cloud.rs

   1use ai_onboarding::YoungAccountBanner;
   2use anthropic::AnthropicModelMode;
   3use anyhow::{Context as _, Result, anyhow};
   4use chrono::{DateTime, Utc};
   5use client::{Client, ModelRequestUsage, UserStore, zed_urls};
   6use cloud_llm_client::{
   7    CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, CURRENT_PLAN_HEADER_NAME, CompletionBody,
   8    CompletionEvent, CompletionRequestStatus, CountTokensBody, CountTokensResponse,
   9    EXPIRED_LLM_TOKEN_HEADER_NAME, ListModelsResponse, MODEL_REQUESTS_RESOURCE_HEADER_VALUE, Plan,
  10    SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME,
  11    TOOL_USE_LIMIT_REACHED_HEADER_NAME, ZED_VERSION_HEADER_NAME,
  12};
  13use futures::{
  14    AsyncBufReadExt, FutureExt, Stream, StreamExt, future::BoxFuture, stream::BoxStream,
  15};
  16use google_ai::GoogleModelMode;
  17use gpui::{
  18    AnyElement, AnyView, App, AsyncApp, Context, Entity, SemanticVersion, Subscription, Task,
  19};
  20use http_client::http::{HeaderMap, HeaderValue};
  21use http_client::{AsyncBody, HttpClient, Method, Response, StatusCode};
  22use language_model::{
  23    AuthenticateError, LanguageModel, LanguageModelCacheConfiguration,
  24    LanguageModelCompletionError, LanguageModelCompletionEvent, LanguageModelId, LanguageModelName,
  25    LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
  26    LanguageModelProviderState, LanguageModelProviderTosView, LanguageModelRequest,
  27    LanguageModelToolChoice, LanguageModelToolSchemaFormat, LlmApiToken,
  28    ModelRequestLimitReachedError, PaymentRequiredError, RateLimiter, RefreshLlmTokenListener,
  29};
  30use release_channel::AppVersion;
  31use schemars::JsonSchema;
  32use serde::{Deserialize, Serialize, de::DeserializeOwned};
  33use settings::SettingsStore;
  34use smol::io::{AsyncReadExt, BufReader};
  35use std::pin::Pin;
  36use std::str::FromStr as _;
  37use std::sync::Arc;
  38use std::time::Duration;
  39use thiserror::Error;
  40use ui::{TintColor, prelude::*};
  41use util::{ResultExt as _, maybe};
  42
  43use crate::provider::anthropic::{AnthropicEventMapper, count_anthropic_tokens, into_anthropic};
  44use crate::provider::google::{GoogleEventMapper, into_google};
  45use crate::provider::open_ai::{OpenAiEventMapper, count_open_ai_tokens, into_open_ai};
  46
  47pub const PROVIDER_ID: LanguageModelProviderId = language_model::ZED_CLOUD_PROVIDER_ID;
  48pub const PROVIDER_NAME: LanguageModelProviderName = language_model::ZED_CLOUD_PROVIDER_NAME;
  49
  50#[derive(Default, Clone, Debug, PartialEq)]
  51pub struct ZedDotDevSettings {
  52    pub available_models: Vec<AvailableModel>,
  53}
  54
  55#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
  56#[serde(rename_all = "lowercase")]
  57pub enum AvailableProvider {
  58    Anthropic,
  59    OpenAi,
  60    Google,
  61}
  62
  63#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
  64pub struct AvailableModel {
  65    /// The provider of the language model.
  66    pub provider: AvailableProvider,
  67    /// The model's name in the provider's API. e.g. claude-3-5-sonnet-20240620
  68    pub name: String,
  69    /// The name displayed in the UI, such as in the assistant panel model dropdown menu.
  70    pub display_name: Option<String>,
  71    /// The size of the context window, indicating the maximum number of tokens the model can process.
  72    pub max_tokens: usize,
  73    /// The maximum number of output tokens allowed by the model.
  74    pub max_output_tokens: Option<u64>,
  75    /// The maximum number of completion tokens allowed by the model (o1-* only)
  76    pub max_completion_tokens: Option<u64>,
  77    /// Override this model with a different Anthropic model for tool calls.
  78    pub tool_override: Option<String>,
  79    /// Indicates whether this custom model supports caching.
  80    pub cache_configuration: Option<LanguageModelCacheConfiguration>,
  81    /// The default temperature to use for this model.
  82    pub default_temperature: Option<f32>,
  83    /// Any extra beta headers to provide when using the model.
  84    #[serde(default)]
  85    pub extra_beta_headers: Vec<String>,
  86    /// The model's mode (e.g. thinking)
  87    pub mode: Option<ModelMode>,
  88}
  89
  90#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
  91#[serde(tag = "type", rename_all = "lowercase")]
  92pub enum ModelMode {
  93    #[default]
  94    Default,
  95    Thinking {
  96        /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
  97        budget_tokens: Option<u32>,
  98    },
  99}
 100
 101impl From<ModelMode> for AnthropicModelMode {
 102    fn from(value: ModelMode) -> Self {
 103        match value {
 104            ModelMode::Default => AnthropicModelMode::Default,
 105            ModelMode::Thinking { budget_tokens } => AnthropicModelMode::Thinking { budget_tokens },
 106        }
 107    }
 108}
 109
 110pub struct CloudLanguageModelProvider {
 111    client: Arc<Client>,
 112    state: gpui::Entity<State>,
 113    _maintain_client_status: Task<()>,
 114}
 115
 116pub struct State {
 117    client: Arc<Client>,
 118    llm_api_token: LlmApiToken,
 119    user_store: Entity<UserStore>,
 120    status: client::Status,
 121    accept_terms_of_service_task: Option<Task<Result<()>>>,
 122    models: Vec<Arc<cloud_llm_client::LanguageModel>>,
 123    default_model: Option<Arc<cloud_llm_client::LanguageModel>>,
 124    default_fast_model: Option<Arc<cloud_llm_client::LanguageModel>>,
 125    recommended_models: Vec<Arc<cloud_llm_client::LanguageModel>>,
 126    _fetch_models_task: Task<()>,
 127    _settings_subscription: Subscription,
 128    _llm_token_subscription: Subscription,
 129}
 130
 131impl State {
 132    fn new(
 133        client: Arc<Client>,
 134        user_store: Entity<UserStore>,
 135        status: client::Status,
 136        cx: &mut Context<Self>,
 137    ) -> Self {
 138        let refresh_llm_token_listener = RefreshLlmTokenListener::global(cx);
 139        let mut current_user = user_store.read(cx).watch_current_user();
 140        Self {
 141            client: client.clone(),
 142            llm_api_token: LlmApiToken::default(),
 143            user_store,
 144            status,
 145            accept_terms_of_service_task: None,
 146            models: Vec::new(),
 147            default_model: None,
 148            default_fast_model: None,
 149            recommended_models: Vec::new(),
 150            _fetch_models_task: cx.spawn(async move |this, cx| {
 151                maybe!(async {
 152                    let (client, llm_api_token) = this
 153                        .read_with(cx, |this, _cx| (client.clone(), this.llm_api_token.clone()))?;
 154
 155                    while current_user.borrow().is_none() {
 156                        current_user.next().await;
 157                    }
 158
 159                    let response =
 160                        Self::fetch_models(client.clone(), llm_api_token.clone()).await?;
 161                    this.update(cx, |this, cx| this.update_models(response, cx))?;
 162                    anyhow::Ok(())
 163                })
 164                .await
 165                .context("failed to fetch Zed models")
 166                .log_err();
 167            }),
 168            _settings_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
 169                cx.notify();
 170            }),
 171            _llm_token_subscription: cx.subscribe(
 172                &refresh_llm_token_listener,
 173                move |this, _listener, _event, cx| {
 174                    let client = this.client.clone();
 175                    let llm_api_token = this.llm_api_token.clone();
 176                    cx.spawn(async move |this, cx| {
 177                        llm_api_token.refresh(&client).await?;
 178                        let response = Self::fetch_models(client, llm_api_token).await?;
 179                        this.update(cx, |this, cx| {
 180                            this.update_models(response, cx);
 181                        })
 182                    })
 183                    .detach_and_log_err(cx);
 184                },
 185            ),
 186        }
 187    }
 188
 189    fn is_signed_out(&self, cx: &App) -> bool {
 190        self.user_store.read(cx).current_user().is_none()
 191    }
 192
 193    fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
 194        let client = self.client.clone();
 195        cx.spawn(async move |state, cx| {
 196            client.sign_in_with_optional_connect(true, cx).await?;
 197            state.update(cx, |_, cx| cx.notify())
 198        })
 199    }
 200
 201    fn has_accepted_terms_of_service(&self, cx: &App) -> bool {
 202        self.user_store.read(cx).has_accepted_terms_of_service()
 203    }
 204
 205    fn accept_terms_of_service(&mut self, cx: &mut Context<Self>) {
 206        let user_store = self.user_store.clone();
 207        self.accept_terms_of_service_task = Some(cx.spawn(async move |this, cx| {
 208            let _ = user_store
 209                .update(cx, |store, cx| store.accept_terms_of_service(cx))?
 210                .await;
 211            this.update(cx, |this, cx| {
 212                this.accept_terms_of_service_task = None;
 213                cx.notify()
 214            })
 215        }));
 216    }
 217
 218    fn update_models(&mut self, response: ListModelsResponse, cx: &mut Context<Self>) {
 219        let mut models = Vec::new();
 220
 221        for model in response.models {
 222            models.push(Arc::new(model.clone()));
 223
 224            // Right now we represent thinking variants of models as separate models on the client,
 225            // so we need to insert variants for any model that supports thinking.
 226            if model.supports_thinking {
 227                models.push(Arc::new(cloud_llm_client::LanguageModel {
 228                    id: cloud_llm_client::LanguageModelId(format!("{}-thinking", model.id).into()),
 229                    display_name: format!("{} Thinking", model.display_name),
 230                    ..model
 231                }));
 232            }
 233        }
 234
 235        self.default_model = models
 236            .iter()
 237            .find(|model| model.id == response.default_model)
 238            .cloned();
 239        self.default_fast_model = models
 240            .iter()
 241            .find(|model| model.id == response.default_fast_model)
 242            .cloned();
 243        self.recommended_models = response
 244            .recommended_models
 245            .iter()
 246            .filter_map(|id| models.iter().find(|model| &model.id == id))
 247            .cloned()
 248            .collect();
 249        self.models = models;
 250        cx.notify();
 251    }
 252
 253    async fn fetch_models(
 254        client: Arc<Client>,
 255        llm_api_token: LlmApiToken,
 256    ) -> Result<ListModelsResponse> {
 257        let http_client = &client.http_client();
 258        let token = llm_api_token.acquire(&client).await?;
 259
 260        let request = http_client::Request::builder()
 261            .method(Method::GET)
 262            .uri(http_client.build_zed_llm_url("/models", &[])?.as_ref())
 263            .header("Authorization", format!("Bearer {token}"))
 264            .body(AsyncBody::empty())?;
 265        let mut response = http_client
 266            .send(request)
 267            .await
 268            .context("failed to send list models request")?;
 269
 270        if response.status().is_success() {
 271            let mut body = String::new();
 272            response.body_mut().read_to_string(&mut body).await?;
 273            Ok(serde_json::from_str(&body)?)
 274        } else {
 275            let mut body = String::new();
 276            response.body_mut().read_to_string(&mut body).await?;
 277            anyhow::bail!(
 278                "error listing models.\nStatus: {:?}\nBody: {body}",
 279                response.status(),
 280            );
 281        }
 282    }
 283}
 284
 285impl CloudLanguageModelProvider {
 286    pub fn new(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) -> Self {
 287        let mut status_rx = client.status();
 288        let status = *status_rx.borrow();
 289
 290        let state = cx.new(|cx| State::new(client.clone(), user_store.clone(), status, cx));
 291
 292        let state_ref = state.downgrade();
 293        let maintain_client_status = cx.spawn(async move |cx| {
 294            while let Some(status) = status_rx.next().await {
 295                if let Some(this) = state_ref.upgrade() {
 296                    _ = this.update(cx, |this, cx| {
 297                        if this.status != status {
 298                            this.status = status;
 299                            cx.notify();
 300                        }
 301                    });
 302                } else {
 303                    break;
 304                }
 305            }
 306        });
 307
 308        Self {
 309            client,
 310            state,
 311            _maintain_client_status: maintain_client_status,
 312        }
 313    }
 314
 315    fn create_language_model(
 316        &self,
 317        model: Arc<cloud_llm_client::LanguageModel>,
 318        llm_api_token: LlmApiToken,
 319    ) -> Arc<dyn LanguageModel> {
 320        Arc::new(CloudLanguageModel {
 321            id: LanguageModelId(SharedString::from(model.id.0.clone())),
 322            model,
 323            llm_api_token,
 324            client: self.client.clone(),
 325            request_limiter: RateLimiter::new(4),
 326        })
 327    }
 328}
 329
 330impl LanguageModelProviderState for CloudLanguageModelProvider {
 331    type ObservableEntity = State;
 332
 333    fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
 334        Some(self.state.clone())
 335    }
 336}
 337
 338impl LanguageModelProvider for CloudLanguageModelProvider {
 339    fn id(&self) -> LanguageModelProviderId {
 340        PROVIDER_ID
 341    }
 342
 343    fn name(&self) -> LanguageModelProviderName {
 344        PROVIDER_NAME
 345    }
 346
 347    fn icon(&self) -> IconName {
 348        IconName::AiZed
 349    }
 350
 351    fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
 352        let default_model = self.state.read(cx).default_model.clone()?;
 353        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 354        Some(self.create_language_model(default_model, llm_api_token))
 355    }
 356
 357    fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
 358        let default_fast_model = self.state.read(cx).default_fast_model.clone()?;
 359        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 360        Some(self.create_language_model(default_fast_model, llm_api_token))
 361    }
 362
 363    fn recommended_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
 364        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 365        self.state
 366            .read(cx)
 367            .recommended_models
 368            .iter()
 369            .cloned()
 370            .map(|model| self.create_language_model(model, llm_api_token.clone()))
 371            .collect()
 372    }
 373
 374    fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
 375        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 376        self.state
 377            .read(cx)
 378            .models
 379            .iter()
 380            .cloned()
 381            .map(|model| self.create_language_model(model, llm_api_token.clone()))
 382            .collect()
 383    }
 384
 385    fn is_authenticated(&self, cx: &App) -> bool {
 386        let state = self.state.read(cx);
 387        !state.is_signed_out(cx) && state.has_accepted_terms_of_service(cx)
 388    }
 389
 390    fn authenticate(&self, _cx: &mut App) -> Task<Result<(), AuthenticateError>> {
 391        Task::ready(Ok(()))
 392    }
 393
 394    fn configuration_view(
 395        &self,
 396        _target_agent: language_model::ConfigurationViewTargetAgent,
 397        _: &mut Window,
 398        cx: &mut App,
 399    ) -> AnyView {
 400        cx.new(|_| ConfigurationView::new(self.state.clone()))
 401            .into()
 402    }
 403
 404    fn must_accept_terms(&self, cx: &App) -> bool {
 405        !self.state.read(cx).has_accepted_terms_of_service(cx)
 406    }
 407
 408    fn render_accept_terms(
 409        &self,
 410        view: LanguageModelProviderTosView,
 411        cx: &mut App,
 412    ) -> Option<AnyElement> {
 413        let state = self.state.read(cx);
 414        if state.has_accepted_terms_of_service(cx) {
 415            return None;
 416        }
 417        Some(
 418            render_accept_terms(view, state.accept_terms_of_service_task.is_some(), {
 419                let state = self.state.clone();
 420                move |_window, cx| {
 421                    state.update(cx, |state, cx| state.accept_terms_of_service(cx));
 422                }
 423            })
 424            .into_any_element(),
 425        )
 426    }
 427
 428    fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
 429        Task::ready(Ok(()))
 430    }
 431}
 432
 433fn render_accept_terms(
 434    view_kind: LanguageModelProviderTosView,
 435    accept_terms_of_service_in_progress: bool,
 436    accept_terms_callback: impl Fn(&mut Window, &mut App) + 'static,
 437) -> impl IntoElement {
 438    let thread_fresh_start = matches!(view_kind, LanguageModelProviderTosView::ThreadFreshStart);
 439    let thread_empty_state = matches!(view_kind, LanguageModelProviderTosView::ThreadEmptyState);
 440
 441    let terms_button = Button::new("terms_of_service", "Terms of Service")
 442        .style(ButtonStyle::Subtle)
 443        .icon(IconName::ArrowUpRight)
 444        .icon_color(Color::Muted)
 445        .icon_size(IconSize::Small)
 446        .when(thread_empty_state, |this| this.label_size(LabelSize::Small))
 447        .on_click(move |_, _window, cx| cx.open_url("https://zed.dev/terms-of-service"));
 448
 449    let button_container = h_flex().child(
 450        Button::new("accept_terms", "I accept the Terms of Service")
 451            .when(!thread_empty_state, |this| {
 452                this.full_width()
 453                    .style(ButtonStyle::Tinted(TintColor::Accent))
 454                    .icon(IconName::Check)
 455                    .icon_position(IconPosition::Start)
 456                    .icon_size(IconSize::Small)
 457            })
 458            .when(thread_empty_state, |this| {
 459                this.style(ButtonStyle::Tinted(TintColor::Warning))
 460                    .label_size(LabelSize::Small)
 461            })
 462            .disabled(accept_terms_of_service_in_progress)
 463            .on_click(move |_, window, cx| (accept_terms_callback)(window, cx)),
 464    );
 465
 466    if thread_empty_state {
 467        h_flex()
 468            .w_full()
 469            .flex_wrap()
 470            .justify_between()
 471            .child(
 472                h_flex()
 473                    .child(
 474                        Label::new("To start using Zed AI, please read and accept the")
 475                            .size(LabelSize::Small),
 476                    )
 477                    .child(terms_button),
 478            )
 479            .child(button_container)
 480    } else {
 481        v_flex()
 482            .w_full()
 483            .gap_2()
 484            .child(
 485                h_flex()
 486                    .flex_wrap()
 487                    .when(thread_fresh_start, |this| this.justify_center())
 488                    .child(Label::new(
 489                        "To start using Zed AI, please read and accept the",
 490                    ))
 491                    .child(terms_button),
 492            )
 493            .child({
 494                match view_kind {
 495                    LanguageModelProviderTosView::TextThreadPopup => {
 496                        button_container.w_full().justify_end()
 497                    }
 498                    LanguageModelProviderTosView::Configuration => {
 499                        button_container.w_full().justify_start()
 500                    }
 501                    LanguageModelProviderTosView::ThreadFreshStart => {
 502                        button_container.w_full().justify_center()
 503                    }
 504                    LanguageModelProviderTosView::ThreadEmptyState => div().w_0(),
 505                }
 506            })
 507    }
 508}
 509
 510pub struct CloudLanguageModel {
 511    id: LanguageModelId,
 512    model: Arc<cloud_llm_client::LanguageModel>,
 513    llm_api_token: LlmApiToken,
 514    client: Arc<Client>,
 515    request_limiter: RateLimiter,
 516}
 517
 518struct PerformLlmCompletionResponse {
 519    response: Response<AsyncBody>,
 520    usage: Option<ModelRequestUsage>,
 521    tool_use_limit_reached: bool,
 522    includes_status_messages: bool,
 523}
 524
 525impl CloudLanguageModel {
 526    async fn perform_llm_completion(
 527        client: Arc<Client>,
 528        llm_api_token: LlmApiToken,
 529        app_version: Option<SemanticVersion>,
 530        body: CompletionBody,
 531    ) -> Result<PerformLlmCompletionResponse> {
 532        let http_client = &client.http_client();
 533
 534        let mut token = llm_api_token.acquire(&client).await?;
 535        let mut refreshed_token = false;
 536
 537        loop {
 538            let request_builder = http_client::Request::builder()
 539                .method(Method::POST)
 540                .uri(http_client.build_zed_llm_url("/completions", &[])?.as_ref());
 541            let request_builder = if let Some(app_version) = app_version {
 542                request_builder.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
 543            } else {
 544                request_builder
 545            };
 546
 547            let request = request_builder
 548                .header("Content-Type", "application/json")
 549                .header("Authorization", format!("Bearer {token}"))
 550                .header(CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, "true")
 551                .body(serde_json::to_string(&body)?.into())?;
 552            let mut response = http_client.send(request).await?;
 553            let status = response.status();
 554            if status.is_success() {
 555                let includes_status_messages = response
 556                    .headers()
 557                    .get(SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME)
 558                    .is_some();
 559
 560                let tool_use_limit_reached = response
 561                    .headers()
 562                    .get(TOOL_USE_LIMIT_REACHED_HEADER_NAME)
 563                    .is_some();
 564
 565                let usage = if includes_status_messages {
 566                    None
 567                } else {
 568                    ModelRequestUsage::from_headers(response.headers()).ok()
 569                };
 570
 571                return Ok(PerformLlmCompletionResponse {
 572                    response,
 573                    usage,
 574                    includes_status_messages,
 575                    tool_use_limit_reached,
 576                });
 577            }
 578
 579            if !refreshed_token
 580                && response
 581                    .headers()
 582                    .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
 583                    .is_some()
 584            {
 585                token = llm_api_token.refresh(&client).await?;
 586                refreshed_token = true;
 587                continue;
 588            }
 589
 590            if status == StatusCode::FORBIDDEN
 591                && response
 592                    .headers()
 593                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 594                    .is_some()
 595            {
 596                if let Some(MODEL_REQUESTS_RESOURCE_HEADER_VALUE) = response
 597                    .headers()
 598                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 599                    .and_then(|resource| resource.to_str().ok())
 600                    && let Some(plan) = response
 601                        .headers()
 602                        .get(CURRENT_PLAN_HEADER_NAME)
 603                        .and_then(|plan| plan.to_str().ok())
 604                        .and_then(|plan| cloud_llm_client::Plan::from_str(plan).ok())
 605                {
 606                    return Err(anyhow!(ModelRequestLimitReachedError { plan }));
 607                }
 608            } else if status == StatusCode::PAYMENT_REQUIRED {
 609                return Err(anyhow!(PaymentRequiredError));
 610            }
 611
 612            let mut body = String::new();
 613            let headers = response.headers().clone();
 614            response.body_mut().read_to_string(&mut body).await?;
 615            return Err(anyhow!(ApiError {
 616                status,
 617                body,
 618                headers
 619            }));
 620        }
 621    }
 622}
 623
 624#[derive(Debug, Error)]
 625#[error("cloud language model request failed with status {status}: {body}")]
 626struct ApiError {
 627    status: StatusCode,
 628    body: String,
 629    headers: HeaderMap<HeaderValue>,
 630}
 631
 632/// Represents error responses from Zed's cloud API.
 633///
 634/// Example JSON for an upstream HTTP error:
 635/// ```json
 636/// {
 637///   "code": "upstream_http_error",
 638///   "message": "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout",
 639///   "upstream_status": 503
 640/// }
 641/// ```
 642#[derive(Debug, serde::Deserialize)]
 643struct CloudApiError {
 644    code: String,
 645    message: String,
 646    #[serde(default)]
 647    #[serde(deserialize_with = "deserialize_optional_status_code")]
 648    upstream_status: Option<StatusCode>,
 649    #[serde(default)]
 650    retry_after: Option<f64>,
 651}
 652
 653fn deserialize_optional_status_code<'de, D>(deserializer: D) -> Result<Option<StatusCode>, D::Error>
 654where
 655    D: serde::Deserializer<'de>,
 656{
 657    let opt: Option<u16> = Option::deserialize(deserializer)?;
 658    Ok(opt.and_then(|code| StatusCode::from_u16(code).ok()))
 659}
 660
 661impl From<ApiError> for LanguageModelCompletionError {
 662    fn from(error: ApiError) -> Self {
 663        if let Ok(cloud_error) = serde_json::from_str::<CloudApiError>(&error.body)
 664            && cloud_error.code.starts_with("upstream_http_")
 665        {
 666            let status = if let Some(status) = cloud_error.upstream_status {
 667                status
 668            } else if cloud_error.code.ends_with("_error") {
 669                error.status
 670            } else {
 671                // If there's a status code in the code string (e.g. "upstream_http_429")
 672                // then use that; otherwise, see if the JSON contains a status code.
 673                cloud_error
 674                    .code
 675                    .strip_prefix("upstream_http_")
 676                    .and_then(|code_str| code_str.parse::<u16>().ok())
 677                    .and_then(|code| StatusCode::from_u16(code).ok())
 678                    .unwrap_or(error.status)
 679            };
 680
 681            return LanguageModelCompletionError::UpstreamProviderError {
 682                message: cloud_error.message,
 683                status,
 684                retry_after: cloud_error.retry_after.map(Duration::from_secs_f64),
 685            };
 686        }
 687
 688        let retry_after = None;
 689        LanguageModelCompletionError::from_http_status(
 690            PROVIDER_NAME,
 691            error.status,
 692            error.body,
 693            retry_after,
 694        )
 695    }
 696}
 697
 698impl LanguageModel for CloudLanguageModel {
 699    fn id(&self) -> LanguageModelId {
 700        self.id.clone()
 701    }
 702
 703    fn name(&self) -> LanguageModelName {
 704        LanguageModelName::from(self.model.display_name.clone())
 705    }
 706
 707    fn provider_id(&self) -> LanguageModelProviderId {
 708        PROVIDER_ID
 709    }
 710
 711    fn provider_name(&self) -> LanguageModelProviderName {
 712        PROVIDER_NAME
 713    }
 714
 715    fn upstream_provider_id(&self) -> LanguageModelProviderId {
 716        use cloud_llm_client::LanguageModelProvider::*;
 717        match self.model.provider {
 718            Anthropic => language_model::ANTHROPIC_PROVIDER_ID,
 719            OpenAi => language_model::OPEN_AI_PROVIDER_ID,
 720            Google => language_model::GOOGLE_PROVIDER_ID,
 721        }
 722    }
 723
 724    fn upstream_provider_name(&self) -> LanguageModelProviderName {
 725        use cloud_llm_client::LanguageModelProvider::*;
 726        match self.model.provider {
 727            Anthropic => language_model::ANTHROPIC_PROVIDER_NAME,
 728            OpenAi => language_model::OPEN_AI_PROVIDER_NAME,
 729            Google => language_model::GOOGLE_PROVIDER_NAME,
 730        }
 731    }
 732
 733    fn supports_tools(&self) -> bool {
 734        self.model.supports_tools
 735    }
 736
 737    fn supports_images(&self) -> bool {
 738        self.model.supports_images
 739    }
 740
 741    fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
 742        match choice {
 743            LanguageModelToolChoice::Auto
 744            | LanguageModelToolChoice::Any
 745            | LanguageModelToolChoice::None => true,
 746        }
 747    }
 748
 749    fn supports_burn_mode(&self) -> bool {
 750        self.model.supports_max_mode
 751    }
 752
 753    fn telemetry_id(&self) -> String {
 754        format!("zed.dev/{}", self.model.id)
 755    }
 756
 757    fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
 758        match self.model.provider {
 759            cloud_llm_client::LanguageModelProvider::Anthropic
 760            | cloud_llm_client::LanguageModelProvider::OpenAi => {
 761                LanguageModelToolSchemaFormat::JsonSchema
 762            }
 763            cloud_llm_client::LanguageModelProvider::Google => {
 764                LanguageModelToolSchemaFormat::JsonSchemaSubset
 765            }
 766        }
 767    }
 768
 769    fn max_token_count(&self) -> u64 {
 770        self.model.max_token_count as u64
 771    }
 772
 773    fn max_token_count_in_burn_mode(&self) -> Option<u64> {
 774        self.model
 775            .max_token_count_in_max_mode
 776            .filter(|_| self.model.supports_max_mode)
 777            .map(|max_token_count| max_token_count as u64)
 778    }
 779
 780    fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
 781        match &self.model.provider {
 782            cloud_llm_client::LanguageModelProvider::Anthropic => {
 783                Some(LanguageModelCacheConfiguration {
 784                    min_total_token: 2_048,
 785                    should_speculate: true,
 786                    max_cache_anchors: 4,
 787                })
 788            }
 789            cloud_llm_client::LanguageModelProvider::OpenAi
 790            | cloud_llm_client::LanguageModelProvider::Google => None,
 791        }
 792    }
 793
 794    fn count_tokens(
 795        &self,
 796        request: LanguageModelRequest,
 797        cx: &App,
 798    ) -> BoxFuture<'static, Result<u64>> {
 799        match self.model.provider {
 800            cloud_llm_client::LanguageModelProvider::Anthropic => {
 801                count_anthropic_tokens(request, cx)
 802            }
 803            cloud_llm_client::LanguageModelProvider::OpenAi => {
 804                let model = match open_ai::Model::from_id(&self.model.id.0) {
 805                    Ok(model) => model,
 806                    Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
 807                };
 808                count_open_ai_tokens(request, model, cx)
 809            }
 810            cloud_llm_client::LanguageModelProvider::Google => {
 811                let client = self.client.clone();
 812                let llm_api_token = self.llm_api_token.clone();
 813                let model_id = self.model.id.to_string();
 814                let generate_content_request =
 815                    into_google(request, model_id.clone(), GoogleModelMode::Default);
 816                async move {
 817                    let http_client = &client.http_client();
 818                    let token = llm_api_token.acquire(&client).await?;
 819
 820                    let request_body = CountTokensBody {
 821                        provider: cloud_llm_client::LanguageModelProvider::Google,
 822                        model: model_id,
 823                        provider_request: serde_json::to_value(&google_ai::CountTokensRequest {
 824                            generate_content_request,
 825                        })?,
 826                    };
 827                    let request = http_client::Request::builder()
 828                        .method(Method::POST)
 829                        .uri(
 830                            http_client
 831                                .build_zed_llm_url("/count_tokens", &[])?
 832                                .as_ref(),
 833                        )
 834                        .header("Content-Type", "application/json")
 835                        .header("Authorization", format!("Bearer {token}"))
 836                        .body(serde_json::to_string(&request_body)?.into())?;
 837                    let mut response = http_client.send(request).await?;
 838                    let status = response.status();
 839                    let headers = response.headers().clone();
 840                    let mut response_body = String::new();
 841                    response
 842                        .body_mut()
 843                        .read_to_string(&mut response_body)
 844                        .await?;
 845
 846                    if status.is_success() {
 847                        let response_body: CountTokensResponse =
 848                            serde_json::from_str(&response_body)?;
 849
 850                        Ok(response_body.tokens as u64)
 851                    } else {
 852                        Err(anyhow!(ApiError {
 853                            status,
 854                            body: response_body,
 855                            headers
 856                        }))
 857                    }
 858                }
 859                .boxed()
 860            }
 861        }
 862    }
 863
 864    fn stream_completion(
 865        &self,
 866        request: LanguageModelRequest,
 867        cx: &AsyncApp,
 868    ) -> BoxFuture<
 869        'static,
 870        Result<
 871            BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
 872            LanguageModelCompletionError,
 873        >,
 874    > {
 875        let thread_id = request.thread_id.clone();
 876        let prompt_id = request.prompt_id.clone();
 877        let intent = request.intent;
 878        let mode = request.mode;
 879        let app_version = cx.update(|cx| AppVersion::global(cx)).ok();
 880        let thinking_allowed = request.thinking_allowed;
 881        match self.model.provider {
 882            cloud_llm_client::LanguageModelProvider::Anthropic => {
 883                let request = into_anthropic(
 884                    request,
 885                    self.model.id.to_string(),
 886                    1.0,
 887                    self.model.max_output_tokens as u64,
 888                    if thinking_allowed && self.model.id.0.ends_with("-thinking") {
 889                        AnthropicModelMode::Thinking {
 890                            budget_tokens: Some(4_096),
 891                        }
 892                    } else {
 893                        AnthropicModelMode::Default
 894                    },
 895                );
 896                let client = self.client.clone();
 897                let llm_api_token = self.llm_api_token.clone();
 898                let future = self.request_limiter.stream(async move {
 899                    let PerformLlmCompletionResponse {
 900                        response,
 901                        usage,
 902                        includes_status_messages,
 903                        tool_use_limit_reached,
 904                    } = Self::perform_llm_completion(
 905                        client.clone(),
 906                        llm_api_token,
 907                        app_version,
 908                        CompletionBody {
 909                            thread_id,
 910                            prompt_id,
 911                            intent,
 912                            mode,
 913                            provider: cloud_llm_client::LanguageModelProvider::Anthropic,
 914                            model: request.model.clone(),
 915                            provider_request: serde_json::to_value(&request)
 916                                .map_err(|e| anyhow!(e))?,
 917                        },
 918                    )
 919                    .await
 920                    .map_err(|err| match err.downcast::<ApiError>() {
 921                        Ok(api_err) => anyhow!(LanguageModelCompletionError::from(api_err)),
 922                        Err(err) => anyhow!(err),
 923                    })?;
 924
 925                    let mut mapper = AnthropicEventMapper::new();
 926                    Ok(map_cloud_completion_events(
 927                        Box::pin(
 928                            response_lines(response, includes_status_messages)
 929                                .chain(usage_updated_event(usage))
 930                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
 931                        ),
 932                        move |event| mapper.map_event(event),
 933                    ))
 934                });
 935                async move { Ok(future.await?.boxed()) }.boxed()
 936            }
 937            cloud_llm_client::LanguageModelProvider::OpenAi => {
 938                let client = self.client.clone();
 939                let model = match open_ai::Model::from_id(&self.model.id.0) {
 940                    Ok(model) => model,
 941                    Err(err) => return async move { Err(anyhow!(err).into()) }.boxed(),
 942                };
 943                let request = into_open_ai(
 944                    request,
 945                    model.id(),
 946                    model.supports_parallel_tool_calls(),
 947                    model.supports_prompt_cache_key(),
 948                    None,
 949                    None,
 950                );
 951                let llm_api_token = self.llm_api_token.clone();
 952                let future = self.request_limiter.stream(async move {
 953                    let PerformLlmCompletionResponse {
 954                        response,
 955                        usage,
 956                        includes_status_messages,
 957                        tool_use_limit_reached,
 958                    } = Self::perform_llm_completion(
 959                        client.clone(),
 960                        llm_api_token,
 961                        app_version,
 962                        CompletionBody {
 963                            thread_id,
 964                            prompt_id,
 965                            intent,
 966                            mode,
 967                            provider: cloud_llm_client::LanguageModelProvider::OpenAi,
 968                            model: request.model.clone(),
 969                            provider_request: serde_json::to_value(&request)
 970                                .map_err(|e| anyhow!(e))?,
 971                        },
 972                    )
 973                    .await?;
 974
 975                    let mut mapper = OpenAiEventMapper::new();
 976                    Ok(map_cloud_completion_events(
 977                        Box::pin(
 978                            response_lines(response, includes_status_messages)
 979                                .chain(usage_updated_event(usage))
 980                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
 981                        ),
 982                        move |event| mapper.map_event(event),
 983                    ))
 984                });
 985                async move { Ok(future.await?.boxed()) }.boxed()
 986            }
 987            cloud_llm_client::LanguageModelProvider::Google => {
 988                let client = self.client.clone();
 989                let request =
 990                    into_google(request, self.model.id.to_string(), GoogleModelMode::Default);
 991                let llm_api_token = self.llm_api_token.clone();
 992                let future = self.request_limiter.stream(async move {
 993                    let PerformLlmCompletionResponse {
 994                        response,
 995                        usage,
 996                        includes_status_messages,
 997                        tool_use_limit_reached,
 998                    } = Self::perform_llm_completion(
 999                        client.clone(),
1000                        llm_api_token,
1001                        app_version,
1002                        CompletionBody {
1003                            thread_id,
1004                            prompt_id,
1005                            intent,
1006                            mode,
1007                            provider: cloud_llm_client::LanguageModelProvider::Google,
1008                            model: request.model.model_id.clone(),
1009                            provider_request: serde_json::to_value(&request)
1010                                .map_err(|e| anyhow!(e))?,
1011                        },
1012                    )
1013                    .await?;
1014
1015                    let mut mapper = GoogleEventMapper::new();
1016                    Ok(map_cloud_completion_events(
1017                        Box::pin(
1018                            response_lines(response, includes_status_messages)
1019                                .chain(usage_updated_event(usage))
1020                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
1021                        ),
1022                        move |event| mapper.map_event(event),
1023                    ))
1024                });
1025                async move { Ok(future.await?.boxed()) }.boxed()
1026            }
1027        }
1028    }
1029}
1030
1031fn map_cloud_completion_events<T, F>(
1032    stream: Pin<Box<dyn Stream<Item = Result<CompletionEvent<T>>> + Send>>,
1033    mut map_callback: F,
1034) -> BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
1035where
1036    T: DeserializeOwned + 'static,
1037    F: FnMut(T) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
1038        + Send
1039        + 'static,
1040{
1041    stream
1042        .flat_map(move |event| {
1043            futures::stream::iter(match event {
1044                Err(error) => {
1045                    vec![Err(LanguageModelCompletionError::from(error))]
1046                }
1047                Ok(CompletionEvent::Status(event)) => {
1048                    vec![Ok(LanguageModelCompletionEvent::StatusUpdate(event))]
1049                }
1050                Ok(CompletionEvent::Event(event)) => map_callback(event),
1051            })
1052        })
1053        .boxed()
1054}
1055
1056fn usage_updated_event<T>(
1057    usage: Option<ModelRequestUsage>,
1058) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1059    futures::stream::iter(usage.map(|usage| {
1060        Ok(CompletionEvent::Status(
1061            CompletionRequestStatus::UsageUpdated {
1062                amount: usage.amount as usize,
1063                limit: usage.limit,
1064            },
1065        ))
1066    }))
1067}
1068
1069fn tool_use_limit_reached_event<T>(
1070    tool_use_limit_reached: bool,
1071) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1072    futures::stream::iter(tool_use_limit_reached.then(|| {
1073        Ok(CompletionEvent::Status(
1074            CompletionRequestStatus::ToolUseLimitReached,
1075        ))
1076    }))
1077}
1078
1079fn response_lines<T: DeserializeOwned>(
1080    response: Response<AsyncBody>,
1081    includes_status_messages: bool,
1082) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1083    futures::stream::try_unfold(
1084        (String::new(), BufReader::new(response.into_body())),
1085        move |(mut line, mut body)| async move {
1086            match body.read_line(&mut line).await {
1087                Ok(0) => Ok(None),
1088                Ok(_) => {
1089                    let event = if includes_status_messages {
1090                        serde_json::from_str::<CompletionEvent<T>>(&line)?
1091                    } else {
1092                        CompletionEvent::Event(serde_json::from_str::<T>(&line)?)
1093                    };
1094
1095                    line.clear();
1096                    Ok(Some((event, (line, body))))
1097                }
1098                Err(e) => Err(e.into()),
1099            }
1100        },
1101    )
1102}
1103
1104#[derive(IntoElement, RegisterComponent)]
1105struct ZedAiConfiguration {
1106    is_connected: bool,
1107    plan: Option<Plan>,
1108    subscription_period: Option<(DateTime<Utc>, DateTime<Utc>)>,
1109    eligible_for_trial: bool,
1110    has_accepted_terms_of_service: bool,
1111    account_too_young: bool,
1112    accept_terms_of_service_in_progress: bool,
1113    accept_terms_of_service_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1114    sign_in_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1115}
1116
1117impl RenderOnce for ZedAiConfiguration {
1118    fn render(self, _window: &mut Window, _cx: &mut App) -> impl IntoElement {
1119        let young_account_banner = YoungAccountBanner;
1120
1121        let is_pro = self.plan == Some(Plan::ZedPro);
1122        let subscription_text = match (self.plan, self.subscription_period) {
1123            (Some(Plan::ZedPro), Some(_)) => {
1124                "You have access to Zed's hosted models through your Pro subscription."
1125            }
1126            (Some(Plan::ZedProTrial), Some(_)) => {
1127                "You have access to Zed's hosted models through your Pro trial."
1128            }
1129            (Some(Plan::ZedFree), Some(_)) => {
1130                "You have basic access to Zed's hosted models through the Free plan."
1131            }
1132            _ => {
1133                if self.eligible_for_trial {
1134                    "Subscribe for access to Zed's hosted models. Start with a 14 day free trial."
1135                } else {
1136                    "Subscribe for access to Zed's hosted models."
1137                }
1138            }
1139        };
1140
1141        let manage_subscription_buttons = if is_pro {
1142            Button::new("manage_settings", "Manage Subscription")
1143                .full_width()
1144                .style(ButtonStyle::Tinted(TintColor::Accent))
1145                .on_click(|_, _, cx| cx.open_url(&zed_urls::account_url(cx)))
1146                .into_any_element()
1147        } else if self.plan.is_none() || self.eligible_for_trial {
1148            Button::new("start_trial", "Start 14-day Free Pro Trial")
1149                .full_width()
1150                .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1151                .on_click(|_, _, cx| cx.open_url(&zed_urls::start_trial_url(cx)))
1152                .into_any_element()
1153        } else {
1154            Button::new("upgrade", "Upgrade to Pro")
1155                .full_width()
1156                .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1157                .on_click(|_, _, cx| cx.open_url(&zed_urls::upgrade_to_zed_pro_url(cx)))
1158                .into_any_element()
1159        };
1160
1161        if !self.is_connected {
1162            return v_flex()
1163                .gap_2()
1164                .child(Label::new("Sign in to have access to Zed's complete agentic experience with hosted models."))
1165                .child(
1166                    Button::new("sign_in", "Sign In to use Zed AI")
1167                        .icon_color(Color::Muted)
1168                        .icon(IconName::Github)
1169                        .icon_size(IconSize::Small)
1170                        .icon_position(IconPosition::Start)
1171                        .full_width()
1172                        .on_click({
1173                            let callback = self.sign_in_callback.clone();
1174                            move |_, window, cx| (callback)(window, cx)
1175                        }),
1176                );
1177        }
1178
1179        v_flex()
1180            .gap_2()
1181            .w_full()
1182            .when(!self.has_accepted_terms_of_service, |this| {
1183                this.child(render_accept_terms(
1184                    LanguageModelProviderTosView::Configuration,
1185                    self.accept_terms_of_service_in_progress,
1186                    {
1187                        let callback = self.accept_terms_of_service_callback.clone();
1188                        move |window, cx| (callback)(window, cx)
1189                    },
1190                ))
1191            })
1192            .map(|this| {
1193                if self.has_accepted_terms_of_service && self.account_too_young {
1194                    this.child(young_account_banner).child(
1195                        Button::new("upgrade", "Upgrade to Pro")
1196                            .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1197                            .full_width()
1198                            .on_click(|_, _, cx| {
1199                                cx.open_url(&zed_urls::upgrade_to_zed_pro_url(cx))
1200                            }),
1201                    )
1202                } else if self.has_accepted_terms_of_service {
1203                    this.text_sm()
1204                        .child(subscription_text)
1205                        .child(manage_subscription_buttons)
1206                } else {
1207                    this
1208                }
1209            })
1210            .when(self.has_accepted_terms_of_service, |this| this)
1211    }
1212}
1213
1214struct ConfigurationView {
1215    state: Entity<State>,
1216    accept_terms_of_service_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1217    sign_in_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1218}
1219
1220impl ConfigurationView {
1221    fn new(state: Entity<State>) -> Self {
1222        let accept_terms_of_service_callback = Arc::new({
1223            let state = state.clone();
1224            move |_window: &mut Window, cx: &mut App| {
1225                state.update(cx, |state, cx| {
1226                    state.accept_terms_of_service(cx);
1227                });
1228            }
1229        });
1230
1231        let sign_in_callback = Arc::new({
1232            let state = state.clone();
1233            move |_window: &mut Window, cx: &mut App| {
1234                state.update(cx, |state, cx| {
1235                    state.authenticate(cx).detach_and_log_err(cx);
1236                });
1237            }
1238        });
1239
1240        Self {
1241            state,
1242            accept_terms_of_service_callback,
1243            sign_in_callback,
1244        }
1245    }
1246}
1247
1248impl Render for ConfigurationView {
1249    fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
1250        let state = self.state.read(cx);
1251        let user_store = state.user_store.read(cx);
1252
1253        ZedAiConfiguration {
1254            is_connected: !state.is_signed_out(cx),
1255            plan: user_store.plan(),
1256            subscription_period: user_store.subscription_period(),
1257            eligible_for_trial: user_store.trial_started_at().is_none(),
1258            has_accepted_terms_of_service: state.has_accepted_terms_of_service(cx),
1259            account_too_young: user_store.account_too_young(),
1260            accept_terms_of_service_in_progress: state.accept_terms_of_service_task.is_some(),
1261            accept_terms_of_service_callback: self.accept_terms_of_service_callback.clone(),
1262            sign_in_callback: self.sign_in_callback.clone(),
1263        }
1264    }
1265}
1266
1267impl Component for ZedAiConfiguration {
1268    fn name() -> &'static str {
1269        "AI Configuration Content"
1270    }
1271
1272    fn sort_name() -> &'static str {
1273        "AI Configuration Content"
1274    }
1275
1276    fn scope() -> ComponentScope {
1277        ComponentScope::Onboarding
1278    }
1279
1280    fn preview(_window: &mut Window, _cx: &mut App) -> Option<AnyElement> {
1281        fn configuration(
1282            is_connected: bool,
1283            plan: Option<Plan>,
1284            eligible_for_trial: bool,
1285            account_too_young: bool,
1286            has_accepted_terms_of_service: bool,
1287        ) -> AnyElement {
1288            ZedAiConfiguration {
1289                is_connected,
1290                plan,
1291                subscription_period: plan
1292                    .is_some()
1293                    .then(|| (Utc::now(), Utc::now() + chrono::Duration::days(7))),
1294                eligible_for_trial,
1295                has_accepted_terms_of_service,
1296                account_too_young,
1297                accept_terms_of_service_in_progress: false,
1298                accept_terms_of_service_callback: Arc::new(|_, _| {}),
1299                sign_in_callback: Arc::new(|_, _| {}),
1300            }
1301            .into_any_element()
1302        }
1303
1304        Some(
1305            v_flex()
1306                .p_4()
1307                .gap_4()
1308                .children(vec![
1309                    single_example(
1310                        "Not connected",
1311                        configuration(false, None, false, false, true),
1312                    ),
1313                    single_example(
1314                        "Accept Terms of Service",
1315                        configuration(true, None, true, false, false),
1316                    ),
1317                    single_example(
1318                        "No Plan - Not eligible for trial",
1319                        configuration(true, None, false, false, true),
1320                    ),
1321                    single_example(
1322                        "No Plan - Eligible for trial",
1323                        configuration(true, None, true, false, true),
1324                    ),
1325                    single_example(
1326                        "Free Plan",
1327                        configuration(true, Some(Plan::ZedFree), true, false, true),
1328                    ),
1329                    single_example(
1330                        "Zed Pro Trial Plan",
1331                        configuration(true, Some(Plan::ZedProTrial), true, false, true),
1332                    ),
1333                    single_example(
1334                        "Zed Pro Plan",
1335                        configuration(true, Some(Plan::ZedPro), true, false, true),
1336                    ),
1337                ])
1338                .into_any_element(),
1339        )
1340    }
1341}
1342
1343#[cfg(test)]
1344mod tests {
1345    use super::*;
1346    use http_client::http::{HeaderMap, StatusCode};
1347    use language_model::LanguageModelCompletionError;
1348
1349    #[test]
1350    fn test_api_error_conversion_with_upstream_http_error() {
1351        // upstream_http_error with 503 status should become ServerOverloaded
1352        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}"#;
1353
1354        let api_error = ApiError {
1355            status: StatusCode::INTERNAL_SERVER_ERROR,
1356            body: error_body.to_string(),
1357            headers: HeaderMap::new(),
1358        };
1359
1360        let completion_error: LanguageModelCompletionError = api_error.into();
1361
1362        match completion_error {
1363            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1364                assert_eq!(
1365                    message,
1366                    "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout"
1367                );
1368            }
1369            _ => panic!(
1370                "Expected UpstreamProviderError for upstream 503, got: {:?}",
1371                completion_error
1372            ),
1373        }
1374
1375        // upstream_http_error with 500 status should become ApiInternalServerError
1376        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the OpenAI API: internal server error","upstream_status":500}"#;
1377
1378        let api_error = ApiError {
1379            status: StatusCode::INTERNAL_SERVER_ERROR,
1380            body: error_body.to_string(),
1381            headers: HeaderMap::new(),
1382        };
1383
1384        let completion_error: LanguageModelCompletionError = api_error.into();
1385
1386        match completion_error {
1387            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1388                assert_eq!(
1389                    message,
1390                    "Received an error from the OpenAI API: internal server error"
1391                );
1392            }
1393            _ => panic!(
1394                "Expected UpstreamProviderError for upstream 500, got: {:?}",
1395                completion_error
1396            ),
1397        }
1398
1399        // upstream_http_error with 429 status should become RateLimitExceeded
1400        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the Google API: rate limit exceeded","upstream_status":429}"#;
1401
1402        let api_error = ApiError {
1403            status: StatusCode::INTERNAL_SERVER_ERROR,
1404            body: error_body.to_string(),
1405            headers: HeaderMap::new(),
1406        };
1407
1408        let completion_error: LanguageModelCompletionError = api_error.into();
1409
1410        match completion_error {
1411            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1412                assert_eq!(
1413                    message,
1414                    "Received an error from the Google API: rate limit exceeded"
1415                );
1416            }
1417            _ => panic!(
1418                "Expected UpstreamProviderError for upstream 429, got: {:?}",
1419                completion_error
1420            ),
1421        }
1422
1423        // Regular 500 error without upstream_http_error should remain ApiInternalServerError for Zed
1424        let error_body = "Regular internal server error";
1425
1426        let api_error = ApiError {
1427            status: StatusCode::INTERNAL_SERVER_ERROR,
1428            body: error_body.to_string(),
1429            headers: HeaderMap::new(),
1430        };
1431
1432        let completion_error: LanguageModelCompletionError = api_error.into();
1433
1434        match completion_error {
1435            LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
1436                assert_eq!(provider, PROVIDER_NAME);
1437                assert_eq!(message, "Regular internal server error");
1438            }
1439            _ => panic!(
1440                "Expected ApiInternalServerError for regular 500, got: {:?}",
1441                completion_error
1442            ),
1443        }
1444
1445        // upstream_http_429 format should be converted to UpstreamProviderError
1446        let error_body = r#"{"code":"upstream_http_429","message":"Upstream Anthropic rate limit exceeded.","retry_after":30.5}"#;
1447
1448        let api_error = ApiError {
1449            status: StatusCode::INTERNAL_SERVER_ERROR,
1450            body: error_body.to_string(),
1451            headers: HeaderMap::new(),
1452        };
1453
1454        let completion_error: LanguageModelCompletionError = api_error.into();
1455
1456        match completion_error {
1457            LanguageModelCompletionError::UpstreamProviderError {
1458                message,
1459                status,
1460                retry_after,
1461            } => {
1462                assert_eq!(message, "Upstream Anthropic rate limit exceeded.");
1463                assert_eq!(status, StatusCode::TOO_MANY_REQUESTS);
1464                assert_eq!(retry_after, Some(Duration::from_secs_f64(30.5)));
1465            }
1466            _ => panic!(
1467                "Expected UpstreamProviderError for upstream_http_429, got: {:?}",
1468                completion_error
1469            ),
1470        }
1471
1472        // Invalid JSON in error body should fall back to regular error handling
1473        let error_body = "Not JSON at all";
1474
1475        let api_error = ApiError {
1476            status: StatusCode::INTERNAL_SERVER_ERROR,
1477            body: error_body.to_string(),
1478            headers: HeaderMap::new(),
1479        };
1480
1481        let completion_error: LanguageModelCompletionError = api_error.into();
1482
1483        match completion_error {
1484            LanguageModelCompletionError::ApiInternalServerError { provider, .. } => {
1485                assert_eq!(provider, PROVIDER_NAME);
1486            }
1487            _ => panic!(
1488                "Expected ApiInternalServerError for invalid JSON, got: {:?}",
1489                completion_error
1490            ),
1491        }
1492    }
1493}