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(
 414                view,
 415                state.accept_terms_of_service_task.is_some(),
 416                {
 417                    let state = self.state.clone();
 418                    move |_window, cx| {
 419                        state.update(cx, |state, cx| state.accept_terms_of_service(cx));
 420                    }
 421                },
 422                cx,
 423            )
 424            .into_any_element(),
 425        )
 426    }
 427
 428    fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
 429        Task::ready(Ok(()))
 430    }
 431}
 432
 433fn render_accept_terms(
 434    view_kind: LanguageModelProviderTosView,
 435    accept_terms_of_service_in_progress: bool,
 436    accept_terms_callback: impl Fn(&mut Window, &mut App) + 'static,
 437    app: &App,
 438) -> impl IntoElement {
 439    let thread_fresh_start = matches!(view_kind, LanguageModelProviderTosView::ThreadFreshStart);
 440    let thread_empty_state = matches!(view_kind, LanguageModelProviderTosView::ThreadEmptyState);
 441
 442    let terms_button = Button::new("terms_of_service", "Terms of Service", app)
 443        .style(ButtonStyle::Subtle)
 444        .icon(IconName::ArrowUpRight)
 445        .icon_color(Color::Muted)
 446        .icon_size(IconSize::Small)
 447        .when(thread_empty_state, |this| this.label_size(LabelSize::Small))
 448        .on_click(move |_, _window, cx| cx.open_url("https://zed.dev/terms-of-service"));
 449
 450    let button_container = h_flex().child(
 451        Button::new("accept_terms", "I accept the Terms of Service", app)
 452            .when(!thread_empty_state, |this| {
 453                this.full_width()
 454                    .style(ButtonStyle::Tinted(TintColor::Accent))
 455                    .icon(IconName::Check)
 456                    .icon_position(IconPosition::Start)
 457                    .icon_size(IconSize::Small)
 458            })
 459            .when(thread_empty_state, |this| {
 460                this.style(ButtonStyle::Tinted(TintColor::Warning))
 461                    .label_size(LabelSize::Small)
 462            })
 463            .disabled(accept_terms_of_service_in_progress)
 464            .on_click(move |_, window, cx| (accept_terms_callback)(window, cx)),
 465    );
 466
 467    if thread_empty_state {
 468        h_flex()
 469            .w_full()
 470            .flex_wrap()
 471            .justify_between()
 472            .child(
 473                h_flex()
 474                    .child(
 475                        Label::new("To start using Zed AI, please read and accept the")
 476                            .size(LabelSize::Small),
 477                    )
 478                    .child(terms_button),
 479            )
 480            .child(button_container)
 481    } else {
 482        v_flex()
 483            .w_full()
 484            .gap_2()
 485            .child(
 486                h_flex()
 487                    .flex_wrap()
 488                    .when(thread_fresh_start, |this| this.justify_center())
 489                    .child(Label::new(
 490                        "To start using Zed AI, please read and accept the",
 491                    ))
 492                    .child(terms_button),
 493            )
 494            .child({
 495                match view_kind {
 496                    LanguageModelProviderTosView::TextThreadPopup => {
 497                        button_container.w_full().justify_end()
 498                    }
 499                    LanguageModelProviderTosView::Configuration => {
 500                        button_container.w_full().justify_start()
 501                    }
 502                    LanguageModelProviderTosView::ThreadFreshStart => {
 503                        button_container.w_full().justify_center()
 504                    }
 505                    LanguageModelProviderTosView::ThreadEmptyState => div().w_0(),
 506                }
 507            })
 508    }
 509}
 510
 511pub struct CloudLanguageModel {
 512    id: LanguageModelId,
 513    model: Arc<cloud_llm_client::LanguageModel>,
 514    llm_api_token: LlmApiToken,
 515    client: Arc<Client>,
 516    request_limiter: RateLimiter,
 517}
 518
 519struct PerformLlmCompletionResponse {
 520    response: Response<AsyncBody>,
 521    usage: Option<ModelRequestUsage>,
 522    tool_use_limit_reached: bool,
 523    includes_status_messages: bool,
 524}
 525
 526impl CloudLanguageModel {
 527    async fn perform_llm_completion(
 528        client: Arc<Client>,
 529        llm_api_token: LlmApiToken,
 530        app_version: Option<SemanticVersion>,
 531        body: CompletionBody,
 532    ) -> Result<PerformLlmCompletionResponse> {
 533        let http_client = &client.http_client();
 534
 535        let mut token = llm_api_token.acquire(&client).await?;
 536        let mut refreshed_token = false;
 537
 538        loop {
 539            let request_builder = http_client::Request::builder()
 540                .method(Method::POST)
 541                .uri(http_client.build_zed_llm_url("/completions", &[])?.as_ref());
 542            let request_builder = if let Some(app_version) = app_version {
 543                request_builder.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
 544            } else {
 545                request_builder
 546            };
 547
 548            let request = request_builder
 549                .header("Content-Type", "application/json")
 550                .header("Authorization", format!("Bearer {token}"))
 551                .header(CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, "true")
 552                .body(serde_json::to_string(&body)?.into())?;
 553            let mut response = http_client.send(request).await?;
 554            let status = response.status();
 555            if status.is_success() {
 556                let includes_status_messages = response
 557                    .headers()
 558                    .get(SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME)
 559                    .is_some();
 560
 561                let tool_use_limit_reached = response
 562                    .headers()
 563                    .get(TOOL_USE_LIMIT_REACHED_HEADER_NAME)
 564                    .is_some();
 565
 566                let usage = if includes_status_messages {
 567                    None
 568                } else {
 569                    ModelRequestUsage::from_headers(response.headers()).ok()
 570                };
 571
 572                return Ok(PerformLlmCompletionResponse {
 573                    response,
 574                    usage,
 575                    includes_status_messages,
 576                    tool_use_limit_reached,
 577                });
 578            }
 579
 580            if !refreshed_token
 581                && response
 582                    .headers()
 583                    .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
 584                    .is_some()
 585            {
 586                token = llm_api_token.refresh(&client).await?;
 587                refreshed_token = true;
 588                continue;
 589            }
 590
 591            if status == StatusCode::FORBIDDEN
 592                && response
 593                    .headers()
 594                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 595                    .is_some()
 596            {
 597                if let Some(MODEL_REQUESTS_RESOURCE_HEADER_VALUE) = response
 598                    .headers()
 599                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 600                    .and_then(|resource| resource.to_str().ok())
 601                {
 602                    if let Some(plan) = response
 603                        .headers()
 604                        .get(CURRENT_PLAN_HEADER_NAME)
 605                        .and_then(|plan| plan.to_str().ok())
 606                        .and_then(|plan| cloud_llm_client::Plan::from_str(plan).ok())
 607                    {
 608                        return Err(anyhow!(ModelRequestLimitReachedError { plan }));
 609                    }
 610                }
 611            } else if status == StatusCode::PAYMENT_REQUIRED {
 612                return Err(anyhow!(PaymentRequiredError));
 613            }
 614
 615            let mut body = String::new();
 616            let headers = response.headers().clone();
 617            response.body_mut().read_to_string(&mut body).await?;
 618            return Err(anyhow!(ApiError {
 619                status,
 620                body,
 621                headers
 622            }));
 623        }
 624    }
 625}
 626
 627#[derive(Debug, Error)]
 628#[error("cloud language model request failed with status {status}: {body}")]
 629struct ApiError {
 630    status: StatusCode,
 631    body: String,
 632    headers: HeaderMap<HeaderValue>,
 633}
 634
 635/// Represents error responses from Zed's cloud API.
 636///
 637/// Example JSON for an upstream HTTP error:
 638/// ```json
 639/// {
 640///   "code": "upstream_http_error",
 641///   "message": "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout",
 642///   "upstream_status": 503
 643/// }
 644/// ```
 645#[derive(Debug, serde::Deserialize)]
 646struct CloudApiError {
 647    code: String,
 648    message: String,
 649    #[serde(default)]
 650    #[serde(deserialize_with = "deserialize_optional_status_code")]
 651    upstream_status: Option<StatusCode>,
 652    #[serde(default)]
 653    retry_after: Option<f64>,
 654}
 655
 656fn deserialize_optional_status_code<'de, D>(deserializer: D) -> Result<Option<StatusCode>, D::Error>
 657where
 658    D: serde::Deserializer<'de>,
 659{
 660    let opt: Option<u16> = Option::deserialize(deserializer)?;
 661    Ok(opt.and_then(|code| StatusCode::from_u16(code).ok()))
 662}
 663
 664impl From<ApiError> for LanguageModelCompletionError {
 665    fn from(error: ApiError) -> Self {
 666        if let Ok(cloud_error) = serde_json::from_str::<CloudApiError>(&error.body) {
 667            if cloud_error.code.starts_with("upstream_http_") {
 668                let status = if let Some(status) = cloud_error.upstream_status {
 669                    status
 670                } else if cloud_error.code.ends_with("_error") {
 671                    error.status
 672                } else {
 673                    // If there's a status code in the code string (e.g. "upstream_http_429")
 674                    // then use that; otherwise, see if the JSON contains a status code.
 675                    cloud_error
 676                        .code
 677                        .strip_prefix("upstream_http_")
 678                        .and_then(|code_str| code_str.parse::<u16>().ok())
 679                        .and_then(|code| StatusCode::from_u16(code).ok())
 680                        .unwrap_or(error.status)
 681                };
 682
 683                return LanguageModelCompletionError::UpstreamProviderError {
 684                    message: cloud_error.message,
 685                    status,
 686                    retry_after: cloud_error.retry_after.map(Duration::from_secs_f64),
 687                };
 688            }
 689        }
 690
 691        let retry_after = None;
 692        LanguageModelCompletionError::from_http_status(
 693            PROVIDER_NAME,
 694            error.status,
 695            error.body,
 696            retry_after,
 697        )
 698    }
 699}
 700
 701impl LanguageModel for CloudLanguageModel {
 702    fn id(&self) -> LanguageModelId {
 703        self.id.clone()
 704    }
 705
 706    fn name(&self) -> LanguageModelName {
 707        LanguageModelName::from(self.model.display_name.clone())
 708    }
 709
 710    fn provider_id(&self) -> LanguageModelProviderId {
 711        PROVIDER_ID
 712    }
 713
 714    fn provider_name(&self) -> LanguageModelProviderName {
 715        PROVIDER_NAME
 716    }
 717
 718    fn upstream_provider_id(&self) -> LanguageModelProviderId {
 719        use cloud_llm_client::LanguageModelProvider::*;
 720        match self.model.provider {
 721            Anthropic => language_model::ANTHROPIC_PROVIDER_ID,
 722            OpenAi => language_model::OPEN_AI_PROVIDER_ID,
 723            Google => language_model::GOOGLE_PROVIDER_ID,
 724        }
 725    }
 726
 727    fn upstream_provider_name(&self) -> LanguageModelProviderName {
 728        use cloud_llm_client::LanguageModelProvider::*;
 729        match self.model.provider {
 730            Anthropic => language_model::ANTHROPIC_PROVIDER_NAME,
 731            OpenAi => language_model::OPEN_AI_PROVIDER_NAME,
 732            Google => language_model::GOOGLE_PROVIDER_NAME,
 733        }
 734    }
 735
 736    fn supports_tools(&self) -> bool {
 737        self.model.supports_tools
 738    }
 739
 740    fn supports_images(&self) -> bool {
 741        self.model.supports_images
 742    }
 743
 744    fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
 745        match choice {
 746            LanguageModelToolChoice::Auto
 747            | LanguageModelToolChoice::Any
 748            | LanguageModelToolChoice::None => true,
 749        }
 750    }
 751
 752    fn supports_burn_mode(&self) -> bool {
 753        self.model.supports_max_mode
 754    }
 755
 756    fn telemetry_id(&self) -> String {
 757        format!("zed.dev/{}", self.model.id)
 758    }
 759
 760    fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
 761        match self.model.provider {
 762            cloud_llm_client::LanguageModelProvider::Anthropic
 763            | cloud_llm_client::LanguageModelProvider::OpenAi => {
 764                LanguageModelToolSchemaFormat::JsonSchema
 765            }
 766            cloud_llm_client::LanguageModelProvider::Google => {
 767                LanguageModelToolSchemaFormat::JsonSchemaSubset
 768            }
 769        }
 770    }
 771
 772    fn max_token_count(&self) -> u64 {
 773        self.model.max_token_count as u64
 774    }
 775
 776    fn max_token_count_in_burn_mode(&self) -> Option<u64> {
 777        self.model
 778            .max_token_count_in_max_mode
 779            .filter(|_| self.model.supports_max_mode)
 780            .map(|max_token_count| max_token_count as u64)
 781    }
 782
 783    fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
 784        match &self.model.provider {
 785            cloud_llm_client::LanguageModelProvider::Anthropic => {
 786                Some(LanguageModelCacheConfiguration {
 787                    min_total_token: 2_048,
 788                    should_speculate: true,
 789                    max_cache_anchors: 4,
 790                })
 791            }
 792            cloud_llm_client::LanguageModelProvider::OpenAi
 793            | cloud_llm_client::LanguageModelProvider::Google => None,
 794        }
 795    }
 796
 797    fn count_tokens(
 798        &self,
 799        request: LanguageModelRequest,
 800        cx: &App,
 801    ) -> BoxFuture<'static, Result<u64>> {
 802        match self.model.provider {
 803            cloud_llm_client::LanguageModelProvider::Anthropic => {
 804                count_anthropic_tokens(request, cx)
 805            }
 806            cloud_llm_client::LanguageModelProvider::OpenAi => {
 807                let model = match open_ai::Model::from_id(&self.model.id.0) {
 808                    Ok(model) => model,
 809                    Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
 810                };
 811                count_open_ai_tokens(request, model, cx)
 812            }
 813            cloud_llm_client::LanguageModelProvider::Google => {
 814                let client = self.client.clone();
 815                let llm_api_token = self.llm_api_token.clone();
 816                let model_id = self.model.id.to_string();
 817                let generate_content_request =
 818                    into_google(request, model_id.clone(), GoogleModelMode::Default);
 819                async move {
 820                    let http_client = &client.http_client();
 821                    let token = llm_api_token.acquire(&client).await?;
 822
 823                    let request_body = CountTokensBody {
 824                        provider: cloud_llm_client::LanguageModelProvider::Google,
 825                        model: model_id,
 826                        provider_request: serde_json::to_value(&google_ai::CountTokensRequest {
 827                            generate_content_request,
 828                        })?,
 829                    };
 830                    let request = http_client::Request::builder()
 831                        .method(Method::POST)
 832                        .uri(
 833                            http_client
 834                                .build_zed_llm_url("/count_tokens", &[])?
 835                                .as_ref(),
 836                        )
 837                        .header("Content-Type", "application/json")
 838                        .header("Authorization", format!("Bearer {token}"))
 839                        .body(serde_json::to_string(&request_body)?.into())?;
 840                    let mut response = http_client.send(request).await?;
 841                    let status = response.status();
 842                    let headers = response.headers().clone();
 843                    let mut response_body = String::new();
 844                    response
 845                        .body_mut()
 846                        .read_to_string(&mut response_body)
 847                        .await?;
 848
 849                    if status.is_success() {
 850                        let response_body: CountTokensResponse =
 851                            serde_json::from_str(&response_body)?;
 852
 853                        Ok(response_body.tokens as u64)
 854                    } else {
 855                        Err(anyhow!(ApiError {
 856                            status,
 857                            body: response_body,
 858                            headers
 859                        }))
 860                    }
 861                }
 862                .boxed()
 863            }
 864        }
 865    }
 866
 867    fn stream_completion(
 868        &self,
 869        request: LanguageModelRequest,
 870        cx: &AsyncApp,
 871    ) -> BoxFuture<
 872        'static,
 873        Result<
 874            BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
 875            LanguageModelCompletionError,
 876        >,
 877    > {
 878        let thread_id = request.thread_id.clone();
 879        let prompt_id = request.prompt_id.clone();
 880        let intent = request.intent;
 881        let mode = request.mode;
 882        let app_version = cx.update(|cx| AppVersion::global(cx)).ok();
 883        let thinking_allowed = request.thinking_allowed;
 884        match self.model.provider {
 885            cloud_llm_client::LanguageModelProvider::Anthropic => {
 886                let request = into_anthropic(
 887                    request,
 888                    self.model.id.to_string(),
 889                    1.0,
 890                    self.model.max_output_tokens as u64,
 891                    if thinking_allowed && self.model.id.0.ends_with("-thinking") {
 892                        AnthropicModelMode::Thinking {
 893                            budget_tokens: Some(4_096),
 894                        }
 895                    } else {
 896                        AnthropicModelMode::Default
 897                    },
 898                );
 899                let client = self.client.clone();
 900                let llm_api_token = self.llm_api_token.clone();
 901                let future = self.request_limiter.stream(async move {
 902                    let PerformLlmCompletionResponse {
 903                        response,
 904                        usage,
 905                        includes_status_messages,
 906                        tool_use_limit_reached,
 907                    } = Self::perform_llm_completion(
 908                        client.clone(),
 909                        llm_api_token,
 910                        app_version,
 911                        CompletionBody {
 912                            thread_id,
 913                            prompt_id,
 914                            intent,
 915                            mode,
 916                            provider: cloud_llm_client::LanguageModelProvider::Anthropic,
 917                            model: request.model.clone(),
 918                            provider_request: serde_json::to_value(&request)
 919                                .map_err(|e| anyhow!(e))?,
 920                        },
 921                    )
 922                    .await
 923                    .map_err(|err| match err.downcast::<ApiError>() {
 924                        Ok(api_err) => anyhow!(LanguageModelCompletionError::from(api_err)),
 925                        Err(err) => anyhow!(err),
 926                    })?;
 927
 928                    let mut mapper = AnthropicEventMapper::new();
 929                    Ok(map_cloud_completion_events(
 930                        Box::pin(
 931                            response_lines(response, includes_status_messages)
 932                                .chain(usage_updated_event(usage))
 933                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
 934                        ),
 935                        move |event| mapper.map_event(event),
 936                    ))
 937                });
 938                async move { Ok(future.await?.boxed()) }.boxed()
 939            }
 940            cloud_llm_client::LanguageModelProvider::OpenAi => {
 941                let client = self.client.clone();
 942                let model = match open_ai::Model::from_id(&self.model.id.0) {
 943                    Ok(model) => model,
 944                    Err(err) => return async move { Err(anyhow!(err).into()) }.boxed(),
 945                };
 946                let request = into_open_ai(
 947                    request,
 948                    model.id(),
 949                    model.supports_parallel_tool_calls(),
 950                    None,
 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", _cx)
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", _cx)
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", _cx)
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", _cx)
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                    _cx,
1193                ))
1194            })
1195            .map(|this| {
1196                if self.has_accepted_terms_of_service && self.account_too_young {
1197                    this.child(young_account_banner).child(
1198                        Button::new("upgrade", "Upgrade to Pro", _cx)
1199                            .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1200                            .full_width()
1201                            .on_click(|_, _, cx| {
1202                                cx.open_url(&zed_urls::upgrade_to_zed_pro_url(cx))
1203                            }),
1204                    )
1205                } else if self.has_accepted_terms_of_service {
1206                    this.text_sm()
1207                        .child(subscription_text)
1208                        .child(manage_subscription_buttons)
1209                } else {
1210                    this
1211                }
1212            })
1213            .when(self.has_accepted_terms_of_service, |this| this)
1214    }
1215}
1216
1217struct ConfigurationView {
1218    state: Entity<State>,
1219    accept_terms_of_service_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1220    sign_in_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1221}
1222
1223impl ConfigurationView {
1224    fn new(state: Entity<State>) -> Self {
1225        let accept_terms_of_service_callback = Arc::new({
1226            let state = state.clone();
1227            move |_window: &mut Window, cx: &mut App| {
1228                state.update(cx, |state, cx| {
1229                    state.accept_terms_of_service(cx);
1230                });
1231            }
1232        });
1233
1234        let sign_in_callback = Arc::new({
1235            let state = state.clone();
1236            move |_window: &mut Window, cx: &mut App| {
1237                state.update(cx, |state, cx| {
1238                    state.authenticate(cx).detach_and_log_err(cx);
1239                });
1240            }
1241        });
1242
1243        Self {
1244            state,
1245            accept_terms_of_service_callback,
1246            sign_in_callback,
1247        }
1248    }
1249}
1250
1251impl Render for ConfigurationView {
1252    fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
1253        let state = self.state.read(cx);
1254        let user_store = state.user_store.read(cx);
1255
1256        ZedAiConfiguration {
1257            is_connected: !state.is_signed_out(cx),
1258            plan: user_store.plan(),
1259            subscription_period: user_store.subscription_period(),
1260            eligible_for_trial: user_store.trial_started_at().is_none(),
1261            has_accepted_terms_of_service: state.has_accepted_terms_of_service(cx),
1262            account_too_young: user_store.account_too_young(),
1263            accept_terms_of_service_in_progress: state.accept_terms_of_service_task.is_some(),
1264            accept_terms_of_service_callback: self.accept_terms_of_service_callback.clone(),
1265            sign_in_callback: self.sign_in_callback.clone(),
1266        }
1267    }
1268}
1269
1270impl Component for ZedAiConfiguration {
1271    fn name() -> &'static str {
1272        "AI Configuration Content"
1273    }
1274
1275    fn sort_name() -> &'static str {
1276        "AI Configuration Content"
1277    }
1278
1279    fn scope() -> ComponentScope {
1280        ComponentScope::Onboarding
1281    }
1282
1283    fn preview(_window: &mut Window, _cx: &mut App) -> Option<AnyElement> {
1284        fn configuration(
1285            is_connected: bool,
1286            plan: Option<Plan>,
1287            eligible_for_trial: bool,
1288            account_too_young: bool,
1289            has_accepted_terms_of_service: bool,
1290        ) -> AnyElement {
1291            ZedAiConfiguration {
1292                is_connected,
1293                plan,
1294                subscription_period: plan
1295                    .is_some()
1296                    .then(|| (Utc::now(), Utc::now() + chrono::Duration::days(7))),
1297                eligible_for_trial,
1298                has_accepted_terms_of_service,
1299                account_too_young,
1300                accept_terms_of_service_in_progress: false,
1301                accept_terms_of_service_callback: Arc::new(|_, _| {}),
1302                sign_in_callback: Arc::new(|_, _| {}),
1303            }
1304            .into_any_element()
1305        }
1306
1307        Some(
1308            v_flex()
1309                .p_4()
1310                .gap_4()
1311                .children(vec![
1312                    single_example(
1313                        "Not connected",
1314                        configuration(false, None, false, false, true),
1315                    ),
1316                    single_example(
1317                        "Accept Terms of Service",
1318                        configuration(true, None, true, false, false),
1319                    ),
1320                    single_example(
1321                        "No Plan - Not eligible for trial",
1322                        configuration(true, None, false, false, true),
1323                    ),
1324                    single_example(
1325                        "No Plan - Eligible for trial",
1326                        configuration(true, None, true, false, true),
1327                    ),
1328                    single_example(
1329                        "Free Plan",
1330                        configuration(true, Some(Plan::ZedFree), true, false, true),
1331                    ),
1332                    single_example(
1333                        "Zed Pro Trial Plan",
1334                        configuration(true, Some(Plan::ZedProTrial), true, false, true),
1335                    ),
1336                    single_example(
1337                        "Zed Pro Plan",
1338                        configuration(true, Some(Plan::ZedPro), true, false, true),
1339                    ),
1340                ])
1341                .into_any_element(),
1342        )
1343    }
1344}
1345
1346#[cfg(test)]
1347mod tests {
1348    use super::*;
1349    use http_client::http::{HeaderMap, StatusCode};
1350    use language_model::LanguageModelCompletionError;
1351
1352    #[test]
1353    fn test_api_error_conversion_with_upstream_http_error() {
1354        // upstream_http_error with 503 status should become ServerOverloaded
1355        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}"#;
1356
1357        let api_error = ApiError {
1358            status: StatusCode::INTERNAL_SERVER_ERROR,
1359            body: error_body.to_string(),
1360            headers: HeaderMap::new(),
1361        };
1362
1363        let completion_error: LanguageModelCompletionError = api_error.into();
1364
1365        match completion_error {
1366            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1367                assert_eq!(
1368                    message,
1369                    "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout"
1370                );
1371            }
1372            _ => panic!(
1373                "Expected UpstreamProviderError for upstream 503, got: {:?}",
1374                completion_error
1375            ),
1376        }
1377
1378        // upstream_http_error with 500 status should become ApiInternalServerError
1379        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the OpenAI API: internal server error","upstream_status":500}"#;
1380
1381        let api_error = ApiError {
1382            status: StatusCode::INTERNAL_SERVER_ERROR,
1383            body: error_body.to_string(),
1384            headers: HeaderMap::new(),
1385        };
1386
1387        let completion_error: LanguageModelCompletionError = api_error.into();
1388
1389        match completion_error {
1390            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1391                assert_eq!(
1392                    message,
1393                    "Received an error from the OpenAI API: internal server error"
1394                );
1395            }
1396            _ => panic!(
1397                "Expected UpstreamProviderError for upstream 500, got: {:?}",
1398                completion_error
1399            ),
1400        }
1401
1402        // upstream_http_error with 429 status should become RateLimitExceeded
1403        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the Google API: rate limit exceeded","upstream_status":429}"#;
1404
1405        let api_error = ApiError {
1406            status: StatusCode::INTERNAL_SERVER_ERROR,
1407            body: error_body.to_string(),
1408            headers: HeaderMap::new(),
1409        };
1410
1411        let completion_error: LanguageModelCompletionError = api_error.into();
1412
1413        match completion_error {
1414            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1415                assert_eq!(
1416                    message,
1417                    "Received an error from the Google API: rate limit exceeded"
1418                );
1419            }
1420            _ => panic!(
1421                "Expected UpstreamProviderError for upstream 429, got: {:?}",
1422                completion_error
1423            ),
1424        }
1425
1426        // Regular 500 error without upstream_http_error should remain ApiInternalServerError for Zed
1427        let error_body = "Regular internal server error";
1428
1429        let api_error = ApiError {
1430            status: StatusCode::INTERNAL_SERVER_ERROR,
1431            body: error_body.to_string(),
1432            headers: HeaderMap::new(),
1433        };
1434
1435        let completion_error: LanguageModelCompletionError = api_error.into();
1436
1437        match completion_error {
1438            LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
1439                assert_eq!(provider, PROVIDER_NAME);
1440                assert_eq!(message, "Regular internal server error");
1441            }
1442            _ => panic!(
1443                "Expected ApiInternalServerError for regular 500, got: {:?}",
1444                completion_error
1445            ),
1446        }
1447
1448        // upstream_http_429 format should be converted to UpstreamProviderError
1449        let error_body = r#"{"code":"upstream_http_429","message":"Upstream Anthropic rate limit exceeded.","retry_after":30.5}"#;
1450
1451        let api_error = ApiError {
1452            status: StatusCode::INTERNAL_SERVER_ERROR,
1453            body: error_body.to_string(),
1454            headers: HeaderMap::new(),
1455        };
1456
1457        let completion_error: LanguageModelCompletionError = api_error.into();
1458
1459        match completion_error {
1460            LanguageModelCompletionError::UpstreamProviderError {
1461                message,
1462                status,
1463                retry_after,
1464            } => {
1465                assert_eq!(message, "Upstream Anthropic rate limit exceeded.");
1466                assert_eq!(status, StatusCode::TOO_MANY_REQUESTS);
1467                assert_eq!(retry_after, Some(Duration::from_secs_f64(30.5)));
1468            }
1469            _ => panic!(
1470                "Expected UpstreamProviderError for upstream_http_429, got: {:?}",
1471                completion_error
1472            ),
1473        }
1474
1475        // Invalid JSON in error body should fall back to regular error handling
1476        let error_body = "Not JSON at all";
1477
1478        let api_error = ApiError {
1479            status: StatusCode::INTERNAL_SERVER_ERROR,
1480            body: error_body.to_string(),
1481            headers: HeaderMap::new(),
1482        };
1483
1484        let completion_error: LanguageModelCompletionError = api_error.into();
1485
1486        match completion_error {
1487            LanguageModelCompletionError::ApiInternalServerError { provider, .. } => {
1488                assert_eq!(provider, PROVIDER_NAME);
1489            }
1490            _ => panic!(
1491                "Expected ApiInternalServerError for invalid JSON, got: {:?}",
1492                completion_error
1493            ),
1494        }
1495    }
1496}