventMapper {
+ pub fn new() -> Self {
+ Self {
+ tool_calls_by_index: HashMap::default(),
+ }
+ }
+
+ pub fn map_stream(
+ mut self,
+ events: Pin<Box<dyn Send + Stream<Item = Result<ResponseStreamEvent>>>>,
+ ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
+ {
+ events.flat_map(move |event| {
+ futures::stream::iter(match event {
+ Ok(event) => self.map_event(event),
+ Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
+ })
+ })
+ }
+
+ pub fn map_event(
+ &mut self,
+ event: ResponseStreamEvent,
+ ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
+ let mut events = Vec::new();
+ if let Some(usage) = event.usage {
+ events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
+ input_tokens: usage.prompt_tokens,
+ output_tokens: usage.completion_tokens,
+ cache_creation_input_tokens: 0,
+ cache_read_input_tokens: 0,
+ })));
+ }
+
+ let Some(choice) = event.choices.first() else {
+ return events;
+ };
+
+ if let Some(delta) = choice.delta.as_ref() {
+ if let Some(reasoning_content) = delta.reasoning_content.clone() {
+ if !reasoning_content.is_empty() {
+ events.push(Ok(LanguageModelCompletionEvent::Thinking {
+ text: reasoning_content,
+ signature: None,
+ }));
+ }
+ }
+ if let Some(content) = delta.content.clone() {
+ if !content.is_empty() {
+ events.push(Ok(LanguageModelCompletionEvent::Text(content)));
+ }
+ }
+
+ if let Some(tool_calls) = delta.tool_calls.as_ref() {
+ for tool_call in tool_calls {
+ let entry = self.tool_calls_by_index.entry(tool_call.index).or_default();
+
+ if let Some(tool_id) = tool_call.id.clone() {
+ entry.id = tool_id;
+ }
+
+ if let Some(function) = tool_call.function.as_ref() {
+ if let Some(name) = function.name.clone() {
+ entry.name = name;
+ }
+
+ if let Some(arguments) = function.arguments.clone() {
+ entry.arguments.push_str(&arguments);
+ }
+ }
+
+ if !entry.id.is_empty() && !entry.name.is_empty() {
+ if let Ok(input) = serde_json::from_str::<serde_json::Value>(
+ &fix_streamed_json(&entry.arguments),
+ ) {
+ events.push(Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id: entry.id.clone().into(),
+ name: entry.name.as_str().into(),
+ is_input_complete: false,
+ input,
+ raw_input: entry.arguments.clone(),
+ thought_signature: None,
+ },
+ )));
+ }
+ }
+ }
+ }
+ }
+
+ match choice.finish_reason.as_deref() {
+ Some("stop") => {
+ events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
+ }
+ Some("tool_calls") => {
+ events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
+ match parse_tool_arguments(&tool_call.arguments) {
+ Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id: tool_call.id.clone().into(),
+ name: tool_call.name.as_str().into(),
+ is_input_complete: true,
+ input,
+ raw_input: tool_call.arguments.clone(),
+ thought_signature: None,
+ },
+ )),
+ Err(error) => Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
+ id: tool_call.id.into(),
+ tool_name: tool_call.name.into(),
+ raw_input: tool_call.arguments.clone().into(),
+ json_parse_error: error.to_string(),
+ }),
+ }
+ }));
+
+ events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
+ }
+ Some(stop_reason) => {
+ log::error!("Unexpected OpenAI stop_reason: {stop_reason:?}",);
+ events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
+ }
+ None => {}
+ }
+
+ events
+ }
+}
+
+#[derive(Default)]
+struct RawToolCall {
+ id: String,
+ name: String,
+ arguments: String,
+}
+
+pub struct OpenAiResponseEventMapper {
+ function_calls_by_item: HashMap<String, PendingResponseFunctionCall>,
+ pending_stop_reason: Option<StopReason>,
+}
+
+#[derive(Default)]
+struct PendingResponseFunctionCall {
+ call_id: String,
+ name: Arc<str>,
+ arguments: String,
+}
+
+impl OpenAiResponseEventMapper {
+ pub fn new() -> Self {
+ Self {
+ function_calls_by_item: HashMap::default(),
+ pending_stop_reason: None,
+ }
+ }
+
+ pub fn map_stream(
+ mut self,
+ events: Pin<Box<dyn Send + Stream<Item = Result<ResponsesStreamEvent>>>>,
+ ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
+ {
+ events.flat_map(move |event| {
+ futures::stream::iter(match event {
+ Ok(event) => self.map_event(event),
+ Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
+ })
+ })
+ }
+
+ pub fn map_event(
+ &mut self,
+ event: ResponsesStreamEvent,
+ ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
+ match event {
+ ResponsesStreamEvent::OutputItemAdded { item, .. } => {
+ let mut events = Vec::new();
+
+ match &item {
+ ResponseOutputItem::Message(message) => {
+ if let Some(id) = &message.id {
+ events.push(Ok(LanguageModelCompletionEvent::StartMessage {
+ message_id: id.clone(),
+ }));
+ }
+ }
+ ResponseOutputItem::FunctionCall(function_call) => {
+ if let Some(item_id) = function_call.id.clone() {
+ let call_id = function_call
+ .call_id
+ .clone()
+ .or_else(|| function_call.id.clone())
+ .unwrap_or_else(|| item_id.clone());
+ let entry = PendingResponseFunctionCall {
+ call_id,
+ name: Arc::<str>::from(
+ function_call.name.clone().unwrap_or_default(),
+ ),
+ arguments: function_call.arguments.clone(),
+ };
+ self.function_calls_by_item.insert(item_id, entry);
+ }
+ }
+ ResponseOutputItem::Reasoning(_) | ResponseOutputItem::Unknown => {}
+ }
+ events
+ }
+ ResponsesStreamEvent::ReasoningSummaryTextDelta { delta, .. } => {
+ if delta.is_empty() {
+ Vec::new()
+ } else {
+ vec![Ok(LanguageModelCompletionEvent::Thinking {
+ text: delta,
+ signature: None,
+ })]
+ }
+ }
+ ResponsesStreamEvent::OutputTextDelta { delta, .. } => {
+ if delta.is_empty() {
+ Vec::new()
+ } else {
+ vec![Ok(LanguageModelCompletionEvent::Text(delta))]
+ }
+ }
+ ResponsesStreamEvent::FunctionCallArgumentsDelta { item_id, delta, .. } => {
+ if let Some(entry) = self.function_calls_by_item.get_mut(&item_id) {
+ entry.arguments.push_str(&delta);
+ if let Ok(input) = serde_json::from_str::<serde_json::Value>(
+ &fix_streamed_json(&entry.arguments),
+ ) {
+ return vec![Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id: LanguageModelToolUseId::from(entry.call_id.clone()),
+ name: entry.name.clone(),
+ is_input_complete: false,
+ input,
+ raw_input: entry.arguments.clone(),
+ thought_signature: None,
+ },
+ ))];
+ }
+ }
+ Vec::new()
+ }
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id, arguments, ..
+ } => {
+ if let Some(mut entry) = self.function_calls_by_item.remove(&item_id) {
+ if !arguments.is_empty() {
+ entry.arguments = arguments;
+ }
+ let raw_input = entry.arguments.clone();
+ self.pending_stop_reason = Some(StopReason::ToolUse);
+ match parse_tool_arguments(&entry.arguments) {
+ Ok(input) => {
+ vec![Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id: LanguageModelToolUseId::from(entry.call_id.clone()),
+ name: entry.name.clone(),
+ is_input_complete: true,
+ input,
+ raw_input,
+ thought_signature: None,
+ },
+ ))]
+ }
+ Err(error) => {
+ vec![Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
+ id: LanguageModelToolUseId::from(entry.call_id.clone()),
+ tool_name: entry.name.clone(),
+ raw_input: Arc::<str>::from(raw_input),
+ json_parse_error: error.to_string(),
+ })]
+ }
+ }
+ } else {
+ Vec::new()
+ }
+ }
+ ResponsesStreamEvent::Completed { response } => {
+ self.handle_completion(response, StopReason::EndTurn)
+ }
+ ResponsesStreamEvent::Incomplete { response } => {
+ let reason = response
+ .status_details
+ .as_ref()
+ .and_then(|details| details.reason.as_deref());
+ let stop_reason = match reason {
+ Some("max_output_tokens") => StopReason::MaxTokens,
+ Some("content_filter") => {
+ self.pending_stop_reason = Some(StopReason::Refusal);
+ StopReason::Refusal
+ }
+ _ => self
+ .pending_stop_reason
+ .take()
+ .unwrap_or(StopReason::EndTurn),
+ };
+
+ let mut events = Vec::new();
+ if self.pending_stop_reason.is_none() {
+ events.extend(self.emit_tool_calls_from_output(&response.output));
+ }
+ if let Some(usage) = response.usage.as_ref() {
+ events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
+ token_usage_from_response_usage(usage),
+ )));
+ }
+ events.push(Ok(LanguageModelCompletionEvent::Stop(stop_reason)));
+ events
+ }
+ ResponsesStreamEvent::Failed { response } => {
+ let message = response
+ .status_details
+ .and_then(|details| details.error)
+ .map(|error| error.to_string())
+ .unwrap_or_else(|| "response failed".to_string());
+ vec![Err(LanguageModelCompletionError::Other(anyhow!(message)))]
+ }
+ ResponsesStreamEvent::Error { error }
+ | ResponsesStreamEvent::GenericError { error } => {
+ vec![Err(LanguageModelCompletionError::Other(anyhow!(
+ error.message
+ )))]
+ }
+ ResponsesStreamEvent::ReasoningSummaryPartAdded { summary_index, .. } => {
+ if summary_index > 0 {
+ vec![Ok(LanguageModelCompletionEvent::Thinking {
+ text: "\n\n".to_string(),
+ signature: None,
+ })]
+ } else {
+ Vec::new()
+ }
+ }
+ ResponsesStreamEvent::OutputTextDone { .. }
+ | ResponsesStreamEvent::OutputItemDone { .. }
+ | ResponsesStreamEvent::ContentPartAdded { .. }
+ | ResponsesStreamEvent::ContentPartDone { .. }
+ | ResponsesStreamEvent::ReasoningSummaryTextDone { .. }
+ | ResponsesStreamEvent::ReasoningSummaryPartDone { .. }
+ | ResponsesStreamEvent::Created { .. }
+ | ResponsesStreamEvent::InProgress { .. }
+ | ResponsesStreamEvent::Unknown => Vec::new(),
+ }
+ }
+
+ fn handle_completion(
+ &mut self,
+ response: ResponsesSummary,
+ default_reason: StopReason,
+ ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
+ let mut events = Vec::new();
+
+ if self.pending_stop_reason.is_none() {
+ events.extend(self.emit_tool_calls_from_output(&response.output));
+ }
+
+ if let Some(usage) = response.usage.as_ref() {
+ events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
+ token_usage_from_response_usage(usage),
+ )));
+ }
+
+ let stop_reason = self.pending_stop_reason.take().unwrap_or(default_reason);
+ events.push(Ok(LanguageModelCompletionEvent::Stop(stop_reason)));
+ events
+ }
+
+ fn emit_tool_calls_from_output(
+ &mut self,
+ output: &[ResponseOutputItem],
+ ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
+ let mut events = Vec::new();
+ for item in output {
+ if let ResponseOutputItem::FunctionCall(function_call) = item {
+ let Some(call_id) = function_call
+ .call_id
+ .clone()
+ .or_else(|| function_call.id.clone())
+ else {
+ log::error!(
+ "Function call item missing both call_id and id: {:?}",
+ function_call
+ );
+ continue;
+ };
+ let name: Arc<str> = Arc::from(function_call.name.clone().unwrap_or_default());
+ let arguments = &function_call.arguments;
+ self.pending_stop_reason = Some(StopReason::ToolUse);
+ match parse_tool_arguments(arguments) {
+ Ok(input) => {
+ events.push(Ok(LanguageModelCompletionEvent::ToolUse(
+ LanguageModelToolUse {
+ id: LanguageModelToolUseId::from(call_id.clone()),
+ name: name.clone(),
+ is_input_complete: true,
+ input,
+ raw_input: arguments.clone(),
+ thought_signature: None,
+ },
+ )));
+ }
+ Err(error) => {
+ events.push(Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
+ id: LanguageModelToolUseId::from(call_id.clone()),
+ tool_name: name.clone(),
+ raw_input: Arc::<str>::from(arguments.clone()),
+ json_parse_error: error.to_string(),
+ }));
+ }
+ }
+ }
+ }
+ events
+ }
+}
+
+fn token_usage_from_response_usage(usage: &ResponsesUsage) -> TokenUsage {
+ TokenUsage {
+ input_tokens: usage.input_tokens.unwrap_or_default(),
+ output_tokens: usage.output_tokens.unwrap_or_default(),
+ cache_creation_input_tokens: 0,
+ cache_read_input_tokens: 0,
+ }
+}
+
+pub fn collect_tiktoken_messages(
+ request: LanguageModelRequest,
+) -> Vec<tiktoken_rs::ChatCompletionRequestMessage> {
+ request
+ .messages
+ .into_iter()
+ .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
+ role: match message.role {
+ Role::User => "user".into(),
+ Role::Assistant => "assistant".into(),
+ Role::System => "system".into(),
+ },
+ content: Some(message.string_contents()),
+ name: None,
+ function_call: None,
+ })
+ .collect::<Vec<_>>()
+}
+
+/// Count tokens for an OpenAI model. This is synchronous; callers should spawn
+/// it on a background thread if needed.
+pub fn count_open_ai_tokens(request: LanguageModelRequest, model: Model) -> Result<u64> {
+ let messages = collect_tiktoken_messages(request);
+ match model {
+ Model::Custom { max_tokens, .. } => {
+ let model = if max_tokens >= 100_000 {
+ // If the max tokens is 100k or more, it likely uses the o200k_base tokenizer
+ "gpt-4o"
+ } else {
+ // Otherwise fallback to gpt-4, since only cl100k_base and o200k_base are
+ // supported with this tiktoken method
+ "gpt-4"
+ };
+ tiktoken_rs::num_tokens_from_messages(model, &messages)
+ }
+ // Currently supported by tiktoken_rs
+ // Sometimes tiktoken-rs is behind on model support. If that is the case, make a new branch
+ // arm with an override. We enumerate all supported models here so that we can check if new
+ // models are supported yet or not.
+ Model::ThreePointFiveTurbo
+ | Model::Four
+ | Model::FourTurbo
+ | Model::FourOmniMini
+ | Model::FourPointOneNano
+ | Model::O1
+ | Model::O3
+ | Model::O3Mini
+ | Model::O4Mini
+ | Model::Five
+ | Model::FiveCodex
+ | Model::FiveMini
+ | Model::FiveNano => tiktoken_rs::num_tokens_from_messages(model.id(), &messages),
+ // GPT-5.1, 5.2, 5.2-codex, 5.3-codex, 5.4, and 5.4-pro don't have dedicated tiktoken support; use gpt-5 tokenizer
+ Model::FivePointOne
+ | Model::FivePointTwo
+ | Model::FivePointTwoCodex
+ | Model::FivePointThreeCodex
+ | Model::FivePointFour
+ | Model::FivePointFourPro => tiktoken_rs::num_tokens_from_messages("gpt-5", &messages),
+ }
+ .map(|tokens| tokens as u64)
+}
+
+#[cfg(test)]
+mod tests {
+ use crate::responses::{
+ ReasoningSummaryPart, ResponseFunctionToolCall, ResponseOutputItem, ResponseOutputMessage,
+ ResponseReasoningItem, ResponseStatusDetails, ResponseSummary, ResponseUsage,
+ StreamEvent as ResponsesStreamEvent,
+ };
+ use futures::{StreamExt, executor::block_on};
+ use language_model_core::{
+ LanguageModelImage, LanguageModelRequestMessage, LanguageModelRequestTool,
+ LanguageModelToolResult, LanguageModelToolResultContent, LanguageModelToolUse,
+ LanguageModelToolUseId, SharedString,
+ };
+ use pretty_assertions::assert_eq;
+ use serde_json::json;
+
+ use super::*;
+
+ fn map_response_events(events: Vec<ResponsesStreamEvent>) -> Vec<LanguageModelCompletionEvent> {
+ block_on(async {
+ OpenAiResponseEventMapper::new()
+ .map_stream(Box::pin(futures::stream::iter(events.into_iter().map(Ok))))
+ .collect::<Vec<_>>()
+ .await
+ .into_iter()
+ .map(Result::unwrap)
+ .collect()
+ })
+ }
+
+ fn response_item_message(id: &str) -> ResponseOutputItem {
+ ResponseOutputItem::Message(ResponseOutputMessage {
+ id: Some(id.to_string()),
+ role: Some("assistant".to_string()),
+ status: Some("in_progress".to_string()),
+ content: vec![],
+ })
+ }
+
+ fn response_item_function_call(id: &str, args: Option<&str>) -> ResponseOutputItem {
+ ResponseOutputItem::FunctionCall(ResponseFunctionToolCall {
+ id: Some(id.to_string()),
+ status: Some("in_progress".to_string()),
+ name: Some("get_weather".to_string()),
+ call_id: Some("call_123".to_string()),
+ arguments: args.map(|s| s.to_string()).unwrap_or_default(),
+ })
+ }
+
+ #[test]
+ fn tiktoken_rs_support() {
+ let request = LanguageModelRequest {
+ thread_id: None,
+ prompt_id: None,
+ intent: None,
+ messages: vec![LanguageModelRequestMessage {
+ role: Role::User,
+ content: vec![MessageContent::Text("message".into())],
+ cache: false,
+ reasoning_details: None,
+ }],
+ tools: vec![],
+ tool_choice: None,
+ stop: vec![],
+ temperature: None,
+ thinking_allowed: true,
+ thinking_effort: None,
+ speed: None,
+ };
+
+ // Validate that all models are supported by tiktoken-rs
+ for model in <Model as strum::IntoEnumIterator>::iter() {
+ let count = count_open_ai_tokens(request.clone(), model).unwrap();
+ assert!(count > 0);
+ }
+ }
+
+ #[test]
+ fn responses_stream_maps_text_and_usage() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_message("msg_123"),
+ },
+ ResponsesStreamEvent::OutputTextDelta {
+ item_id: "msg_123".into(),
+ output_index: 0,
+ content_index: Some(0),
+ delta: "Hello".into(),
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary {
+ usage: Some(ResponseUsage {
+ input_tokens: Some(5),
+ output_tokens: Some(3),
+ total_tokens: Some(8),
+ }),
+ ..Default::default()
+ },
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert!(matches!(
+ mapped[0],
+ LanguageModelCompletionEvent::StartMessage { ref message_id } if message_id == "msg_123"
+ ));
+ assert!(matches!(
+ mapped[1],
+ LanguageModelCompletionEvent::Text(ref text) if text == "Hello"
+ ));
+ assert!(matches!(
+ mapped[2],
+ LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
+ input_tokens: 5,
+ output_tokens: 3,
+ ..
+ })
+ ));
+ assert!(matches!(
+ mapped[3],
+ LanguageModelCompletionEvent::Stop(StopReason::EndTurn)
+ ));
+ }
+
+ #[test]
+ fn into_open_ai_response_builds_complete_payload() {
+ let tool_call_id = LanguageModelToolUseId::from("call-42");
+ let tool_input = json!({ "city": "Boston" });
+ let tool_arguments = serde_json::to_string(&tool_input).unwrap();
+ let tool_use = LanguageModelToolUse {
+ id: tool_call_id.clone(),
+ name: Arc::from("get_weather"),
+ raw_input: tool_arguments.clone(),
+ input: tool_input,
+ is_input_complete: true,
+ thought_signature: None,
+ };
+ let tool_result = LanguageModelToolResult {
+ tool_use_id: tool_call_id,
+ tool_name: Arc::from("get_weather"),
+ is_error: false,
+ content: LanguageModelToolResultContent::Text(Arc::from("Sunny")),
+ output: Some(json!({ "forecast": "Sunny" })),
+ };
+ let user_image = LanguageModelImage {
+ source: SharedString::from("aGVsbG8="),
+ size: None,
+ };
+ let expected_image_url = user_image.to_base64_url();
+
+ let request = LanguageModelRequest {
+ thread_id: Some("thread-123".into()),
+ prompt_id: None,
+ intent: None,
+ messages: vec![
+ LanguageModelRequestMessage {
+ role: Role::System,
+ content: vec![MessageContent::Text("System context".into())],
+ cache: false,
+ reasoning_details: None,
+ },
+ LanguageModelRequestMessage {
+ role: Role::User,
+ content: vec![
+ MessageContent::Text("Please check the weather.".into()),
+ MessageContent::Image(user_image),
+ ],
+ cache: false,
+ reasoning_details: None,
+ },
+ LanguageModelRequestMessage {
+ role: Role::Assistant,
+ content: vec![
+ MessageContent::Text("Looking that up.".into()),
+ MessageContent::ToolUse(tool_use),
+ ],
+ cache: false,
+ reasoning_details: None,
+ },
+ LanguageModelRequestMessage {
+ role: Role::Assistant,
+ content: vec![MessageContent::ToolResult(tool_result)],
+ cache: false,
+ reasoning_details: None,
+ },
+ ],
+ tools: vec![LanguageModelRequestTool {
+ name: "get_weather".into(),
+ description: "Fetches the weather".into(),
+ input_schema: json!({ "type": "object" }),
+ use_input_streaming: false,
+ }],
+ tool_choice: Some(LanguageModelToolChoice::Any),
+ stop: vec!["<STOP>".into()],
+ temperature: None,
+ thinking_allowed: false,
+ thinking_effort: None,
+ speed: None,
+ };
+
+ let response = into_open_ai_response(
+ request,
+ "custom-model",
+ true,
+ true,
+ Some(2048),
+ Some(ReasoningEffort::Low),
+ );
+
+ let serialized = serde_json::to_value(&response).unwrap();
+ let expected = json!({
+ "model": "custom-model",
+ "input": [
+ {
+ "type": "message",
+ "role": "system",
+ "content": [
+ { "type": "input_text", "text": "System context" }
+ ]
+ },
+ {
+ "type": "message",
+ "role": "user",
+ "content": [
+ { "type": "input_text", "text": "Please check the weather." },
+ { "type": "input_image", "image_url": expected_image_url }
+ ]
+ },
+ {
+ "type": "message",
+ "role": "assistant",
+ "content": [
+ { "type": "output_text", "text": "Looking that up.", "annotations": [] }
+ ]
+ },
+ {
+ "type": "function_call",
+ "call_id": "call-42",
+ "name": "get_weather",
+ "arguments": tool_arguments
+ },
+ {
+ "type": "function_call_output",
+ "call_id": "call-42",
+ "output": "Sunny"
+ }
+ ],
+ "stream": true,
+ "max_output_tokens": 2048,
+ "parallel_tool_calls": true,
+ "tool_choice": "required",
+ "tools": [
+ {
+ "type": "function",
+ "name": "get_weather",
+ "description": "Fetches the weather",
+ "parameters": { "type": "object" }
+ }
+ ],
+ "prompt_cache_key": "thread-123",
+ "reasoning": { "effort": "low", "summary": "auto" }
+ });
+
+ assert_eq!(serialized, expected);
+ }
+
+ #[test]
+ fn responses_stream_maps_tool_calls() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_function_call("item_fn", Some("{\"city\":\"Bos")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDelta {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ delta: "ton\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ arguments: "{\"city\":\"Boston\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert_eq!(mapped.len(), 3);
+ assert!(matches!(
+ mapped[0],
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
+ is_input_complete: false,
+ ..
+ })
+ ));
+ assert!(matches!(
+ mapped[1],
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
+ ref id,
+ ref name,
+ ref raw_input,
+ is_input_complete: true,
+ ..
+ }) if id.to_string() == "call_123"
+ && name.as_ref() == "get_weather"
+ && raw_input == "{\"city\":\"Boston\"}"
+ ));
+ assert!(matches!(
+ mapped[2],
+ LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
+ ));
+ }
+
+ #[test]
+ fn responses_stream_uses_max_tokens_stop_reason() {
+ let events = vec![ResponsesStreamEvent::Incomplete {
+ response: ResponseSummary {
+ status_details: Some(ResponseStatusDetails {
+ reason: Some("max_output_tokens".into()),
+ r#type: Some("incomplete".into()),
+ error: None,
+ }),
+ usage: Some(ResponseUsage {
+ input_tokens: Some(10),
+ output_tokens: Some(20),
+ total_tokens: Some(30),
+ }),
+ ..Default::default()
+ },
+ }];
+
+ let mapped = map_response_events(events);
+ assert!(matches!(
+ mapped[0],
+ LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
+ input_tokens: 10,
+ output_tokens: 20,
+ ..
+ })
+ ));
+ assert!(matches!(
+ mapped[1],
+ LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
+ ));
+ }
+
+ #[test]
+ fn responses_stream_handles_multiple_tool_calls() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_function_call("item_fn1", Some("{\"city\":\"NYC\"}")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn1".into(),
+ output_index: 0,
+ arguments: "{\"city\":\"NYC\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 1,
+ sequence_number: None,
+ item: response_item_function_call("item_fn2", Some("{\"city\":\"LA\"}")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn2".into(),
+ output_index: 1,
+ arguments: "{\"city\":\"LA\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert_eq!(mapped.len(), 3);
+ assert!(matches!(
+ mapped[0],
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. })
+ if raw_input == "{\"city\":\"NYC\"}"
+ ));
+ assert!(matches!(
+ mapped[1],
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. })
+ if raw_input == "{\"city\":\"LA\"}"
+ ));
+ assert!(matches!(
+ mapped[2],
+ LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
+ ));
+ }
+
+ #[test]
+ fn responses_stream_handles_mixed_text_and_tool_calls() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_message("msg_123"),
+ },
+ ResponsesStreamEvent::OutputTextDelta {
+ item_id: "msg_123".into(),
+ output_index: 0,
+ content_index: Some(0),
+ delta: "Let me check that".into(),
+ },
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 1,
+ sequence_number: None,
+ item: response_item_function_call("item_fn", Some("{\"query\":\"test\"}")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn".into(),
+ output_index: 1,
+ arguments: "{\"query\":\"test\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert!(matches!(
+ mapped[0],
+ LanguageModelCompletionEvent::StartMessage { .. }
+ ));
+ assert!(
+ matches!(mapped[1], LanguageModelCompletionEvent::Text(ref text) if text == "Let me check that")
+ );
+ assert!(
+ matches!(mapped[2], LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. }) if raw_input == "{\"query\":\"test\"}")
+ );
+ assert!(matches!(
+ mapped[3],
+ LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
+ ));
+ }
+
+ #[test]
+ fn responses_stream_handles_json_parse_error() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_function_call("item_fn", Some("{invalid json")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ arguments: "{invalid json".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert!(matches!(
+ mapped[0],
+ LanguageModelCompletionEvent::ToolUseJsonParseError { ref raw_input, .. }
+ if raw_input.as_ref() == "{invalid json"
+ ));
+ }
+
+ #[test]
+ fn responses_stream_handles_incomplete_function_call() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_function_call("item_fn", Some("{\"city\":")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDelta {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ delta: "\"Boston\"".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Incomplete {
+ response: ResponseSummary {
+ status_details: Some(ResponseStatusDetails {
+ reason: Some("max_output_tokens".into()),
+ r#type: Some("incomplete".into()),
+ error: None,
+ }),
+ output: vec![response_item_function_call(
+ "item_fn",
+ Some("{\"city\":\"Boston\"}"),
+ )],
+ ..Default::default()
+ },
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert_eq!(mapped.len(), 3);
+ assert!(matches!(
+ mapped[0],
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
+ is_input_complete: false,
+ ..
+ })
+ ));
+ assert!(
+ matches!(mapped[1], LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, is_input_complete: true, .. }) if raw_input == "{\"city\":\"Boston\"}")
+ );
+ assert!(matches!(
+ mapped[2],
+ LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
+ ));
+ }
+
+ #[test]
+ fn responses_stream_incomplete_does_not_duplicate_tool_calls() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_function_call("item_fn", Some("{\"city\":\"Boston\"}")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ arguments: "{\"city\":\"Boston\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Incomplete {
+ response: ResponseSummary {
+ status_details: Some(ResponseStatusDetails {
+ reason: Some("max_output_tokens".into()),
+ r#type: Some("incomplete".into()),
+ error: None,
+ }),
+ output: vec![response_item_function_call(
+ "item_fn",
+ Some("{\"city\":\"Boston\"}"),
+ )],
+ ..Default::default()
+ },
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert_eq!(mapped.len(), 2);
+ assert!(
+ matches!(mapped[0], LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse { ref raw_input, .. }) if raw_input == "{\"city\":\"Boston\"}")
+ );
+ assert!(matches!(
+ mapped[1],
+ LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
+ ));
+ }
+
+ #[test]
+ fn responses_stream_handles_empty_tool_arguments() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: response_item_function_call("item_fn", Some("")),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ arguments: "".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert_eq!(mapped.len(), 2);
+ assert!(matches!(
+ &mapped[0],
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
+ id, name, raw_input, input, ..
+ }) if id.to_string() == "call_123"
+ && name.as_ref() == "get_weather"
+ && raw_input == ""
+ && input.is_object()
+ && input.as_object().unwrap().is_empty()
+ ));
+ assert!(matches!(
+ mapped[1],
+ LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
+ ));
+ }
+
+ #[test]
+ fn responses_stream_emits_partial_tool_use_events() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: ResponseOutputItem::FunctionCall(
+ crate::responses::ResponseFunctionToolCall {
+ id: Some("item_fn".to_string()),
+ status: Some("in_progress".to_string()),
+ name: Some("get_weather".to_string()),
+ call_id: Some("call_abc".to_string()),
+ arguments: String::new(),
+ },
+ ),
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDelta {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ delta: "{\"city\":\"Bos".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDelta {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ delta: "ton\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::FunctionCallArgumentsDone {
+ item_id: "item_fn".into(),
+ output_index: 0,
+ arguments: "{\"city\":\"Boston\"}".into(),
+ sequence_number: None,
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert!(mapped.len() >= 3);
+
+ let complete_tool_use = mapped.iter().find(|e| {
+ matches!(
+ e,
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
+ is_input_complete: true,
+ ..
+ })
+ )
+ });
+ assert!(
+ complete_tool_use.is_some(),
+ "should have a complete tool use event"
+ );
+
+ let tool_uses: Vec<_> = mapped
+ .iter()
+ .filter(|e| matches!(e, LanguageModelCompletionEvent::ToolUse(_)))
+ .collect();
+ assert!(
+ tool_uses.len() >= 2,
+ "should have at least one partial and one complete event"
+ );
+ assert!(matches!(
+ tool_uses.last().unwrap(),
+ LanguageModelCompletionEvent::ToolUse(LanguageModelToolUse {
+ is_input_complete: true,
+ ..
+ })
+ ));
+ }
+
+ #[test]
+ fn responses_stream_maps_reasoning_summary_deltas() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
+ id: Some("rs_123".into()),
+ summary: vec![],
+ }),
+ },
+ ResponsesStreamEvent::ReasoningSummaryPartAdded {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ summary_index: 0,
+ },
+ ResponsesStreamEvent::ReasoningSummaryTextDelta {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ delta: "Thinking about".into(),
+ },
+ ResponsesStreamEvent::ReasoningSummaryTextDelta {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ delta: " the answer".into(),
+ },
+ ResponsesStreamEvent::ReasoningSummaryTextDone {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ text: "Thinking about the answer".into(),
+ },
+ ResponsesStreamEvent::ReasoningSummaryPartDone {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ summary_index: 0,
+ },
+ ResponsesStreamEvent::ReasoningSummaryPartAdded {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ summary_index: 1,
+ },
+ ResponsesStreamEvent::ReasoningSummaryTextDelta {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ delta: "Second part".into(),
+ },
+ ResponsesStreamEvent::ReasoningSummaryTextDone {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ text: "Second part".into(),
+ },
+ ResponsesStreamEvent::ReasoningSummaryPartDone {
+ item_id: "rs_123".into(),
+ output_index: 0,
+ summary_index: 1,
+ },
+ ResponsesStreamEvent::OutputItemDone {
+ output_index: 0,
+ sequence_number: None,
+ item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
+ id: Some("rs_123".into()),
+ summary: vec![
+ ReasoningSummaryPart::SummaryText {
+ text: "Thinking about the answer".into(),
+ },
+ ReasoningSummaryPart::SummaryText {
+ text: "Second part".into(),
+ },
+ ],
+ }),
+ },
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 1,
+ sequence_number: None,
+ item: response_item_message("msg_456"),
+ },
+ ResponsesStreamEvent::OutputTextDelta {
+ item_id: "msg_456".into(),
+ output_index: 1,
+ content_index: Some(0),
+ delta: "The answer is 42".into(),
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+
+ let thinking_events: Vec<_> = mapped
+ .iter()
+ .filter(|e| matches!(e, LanguageModelCompletionEvent::Thinking { .. }))
+ .collect();
+ assert_eq!(
+ thinking_events.len(),
+ 4,
+ "expected 4 thinking events, got {:?}",
+ thinking_events
+ );
+ assert!(
+ matches!(&thinking_events[0], LanguageModelCompletionEvent::Thinking { text, .. } if text == "Thinking about")
+ );
+ assert!(
+ matches!(&thinking_events[1], LanguageModelCompletionEvent::Thinking { text, .. } if text == " the answer")
+ );
+ assert!(
+ matches!(&thinking_events[2], LanguageModelCompletionEvent::Thinking { text, .. } if text == "\n\n"),
+ "expected separator between summary parts"
+ );
+ assert!(
+ matches!(&thinking_events[3], LanguageModelCompletionEvent::Thinking { text, .. } if text == "Second part")
+ );
+
+ assert!(mapped.iter().any(
+ |e| matches!(e, LanguageModelCompletionEvent::Text(t) if t == "The answer is 42")
+ ));
+ }
+
+ #[test]
+ fn responses_stream_maps_reasoning_from_done_only() {
+ let events = vec![
+ ResponsesStreamEvent::OutputItemAdded {
+ output_index: 0,
+ sequence_number: None,
+ item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
+ id: Some("rs_789".into()),
+ summary: vec![],
+ }),
+ },
+ ResponsesStreamEvent::OutputItemDone {
+ output_index: 0,
+ sequence_number: None,
+ item: ResponseOutputItem::Reasoning(ResponseReasoningItem {
+ id: Some("rs_789".into()),
+ summary: vec![ReasoningSummaryPart::SummaryText {
+ text: "Summary without deltas".into(),
+ }],
+ }),
+ },
+ ResponsesStreamEvent::Completed {
+ response: ResponseSummary::default(),
+ },
+ ];
+
+ let mapped = map_response_events(events);
+ assert!(
+ !mapped
+ .iter()
+ .any(|e| matches!(e, LanguageModelCompletionEvent::Thinking { .. })),
+ "OutputItemDone reasoning should not produce Thinking events"
+ );
+ }
+}
@@ -1,4 +1,5 @@
pub mod batches;
+pub mod completion;
pub mod responses;
use anyhow::{Context as _, Result, anyhow};
@@ -7,9 +8,9 @@ use http_client::{
AsyncBody, HttpClient, Method, Request as HttpRequest, StatusCode,
http::{HeaderMap, HeaderValue},
};
+pub use language_model_core::ReasoningEffort;
use serde::{Deserialize, Serialize};
use serde_json::Value;
-pub use settings::OpenAiReasoningEffort as ReasoningEffort;
use std::{convert::TryFrom, future::Future};
use strum::EnumIter;
use thiserror::Error;
@@ -727,3 +728,26 @@ pub fn embed<'a>(
Ok(response)
}
}
+
+// -- Conversions to `language_model_core` types --
+
+impl From<RequestError> for language_model_core::LanguageModelCompletionError {
+ fn from(error: RequestError) -> Self {
+ match error {
+ RequestError::HttpResponseError {
+ provider,
+ status_code,
+ body,
+ headers,
+ } => {
+ let retry_after = headers
+ .get(http_client::http::header::RETRY_AFTER)
+ .and_then(|val| val.to_str().ok()?.parse::<u64>().ok())
+ .map(std::time::Duration::from_secs);
+
+ Self::from_http_status(provider.into(), status_code, body, retry_after)
+ }
+ RequestError::Other(e) => Self::Other(e),
+ }
+ }
+}
@@ -19,6 +19,7 @@ schemars = ["dep:schemars"]
anyhow.workspace = true
futures.workspace = true
http_client.workspace = true
+language_model_core.workspace = true
schemars = { workspace = true, optional = true }
serde.workspace = true
serde_json.workspace = true
@@ -744,3 +744,71 @@ impl ApiErrorCode {
}
}
}
+
+// -- Conversions to `language_model_core` types --
+
+impl From<OpenRouterError> for language_model_core::LanguageModelCompletionError {
+ fn from(error: OpenRouterError) -> Self {
+ let provider = language_model_core::LanguageModelProviderName::new("OpenRouter");
+ match error {
+ OpenRouterError::SerializeRequest(error) => Self::SerializeRequest { provider, error },
+ OpenRouterError::BuildRequestBody(error) => Self::BuildRequestBody { provider, error },
+ OpenRouterError::HttpSend(error) => Self::HttpSend { provider, error },
+ OpenRouterError::DeserializeResponse(error) => {
+ Self::DeserializeResponse { provider, error }
+ }
+ OpenRouterError::ReadResponse(error) => Self::ApiReadResponseError { provider, error },
+ OpenRouterError::RateLimit { retry_after } => Self::RateLimitExceeded {
+ provider,
+ retry_after: Some(retry_after),
+ },
+ OpenRouterError::ServerOverloaded { retry_after } => Self::ServerOverloaded {
+ provider,
+ retry_after,
+ },
+ OpenRouterError::ApiError(api_error) => api_error.into(),
+ }
+ }
+}
+
+impl From<ApiError> for language_model_core::LanguageModelCompletionError {
+ fn from(error: ApiError) -> Self {
+ use ApiErrorCode::*;
+ let provider = language_model_core::LanguageModelProviderName::new("OpenRouter");
+ match error.code {
+ InvalidRequestError => Self::BadRequestFormat {
+ provider,
+ message: error.message,
+ },
+ AuthenticationError => Self::AuthenticationError {
+ provider,
+ message: error.message,
+ },
+ PaymentRequiredError => Self::AuthenticationError {
+ provider,
+ message: format!("Payment required: {}", error.message),
+ },
+ PermissionError => Self::PermissionError {
+ provider,
+ message: error.message,
+ },
+ RequestTimedOut => Self::HttpResponseError {
+ provider,
+ status_code: http_client::StatusCode::REQUEST_TIMEOUT,
+ message: error.message,
+ },
+ RateLimitError => Self::RateLimitExceeded {
+ provider,
+ retry_after: None,
+ },
+ ApiError => Self::ApiInternalServerError {
+ provider,
+ message: error.message,
+ },
+ OverloadedError => Self::ServerOverloaded {
+ provider,
+ retry_after: None,
+ },
+ }
+ }
+}
@@ -23,8 +23,8 @@ use gpui::{
uniform_list,
};
use itertools::Itertools;
-use language::language_settings::LanguageSettings;
use language::{Anchor, BufferId, BufferSnapshot, OffsetRangeExt, OutlineItem};
+use language::{LanguageAwareStyling, language_settings::LanguageSettings};
use menu::{Cancel, SelectFirst, SelectLast, SelectNext, SelectPrevious};
use std::{
@@ -217,10 +217,13 @@ impl SearchState {
let mut offset = context_offset_range.start;
let mut context_text = String::new();
let mut highlight_ranges = Vec::new();
- for mut chunk in highlight_arguments
- .multi_buffer_snapshot
- .chunks(context_offset_range.start..context_offset_range.end, true)
- {
+ for mut chunk in highlight_arguments.multi_buffer_snapshot.chunks(
+ context_offset_range.start..context_offset_range.end,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ ) {
if !non_whitespace_symbol_occurred {
for c in chunk.text.chars() {
if c.is_whitespace() {
@@ -5,6 +5,7 @@ pub struct HighlightedMatchWithPaths {
pub prefix: Option<SharedString>,
pub match_label: HighlightedMatch,
pub paths: Vec<HighlightedMatch>,
+ pub active: bool,
}
#[derive(Debug, Clone, IntoElement)]
@@ -63,18 +64,30 @@ impl HighlightedMatchWithPaths {
.color(Color::Muted)
}))
}
+
+ pub fn is_active(mut self, active: bool) -> Self {
+ self.active = active;
+ self
+ }
}
impl RenderOnce for HighlightedMatchWithPaths {
fn render(mut self, _window: &mut Window, _: &mut App) -> impl IntoElement {
v_flex()
.child(
- h_flex().gap_1().child(self.match_label.clone()).when_some(
- self.prefix.as_ref(),
- |this, prefix| {
+ h_flex()
+ .gap_1()
+ .child(self.match_label.clone())
+ .when_some(self.prefix.as_ref(), |this, prefix| {
this.child(Label::new(format!("({})", prefix)).color(Color::Muted))
- },
- ),
+ })
+ .when(self.active, |this| {
+ this.child(
+ Icon::new(IconName::Check)
+ .size(IconSize::Small)
+ .color(Color::Accent),
+ )
+ }),
)
.when(!self.paths.is_empty(), |this| {
self.render_paths_children(this)
@@ -52,6 +52,7 @@ fancy-regex.workspace = true
fs.workspace = true
futures.workspace = true
fuzzy.workspace = true
+fuzzy_nucleo.workspace = true
git.workspace = true
git_hosting_providers.workspace = true
globset.workspace = true
@@ -32,10 +32,10 @@ use git::{
blame::Blame,
parse_git_remote_url,
repository::{
- Branch, CommitDetails, CommitDiff, CommitFile, CommitOptions, DiffType, FetchOptions,
- GitRepository, GitRepositoryCheckpoint, GraphCommitData, InitialGraphCommitData, LogOrder,
- LogSource, PushOptions, Remote, RemoteCommandOutput, RepoPath, ResetMode, SearchCommitArgs,
- UpstreamTrackingStatus, Worktree as GitWorktree,
+ Branch, CommitDetails, CommitDiff, CommitFile, CommitOptions, CreateWorktreeTarget,
+ DiffType, FetchOptions, GitRepository, GitRepositoryCheckpoint, GraphCommitData,
+ InitialGraphCommitData, LogOrder, LogSource, PushOptions, Remote, RemoteCommandOutput,
+ RepoPath, ResetMode, SearchCommitArgs, UpstreamTrackingStatus, Worktree as GitWorktree,
},
stash::{GitStash, StashEntry},
status::{
@@ -329,12 +329,6 @@ pub struct GraphDataResponse<'a> {
pub error: Option<SharedString>,
}
-#[derive(Clone, Debug)]
-enum CreateWorktreeStartPoint {
- Detached,
- Branched { name: String },
-}
-
pub struct Repository {
this: WeakEntity<Self>,
snapshot: RepositorySnapshot,
@@ -2414,18 +2408,23 @@ impl GitStore {
let repository_id = RepositoryId::from_proto(envelope.payload.repository_id);
let repository_handle = Self::repository_for_request(&this, repository_id, &mut cx)?;
let directory = PathBuf::from(envelope.payload.directory);
- let start_point = if envelope.payload.name.is_empty() {
- CreateWorktreeStartPoint::Detached
+ let name = envelope.payload.name;
+ let commit = envelope.payload.commit;
+ let use_existing_branch = envelope.payload.use_existing_branch;
+ let target = if name.is_empty() {
+ CreateWorktreeTarget::Detached { base_sha: commit }
+ } else if use_existing_branch {
+ CreateWorktreeTarget::ExistingBranch { branch_name: name }
} else {
- CreateWorktreeStartPoint::Branched {
- name: envelope.payload.name,
+ CreateWorktreeTarget::NewBranch {
+ branch_name: name,
+ base_sha: commit,
}
};
- let commit = envelope.payload.commit;
repository_handle
.update(&mut cx, |repository_handle, _| {
- repository_handle.create_worktree_with_start_point(start_point, directory, commit)
+ repository_handle.create_worktree(target, directory)
})
.await??;
@@ -6004,50 +6003,43 @@ impl Repository {
})
}
- fn create_worktree_with_start_point(
+ pub fn create_worktree(
&mut self,
- start_point: CreateWorktreeStartPoint,
+ target: CreateWorktreeTarget,
path: PathBuf,
- commit: Option<String>,
) -> oneshot::Receiver<Result<()>> {
- if matches!(
- &start_point,
- CreateWorktreeStartPoint::Branched { name } if name.is_empty()
- ) {
- let (sender, receiver) = oneshot::channel();
- sender
- .send(Err(anyhow!("branch name cannot be empty")))
- .ok();
- return receiver;
- }
-
let id = self.id;
- let message = match &start_point {
- CreateWorktreeStartPoint::Detached => "git worktree add (detached)".into(),
- CreateWorktreeStartPoint::Branched { name } => {
- format!("git worktree add: {name}").into()
- }
+ let job_description = match target.branch_name() {
+ Some(branch_name) => format!("git worktree add: {branch_name}"),
+ None => "git worktree add (detached)".to_string(),
};
-
- self.send_job(Some(message), move |repo, _cx| async move {
- let branch_name = match start_point {
- CreateWorktreeStartPoint::Detached => None,
- CreateWorktreeStartPoint::Branched { name } => Some(name),
- };
- let remote_name = branch_name.clone().unwrap_or_default();
-
+ self.send_job(Some(job_description.into()), move |repo, _cx| async move {
match repo {
RepositoryState::Local(LocalRepositoryState { backend, .. }) => {
- backend.create_worktree(branch_name, path, commit).await
+ backend.create_worktree(target, path).await
}
RepositoryState::Remote(RemoteRepositoryState { project_id, client }) => {
+ let (name, commit, use_existing_branch) = match target {
+ CreateWorktreeTarget::ExistingBranch { branch_name } => {
+ (branch_name, None, true)
+ }
+ CreateWorktreeTarget::NewBranch {
+ branch_name,
+ base_sha: start_point,
+ } => (branch_name, start_point, false),
+ CreateWorktreeTarget::Detached {
+ base_sha: start_point,
+ } => (String::new(), start_point, false),
+ };
+
client
.request(proto::GitCreateWorktree {
project_id: project_id.0,
repository_id: id.to_proto(),
- name: remote_name,
+ name,
directory: path.to_string_lossy().to_string(),
commit,
+ use_existing_branch,
})
.await?;
@@ -6057,28 +6049,16 @@ impl Repository {
})
}
- pub fn create_worktree(
- &mut self,
- branch_name: String,
- path: PathBuf,
- commit: Option<String>,
- ) -> oneshot::Receiver<Result<()>> {
- self.create_worktree_with_start_point(
- CreateWorktreeStartPoint::Branched { name: branch_name },
- path,
- commit,
- )
- }
-
pub fn create_worktree_detached(
&mut self,
path: PathBuf,
commit: String,
) -> oneshot::Receiver<Result<()>> {
- self.create_worktree_with_start_point(
- CreateWorktreeStartPoint::Detached,
+ self.create_worktree(
+ CreateWorktreeTarget::Detached {
+ base_sha: Some(commit),
+ },
path,
- Some(commit),
)
}
@@ -72,9 +72,10 @@ use itertools::Itertools as _;
use language::{
Bias, BinaryStatus, Buffer, BufferRow, BufferSnapshot, CachedLspAdapter, Capability, CodeLabel,
CodeLabelExt, Diagnostic, DiagnosticEntry, DiagnosticSet, DiagnosticSourceKind, Diff,
- File as _, Language, LanguageName, LanguageRegistry, LocalFile, LspAdapter, LspAdapterDelegate,
- LspInstaller, ManifestDelegate, ManifestName, ModelineSettings, OffsetUtf16, Patch, PointUtf16,
- TextBufferSnapshot, ToOffset, ToOffsetUtf16, ToPointUtf16, Toolchain, Transaction, Unclipped,
+ File as _, Language, LanguageAwareStyling, LanguageName, LanguageRegistry, LocalFile,
+ LspAdapter, LspAdapterDelegate, LspInstaller, ManifestDelegate, ManifestName, ModelineSettings,
+ OffsetUtf16, Patch, PointUtf16, TextBufferSnapshot, ToOffset, ToOffsetUtf16, ToPointUtf16,
+ Toolchain, Transaction, Unclipped,
language_settings::{
AllLanguageSettings, FormatOnSave, Formatter, LanguageSettings, all_language_settings,
},
@@ -13527,7 +13528,13 @@ fn resolve_word_completion(snapshot: &BufferSnapshot, completion: &mut Completio
}
let mut offset = 0;
- for chunk in snapshot.chunks(word_range.clone(), true) {
+ for chunk in snapshot.chunks(
+ word_range.clone(),
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ ) {
let end_offset = offset + chunk.text.len();
if let Some(highlight_id) = chunk.syntax_highlight_id {
completion
@@ -412,7 +412,7 @@ impl PrettierStore {
prettier_store
.update(cx, |prettier_store, cx| {
let name = if is_default {
- LanguageServerName("prettier (default)".to_string().into())
+ LanguageServerName("prettier (default)".into())
} else {
let worktree_path = worktree_id
.and_then(|id| {
@@ -6186,6 +6186,76 @@ impl<'a> Iterator for PathMatchCandidateSetIter<'a> {
}
}
+impl<'a> fuzzy_nucleo::PathMatchCandidateSet<'a> for PathMatchCandidateSet {
+ type Candidates = PathMatchCandidateSetNucleoIter<'a>;
+ fn id(&self) -> usize {
+ self.snapshot.id().to_usize()
+ }
+ fn len(&self) -> usize {
+ match self.candidates {
+ Candidates::Files => {
+ if self.include_ignored {
+ self.snapshot.file_count()
+ } else {
+ self.snapshot.visible_file_count()
+ }
+ }
+ Candidates::Directories => {
+ if self.include_ignored {
+ self.snapshot.dir_count()
+ } else {
+ self.snapshot.visible_dir_count()
+ }
+ }
+ Candidates::Entries => {
+ if self.include_ignored {
+ self.snapshot.entry_count()
+ } else {
+ self.snapshot.visible_entry_count()
+ }
+ }
+ }
+ }
+ fn prefix(&self) -> Arc<RelPath> {
+ if self.snapshot.root_entry().is_some_and(|e| e.is_file()) || self.include_root_name {
+ self.snapshot.root_name().into()
+ } else {
+ RelPath::empty().into()
+ }
+ }
+ fn root_is_file(&self) -> bool {
+ self.snapshot.root_entry().is_some_and(|f| f.is_file())
+ }
+ fn path_style(&self) -> PathStyle {
+ self.snapshot.path_style()
+ }
+ fn candidates(&'a self, start: usize) -> Self::Candidates {
+ PathMatchCandidateSetNucleoIter {
+ traversal: match self.candidates {
+ Candidates::Directories => self.snapshot.directories(self.include_ignored, start),
+ Candidates::Files => self.snapshot.files(self.include_ignored, start),
+ Candidates::Entries => self.snapshot.entries(self.include_ignored, start),
+ },
+ }
+ }
+}
+
+pub struct PathMatchCandidateSetNucleoIter<'a> {
+ traversal: Traversal<'a>,
+}
+
+impl<'a> Iterator for PathMatchCandidateSetNucleoIter<'a> {
+ type Item = fuzzy_nucleo::PathMatchCandidate<'a>;
+ fn next(&mut self) -> Option<Self::Item> {
+ self.traversal
+ .next()
+ .map(|entry| fuzzy_nucleo::PathMatchCandidate {
+ is_dir: entry.kind.is_dir(),
+ path: &entry.path,
+ })
+ }
+}
+
impl EventEmitter<Event> for Project {}
impl<'a> From<&'a ProjectPath> for SettingsLocation<'a> {
@@ -1267,9 +1267,11 @@ mod git_worktrees {
cx.update(|cx| {
repository.update(cx, |repository, _| {
repository.create_worktree(
- "feature-branch".to_string(),
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: "feature-branch".to_string(),
+ base_sha: Some("abc123".to_string()),
+ },
worktree_1_directory.clone(),
- Some("abc123".to_string()),
)
})
})
@@ -1297,9 +1299,11 @@ mod git_worktrees {
cx.update(|cx| {
repository.update(cx, |repository, _| {
repository.create_worktree(
- "bugfix-branch".to_string(),
+ git::repository::CreateWorktreeTarget::NewBranch {
+ branch_name: "bugfix-branch".to_string(),
+ base_sha: None,
+ },
worktree_2_directory.clone(),
- None,
)
})
})
@@ -41,9 +41,10 @@ use gpui::{
use itertools::Itertools;
use language::{
Buffer, BufferEvent, Diagnostic, DiagnosticEntry, DiagnosticEntryRef, DiagnosticSet,
- DiagnosticSourceKind, DiskState, FakeLspAdapter, Language, LanguageConfig, LanguageMatcher,
- LanguageName, LineEnding, ManifestName, ManifestProvider, ManifestQuery, OffsetRangeExt, Point,
- ToPoint, Toolchain, ToolchainList, ToolchainLister, ToolchainMetadata,
+ DiagnosticSourceKind, DiskState, FakeLspAdapter, Language, LanguageAwareStyling,
+ LanguageConfig, LanguageMatcher, LanguageName, LineEnding, ManifestName, ManifestProvider,
+ ManifestQuery, OffsetRangeExt, Point, ToPoint, Toolchain, ToolchainList, ToolchainLister,
+ ToolchainMetadata,
language_settings::{LanguageSettings, LanguageSettingsContent},
markdown_lang, rust_lang, tree_sitter_typescript,
};
@@ -4382,7 +4383,13 @@ fn chunks_with_diagnostics<T: ToOffset + ToPoint>(
range: Range<T>,
) -> Vec<(String, Option<DiagnosticSeverity>)> {
let mut chunks: Vec<(String, Option<DiagnosticSeverity>)> = Vec::new();
- for chunk in buffer.snapshot().chunks(range, true) {
+ for chunk in buffer.snapshot().chunks(
+ range,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
+ ) {
if chunks
.last()
.is_some_and(|prev_chunk| prev_chunk.1 == chunk.diagnostic_severity)
@@ -11,7 +11,7 @@ use std::path::{Path, PathBuf};
use util::{path, paths::PathStyle, rel_path::rel_path};
use workspace::{
AppState, ItemHandle, MultiWorkspace, Pane, Workspace,
- item::{Item, ProjectItem},
+ item::{Item, ProjectItem, test::TestItem},
register_project_item,
};
@@ -6015,6 +6015,150 @@ async fn test_explicit_reveal(cx: &mut gpui::TestAppContext) {
);
}
+#[gpui::test]
+async fn test_reveal_in_project_panel_notifications(cx: &mut gpui::TestAppContext) {
+ init_test_with_editor(cx);
+ let fs = FakeFs::new(cx.background_executor.clone());
+ fs.insert_tree(
+ "/workspace",
+ json!({
+ "README.md": ""
+ }),
+ )
+ .await;
+
+ let project = Project::test(fs.clone(), ["/workspace".as_ref()], cx).await;
+ let window = cx.add_window(|window, cx| MultiWorkspace::test_new(project.clone(), window, cx));
+ let workspace = window
+ .read_with(cx, |mw, _| mw.workspace().clone())
+ .unwrap();
+ let cx = &mut VisualTestContext::from_window(window.into(), cx);
+ let panel = workspace.update_in(cx, ProjectPanel::new);
+ cx.run_until_parked();
+
+ // Ensure that, attempting to run `pane: reveal in project panel` without
+ // any active item does nothing, i.e., does not focus the project panel but
+ // it also does not show a notification.
+ cx.dispatch_action(workspace::RevealInProjectPanel::default());
+ cx.run_until_parked();
+
+ panel.update_in(cx, |panel, window, cx| {
+ assert!(
+ !panel.focus_handle(cx).is_focused(window),
+ "Project panel should not be focused after attempting to reveal an invisible worktree entry"
+ );
+
+ panel.workspace.update(cx, |workspace, cx| {
+ assert!(
+ workspace.active_item(cx).is_none(),
+ "Workspace should not have an active item"
+ );
+ assert_eq!(
+ workspace.notification_ids(),
+ vec![],
+ "No notification should be shown when there's no active item"
+ );
+ }).unwrap();
+ });
+
+ // Create a file in a different folder than the one in the project so we can
+ // later open it and ensure that, attempting to reveal it in the project
+ // panel shows a notification and does not focus the project panel.
+ fs.insert_tree(
+ "/external",
+ json!({
+ "file.txt": "External File",
+ }),
+ )
+ .await;
+
+ let (worktree, _) = project
+ .update(cx, |project, cx| {
+ project.find_or_create_worktree("/external/file.txt", false, cx)
+ })
+ .await
+ .unwrap();
+
+ workspace
+ .update_in(cx, |workspace, window, cx| {
+ let worktree_id = worktree.read(cx).id();
+ let path = rel_path("").into();
+ let project_path = ProjectPath { worktree_id, path };
+
+ workspace.open_path(project_path, None, true, window, cx)
+ })
+ .await
+ .unwrap();
+ cx.run_until_parked();
+
+ cx.dispatch_action(workspace::RevealInProjectPanel::default());
+ cx.run_until_parked();
+
+ panel.update_in(cx, |panel, window, cx| {
+ assert!(
+ !panel.focus_handle(cx).is_focused(window),
+ "Project panel should not be focused after attempting to reveal an invisible worktree entry"
+ );
+
+ panel.workspace.update(cx, |workspace, cx| {
+ assert!(
+ workspace.active_item(cx).is_some(),
+ "Workspace should have an active item"
+ );
+
+ let notification_ids = workspace.notification_ids();
+ assert_eq!(
+ notification_ids.len(),
+ 1,
+ "A notification should be shown when trying to reveal an invisible worktree entry"
+ );
+
+ workspace.dismiss_notification(¬ification_ids[0], cx);
+ assert_eq!(
+ workspace.notification_ids().len(),
+ 0,
+ "No notifications should be left after dismissing"
+ );
+ }).unwrap();
+ });
+
+ // Create an empty buffer so we can ensure that, attempting to reveal it in
+ // the project panel shows a notification and does not focus the project
+ // panel.
+ let pane = workspace.update(cx, |workspace, _| workspace.active_pane().clone());
+ pane.update_in(cx, |pane, window, cx| {
+ let item = cx.new(|cx| TestItem::new(cx).with_label("Unsaved buffer"));
+ pane.add_item(Box::new(item), false, false, None, window, cx);
+ });
+
+ cx.dispatch_action(workspace::RevealInProjectPanel::default());
+ cx.run_until_parked();
+
+ panel.update_in(cx, |panel, window, cx| {
+ assert!(
+ !panel.focus_handle(cx).is_focused(window),
+ "Project panel should not be focused after attempting to reveal an unsaved buffer"
+ );
+
+ panel
+ .workspace
+ .update(cx, |workspace, cx| {
+ assert!(
+ workspace.active_item(cx).is_some(),
+ "Workspace should have an active item"
+ );
+
+ let notification_ids = workspace.notification_ids();
+ assert_eq!(
+ notification_ids.len(),
+ 1,
+ "A notification should be shown when trying to reveal an unsaved buffer"
+ );
+ })
+ .unwrap();
+ });
+}
+
#[gpui::test]
async fn test_creating_excluded_entries(cx: &mut gpui::TestAppContext) {
init_test(cx);
@@ -594,6 +594,7 @@ message GitCreateWorktree {
string name = 3;
string directory = 4;
optional string commit = 5;
+ bool use_existing_branch = 6;
}
message GitCreateCheckpoint {
@@ -720,6 +720,9 @@ impl RecentProjects {
picker.delegate.workspaces.get(hit.candidate_id)
{
let workspace_id = *workspace_id;
+ if picker.delegate.is_current_workspace(workspace_id, cx) {
+ return;
+ }
picker
.delegate
.remove_sibling_workspace(workspace_id, window, cx);
@@ -939,7 +942,7 @@ impl PickerDelegate for RecentProjectsDelegate {
.workspaces
.iter()
.enumerate()
- .filter(|(_, (id, _, _, _))| self.is_sibling_workspace(*id, cx))
+ .filter(|(_, (id, _, _, _))| self.sibling_workspace_ids.contains(id))
.map(|(id, (_, _, paths, _))| {
let combined_string = paths
.ordered_paths()
@@ -1028,7 +1031,7 @@ impl PickerDelegate for RecentProjectsDelegate {
if is_empty_query {
for (id, (workspace_id, _, _, _)) in self.workspaces.iter().enumerate() {
- if self.is_sibling_workspace(*workspace_id, cx) {
+ if self.sibling_workspace_ids.contains(workspace_id) {
entries.push(ProjectPickerEntry::OpenProject(StringMatch {
candidate_id: id,
score: 0.0,
@@ -1106,6 +1109,11 @@ impl PickerDelegate for RecentProjectsDelegate {
};
let workspace_id = *workspace_id;
+ if self.is_current_workspace(workspace_id, cx) {
+ cx.emit(DismissEvent);
+ return;
+ }
+
if let Some(handle) = window.window_handle().downcast::<MultiWorkspace>() {
cx.defer(move |cx| {
handle
@@ -1349,6 +1357,7 @@ impl PickerDelegate for RecentProjectsDelegate {
ProjectPickerEntry::OpenProject(hit) => {
let (workspace_id, location, paths, _) = self.workspaces.get(hit.candidate_id)?;
let workspace_id = *workspace_id;
+ let is_current = self.is_current_workspace(workspace_id, cx);
let ordered_paths: Vec<_> = paths
.ordered_paths()
.map(|p| p.compact().to_string_lossy().to_string())
@@ -1388,6 +1397,7 @@ impl PickerDelegate for RecentProjectsDelegate {
prefix,
match_label: HighlightedMatch::join(match_labels.into_iter().flatten(), ", "),
paths,
+ active: is_current,
};
let icon = icon_for_remote_connection(match location {
@@ -1397,20 +1407,24 @@ impl PickerDelegate for RecentProjectsDelegate {
let secondary_actions = h_flex()
.gap_1()
- .child(
- IconButton::new("remove_open_project", IconName::Close)
- .icon_size(IconSize::Small)
- .tooltip(Tooltip::text("Remove Project from Window"))
- .on_click(cx.listener(move |picker, _, window, cx| {
- cx.stop_propagation();
- window.prevent_default();
- picker
- .delegate
- .remove_sibling_workspace(workspace_id, window, cx);
- let query = picker.query(cx);
- picker.update_matches(query, window, cx);
- })),
- )
+ .when(!is_current, |this| {
+ this.child(
+ IconButton::new("remove_open_project", IconName::Close)
+ .icon_size(IconSize::Small)
+ .tooltip(Tooltip::text("Remove Project from Window"))
+ .on_click(cx.listener(move |picker, _, window, cx| {
+ cx.stop_propagation();
+ window.prevent_default();
+ picker.delegate.remove_sibling_workspace(
+ workspace_id,
+ window,
+ cx,
+ );
+ let query = picker.query(cx);
+ picker.update_matches(query, window, cx);
+ })),
+ )
+ })
.into_any_element();
Some(
@@ -1483,6 +1497,7 @@ impl PickerDelegate for RecentProjectsDelegate {
prefix,
match_label: HighlightedMatch::join(match_labels.into_iter().flatten(), ", "),
paths,
+ active: false,
};
let focus_handle = self.focus_handle.clone();
@@ -1491,9 +1506,16 @@ impl PickerDelegate for RecentProjectsDelegate {
.gap_px()
.when(is_local, |this| {
this.child(
- IconButton::new("add_to_workspace", IconName::FolderPlus)
+ IconButton::new("add_to_workspace", IconName::FolderOpenAdd)
.icon_size(IconSize::Small)
- .tooltip(Tooltip::text("Add Project to this Workspace"))
+ .tooltip(move |_, cx| {
+ Tooltip::with_meta(
+ "Add Project to this Workspace",
+ None,
+ "As a multi-root folder project",
+ cx,
+ )
+ })
.on_click({
let paths_to_add = paths_to_add.clone();
cx.listener(move |picker, _event, window, cx| {
@@ -1509,8 +1531,8 @@ impl PickerDelegate for RecentProjectsDelegate {
)
})
.child(
- IconButton::new("open_new_window", IconName::ArrowUpRight)
- .icon_size(IconSize::XSmall)
+ IconButton::new("open_new_window", IconName::OpenNewWindow)
+ .icon_size(IconSize::Small)
.tooltip({
move |_, cx| {
Tooltip::for_action_in(
@@ -1565,7 +1587,14 @@ impl PickerDelegate for RecentProjectsDelegate {
}
highlighted.render(window, cx)
})
- .tooltip(Tooltip::text(tooltip_path)),
+ .tooltip(move |_, cx| {
+ Tooltip::with_meta(
+ "Open Project in This Window",
+ None,
+ tooltip_path.clone(),
+ cx,
+ )
+ }),
)
.end_slot(secondary_actions)
.show_end_slot_on_hover()
@@ -1625,27 +1654,41 @@ impl PickerDelegate for RecentProjectsDelegate {
let selected_entry = self.filtered_entries.get(self.selected_index);
+ let is_current_workspace_entry =
+ if let Some(ProjectPickerEntry::OpenProject(hit)) = selected_entry {
+ self.workspaces
+ .get(hit.candidate_id)
+ .map(|(id, ..)| self.is_current_workspace(*id, cx))
+ .unwrap_or(false)
+ } else {
+ false
+ };
+
let secondary_footer_actions: Option<AnyElement> = match selected_entry {
- Some(ProjectPickerEntry::OpenFolder { .. } | ProjectPickerEntry::OpenProject(_)) => {
- let label = if matches!(selected_entry, Some(ProjectPickerEntry::OpenFolder { .. }))
- {
- "Remove Folder"
- } else {
- "Remove from Window"
- };
- Some(
- Button::new("remove_selected", label)
- .key_binding(KeyBinding::for_action_in(
- &RemoveSelected,
- &focus_handle,
- cx,
- ))
- .on_click(|_, window, cx| {
- window.dispatch_action(RemoveSelected.boxed_clone(), cx)
- })
- .into_any_element(),
- )
- }
+ Some(ProjectPickerEntry::OpenFolder { .. }) => Some(
+ Button::new("remove_selected", "Remove Folder")
+ .key_binding(KeyBinding::for_action_in(
+ &RemoveSelected,
+ &focus_handle,
+ cx,
+ ))
+ .on_click(|_, window, cx| {
+ window.dispatch_action(RemoveSelected.boxed_clone(), cx)
+ })
+ .into_any_element(),
+ ),
+ Some(ProjectPickerEntry::OpenProject(_)) if !is_current_workspace_entry => Some(
+ Button::new("remove_selected", "Remove from Window")
+ .key_binding(KeyBinding::for_action_in(
+ &RemoveSelected,
+ &focus_handle,
+ cx,
+ ))
+ .on_click(|_, window, cx| {
+ window.dispatch_action(RemoveSelected.boxed_clone(), cx)
+ })
+ .into_any_element(),
+ ),
Some(ProjectPickerEntry::RecentProject(_)) => Some(
Button::new("delete_recent", "Delete")
.key_binding(KeyBinding::for_action_in(
@@ -1748,7 +1791,7 @@ impl PickerDelegate for RecentProjectsDelegate {
menu.context(focus_handle)
.when(show_add_to_workspace, |menu| {
menu.action(
- "Add to Workspace",
+ "Add to this Workspace",
AddToWorkspace.boxed_clone(),
)
.separator()
@@ -374,6 +374,7 @@ impl PickerDelegate for SidebarRecentProjectsDelegate {
prefix,
match_label: HighlightedMatch::join(match_labels.into_iter().flatten(), ", "),
paths: Vec::new(),
+ active: false,
};
let icon = icon_for_remote_connection(match location {
@@ -395,7 +396,14 @@ impl PickerDelegate for SidebarRecentProjectsDelegate {
})
.child(highlighted_match.render(window, cx)),
)
- .tooltip(Tooltip::text(tooltip_path))
+ .tooltip(move |_, cx| {
+ Tooltip::with_meta(
+ "Open Project in This Window",
+ None,
+ tooltip_path.clone(),
+ cx,
+ )
+ })
.into_any_element(),
)
}
@@ -215,7 +215,7 @@ impl SshRunningKernel {
&session_id,
)
.await
- .context("failed to create iopub connection")?;
+ .context("Failed to create iopub connection. Is `ipykernel` installed in the remote environment? Try running `pip install ipykernel` on the remote host.")?;
let peer_identity = runtimelib::peer_identity_for_session(&session_id)?;
let shell_socket = runtimelib::create_client_shell_connection_with_identity(
@@ -354,7 +354,8 @@ impl WslRunningKernel {
"",
&session_id,
)
- .await?;
+ .await
+ .context("Failed to create iopub connection. Is `ipykernel` installed in the WSL environment? Try running `pip install ipykernel` inside your WSL distribution.")?;
let peer_identity = runtimelib::peer_identity_for_session(&session_id)?;
let shell_socket = runtimelib::create_client_shell_connection_with_identity(
@@ -849,6 +849,7 @@ impl BufferSearchBar {
let query_editor = cx.new(|cx| {
let mut editor = Editor::auto_height(1, 4, window, cx);
editor.set_use_autoclose(false);
+ editor.set_use_selection_highlight(false);
editor
});
cx.subscribe_in(&query_editor, window, Self::on_query_editor_event)
@@ -769,6 +769,17 @@ impl ProjectSearchView {
}
}
+ fn set_search_option_enabled(
+ &mut self,
+ option: SearchOptions,
+ enabled: bool,
+ cx: &mut Context<Self>,
+ ) {
+ if self.search_options.contains(option) != enabled {
+ self.toggle_search_option(option, cx);
+ }
+ }
+
fn toggle_search_option(&mut self, option: SearchOptions, cx: &mut Context<Self>) {
self.search_options.toggle(option);
ActiveSettings::update_global(cx, |settings, cx| {
@@ -928,6 +939,7 @@ impl ProjectSearchView {
let mut editor = Editor::auto_height(1, 4, window, cx);
editor.set_placeholder_text("Search all filesβ¦", window, cx);
editor.set_use_autoclose(false);
+ editor.set_use_selection_highlight(false);
editor.set_text(query_text, window, cx);
editor
});
@@ -1153,7 +1165,7 @@ impl ProjectSearchView {
window: &mut Window,
cx: &mut Context<Workspace>,
) {
- Self::existing_or_new_search(workspace, None, &DeploySearch::find(), window, cx)
+ Self::existing_or_new_search(workspace, None, &DeploySearch::default(), window, cx)
}
fn existing_or_new_search(
@@ -1203,8 +1215,29 @@ impl ProjectSearchView {
search.update(cx, |search, cx| {
search.replace_enabled |= action.replace_enabled;
+ if let Some(regex) = action.regex {
+ search.set_search_option_enabled(SearchOptions::REGEX, regex, cx);
+ }
+ if let Some(case_sensitive) = action.case_sensitive {
+ search.set_search_option_enabled(SearchOptions::CASE_SENSITIVE, case_sensitive, cx);
+ }
+ if let Some(whole_word) = action.whole_word {
+ search.set_search_option_enabled(SearchOptions::WHOLE_WORD, whole_word, cx);
+ }
+ if let Some(include_ignored) = action.include_ignored {
+ search.set_search_option_enabled(
+ SearchOptions::INCLUDE_IGNORED,
+ include_ignored,
+ cx,
+ );
+ }
+ let query = action
+ .query
+ .as_deref()
+ .filter(|q| !q.is_empty())
+ .or(query.as_deref());
if let Some(query) = query {
- search.set_query(&query, window, cx);
+ search.set_query(query, window, cx);
}
if let Some(included_files) = action.included_files.as_deref() {
search
@@ -3101,7 +3134,7 @@ pub mod tests {
ProjectSearchView::deploy_search(
workspace,
- &workspace::DeploySearch::find(),
+ &workspace::DeploySearch::default(),
window,
cx,
)
@@ -3252,7 +3285,7 @@ pub mod tests {
workspace.update_in(cx, |workspace, window, cx| {
ProjectSearchView::deploy_search(
workspace,
- &workspace::DeploySearch::find(),
+ &workspace::DeploySearch::default(),
window,
cx,
)
@@ -3325,7 +3358,7 @@ pub mod tests {
ProjectSearchView::deploy_search(
workspace,
- &workspace::DeploySearch::find(),
+ &workspace::DeploySearch::default(),
window,
cx,
)
@@ -4560,7 +4593,7 @@ pub mod tests {
});
// Deploy a new search
- cx.dispatch_action(DeploySearch::find());
+ cx.dispatch_action(DeploySearch::default());
// Both panes should now have a project search in them
workspace.update_in(cx, |workspace, window, cx| {
@@ -4585,7 +4618,7 @@ pub mod tests {
.unwrap();
// Deploy a new search
- cx.dispatch_action(DeploySearch::find());
+ cx.dispatch_action(DeploySearch::default());
// The project search view should now be focused in the second pane
// And the number of items should be unchanged.
@@ -4823,7 +4856,7 @@ pub mod tests {
assert!(workspace.has_active_modal(window, cx));
});
- cx.dispatch_action(DeploySearch::find());
+ cx.dispatch_action(DeploySearch::default());
workspace.update_in(cx, |workspace, window, cx| {
assert!(!workspace.has_active_modal(window, cx));
@@ -5136,6 +5169,271 @@ pub mod tests {
.unwrap();
}
+ #[gpui::test]
+ async fn test_deploy_search_applies_and_resets_options(cx: &mut TestAppContext) {
+ init_test(cx);
+
+ let fs = FakeFs::new(cx.background_executor.clone());
+ fs.insert_tree(
+ path!("/dir"),
+ json!({
+ "one.rs": "const ONE: usize = 1;",
+ }),
+ )
+ .await;
+ let project = Project::test(fs.clone(), [path!("/dir").as_ref()], cx).await;
+ let window = cx.add_window(|window, cx| MultiWorkspace::test_new(project, window, cx));
+ let workspace = window
+ .read_with(cx, |mw, _| mw.workspace().clone())
+ .unwrap();
+ let cx = &mut VisualTestContext::from_window(window.into(), cx);
+ let search_bar = window.build_entity(cx, |_, _| ProjectSearchBar::new());
+
+ workspace.update_in(cx, |workspace, window, cx| {
+ workspace.panes()[0].update(cx, |pane, cx| {
+ pane.toolbar()
+ .update(cx, |toolbar, cx| toolbar.add_item(search_bar, window, cx))
+ });
+
+ ProjectSearchView::deploy_search(
+ workspace,
+ &workspace::DeploySearch {
+ regex: Some(true),
+ case_sensitive: Some(true),
+ whole_word: Some(true),
+ include_ignored: Some(true),
+ query: Some("Test_Query".into()),
+ ..Default::default()
+ },
+ window,
+ cx,
+ )
+ });
+
+ let search_view = cx
+ .read(|cx| {
+ workspace
+ .read(cx)
+ .active_pane()
+ .read(cx)
+ .active_item()
+ .and_then(|item| item.downcast::<ProjectSearchView>())
+ })
+ .expect("Search view should be active after deploy");
+
+ search_view.update_in(cx, |search_view, _window, cx| {
+ assert!(
+ search_view.search_options.contains(SearchOptions::REGEX),
+ "Regex option should be enabled"
+ );
+ assert!(
+ search_view
+ .search_options
+ .contains(SearchOptions::CASE_SENSITIVE),
+ "Case sensitive option should be enabled"
+ );
+ assert!(
+ search_view
+ .search_options
+ .contains(SearchOptions::WHOLE_WORD),
+ "Whole word option should be enabled"
+ );
+ assert!(
+ search_view
+ .search_options
+ .contains(SearchOptions::INCLUDE_IGNORED),
+ "Include ignored option should be enabled"
+ );
+ let query_text = search_view.query_editor.read(cx).text(cx);
+ assert_eq!(
+ query_text, "Test_Query",
+ "Query should be set from the action"
+ );
+ });
+
+ // Redeploy with only regex - unspecified options should be preserved.
+ cx.dispatch_action(menu::Cancel);
+ workspace.update_in(cx, |workspace, window, cx| {
+ ProjectSearchView::deploy_search(
+ workspace,
+ &workspace::DeploySearch {
+ regex: Some(true),
+ ..Default::default()
+ },
+ window,
+ cx,
+ )
+ });
+
+ search_view.update_in(cx, |search_view, _window, _cx| {
+ assert!(
+ search_view.search_options.contains(SearchOptions::REGEX),
+ "Regex should still be enabled"
+ );
+ assert!(
+ search_view
+ .search_options
+ .contains(SearchOptions::CASE_SENSITIVE),
+ "Case sensitive should be preserved from previous deploy"
+ );
+ assert!(
+ search_view
+ .search_options
+ .contains(SearchOptions::WHOLE_WORD),
+ "Whole word should be preserved from previous deploy"
+ );
+ assert!(
+ search_view
+ .search_options
+ .contains(SearchOptions::INCLUDE_IGNORED),
+ "Include ignored should be preserved from previous deploy"
+ );
+ });
+
+ // Redeploy explicitly turning off options.
+ cx.dispatch_action(menu::Cancel);
+ workspace.update_in(cx, |workspace, window, cx| {
+ ProjectSearchView::deploy_search(
+ workspace,
+ &workspace::DeploySearch {
+ regex: Some(true),
+ case_sensitive: Some(false),
+ whole_word: Some(false),
+ include_ignored: Some(false),
+ ..Default::default()
+ },
+ window,
+ cx,
+ )
+ });
+
+ search_view.update_in(cx, |search_view, _window, _cx| {
+ assert_eq!(
+ search_view.search_options,
+ SearchOptions::REGEX,
+ "Explicit Some(false) should turn off options"
+ );
+ });
+
+ // Redeploy with an empty query - should not overwrite the existing query.
+ cx.dispatch_action(menu::Cancel);
+ workspace.update_in(cx, |workspace, window, cx| {
+ ProjectSearchView::deploy_search(
+ workspace,
+ &workspace::DeploySearch {
+ query: Some("".into()),
+ ..Default::default()
+ },
+ window,
+ cx,
+ )
+ });
+
+ search_view.update_in(cx, |search_view, _window, cx| {
+ let query_text = search_view.query_editor.read(cx).text(cx);
+ assert_eq!(
+ query_text, "Test_Query",
+ "Empty query string should not overwrite the existing query"
+ );
+ });
+ }
+
+ #[gpui::test]
+ async fn test_smartcase_overrides_explicit_case_sensitive(cx: &mut TestAppContext) {
+ init_test(cx);
+
+ cx.update(|cx| {
+ cx.update_global::<SettingsStore, _>(|store, cx| {
+ store.update_default_settings(cx, |settings| {
+ settings.editor.use_smartcase_search = Some(true);
+ });
+ });
+ });
+
+ let fs = FakeFs::new(cx.background_executor.clone());
+ fs.insert_tree(
+ path!("/dir"),
+ json!({
+ "one.rs": "const ONE: usize = 1;",
+ }),
+ )
+ .await;
+ let project = Project::test(fs.clone(), [path!("/dir").as_ref()], cx).await;
+ let window = cx.add_window(|window, cx| MultiWorkspace::test_new(project, window, cx));
+ let workspace = window
+ .read_with(cx, |mw, _| mw.workspace().clone())
+ .unwrap();
+ let cx = &mut VisualTestContext::from_window(window.into(), cx);
+ let search_bar = window.build_entity(cx, |_, _| ProjectSearchBar::new());
+
+ workspace.update_in(cx, |workspace, window, cx| {
+ workspace.panes()[0].update(cx, |pane, cx| {
+ pane.toolbar()
+ .update(cx, |toolbar, cx| toolbar.add_item(search_bar, window, cx))
+ });
+
+ ProjectSearchView::deploy_search(
+ workspace,
+ &workspace::DeploySearch {
+ case_sensitive: Some(true),
+ query: Some("lowercase_query".into()),
+ ..Default::default()
+ },
+ window,
+ cx,
+ )
+ });
+
+ let search_view = cx
+ .read(|cx| {
+ workspace
+ .read(cx)
+ .active_pane()
+ .read(cx)
+ .active_item()
+ .and_then(|item| item.downcast::<ProjectSearchView>())
+ })
+ .expect("Search view should be active after deploy");
+
+ // Smartcase should override the explicit case_sensitive flag
+ // because the query is all lowercase.
+ search_view.update_in(cx, |search_view, _window, cx| {
+ assert!(
+ !search_view
+ .search_options
+ .contains(SearchOptions::CASE_SENSITIVE),
+ "Smartcase should disable case sensitivity for a lowercase query, \
+ even when case_sensitive was explicitly set in the action"
+ );
+ let query_text = search_view.query_editor.read(cx).text(cx);
+ assert_eq!(query_text, "lowercase_query");
+ });
+
+ // Now deploy with an uppercase query - smartcase should enable case sensitivity.
+ workspace.update_in(cx, |workspace, window, cx| {
+ ProjectSearchView::deploy_search(
+ workspace,
+ &workspace::DeploySearch {
+ query: Some("Uppercase_Query".into()),
+ ..Default::default()
+ },
+ window,
+ cx,
+ )
+ });
+
+ search_view.update_in(cx, |search_view, _window, cx| {
+ assert!(
+ search_view
+ .search_options
+ .contains(SearchOptions::CASE_SENSITIVE),
+ "Smartcase should enable case sensitivity for a query containing uppercase"
+ );
+ let query_text = search_view.query_editor.read(cx).text(cx);
+ assert_eq!(query_text, "Uppercase_Query");
+ });
+ }
+
fn init_test(cx: &mut TestAppContext) {
cx.update(|cx| {
let settings = SettingsStore::test(cx);
@@ -198,7 +198,7 @@ impl VsCodeSettings {
log: None,
message_editor: None,
node: self.node_binary_settings(),
- notification_panel: None,
+
outline_panel: self.outline_panel_settings_content(),
preview_tabs: self.preview_tabs_settings_content(),
project: self.project_settings_content(),
@@ -19,6 +19,7 @@ anyhow.workspace = true
collections.workspace = true
derive_more.workspace = true
gpui.workspace = true
+language_model_core.workspace = true
log.workspace = true
schemars.workspace = true
serde.workspace = true
@@ -128,6 +128,12 @@ pub struct AgentSettingsContent {
/// Default: 320
#[serde(serialize_with = "crate::serialize_optional_f32_with_two_decimal_places")]
pub default_height: Option<f32>,
+ /// Maximum content width in pixels for the agent panel. Content will be
+ /// centered when the panel is wider than this value.
+ ///
+ /// Default: 850
+ #[serde(serialize_with = "crate::serialize_optional_f32_with_two_decimal_places")]
+ pub max_content_width: Option<f32>,
/// The default model to use when creating new chats and for other features when a specific model is not specified.
pub default_model: Option<LanguageModelSelection>,
/// Favorite models to show at the top of the model selector.
@@ -1,8 +1,8 @@
+use crate::merge_from::MergeFrom;
use collections::HashMap;
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use settings_macros::{MergeFrom, with_fallible_options};
-use strum::EnumString;
use std::sync::Arc;
@@ -237,15 +237,12 @@ pub struct OpenAiAvailableModel {
pub capabilities: OpenAiModelCapabilities,
}
-#[derive(Debug, Serialize, Deserialize, PartialEq, Clone, EnumString, JsonSchema, MergeFrom)]
-#[serde(rename_all = "lowercase")]
-#[strum(serialize_all = "lowercase")]
-pub enum OpenAiReasoningEffort {
- Minimal,
- Low,
- Medium,
- High,
- XHigh,
+pub use language_model_core::ReasoningEffort as OpenAiReasoningEffort;
+
+impl MergeFrom for OpenAiReasoningEffort {
+ fn merge_from(&mut self, other: &Self) {
+ *self = *other;
+ }
}
#[with_fallible_options]
@@ -479,15 +476,10 @@ pub struct LanguageModelCacheConfiguration {
pub min_total_token: u64,
}
-#[derive(
- Copy, Clone, Debug, Default, PartialEq, Eq, Serialize, Deserialize, JsonSchema, MergeFrom,
-)]
-#[serde(tag = "type", rename_all = "lowercase")]
-pub enum ModelMode {
- #[default]
- Default,
- Thinking {
- /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
- budget_tokens: Option<u32>,
- },
+pub use language_model_core::ModelMode;
+
+impl MergeFrom for ModelMode {
+ fn merge_from(&mut self, other: &Self) {
+ *self = *other;
+ }
}
@@ -174,9 +174,6 @@ pub struct SettingsContent {
/// Configuration for Node-related features
pub node: Option<NodeBinarySettings>,
- /// Configuration for the Notification Panel
- pub notification_panel: Option<NotificationPanelSettingsContent>,
-
pub proxy: Option<String>,
/// The URL of the Zed server to connect to.
@@ -631,28 +628,6 @@ pub struct ScrollbarSettings {
pub show: Option<ShowScrollbar>,
}
-#[with_fallible_options]
-#[derive(Clone, Default, Serialize, Deserialize, JsonSchema, MergeFrom, Debug, PartialEq)]
-pub struct NotificationPanelSettingsContent {
- /// Whether to show the panel button in the status bar.
- ///
- /// Default: true
- pub button: Option<bool>,
- /// Where to dock the panel.
- ///
- /// Default: right
- pub dock: Option<DockPosition>,
- /// Default width of the panel in pixels.
- ///
- /// Default: 300
- #[serde(serialize_with = "crate::serialize_optional_f32_with_two_decimal_places")]
- pub default_width: Option<f32>,
- /// Whether to show a badge on the notification panel icon with the count of unread notifications.
- ///
- /// Default: false
- pub show_count_badge: Option<bool>,
-}
-
#[with_fallible_options]
#[derive(Clone, Default, Serialize, Deserialize, JsonSchema, MergeFrom, Debug, PartialEq)]
pub struct PanelSettingsContent {
@@ -109,16 +109,37 @@ impl RenderOnce for SettingsInputField {
..Default::default()
};
+ let first_render_initial_text = window.use_state(cx, |_, _| self.initial_text.clone());
+
let editor = if let Some(id) = self.id {
window.use_keyed_state(id, cx, {
let initial_text = self.initial_text.clone();
let placeholder = self.placeholder;
+ let mut confirm = self.confirm.clone();
+
move |window, cx| {
let mut editor = Editor::single_line(window, cx);
+ let editor_focus_handle = editor.focus_handle(cx);
if let Some(text) = initial_text {
editor.set_text(text, window, cx);
}
+ if let Some(confirm) = confirm.take()
+ && !self.display_confirm_button
+ && !self.display_clear_button
+ && !self.clear_on_confirm
+ {
+ cx.on_focus_out(
+ &editor_focus_handle,
+ window,
+ move |editor, _, window, cx| {
+ let text = Some(editor.text(cx));
+ confirm(text, window, cx);
+ },
+ )
+ .detach();
+ }
+
if let Some(placeholder) = placeholder {
editor.set_placeholder_text(placeholder, window, cx);
}
@@ -130,12 +151,31 @@ impl RenderOnce for SettingsInputField {
window.use_state(cx, {
let initial_text = self.initial_text.clone();
let placeholder = self.placeholder;
+ let mut confirm = self.confirm.clone();
+
move |window, cx| {
let mut editor = Editor::single_line(window, cx);
+ let editor_focus_handle = editor.focus_handle(cx);
if let Some(text) = initial_text {
editor.set_text(text, window, cx);
}
+ if let Some(confirm) = confirm.take()
+ && !self.display_confirm_button
+ && !self.display_clear_button
+ && !self.clear_on_confirm
+ {
+ cx.on_focus_out(
+ &editor_focus_handle,
+ window,
+ move |editor, _, window, cx| {
+ let text = Some(editor.text(cx));
+ confirm(text, window, cx);
+ },
+ )
+ .detach();
+ }
+
if let Some(placeholder) = placeholder {
editor.set_placeholder_text(placeholder, window, cx);
}
@@ -149,11 +189,20 @@ impl RenderOnce for SettingsInputField {
// re-renders but use_keyed_state returns the cached editor with stale text.
// Reconcile with the expected initial_text when the editor is not focused,
// so we don't clobber what the user is actively typing.
- if let Some(initial_text) = &self.initial_text {
- let current_text = editor.read(cx).text(cx);
- if current_text != *initial_text && !editor.read(cx).is_focused(window) {
- editor.update(cx, |editor, cx| {
- editor.set_text(initial_text.clone(), window, cx);
+ if let Some(initial_text) = &self.initial_text
+ && let Some(first_initial) = first_render_initial_text.read(cx)
+ {
+ if initial_text != first_initial && !editor.read(cx).is_focused(window) {
+ *first_render_initial_text.as_mut(cx) = self.initial_text.clone();
+ let weak_editor = editor.downgrade();
+ let initial_text = initial_text.clone();
+
+ window.defer(cx, move |window, cx| {
+ weak_editor
+ .update(cx, |editor, cx| {
+ editor.set_text(initial_text, window, cx);
+ })
+ .ok();
});
}
}
@@ -5579,96 +5579,6 @@ fn panels_page() -> SettingsPage {
]
}
- fn notification_panel_section() -> [SettingsPageItem; 5] {
- [
- SettingsPageItem::SectionHeader("Notification Panel"),
- SettingsPageItem::SettingItem(SettingItem {
- title: "Notification Panel Button",
- description: "Show the notification panel button in the status bar.",
- field: Box::new(SettingField {
- json_path: Some("notification_panel.button"),
- pick: |settings_content| {
- settings_content
- .notification_panel
- .as_ref()?
- .button
- .as_ref()
- },
- write: |settings_content, value| {
- settings_content
- .notification_panel
- .get_or_insert_default()
- .button = value;
- },
- }),
- metadata: None,
- files: USER,
- }),
- SettingsPageItem::SettingItem(SettingItem {
- title: "Notification Panel Dock",
- description: "Where to dock the notification panel.",
- field: Box::new(SettingField {
- json_path: Some("notification_panel.dock"),
- pick: |settings_content| {
- settings_content.notification_panel.as_ref()?.dock.as_ref()
- },
- write: |settings_content, value| {
- settings_content
- .notification_panel
- .get_or_insert_default()
- .dock = value;
- },
- }),
- metadata: None,
- files: USER,
- }),
- SettingsPageItem::SettingItem(SettingItem {
- title: "Notification Panel Default Width",
- description: "Default width of the notification panel in pixels.",
- field: Box::new(SettingField {
- json_path: Some("notification_panel.default_width"),
- pick: |settings_content| {
- settings_content
- .notification_panel
- .as_ref()?
- .default_width
- .as_ref()
- },
- write: |settings_content, value| {
- settings_content
- .notification_panel
- .get_or_insert_default()
- .default_width = value;
- },
- }),
- metadata: None,
- files: USER,
- }),
- SettingsPageItem::SettingItem(SettingItem {
- title: "Show Count Badge",
- description: "Show a badge on the notification panel icon with the count of unread notifications.",
- field: Box::new(SettingField {
- json_path: Some("notification_panel.show_count_badge"),
- pick: |settings_content| {
- settings_content
- .notification_panel
- .as_ref()?
- .show_count_badge
- .as_ref()
- },
- write: |settings_content, value| {
- settings_content
- .notification_panel
- .get_or_insert_default()
- .show_count_badge = value;
- },
- }),
- metadata: None,
- files: USER,
- }),
- ]
- }
-
fn collaboration_panel_section() -> [SettingsPageItem; 4] {
[
SettingsPageItem::SectionHeader("Collaboration Panel"),
@@ -5737,7 +5647,7 @@ fn panels_page() -> SettingsPage {
]
}
- fn agent_panel_section() -> [SettingsPageItem; 6] {
+ fn agent_panel_section() -> [SettingsPageItem; 7] {
[
SettingsPageItem::SectionHeader("Agent Panel"),
SettingsPageItem::SettingItem(SettingItem {
@@ -5812,6 +5722,24 @@ fn panels_page() -> SettingsPage {
metadata: None,
files: USER,
}),
+ SettingsPageItem::SettingItem(SettingItem {
+ title: "Agent Panel Max Content Width",
+ description: "Maximum content width in pixels. Content will be centered when the panel is wider than this value.",
+ field: Box::new(SettingField {
+ json_path: Some("agent.max_content_width"),
+ pick: |settings_content| {
+ settings_content.agent.as_ref()?.max_content_width.as_ref()
+ },
+ write: |settings_content, value| {
+ settings_content
+ .agent
+ .get_or_insert_default()
+ .max_content_width = value;
+ },
+ }),
+ metadata: None,
+ files: USER,
+ }),
]
}
@@ -5823,7 +5751,6 @@ fn panels_page() -> SettingsPage {
outline_panel_section(),
git_panel_section(),
debugger_panel_section(),
- notification_panel_section(),
collaboration_panel_section(),
agent_panel_section(),
],
@@ -5064,6 +5064,7 @@ async fn test_legacy_thread_with_canonical_path_opens_main_repo_workspace(cx: &m
mod property_test {
use super::*;
+ use gpui::proptest::prelude::*;
struct UnopenedWorktree {
path: String,
@@ -5658,7 +5659,10 @@ mod property_test {
Ok(())
}
- #[gpui::property_test]
+ #[gpui::property_test(config = ProptestConfig {
+ cases: 10,
+ ..Default::default()
+ })]
async fn test_sidebar_invariants(
#[strategy = gpui::proptest::collection::vec(0u32..DISTRIBUTION_SLOTS * 10, 1..5)]
raw_operations: Vec<u32>,
@@ -566,9 +566,7 @@ impl PickerDelegate for TasksModalDelegate {
.checked_sub(1);
picker.refresh(window, cx);
}))
- .tooltip(|_, cx| {
- Tooltip::simple("Delete Previously Scheduled Task", cx)
- }),
+ .tooltip(|_, cx| Tooltip::simple("Delete from Recent Tasks", cx)),
);
item.end_slot_on_hover(delete_button)
} else {
@@ -67,7 +67,7 @@ impl Component for CollabNotification {
let avatar = "https://avatars.githubusercontent.com/u/67129314?v=4";
let container = || div().h(px(72.)).w(px(400.)); // Size of the actual notification window
- let examples = vec![
+ let call_examples = vec![
single_example(
"Incoming Call",
container()
@@ -129,6 +129,58 @@ impl Component for CollabNotification {
),
];
- Some(example_group(examples).vertical().into_any_element())
+ let toast_examples = vec![
+ single_example(
+ "Contact Request",
+ container()
+ .child(
+ CollabNotification::new(
+ avatar,
+ Button::new("accept", "Accept"),
+ Button::new("decline", "Decline"),
+ )
+ .child(Label::new("maxbrunsfeld wants to add you as a contact")),
+ )
+ .into_any_element(),
+ ),
+ single_example(
+ "Contact Request Accepted",
+ container()
+ .child(
+ CollabNotification::new(
+ avatar,
+ Button::new("dismiss", "Dismiss"),
+ Button::new("close", "Close"),
+ )
+ .child(Label::new("maxbrunsfeld accepted your contact request")),
+ )
+ .into_any_element(),
+ ),
+ single_example(
+ "Channel Invitation",
+ container()
+ .child(
+ CollabNotification::new(
+ avatar,
+ Button::new("accept", "Accept"),
+ Button::new("decline", "Decline"),
+ )
+ .child(Label::new(
+ "maxbrunsfeld invited you to join the #zed channel",
+ )),
+ )
+ .into_any_element(),
+ ),
+ ];
+
+ Some(
+ v_flex()
+ .gap_6()
+ .child(example_group_with_title("Calls & Projects", call_examples).vertical())
+ .child(
+ example_group_with_title("Contact & Channel Toasts", toast_examples).vertical(),
+ )
+ .into_any_element(),
+ )
}
}
@@ -52,7 +52,7 @@ pub struct ListItem {
overflow_x: bool,
focused: Option<bool>,
docked_right: bool,
- height: Option<Pixels>,
+ height: Option<DefiniteLength>,
}
impl ListItem {
@@ -207,8 +207,8 @@ impl ListItem {
self
}
- pub fn height(mut self, height: Pixels) -> Self {
- self.height = Some(height);
+ pub fn height(mut self, height: impl Into<DefiniteLength>) -> Self {
+ self.height = Some(height.into());
self
}
}
@@ -1782,7 +1782,6 @@ fn generate_commands(_: &App) -> Vec<VimCommand> {
VimCommand::str(("te", "rm"), "terminal_panel::Toggle"),
VimCommand::str(("T", "erm"), "terminal_panel::Toggle"),
VimCommand::str(("C", "ollab"), "collab_panel::ToggleFocus"),
- VimCommand::str(("No", "tifications"), "notification_panel::ToggleFocus"),
VimCommand::str(("A", "I"), "agent::ToggleFocus"),
VimCommand::str(("G", "it"), "git_panel::ToggleFocus"),
VimCommand::str(("D", "ebug"), "debug_panel::ToggleFocus"),
@@ -17,7 +17,7 @@ use gpui::{
Action, App, AppContext, BorrowAppContext, ClipboardEntry, ClipboardItem, DismissEvent, Entity,
EntityId, Global, HighlightStyle, StyledText, Subscription, Task, TextStyle, WeakEntity,
};
-use language::{Buffer, BufferEvent, BufferId, Chunk, Point};
+use language::{Buffer, BufferEvent, BufferId, Chunk, LanguageAwareStyling, Point};
use multi_buffer::MultiBufferRow;
use picker::{Picker, PickerDelegate};
@@ -1504,7 +1504,10 @@ impl PickerDelegate for MarksViewDelegate {
position.row,
snapshot.line_len(MultiBufferRow(position.row)),
),
- true,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
);
matches.push(MarksMatch {
name: name.clone(),
@@ -1530,7 +1533,10 @@ impl PickerDelegate for MarksViewDelegate {
let chunks = snapshot.chunks(
Point::new(position.row, 0)
..Point::new(position.row, snapshot.line_len(position.row)),
- true,
+ LanguageAwareStyling {
+ tree_sitter: true,
+ diagnostics: true,
+ },
);
matches.push(MarksMatch {
@@ -14,6 +14,7 @@ path = "src/web_search_providers.rs"
[dependencies]
anyhow.workspace = true
client.workspace = true
+cloud_api_client.workspace = true
cloud_api_types.workspace = true
cloud_llm_client.workspace = true
futures.workspace = true
@@ -2,12 +2,12 @@ use std::sync::Arc;
use anyhow::{Context as _, Result};
use client::{Client, NeedsLlmTokenRefresh, UserStore, global_llm_token};
+use cloud_api_client::LlmApiToken;
use cloud_api_types::OrganizationId;
use cloud_llm_client::{WebSearchBody, WebSearchResponse};
use futures::AsyncReadExt as _;
use gpui::{App, AppContext, Context, Entity, Task};
use http_client::{HttpClient, Method};
-use language_model::LlmApiToken;
use web_search::{WebSearchProvider, WebSearchProviderId};
pub struct CloudWebSearchProvider {
@@ -276,6 +276,7 @@ pub struct MultiWorkspace {
pending_removal_tasks: Vec<Task<()>>,
_serialize_task: Option<Task<()>>,
_subscriptions: Vec<Subscription>,
+ previous_focus_handle: Option<FocusHandle>,
}
impl EventEmitter<MultiWorkspaceEvent> for MultiWorkspace {}
@@ -333,6 +334,7 @@ impl MultiWorkspace {
quit_subscription,
settings_subscription,
],
+ previous_focus_handle: None,
}
}
@@ -387,6 +389,7 @@ impl MultiWorkspace {
if self.sidebar_open() {
self.close_sidebar(window, cx);
} else {
+ self.previous_focus_handle = window.focused(cx);
self.open_sidebar(cx);
if let Some(sidebar) = &self.sidebar {
sidebar.prepare_for_focus(window, cx);
@@ -417,14 +420,16 @@ impl MultiWorkspace {
.is_some_and(|s| s.focus_handle(cx).contains_focused(window, cx));
if sidebar_is_focused {
- let pane = self.workspace().read(cx).active_pane().clone();
- let pane_focus = pane.read(cx).focus_handle(cx);
- window.focus(&pane_focus, cx);
- } else if let Some(sidebar) = &self.sidebar {
- sidebar.prepare_for_focus(window, cx);
- sidebar.focus(window, cx);
+ self.restore_previous_focus(false, window, cx);
+ } else {
+ self.previous_focus_handle = window.focused(cx);
+ if let Some(sidebar) = &self.sidebar {
+ sidebar.prepare_for_focus(window, cx);
+ sidebar.focus(window, cx);
+ }
}
} else {
+ self.previous_focus_handle = window.focused(cx);
self.open_sidebar(cx);
if let Some(sidebar) = &self.sidebar {
sidebar.prepare_for_focus(window, cx);
@@ -457,13 +462,26 @@ impl MultiWorkspace {
workspace.set_sidebar_focus_handle(None);
});
}
- let pane = self.workspace().read(cx).active_pane().clone();
- let pane_focus = pane.read(cx).focus_handle(cx);
- window.focus(&pane_focus, cx);
+ self.restore_previous_focus(true, window, cx);
self.serialize(cx);
cx.notify();
}
+ fn restore_previous_focus(&mut self, clear: bool, window: &mut Window, cx: &mut Context<Self>) {
+ let focus_handle = if clear {
+ self.previous_focus_handle.take()
+ } else {
+ self.previous_focus_handle.clone()
+ };
+
+ if let Some(previous_focus) = focus_handle {
+ previous_focus.focus(window, cx);
+ } else {
+ let pane = self.workspace().read(cx).active_pane().clone();
+ window.focus(&pane.read(cx).focus_handle(cx), cx);
+ }
+ }
+
pub fn close_window(&mut self, _: &CloseWindow, window: &mut Window, cx: &mut Context<Self>) {
cx.spawn_in(window, async move |this, cx| {
let workspaces = this.update(cx, |multi_workspace, _cx| {
@@ -10,7 +10,10 @@ use crate::{
TabContentParams, TabTooltipContent, WeakItemHandle,
},
move_item,
- notifications::NotifyResultExt,
+ notifications::{
+ NotificationId, NotifyResultExt, show_app_notification,
+ simple_message_notification::MessageNotification,
+ },
toolbar::Toolbar,
workspace_settings::{AutosaveSetting, FocusFollowsMouse, TabBarSettings, WorkspaceSettings},
};
@@ -195,6 +198,16 @@ pub struct DeploySearch {
pub included_files: Option<String>,
#[serde(default)]
pub excluded_files: Option<String>,
+ #[serde(default)]
+ pub query: Option<String>,
+ #[serde(default)]
+ pub regex: Option<bool>,
+ #[serde(default)]
+ pub case_sensitive: Option<bool>,
+ #[serde(default)]
+ pub whole_word: Option<bool>,
+ #[serde(default)]
+ pub include_ignored: Option<bool>,
}
#[derive(Clone, Copy, PartialEq, Debug, Deserialize, JsonSchema, Default)]
@@ -306,16 +319,6 @@ actions!(
]
);
-impl DeploySearch {
- pub fn find() -> Self {
- Self {
- replace_enabled: false,
- included_files: None,
- excluded_files: None,
- }
- }
-}
-
const MAX_NAVIGATION_HISTORY_LEN: usize = 1024;
pub enum Event {
@@ -4185,15 +4188,7 @@ fn default_render_tab_bar_buttons(
menu.action("New File", NewFile.boxed_clone())
.action("Open File", ToggleFileFinder::default().boxed_clone())
.separator()
- .action(
- "Search Project",
- DeploySearch {
- replace_enabled: false,
- included_files: None,
- excluded_files: None,
- }
- .boxed_clone(),
- )
+ .action("Search Project", DeploySearch::default().boxed_clone())
.action("Search Symbols", ToggleProjectSymbols.boxed_clone())
.separator()
.action("New Terminal", NewTerminal::default().boxed_clone())
@@ -4400,17 +4395,64 @@ impl Render for Pane {
))
.on_action(
cx.listener(|pane: &mut Self, action: &RevealInProjectPanel, _, cx| {
+ let Some(active_item) = pane.active_item() else {
+ return;
+ };
+
let entry_id = action
.entry_id
.map(ProjectEntryId::from_proto)
- .or_else(|| pane.active_item()?.project_entry_ids(cx).first().copied());
- if let Some(entry_id) = entry_id {
- pane.project
- .update(cx, |_, cx| {
- cx.emit(project::Event::RevealInProjectPanel(entry_id))
- })
- .ok();
+ .or_else(|| active_item.project_entry_ids(cx).first().copied());
+
+ let show_reveal_error_toast = |display_name: &str, cx: &mut App| {
+ let notification_id = NotificationId::unique::<RevealInProjectPanel>();
+ let message = SharedString::from(format!(
+ "\"{display_name}\" is not part of any open projects."
+ ));
+
+ show_app_notification(notification_id, cx, move |cx| {
+ let message = message.clone();
+ cx.new(|cx| MessageNotification::new(message, cx))
+ });
+ };
+
+ let Some(entry_id) = entry_id else {
+ // When working with an unsaved buffer, display a toast
+ // informing the user that the buffer is not present in
+ // any of the open projects and stop execution, as we
+ // don't want to open the project panel.
+ let display_name = active_item
+ .tab_tooltip_text(cx)
+ .unwrap_or_else(|| active_item.tab_content_text(0, cx));
+
+ return show_reveal_error_toast(&display_name, cx);
+ };
+
+ // We'll now check whether the entry belongs to a visible
+ // worktree and, if that's not the case, it means the user
+ // is interacting with a file that does not belong to any of
+ // the open projects, so we'll show a toast informing them
+ // of this and stop execution.
+ let display_name = pane
+ .project
+ .read_with(cx, |project, cx| {
+ project
+ .worktree_for_entry(entry_id, cx)
+ .filter(|worktree| !worktree.read(cx).is_visible())
+ .map(|worktree| worktree.read(cx).root_name_str().to_string())
+ })
+ .ok()
+ .flatten();
+
+ if let Some(display_name) = display_name {
+ return show_reveal_error_toast(&display_name, cx);
}
+
+ pane.project
+ .update(cx, |_, cx| {
+ cx.emit(project::Event::RevealInProjectPanel(entry_id))
+ })
+ .log_err();
}),
)
.on_action(cx.listener(|_, _: &menu::Cancel, window, cx| {
@@ -17,6 +17,8 @@ schemars = ["dep:schemars"]
[dependencies]
anyhow.workspace = true
+language_model_core.workspace = true
schemars = { workspace = true, optional = true }
serde.workspace = true
strum.workspace = true
+tiktoken-rs.workspace = true
@@ -0,0 +1,30 @@
+use anyhow::Result;
+use language_model_core::{LanguageModelRequest, Role};
+
+use crate::Model;
+
+/// Count tokens for an xAI model using tiktoken. This is synchronous;
+/// callers should spawn it on a background thread if needed.
+pub fn count_xai_tokens(request: LanguageModelRequest, model: Model) -> Result<u64> {
+ let messages = request
+ .messages
+ .into_iter()
+ .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
+ role: match message.role {
+ Role::User => "user".into(),
+ Role::Assistant => "assistant".into(),
+ Role::System => "system".into(),
+ },
+ content: Some(message.string_contents()),
+ name: None,
+ function_call: None,
+ })
+ .collect::<Vec<_>>();
+
+ let model_name = if model.max_token_count() >= 100_000 {
+ "gpt-4o"
+ } else {
+ "gpt-4"
+ };
+ tiktoken_rs::num_tokens_from_messages(model_name, &messages).map(|tokens| tokens as u64)
+}
@@ -1,3 +1,5 @@
+pub mod completion;
+
use anyhow::Result;
use serde::{Deserialize, Serialize};
use strum::EnumIter;
@@ -3080,7 +3080,7 @@ fn run_start_thread_in_selector_visual_tests(
cx: &mut VisualTestAppContext,
update_baseline: bool,
) -> Result<TestResult> {
- use agent_ui::{AgentPanel, StartThreadIn, WorktreeCreationStatus};
+ use agent_ui::{AgentPanel, NewWorktreeBranchTarget, StartThreadIn, WorktreeCreationStatus};
// Enable feature flags so the thread target selector renders
cx.update(|cx| {
@@ -3401,7 +3401,13 @@ edition = "2021"
cx.update_window(workspace_window.into(), |_, _window, cx| {
panel.update(cx, |panel, cx| {
- panel.set_start_thread_in_for_tests(StartThreadIn::NewWorktree, cx);
+ panel.set_start_thread_in_for_tests(
+ StartThreadIn::NewWorktree {
+ worktree_name: None,
+ branch_target: NewWorktreeBranchTarget::default(),
+ },
+ cx,
+ );
});
})?;
cx.run_until_parked();
@@ -3474,7 +3480,13 @@ edition = "2021"
cx.run_until_parked();
cx.update_window(workspace_window.into(), |_, window, cx| {
- window.dispatch_action(Box::new(StartThreadIn::NewWorktree), cx);
+ window.dispatch_action(
+ Box::new(StartThreadIn::NewWorktree {
+ worktree_name: None,
+ branch_target: NewWorktreeBranchTarget::default(),
+ }),
+ cx,
+ );
})?;
cx.run_until_parked();
@@ -652,10 +652,6 @@ fn initialize_panels(window: &mut Window, cx: &mut Context<Workspace>) -> Task<a
let git_panel = GitPanel::load(workspace_handle.clone(), cx.clone());
let channels_panel =
collab_ui::collab_panel::CollabPanel::load(workspace_handle.clone(), cx.clone());
- let notification_panel = collab_ui::notification_panel::NotificationPanel::load(
- workspace_handle.clone(),
- cx.clone(),
- );
let debug_panel = DebugPanel::load(workspace_handle.clone(), cx);
async fn add_panel_when_ready(
@@ -679,7 +675,6 @@ fn initialize_panels(window: &mut Window, cx: &mut Context<Workspace>) -> Task<a
add_panel_when_ready(terminal_panel, workspace_handle.clone(), cx.clone()),
add_panel_when_ready(git_panel, workspace_handle.clone(), cx.clone()),
add_panel_when_ready(channels_panel, workspace_handle.clone(), cx.clone()),
- add_panel_when_ready(notification_panel, workspace_handle.clone(), cx.clone()),
add_panel_when_ready(debug_panel, workspace_handle.clone(), cx.clone()),
initialize_agent_panel(workspace_handle, cx.clone()).map(|r| r.log_err()),
);
@@ -1037,16 +1032,6 @@ fn register_actions(
workspace.toggle_panel_focus::<collab_ui::collab_panel::CollabPanel>(window, cx);
},
)
- .register_action(
- |workspace: &mut Workspace,
- _: &collab_ui::notification_panel::ToggleFocus,
- window: &mut Window,
- cx: &mut Context<Workspace>| {
- workspace.toggle_panel_focus::<collab_ui::notification_panel::NotificationPanel>(
- window, cx,
- );
- },
- )
.register_action(
|workspace: &mut Workspace,
_: &terminal_panel::ToggleFocus,
@@ -4962,7 +4947,6 @@ mod tests {
"multi_workspace",
"new_process_modal",
"notebook",
- "notification_panel",
"onboarding",
"outline",
"outline_panel",
@@ -165,7 +165,7 @@ pub fn app_menus(cx: &mut App) -> Vec<Menu> {
MenuItem::os_action("Paste", editor::actions::Paste, OsAction::Paste),
MenuItem::separator(),
MenuItem::action("Find", search::buffer_search::Deploy::find()),
- MenuItem::action("Find in Project", workspace::DeploySearch::find()),
+ MenuItem::action("Find in Project", workspace::DeploySearch::default()),
MenuItem::separator(),
MenuItem::action(
"Toggle Line Comment",
@@ -105,7 +105,7 @@ To disable this behavior use:
// "outline_panel": {"button": false },
// "collaboration_panel": {"button": false },
// "git_panel": {"button": false },
- // "notification_panel": {"button": false },
+
// "agent": {"button": false },
// "debugger": {"button": false },
// "diagnostics": {"button": false },
@@ -588,16 +588,6 @@ See [Terminal settings](./reference/all-settings.md#terminal) for additional non
"dock": "left", // Where to dock: left, right
"default_width": 240 // Default width of the collaboration panel.
},
- "show_call_status_icon": true, // Shown call status in the OS status bar.
-
- // Notification Panel
- "notification_panel": {
- // Whether to show the notification panel button in the status bar.
- "button": true,
- // Where to dock the notification panel. Can be 'left' or 'right'.
- "dock": "right",
- // Default width of the notification panel.
- "default_width": 380
- }
+ "show_call_status_icon": true // Shown call status in the OS status bar.
}
```