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