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
  47const PROVIDER_ID: LanguageModelProviderId = language_model::ZED_CLOUD_PROVIDER_ID;
  48const 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        Self {
 140            client: client.clone(),
 141            llm_api_token: LlmApiToken::default(),
 142            user_store: user_store.clone(),
 143            status,
 144            accept_terms_of_service_task: None,
 145            models: Vec::new(),
 146            default_model: None,
 147            default_fast_model: None,
 148            recommended_models: Vec::new(),
 149            _fetch_models_task: cx.spawn(async move |this, cx| {
 150                maybe!(async move {
 151                    let (client, llm_api_token) = this
 152                        .read_with(cx, |this, _cx| (client.clone(), this.llm_api_token.clone()))?;
 153
 154                    loop {
 155                        let is_authenticated = user_store
 156                            .read_with(cx, |user_store, _cx| user_store.current_user().is_some())?;
 157                        if is_authenticated {
 158                            break;
 159                        }
 160
 161                        cx.background_executor()
 162                            .timer(Duration::from_millis(100))
 163                            .await;
 164                    }
 165
 166                    let response = Self::fetch_models(client, llm_api_token).await?;
 167                    this.update(cx, |this, cx| {
 168                        this.update_models(response, cx);
 169                    })
 170                })
 171                .await
 172                .context("failed to fetch Zed models")
 173                .log_err();
 174            }),
 175            _settings_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
 176                cx.notify();
 177            }),
 178            _llm_token_subscription: cx.subscribe(
 179                &refresh_llm_token_listener,
 180                move |this, _listener, _event, cx| {
 181                    let client = this.client.clone();
 182                    let llm_api_token = this.llm_api_token.clone();
 183                    cx.spawn(async move |this, cx| {
 184                        llm_api_token.refresh(&client).await?;
 185                        let response = Self::fetch_models(client, llm_api_token).await?;
 186                        this.update(cx, |this, cx| {
 187                            this.update_models(response, cx);
 188                        })
 189                    })
 190                    .detach_and_log_err(cx);
 191                },
 192            ),
 193        }
 194    }
 195
 196    fn is_signed_out(&self, cx: &App) -> bool {
 197        self.user_store.read(cx).current_user().is_none()
 198    }
 199
 200    fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
 201        let client = self.client.clone();
 202        cx.spawn(async move |state, cx| {
 203            client.sign_in_with_optional_connect(true, &cx).await?;
 204            state.update(cx, |_, cx| cx.notify())
 205        })
 206    }
 207
 208    fn has_accepted_terms_of_service(&self, cx: &App) -> bool {
 209        self.user_store.read(cx).has_accepted_terms_of_service()
 210    }
 211
 212    fn accept_terms_of_service(&mut self, cx: &mut Context<Self>) {
 213        let user_store = self.user_store.clone();
 214        self.accept_terms_of_service_task = Some(cx.spawn(async move |this, cx| {
 215            let _ = user_store
 216                .update(cx, |store, cx| store.accept_terms_of_service(cx))?
 217                .await;
 218            this.update(cx, |this, cx| {
 219                this.accept_terms_of_service_task = None;
 220                cx.notify()
 221            })
 222        }));
 223    }
 224
 225    fn update_models(&mut self, response: ListModelsResponse, cx: &mut Context<Self>) {
 226        let mut models = Vec::new();
 227
 228        for model in response.models {
 229            models.push(Arc::new(model.clone()));
 230
 231            // Right now we represent thinking variants of models as separate models on the client,
 232            // so we need to insert variants for any model that supports thinking.
 233            if model.supports_thinking {
 234                models.push(Arc::new(cloud_llm_client::LanguageModel {
 235                    id: cloud_llm_client::LanguageModelId(format!("{}-thinking", model.id).into()),
 236                    display_name: format!("{} Thinking", model.display_name),
 237                    ..model
 238                }));
 239            }
 240        }
 241
 242        self.default_model = models
 243            .iter()
 244            .find(|model| model.id == response.default_model)
 245            .cloned();
 246        self.default_fast_model = models
 247            .iter()
 248            .find(|model| model.id == response.default_fast_model)
 249            .cloned();
 250        self.recommended_models = response
 251            .recommended_models
 252            .iter()
 253            .filter_map(|id| models.iter().find(|model| &model.id == id))
 254            .cloned()
 255            .collect();
 256        self.models = models;
 257        cx.notify();
 258    }
 259
 260    async fn fetch_models(
 261        client: Arc<Client>,
 262        llm_api_token: LlmApiToken,
 263    ) -> Result<ListModelsResponse> {
 264        let http_client = &client.http_client();
 265        let token = llm_api_token.acquire(&client).await?;
 266
 267        let request = http_client::Request::builder()
 268            .method(Method::GET)
 269            .uri(http_client.build_zed_llm_url("/models", &[])?.as_ref())
 270            .header("Authorization", format!("Bearer {token}"))
 271            .body(AsyncBody::empty())?;
 272        let mut response = http_client
 273            .send(request)
 274            .await
 275            .context("failed to send list models request")?;
 276
 277        if response.status().is_success() {
 278            let mut body = String::new();
 279            response.body_mut().read_to_string(&mut body).await?;
 280            return Ok(serde_json::from_str(&body)?);
 281        } else {
 282            let mut body = String::new();
 283            response.body_mut().read_to_string(&mut body).await?;
 284            anyhow::bail!(
 285                "error listing models.\nStatus: {:?}\nBody: {body}",
 286                response.status(),
 287            );
 288        }
 289    }
 290}
 291
 292impl CloudLanguageModelProvider {
 293    pub fn new(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) -> Self {
 294        let mut status_rx = client.status();
 295        let status = *status_rx.borrow();
 296
 297        let state = cx.new(|cx| State::new(client.clone(), user_store.clone(), status, cx));
 298
 299        let state_ref = state.downgrade();
 300        let maintain_client_status = cx.spawn(async move |cx| {
 301            while let Some(status) = status_rx.next().await {
 302                if let Some(this) = state_ref.upgrade() {
 303                    _ = this.update(cx, |this, cx| {
 304                        if this.status != status {
 305                            this.status = status;
 306                            cx.notify();
 307                        }
 308                    });
 309                } else {
 310                    break;
 311                }
 312            }
 313        });
 314
 315        Self {
 316            client,
 317            state: state.clone(),
 318            _maintain_client_status: maintain_client_status,
 319        }
 320    }
 321
 322    fn create_language_model(
 323        &self,
 324        model: Arc<cloud_llm_client::LanguageModel>,
 325        llm_api_token: LlmApiToken,
 326    ) -> Arc<dyn LanguageModel> {
 327        Arc::new(CloudLanguageModel {
 328            id: LanguageModelId(SharedString::from(model.id.0.clone())),
 329            model,
 330            llm_api_token: llm_api_token.clone(),
 331            client: self.client.clone(),
 332            request_limiter: RateLimiter::new(4),
 333        })
 334    }
 335}
 336
 337impl LanguageModelProviderState for CloudLanguageModelProvider {
 338    type ObservableEntity = State;
 339
 340    fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
 341        Some(self.state.clone())
 342    }
 343}
 344
 345impl LanguageModelProvider for CloudLanguageModelProvider {
 346    fn id(&self) -> LanguageModelProviderId {
 347        PROVIDER_ID
 348    }
 349
 350    fn name(&self) -> LanguageModelProviderName {
 351        PROVIDER_NAME
 352    }
 353
 354    fn icon(&self) -> IconName {
 355        IconName::AiZed
 356    }
 357
 358    fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
 359        let default_model = self.state.read(cx).default_model.clone()?;
 360        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 361        Some(self.create_language_model(default_model, llm_api_token))
 362    }
 363
 364    fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
 365        let default_fast_model = self.state.read(cx).default_fast_model.clone()?;
 366        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 367        Some(self.create_language_model(default_fast_model, llm_api_token))
 368    }
 369
 370    fn recommended_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
 371        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 372        self.state
 373            .read(cx)
 374            .recommended_models
 375            .iter()
 376            .cloned()
 377            .map(|model| self.create_language_model(model, llm_api_token.clone()))
 378            .collect()
 379    }
 380
 381    fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
 382        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 383        self.state
 384            .read(cx)
 385            .models
 386            .iter()
 387            .cloned()
 388            .map(|model| self.create_language_model(model, llm_api_token.clone()))
 389            .collect()
 390    }
 391
 392    fn is_authenticated(&self, cx: &App) -> bool {
 393        let state = self.state.read(cx);
 394        !state.is_signed_out(cx) && state.has_accepted_terms_of_service(cx)
 395    }
 396
 397    fn authenticate(&self, _cx: &mut App) -> Task<Result<(), AuthenticateError>> {
 398        Task::ready(Ok(()))
 399    }
 400
 401    fn configuration_view(&self, _: &mut Window, cx: &mut App) -> AnyView {
 402        cx.new(|_| ConfigurationView::new(self.state.clone()))
 403            .into()
 404    }
 405
 406    fn must_accept_terms(&self, cx: &App) -> bool {
 407        !self.state.read(cx).has_accepted_terms_of_service(cx)
 408    }
 409
 410    fn render_accept_terms(
 411        &self,
 412        view: LanguageModelProviderTosView,
 413        cx: &mut App,
 414    ) -> Option<AnyElement> {
 415        let state = self.state.read(cx);
 416        if state.has_accepted_terms_of_service(cx) {
 417            return None;
 418        }
 419        Some(
 420            render_accept_terms(view, state.accept_terms_of_service_task.is_some(), {
 421                let state = self.state.clone();
 422                move |_window, cx| {
 423                    state.update(cx, |state, cx| state.accept_terms_of_service(cx));
 424                }
 425            })
 426            .into_any_element(),
 427        )
 428    }
 429
 430    fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
 431        Task::ready(Ok(()))
 432    }
 433}
 434
 435fn render_accept_terms(
 436    view_kind: LanguageModelProviderTosView,
 437    accept_terms_of_service_in_progress: bool,
 438    accept_terms_callback: impl Fn(&mut Window, &mut App) + 'static,
 439) -> impl IntoElement {
 440    let thread_fresh_start = matches!(view_kind, LanguageModelProviderTosView::ThreadFreshStart);
 441    let thread_empty_state = matches!(view_kind, LanguageModelProviderTosView::ThreadEmptyState);
 442
 443    let terms_button = Button::new("terms_of_service", "Terms of Service")
 444        .style(ButtonStyle::Subtle)
 445        .icon(IconName::ArrowUpRight)
 446        .icon_color(Color::Muted)
 447        .icon_size(IconSize::XSmall)
 448        .when(thread_empty_state, |this| this.label_size(LabelSize::Small))
 449        .on_click(move |_, _window, cx| cx.open_url("https://zed.dev/terms-of-service"));
 450
 451    let button_container = h_flex().child(
 452        Button::new("accept_terms", "I accept the Terms of Service")
 453            .when(!thread_empty_state, |this| {
 454                this.full_width()
 455                    .style(ButtonStyle::Tinted(TintColor::Accent))
 456                    .icon(IconName::Check)
 457                    .icon_position(IconPosition::Start)
 458                    .icon_size(IconSize::Small)
 459            })
 460            .when(thread_empty_state, |this| {
 461                this.style(ButtonStyle::Tinted(TintColor::Warning))
 462                    .label_size(LabelSize::Small)
 463            })
 464            .disabled(accept_terms_of_service_in_progress)
 465            .on_click(move |_, window, cx| (accept_terms_callback)(window, cx)),
 466    );
 467
 468    if thread_empty_state {
 469        h_flex()
 470            .w_full()
 471            .flex_wrap()
 472            .justify_between()
 473            .child(
 474                h_flex()
 475                    .child(
 476                        Label::new("To start using Zed AI, please read and accept the")
 477                            .size(LabelSize::Small),
 478                    )
 479                    .child(terms_button),
 480            )
 481            .child(button_container)
 482    } else {
 483        v_flex()
 484            .w_full()
 485            .gap_2()
 486            .child(
 487                h_flex()
 488                    .flex_wrap()
 489                    .when(thread_fresh_start, |this| this.justify_center())
 490                    .child(Label::new(
 491                        "To start using Zed AI, please read and accept the",
 492                    ))
 493                    .child(terms_button),
 494            )
 495            .child({
 496                match view_kind {
 497                    LanguageModelProviderTosView::TextThreadPopup => {
 498                        button_container.w_full().justify_end()
 499                    }
 500                    LanguageModelProviderTosView::Configuration => {
 501                        button_container.w_full().justify_start()
 502                    }
 503                    LanguageModelProviderTosView::ThreadFreshStart => {
 504                        button_container.w_full().justify_center()
 505                    }
 506                    LanguageModelProviderTosView::ThreadEmptyState => div().w_0(),
 507                }
 508            })
 509    }
 510}
 511
 512pub struct CloudLanguageModel {
 513    id: LanguageModelId,
 514    model: Arc<cloud_llm_client::LanguageModel>,
 515    llm_api_token: LlmApiToken,
 516    client: Arc<Client>,
 517    request_limiter: RateLimiter,
 518}
 519
 520struct PerformLlmCompletionResponse {
 521    response: Response<AsyncBody>,
 522    usage: Option<ModelRequestUsage>,
 523    tool_use_limit_reached: bool,
 524    includes_status_messages: bool,
 525}
 526
 527impl CloudLanguageModel {
 528    async fn perform_llm_completion(
 529        client: Arc<Client>,
 530        llm_api_token: LlmApiToken,
 531        app_version: Option<SemanticVersion>,
 532        body: CompletionBody,
 533    ) -> Result<PerformLlmCompletionResponse> {
 534        let http_client = &client.http_client();
 535
 536        let mut token = llm_api_token.acquire(&client).await?;
 537        let mut refreshed_token = false;
 538
 539        loop {
 540            let request_builder = http_client::Request::builder()
 541                .method(Method::POST)
 542                .uri(http_client.build_zed_llm_url("/completions", &[])?.as_ref());
 543            let request_builder = if let Some(app_version) = app_version {
 544                request_builder.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
 545            } else {
 546                request_builder
 547            };
 548
 549            let request = request_builder
 550                .header("Content-Type", "application/json")
 551                .header("Authorization", format!("Bearer {token}"))
 552                .header(CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, "true")
 553                .body(serde_json::to_string(&body)?.into())?;
 554            let mut response = http_client.send(request).await?;
 555            let status = response.status();
 556            if status.is_success() {
 557                let includes_status_messages = response
 558                    .headers()
 559                    .get(SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME)
 560                    .is_some();
 561
 562                let tool_use_limit_reached = response
 563                    .headers()
 564                    .get(TOOL_USE_LIMIT_REACHED_HEADER_NAME)
 565                    .is_some();
 566
 567                let usage = if includes_status_messages {
 568                    None
 569                } else {
 570                    ModelRequestUsage::from_headers(response.headers()).ok()
 571                };
 572
 573                return Ok(PerformLlmCompletionResponse {
 574                    response,
 575                    usage,
 576                    includes_status_messages,
 577                    tool_use_limit_reached,
 578                });
 579            }
 580
 581            if !refreshed_token
 582                && response
 583                    .headers()
 584                    .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
 585                    .is_some()
 586            {
 587                token = llm_api_token.refresh(&client).await?;
 588                refreshed_token = true;
 589                continue;
 590            }
 591
 592            if status == StatusCode::FORBIDDEN
 593                && response
 594                    .headers()
 595                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 596                    .is_some()
 597            {
 598                if let Some(MODEL_REQUESTS_RESOURCE_HEADER_VALUE) = response
 599                    .headers()
 600                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 601                    .and_then(|resource| resource.to_str().ok())
 602                {
 603                    if let Some(plan) = response
 604                        .headers()
 605                        .get(CURRENT_PLAN_HEADER_NAME)
 606                        .and_then(|plan| plan.to_str().ok())
 607                        .and_then(|plan| cloud_llm_client::Plan::from_str(plan).ok())
 608                    {
 609                        return Err(anyhow!(ModelRequestLimitReachedError { plan }));
 610                    }
 611                }
 612            } else if status == StatusCode::PAYMENT_REQUIRED {
 613                return Err(anyhow!(PaymentRequiredError));
 614            }
 615
 616            let mut body = String::new();
 617            let headers = response.headers().clone();
 618            response.body_mut().read_to_string(&mut body).await?;
 619            return Err(anyhow!(ApiError {
 620                status,
 621                body,
 622                headers
 623            }));
 624        }
 625    }
 626}
 627
 628#[derive(Debug, Error)]
 629#[error("cloud language model request failed with status {status}: {body}")]
 630struct ApiError {
 631    status: StatusCode,
 632    body: String,
 633    headers: HeaderMap<HeaderValue>,
 634}
 635
 636/// Represents error responses from Zed's cloud API.
 637///
 638/// Example JSON for an upstream HTTP error:
 639/// ```json
 640/// {
 641///   "code": "upstream_http_error",
 642///   "message": "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout",
 643///   "upstream_status": 503
 644/// }
 645/// ```
 646#[derive(Debug, serde::Deserialize)]
 647struct CloudApiError {
 648    code: String,
 649    message: String,
 650    #[serde(default)]
 651    #[serde(deserialize_with = "deserialize_optional_status_code")]
 652    upstream_status: Option<StatusCode>,
 653    #[serde(default)]
 654    retry_after: Option<f64>,
 655}
 656
 657fn deserialize_optional_status_code<'de, D>(deserializer: D) -> Result<Option<StatusCode>, D::Error>
 658where
 659    D: serde::Deserializer<'de>,
 660{
 661    let opt: Option<u16> = Option::deserialize(deserializer)?;
 662    Ok(opt.and_then(|code| StatusCode::from_u16(code).ok()))
 663}
 664
 665impl From<ApiError> for LanguageModelCompletionError {
 666    fn from(error: ApiError) -> Self {
 667        if let Ok(cloud_error) = serde_json::from_str::<CloudApiError>(&error.body) {
 668            if cloud_error.code.starts_with("upstream_http_") {
 669                let status = if let Some(status) = cloud_error.upstream_status {
 670                    status
 671                } else if cloud_error.code.ends_with("_error") {
 672                    error.status
 673                } else {
 674                    // If there's a status code in the code string (e.g. "upstream_http_429")
 675                    // then use that; otherwise, see if the JSON contains a status code.
 676                    cloud_error
 677                        .code
 678                        .strip_prefix("upstream_http_")
 679                        .and_then(|code_str| code_str.parse::<u16>().ok())
 680                        .and_then(|code| StatusCode::from_u16(code).ok())
 681                        .unwrap_or(error.status)
 682                };
 683
 684                return LanguageModelCompletionError::UpstreamProviderError {
 685                    message: cloud_error.message,
 686                    status,
 687                    retry_after: cloud_error.retry_after.map(Duration::from_secs_f64),
 688                };
 689            }
 690        }
 691
 692        let retry_after = None;
 693        LanguageModelCompletionError::from_http_status(
 694            PROVIDER_NAME,
 695            error.status,
 696            error.body,
 697            retry_after,
 698        )
 699    }
 700}
 701
 702impl LanguageModel for CloudLanguageModel {
 703    fn id(&self) -> LanguageModelId {
 704        self.id.clone()
 705    }
 706
 707    fn name(&self) -> LanguageModelName {
 708        LanguageModelName::from(self.model.display_name.clone())
 709    }
 710
 711    fn provider_id(&self) -> LanguageModelProviderId {
 712        PROVIDER_ID
 713    }
 714
 715    fn provider_name(&self) -> LanguageModelProviderName {
 716        PROVIDER_NAME
 717    }
 718
 719    fn upstream_provider_id(&self) -> LanguageModelProviderId {
 720        use cloud_llm_client::LanguageModelProvider::*;
 721        match self.model.provider {
 722            Anthropic => language_model::ANTHROPIC_PROVIDER_ID,
 723            OpenAi => language_model::OPEN_AI_PROVIDER_ID,
 724            Google => language_model::GOOGLE_PROVIDER_ID,
 725        }
 726    }
 727
 728    fn upstream_provider_name(&self) -> LanguageModelProviderName {
 729        use cloud_llm_client::LanguageModelProvider::*;
 730        match self.model.provider {
 731            Anthropic => language_model::ANTHROPIC_PROVIDER_NAME,
 732            OpenAi => language_model::OPEN_AI_PROVIDER_NAME,
 733            Google => language_model::GOOGLE_PROVIDER_NAME,
 734        }
 735    }
 736
 737    fn supports_tools(&self) -> bool {
 738        self.model.supports_tools
 739    }
 740
 741    fn supports_images(&self) -> bool {
 742        self.model.supports_images
 743    }
 744
 745    fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
 746        match choice {
 747            LanguageModelToolChoice::Auto
 748            | LanguageModelToolChoice::Any
 749            | LanguageModelToolChoice::None => true,
 750        }
 751    }
 752
 753    fn supports_burn_mode(&self) -> bool {
 754        self.model.supports_max_mode
 755    }
 756
 757    fn telemetry_id(&self) -> String {
 758        format!("zed.dev/{}", self.model.id)
 759    }
 760
 761    fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
 762        match self.model.provider {
 763            cloud_llm_client::LanguageModelProvider::Anthropic
 764            | cloud_llm_client::LanguageModelProvider::OpenAi => {
 765                LanguageModelToolSchemaFormat::JsonSchema
 766            }
 767            cloud_llm_client::LanguageModelProvider::Google => {
 768                LanguageModelToolSchemaFormat::JsonSchemaSubset
 769            }
 770        }
 771    }
 772
 773    fn max_token_count(&self) -> u64 {
 774        self.model.max_token_count as u64
 775    }
 776
 777    fn max_token_count_in_burn_mode(&self) -> Option<u64> {
 778        self.model
 779            .max_token_count_in_max_mode
 780            .filter(|_| self.model.supports_max_mode)
 781            .map(|max_token_count| max_token_count as u64)
 782    }
 783
 784    fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
 785        match &self.model.provider {
 786            cloud_llm_client::LanguageModelProvider::Anthropic => {
 787                Some(LanguageModelCacheConfiguration {
 788                    min_total_token: 2_048,
 789                    should_speculate: true,
 790                    max_cache_anchors: 4,
 791                })
 792            }
 793            cloud_llm_client::LanguageModelProvider::OpenAi
 794            | cloud_llm_client::LanguageModelProvider::Google => None,
 795        }
 796    }
 797
 798    fn count_tokens(
 799        &self,
 800        request: LanguageModelRequest,
 801        cx: &App,
 802    ) -> BoxFuture<'static, Result<u64>> {
 803        match self.model.provider {
 804            cloud_llm_client::LanguageModelProvider::Anthropic => {
 805                count_anthropic_tokens(request, cx)
 806            }
 807            cloud_llm_client::LanguageModelProvider::OpenAi => {
 808                let model = match open_ai::Model::from_id(&self.model.id.0) {
 809                    Ok(model) => model,
 810                    Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
 811                };
 812                count_open_ai_tokens(request, model, cx)
 813            }
 814            cloud_llm_client::LanguageModelProvider::Google => {
 815                let client = self.client.clone();
 816                let llm_api_token = self.llm_api_token.clone();
 817                let model_id = self.model.id.to_string();
 818                let generate_content_request =
 819                    into_google(request, model_id.clone(), GoogleModelMode::Default);
 820                async move {
 821                    let http_client = &client.http_client();
 822                    let token = llm_api_token.acquire(&client).await?;
 823
 824                    let request_body = CountTokensBody {
 825                        provider: cloud_llm_client::LanguageModelProvider::Google,
 826                        model: model_id,
 827                        provider_request: serde_json::to_value(&google_ai::CountTokensRequest {
 828                            generate_content_request,
 829                        })?,
 830                    };
 831                    let request = http_client::Request::builder()
 832                        .method(Method::POST)
 833                        .uri(
 834                            http_client
 835                                .build_zed_llm_url("/count_tokens", &[])?
 836                                .as_ref(),
 837                        )
 838                        .header("Content-Type", "application/json")
 839                        .header("Authorization", format!("Bearer {token}"))
 840                        .body(serde_json::to_string(&request_body)?.into())?;
 841                    let mut response = http_client.send(request).await?;
 842                    let status = response.status();
 843                    let headers = response.headers().clone();
 844                    let mut response_body = String::new();
 845                    response
 846                        .body_mut()
 847                        .read_to_string(&mut response_body)
 848                        .await?;
 849
 850                    if status.is_success() {
 851                        let response_body: CountTokensResponse =
 852                            serde_json::from_str(&response_body)?;
 853
 854                        Ok(response_body.tokens as u64)
 855                    } else {
 856                        Err(anyhow!(ApiError {
 857                            status,
 858                            body: response_body,
 859                            headers
 860                        }))
 861                    }
 862                }
 863                .boxed()
 864            }
 865        }
 866    }
 867
 868    fn stream_completion(
 869        &self,
 870        request: LanguageModelRequest,
 871        cx: &AsyncApp,
 872    ) -> BoxFuture<
 873        'static,
 874        Result<
 875            BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
 876            LanguageModelCompletionError,
 877        >,
 878    > {
 879        let thread_id = request.thread_id.clone();
 880        let prompt_id = request.prompt_id.clone();
 881        let intent = request.intent;
 882        let mode = request.mode;
 883        let app_version = cx.update(|cx| AppVersion::global(cx)).ok();
 884        let thinking_allowed = request.thinking_allowed;
 885        match self.model.provider {
 886            cloud_llm_client::LanguageModelProvider::Anthropic => {
 887                let request = into_anthropic(
 888                    request,
 889                    self.model.id.to_string(),
 890                    1.0,
 891                    self.model.max_output_tokens as u64,
 892                    if thinking_allowed && self.model.id.0.ends_with("-thinking") {
 893                        AnthropicModelMode::Thinking {
 894                            budget_tokens: Some(4_096),
 895                        }
 896                    } else {
 897                        AnthropicModelMode::Default
 898                    },
 899                );
 900                let client = self.client.clone();
 901                let llm_api_token = self.llm_api_token.clone();
 902                let future = self.request_limiter.stream(async move {
 903                    let PerformLlmCompletionResponse {
 904                        response,
 905                        usage,
 906                        includes_status_messages,
 907                        tool_use_limit_reached,
 908                    } = Self::perform_llm_completion(
 909                        client.clone(),
 910                        llm_api_token,
 911                        app_version,
 912                        CompletionBody {
 913                            thread_id,
 914                            prompt_id,
 915                            intent,
 916                            mode,
 917                            provider: cloud_llm_client::LanguageModelProvider::Anthropic,
 918                            model: request.model.clone(),
 919                            provider_request: serde_json::to_value(&request)
 920                                .map_err(|e| anyhow!(e))?,
 921                        },
 922                    )
 923                    .await
 924                    .map_err(|err| match err.downcast::<ApiError>() {
 925                        Ok(api_err) => anyhow!(LanguageModelCompletionError::from(api_err)),
 926                        Err(err) => anyhow!(err),
 927                    })?;
 928
 929                    let mut mapper = AnthropicEventMapper::new();
 930                    Ok(map_cloud_completion_events(
 931                        Box::pin(
 932                            response_lines(response, includes_status_messages)
 933                                .chain(usage_updated_event(usage))
 934                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
 935                        ),
 936                        move |event| mapper.map_event(event),
 937                    ))
 938                });
 939                async move { Ok(future.await?.boxed()) }.boxed()
 940            }
 941            cloud_llm_client::LanguageModelProvider::OpenAi => {
 942                let client = self.client.clone();
 943                let model = match open_ai::Model::from_id(&self.model.id.0) {
 944                    Ok(model) => model,
 945                    Err(err) => return async move { Err(anyhow!(err).into()) }.boxed(),
 946                };
 947                let request = into_open_ai(
 948                    request,
 949                    model.id(),
 950                    model.supports_parallel_tool_calls(),
 951                    None,
 952                );
 953                let llm_api_token = self.llm_api_token.clone();
 954                let future = self.request_limiter.stream(async move {
 955                    let PerformLlmCompletionResponse {
 956                        response,
 957                        usage,
 958                        includes_status_messages,
 959                        tool_use_limit_reached,
 960                    } = Self::perform_llm_completion(
 961                        client.clone(),
 962                        llm_api_token,
 963                        app_version,
 964                        CompletionBody {
 965                            thread_id,
 966                            prompt_id,
 967                            intent,
 968                            mode,
 969                            provider: cloud_llm_client::LanguageModelProvider::OpenAi,
 970                            model: request.model.clone(),
 971                            provider_request: serde_json::to_value(&request)
 972                                .map_err(|e| anyhow!(e))?,
 973                        },
 974                    )
 975                    .await?;
 976
 977                    let mut mapper = OpenAiEventMapper::new();
 978                    Ok(map_cloud_completion_events(
 979                        Box::pin(
 980                            response_lines(response, includes_status_messages)
 981                                .chain(usage_updated_event(usage))
 982                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
 983                        ),
 984                        move |event| mapper.map_event(event),
 985                    ))
 986                });
 987                async move { Ok(future.await?.boxed()) }.boxed()
 988            }
 989            cloud_llm_client::LanguageModelProvider::Google => {
 990                let client = self.client.clone();
 991                let request =
 992                    into_google(request, self.model.id.to_string(), GoogleModelMode::Default);
 993                let llm_api_token = self.llm_api_token.clone();
 994                let future = self.request_limiter.stream(async move {
 995                    let PerformLlmCompletionResponse {
 996                        response,
 997                        usage,
 998                        includes_status_messages,
 999                        tool_use_limit_reached,
1000                    } = Self::perform_llm_completion(
1001                        client.clone(),
1002                        llm_api_token,
1003                        app_version,
1004                        CompletionBody {
1005                            thread_id,
1006                            prompt_id,
1007                            intent,
1008                            mode,
1009                            provider: cloud_llm_client::LanguageModelProvider::Google,
1010                            model: request.model.model_id.clone(),
1011                            provider_request: serde_json::to_value(&request)
1012                                .map_err(|e| anyhow!(e))?,
1013                        },
1014                    )
1015                    .await?;
1016
1017                    let mut mapper = GoogleEventMapper::new();
1018                    Ok(map_cloud_completion_events(
1019                        Box::pin(
1020                            response_lines(response, includes_status_messages)
1021                                .chain(usage_updated_event(usage))
1022                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
1023                        ),
1024                        move |event| mapper.map_event(event),
1025                    ))
1026                });
1027                async move { Ok(future.await?.boxed()) }.boxed()
1028            }
1029        }
1030    }
1031}
1032
1033fn map_cloud_completion_events<T, F>(
1034    stream: Pin<Box<dyn Stream<Item = Result<CompletionEvent<T>>> + Send>>,
1035    mut map_callback: F,
1036) -> BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
1037where
1038    T: DeserializeOwned + 'static,
1039    F: FnMut(T) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
1040        + Send
1041        + 'static,
1042{
1043    stream
1044        .flat_map(move |event| {
1045            futures::stream::iter(match event {
1046                Err(error) => {
1047                    vec![Err(LanguageModelCompletionError::from(error))]
1048                }
1049                Ok(CompletionEvent::Status(event)) => {
1050                    vec![Ok(LanguageModelCompletionEvent::StatusUpdate(event))]
1051                }
1052                Ok(CompletionEvent::Event(event)) => map_callback(event),
1053            })
1054        })
1055        .boxed()
1056}
1057
1058fn usage_updated_event<T>(
1059    usage: Option<ModelRequestUsage>,
1060) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1061    futures::stream::iter(usage.map(|usage| {
1062        Ok(CompletionEvent::Status(
1063            CompletionRequestStatus::UsageUpdated {
1064                amount: usage.amount as usize,
1065                limit: usage.limit,
1066            },
1067        ))
1068    }))
1069}
1070
1071fn tool_use_limit_reached_event<T>(
1072    tool_use_limit_reached: bool,
1073) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1074    futures::stream::iter(tool_use_limit_reached.then(|| {
1075        Ok(CompletionEvent::Status(
1076            CompletionRequestStatus::ToolUseLimitReached,
1077        ))
1078    }))
1079}
1080
1081fn response_lines<T: DeserializeOwned>(
1082    response: Response<AsyncBody>,
1083    includes_status_messages: bool,
1084) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1085    futures::stream::try_unfold(
1086        (String::new(), BufReader::new(response.into_body())),
1087        move |(mut line, mut body)| async move {
1088            match body.read_line(&mut line).await {
1089                Ok(0) => Ok(None),
1090                Ok(_) => {
1091                    let event = if includes_status_messages {
1092                        serde_json::from_str::<CompletionEvent<T>>(&line)?
1093                    } else {
1094                        CompletionEvent::Event(serde_json::from_str::<T>(&line)?)
1095                    };
1096
1097                    line.clear();
1098                    Ok(Some((event, (line, body))))
1099                }
1100                Err(e) => Err(e.into()),
1101            }
1102        },
1103    )
1104}
1105
1106#[derive(IntoElement, RegisterComponent)]
1107struct ZedAiConfiguration {
1108    is_connected: bool,
1109    plan: Option<Plan>,
1110    subscription_period: Option<(DateTime<Utc>, DateTime<Utc>)>,
1111    eligible_for_trial: bool,
1112    has_accepted_terms_of_service: bool,
1113    account_too_young: bool,
1114    accept_terms_of_service_in_progress: bool,
1115    accept_terms_of_service_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1116    sign_in_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1117}
1118
1119impl RenderOnce for ZedAiConfiguration {
1120    fn render(self, _window: &mut Window, _cx: &mut App) -> impl IntoElement {
1121        let young_account_banner = YoungAccountBanner;
1122
1123        let is_pro = self.plan == Some(Plan::ZedPro);
1124        let subscription_text = match (self.plan, self.subscription_period) {
1125            (Some(Plan::ZedPro), Some(_)) => {
1126                "You have access to Zed's hosted models through your Pro subscription."
1127            }
1128            (Some(Plan::ZedProTrial), Some(_)) => {
1129                "You have access to Zed's hosted models through your Pro trial."
1130            }
1131            (Some(Plan::ZedFree), Some(_)) => {
1132                "You have basic access to Zed's hosted models through the Free plan."
1133            }
1134            _ => {
1135                if self.eligible_for_trial {
1136                    "Subscribe for access to Zed's hosted models. Start with a 14 day free trial."
1137                } else {
1138                    "Subscribe for access to Zed's hosted models."
1139                }
1140            }
1141        };
1142
1143        let manage_subscription_buttons = if is_pro {
1144            Button::new("manage_settings", "Manage Subscription")
1145                .full_width()
1146                .style(ButtonStyle::Tinted(TintColor::Accent))
1147                .on_click(|_, _, cx| cx.open_url(&zed_urls::account_url(cx)))
1148                .into_any_element()
1149        } else if self.plan.is_none() || self.eligible_for_trial {
1150            Button::new("start_trial", "Start 14-day Free Pro Trial")
1151                .full_width()
1152                .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1153                .on_click(|_, _, cx| cx.open_url(&zed_urls::start_trial_url(cx)))
1154                .into_any_element()
1155        } else {
1156            Button::new("upgrade", "Upgrade to Pro")
1157                .full_width()
1158                .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1159                .on_click(|_, _, cx| cx.open_url(&zed_urls::upgrade_to_zed_pro_url(cx)))
1160                .into_any_element()
1161        };
1162
1163        if !self.is_connected {
1164            return v_flex()
1165                .gap_2()
1166                .child(Label::new("Sign in to have access to Zed's complete agentic experience with hosted models."))
1167                .child(
1168                    Button::new("sign_in", "Sign In to use Zed AI")
1169                        .icon_color(Color::Muted)
1170                        .icon(IconName::Github)
1171                        .icon_size(IconSize::Small)
1172                        .icon_position(IconPosition::Start)
1173                        .full_width()
1174                        .on_click({
1175                            let callback = self.sign_in_callback.clone();
1176                            move |_, window, cx| (callback)(window, cx)
1177                        }),
1178                );
1179        }
1180
1181        v_flex()
1182            .gap_2()
1183            .w_full()
1184            .when(!self.has_accepted_terms_of_service, |this| {
1185                this.child(render_accept_terms(
1186                    LanguageModelProviderTosView::Configuration,
1187                    self.accept_terms_of_service_in_progress,
1188                    {
1189                        let callback = self.accept_terms_of_service_callback.clone();
1190                        move |window, cx| (callback)(window, cx)
1191                    },
1192                ))
1193            })
1194            .map(|this| {
1195                if self.has_accepted_terms_of_service && self.account_too_young {
1196                    this.child(young_account_banner).child(
1197                        Button::new("upgrade", "Upgrade to Pro")
1198                            .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1199                            .full_width()
1200                            .on_click(|_, _, cx| {
1201                                cx.open_url(&zed_urls::upgrade_to_zed_pro_url(cx))
1202                            }),
1203                    )
1204                } else if self.has_accepted_terms_of_service {
1205                    this.text_sm()
1206                        .child(subscription_text)
1207                        .child(manage_subscription_buttons)
1208                } else {
1209                    this
1210                }
1211            })
1212            .when(self.has_accepted_terms_of_service, |this| this)
1213    }
1214}
1215
1216struct ConfigurationView {
1217    state: Entity<State>,
1218    accept_terms_of_service_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1219    sign_in_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1220}
1221
1222impl ConfigurationView {
1223    fn new(state: Entity<State>) -> Self {
1224        let accept_terms_of_service_callback = Arc::new({
1225            let state = state.clone();
1226            move |_window: &mut Window, cx: &mut App| {
1227                state.update(cx, |state, cx| {
1228                    state.accept_terms_of_service(cx);
1229                });
1230            }
1231        });
1232
1233        let sign_in_callback = Arc::new({
1234            let state = state.clone();
1235            move |_window: &mut Window, cx: &mut App| {
1236                state.update(cx, |state, cx| {
1237                    state.authenticate(cx).detach_and_log_err(cx);
1238                });
1239            }
1240        });
1241
1242        Self {
1243            state,
1244            accept_terms_of_service_callback,
1245            sign_in_callback,
1246        }
1247    }
1248}
1249
1250impl Render for ConfigurationView {
1251    fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
1252        let state = self.state.read(cx);
1253        let user_store = state.user_store.read(cx);
1254
1255        ZedAiConfiguration {
1256            is_connected: !state.is_signed_out(cx),
1257            plan: user_store.plan(),
1258            subscription_period: user_store.subscription_period(),
1259            eligible_for_trial: user_store.trial_started_at().is_none(),
1260            has_accepted_terms_of_service: state.has_accepted_terms_of_service(cx),
1261            account_too_young: user_store.account_too_young(),
1262            accept_terms_of_service_in_progress: state.accept_terms_of_service_task.is_some(),
1263            accept_terms_of_service_callback: self.accept_terms_of_service_callback.clone(),
1264            sign_in_callback: self.sign_in_callback.clone(),
1265        }
1266    }
1267}
1268
1269impl Component for ZedAiConfiguration {
1270    fn name() -> &'static str {
1271        "AI Configuration Content"
1272    }
1273
1274    fn sort_name() -> &'static str {
1275        "AI Configuration Content"
1276    }
1277
1278    fn scope() -> ComponentScope {
1279        ComponentScope::Onboarding
1280    }
1281
1282    fn preview(_window: &mut Window, _cx: &mut App) -> Option<AnyElement> {
1283        fn configuration(
1284            is_connected: bool,
1285            plan: Option<Plan>,
1286            eligible_for_trial: bool,
1287            account_too_young: bool,
1288            has_accepted_terms_of_service: bool,
1289        ) -> AnyElement {
1290            ZedAiConfiguration {
1291                is_connected,
1292                plan,
1293                subscription_period: plan
1294                    .is_some()
1295                    .then(|| (Utc::now(), Utc::now() + chrono::Duration::days(7))),
1296                eligible_for_trial,
1297                has_accepted_terms_of_service,
1298                account_too_young,
1299                accept_terms_of_service_in_progress: false,
1300                accept_terms_of_service_callback: Arc::new(|_, _| {}),
1301                sign_in_callback: Arc::new(|_, _| {}),
1302            }
1303            .into_any_element()
1304        }
1305
1306        Some(
1307            v_flex()
1308                .p_4()
1309                .gap_4()
1310                .children(vec![
1311                    single_example(
1312                        "Not connected",
1313                        configuration(false, None, false, false, true),
1314                    ),
1315                    single_example(
1316                        "Accept Terms of Service",
1317                        configuration(true, None, true, false, false),
1318                    ),
1319                    single_example(
1320                        "No Plan - Not eligible for trial",
1321                        configuration(true, None, false, false, true),
1322                    ),
1323                    single_example(
1324                        "No Plan - Eligible for trial",
1325                        configuration(true, None, true, false, true),
1326                    ),
1327                    single_example(
1328                        "Free Plan",
1329                        configuration(true, Some(Plan::ZedFree), true, false, true),
1330                    ),
1331                    single_example(
1332                        "Zed Pro Trial Plan",
1333                        configuration(true, Some(Plan::ZedProTrial), true, false, true),
1334                    ),
1335                    single_example(
1336                        "Zed Pro Plan",
1337                        configuration(true, Some(Plan::ZedPro), true, false, true),
1338                    ),
1339                ])
1340                .into_any_element(),
1341        )
1342    }
1343}
1344
1345#[cfg(test)]
1346mod tests {
1347    use super::*;
1348    use http_client::http::{HeaderMap, StatusCode};
1349    use language_model::LanguageModelCompletionError;
1350
1351    #[test]
1352    fn test_api_error_conversion_with_upstream_http_error() {
1353        // upstream_http_error with 503 status should become ServerOverloaded
1354        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}"#;
1355
1356        let api_error = ApiError {
1357            status: StatusCode::INTERNAL_SERVER_ERROR,
1358            body: error_body.to_string(),
1359            headers: HeaderMap::new(),
1360        };
1361
1362        let completion_error: LanguageModelCompletionError = api_error.into();
1363
1364        match completion_error {
1365            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1366                assert_eq!(
1367                    message,
1368                    "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout"
1369                );
1370            }
1371            _ => panic!(
1372                "Expected UpstreamProviderError for upstream 503, got: {:?}",
1373                completion_error
1374            ),
1375        }
1376
1377        // upstream_http_error with 500 status should become ApiInternalServerError
1378        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the OpenAI API: internal server error","upstream_status":500}"#;
1379
1380        let api_error = ApiError {
1381            status: StatusCode::INTERNAL_SERVER_ERROR,
1382            body: error_body.to_string(),
1383            headers: HeaderMap::new(),
1384        };
1385
1386        let completion_error: LanguageModelCompletionError = api_error.into();
1387
1388        match completion_error {
1389            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1390                assert_eq!(
1391                    message,
1392                    "Received an error from the OpenAI API: internal server error"
1393                );
1394            }
1395            _ => panic!(
1396                "Expected UpstreamProviderError for upstream 500, got: {:?}",
1397                completion_error
1398            ),
1399        }
1400
1401        // upstream_http_error with 429 status should become RateLimitExceeded
1402        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the Google API: rate limit exceeded","upstream_status":429}"#;
1403
1404        let api_error = ApiError {
1405            status: StatusCode::INTERNAL_SERVER_ERROR,
1406            body: error_body.to_string(),
1407            headers: HeaderMap::new(),
1408        };
1409
1410        let completion_error: LanguageModelCompletionError = api_error.into();
1411
1412        match completion_error {
1413            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1414                assert_eq!(
1415                    message,
1416                    "Received an error from the Google API: rate limit exceeded"
1417                );
1418            }
1419            _ => panic!(
1420                "Expected UpstreamProviderError for upstream 429, got: {:?}",
1421                completion_error
1422            ),
1423        }
1424
1425        // Regular 500 error without upstream_http_error should remain ApiInternalServerError for Zed
1426        let error_body = "Regular internal server error";
1427
1428        let api_error = ApiError {
1429            status: StatusCode::INTERNAL_SERVER_ERROR,
1430            body: error_body.to_string(),
1431            headers: HeaderMap::new(),
1432        };
1433
1434        let completion_error: LanguageModelCompletionError = api_error.into();
1435
1436        match completion_error {
1437            LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
1438                assert_eq!(provider, PROVIDER_NAME);
1439                assert_eq!(message, "Regular internal server error");
1440            }
1441            _ => panic!(
1442                "Expected ApiInternalServerError for regular 500, got: {:?}",
1443                completion_error
1444            ),
1445        }
1446
1447        // upstream_http_429 format should be converted to UpstreamProviderError
1448        let error_body = r#"{"code":"upstream_http_429","message":"Upstream Anthropic rate limit exceeded.","retry_after":30.5}"#;
1449
1450        let api_error = ApiError {
1451            status: StatusCode::INTERNAL_SERVER_ERROR,
1452            body: error_body.to_string(),
1453            headers: HeaderMap::new(),
1454        };
1455
1456        let completion_error: LanguageModelCompletionError = api_error.into();
1457
1458        match completion_error {
1459            LanguageModelCompletionError::UpstreamProviderError {
1460                message,
1461                status,
1462                retry_after,
1463            } => {
1464                assert_eq!(message, "Upstream Anthropic rate limit exceeded.");
1465                assert_eq!(status, StatusCode::TOO_MANY_REQUESTS);
1466                assert_eq!(retry_after, Some(Duration::from_secs_f64(30.5)));
1467            }
1468            _ => panic!(
1469                "Expected UpstreamProviderError for upstream_http_429, got: {:?}",
1470                completion_error
1471            ),
1472        }
1473
1474        // Invalid JSON in error body should fall back to regular error handling
1475        let error_body = "Not JSON at all";
1476
1477        let api_error = ApiError {
1478            status: StatusCode::INTERNAL_SERVER_ERROR,
1479            body: error_body.to_string(),
1480            headers: HeaderMap::new(),
1481        };
1482
1483        let completion_error: LanguageModelCompletionError = api_error.into();
1484
1485        match completion_error {
1486            LanguageModelCompletionError::ApiInternalServerError { provider, .. } => {
1487                assert_eq!(provider, PROVIDER_NAME);
1488            }
1489            _ => panic!(
1490                "Expected ApiInternalServerError for invalid JSON, got: {:?}",
1491                completion_error
1492            ),
1493        }
1494    }
1495}