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 futures::{
   7    AsyncBufReadExt, FutureExt, Stream, StreamExt, future::BoxFuture, stream::BoxStream,
   8};
   9use google_ai::GoogleModelMode;
  10use gpui::{
  11    AnyElement, AnyView, App, AsyncApp, Context, Entity, SemanticVersion, Subscription, Task,
  12};
  13use http_client::http::{HeaderMap, HeaderValue};
  14use http_client::{AsyncBody, HttpClient, Method, Response, StatusCode};
  15use language_model::{
  16    AuthenticateError, LanguageModel, LanguageModelCacheConfiguration,
  17    LanguageModelCompletionError, LanguageModelCompletionEvent, LanguageModelId, LanguageModelName,
  18    LanguageModelProvider, LanguageModelProviderId, LanguageModelProviderName,
  19    LanguageModelProviderState, LanguageModelProviderTosView, LanguageModelRequest,
  20    LanguageModelToolChoice, LanguageModelToolSchemaFormat, LlmApiToken,
  21    ModelRequestLimitReachedError, PaymentRequiredError, RateLimiter, RefreshLlmTokenListener,
  22};
  23use proto::Plan;
  24use release_channel::AppVersion;
  25use schemars::JsonSchema;
  26use serde::{Deserialize, Serialize, de::DeserializeOwned};
  27use settings::SettingsStore;
  28use smol::io::{AsyncReadExt, BufReader};
  29use std::pin::Pin;
  30use std::str::FromStr as _;
  31use std::sync::Arc;
  32use std::time::Duration;
  33use thiserror::Error;
  34use ui::{TintColor, prelude::*};
  35use util::{ResultExt as _, maybe};
  36use zed_llm_client::{
  37    CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, CURRENT_PLAN_HEADER_NAME, CompletionBody,
  38    CompletionEvent, CompletionRequestStatus, CountTokensBody, CountTokensResponse,
  39    EXPIRED_LLM_TOKEN_HEADER_NAME, ListModelsResponse, MODEL_REQUESTS_RESOURCE_HEADER_VALUE,
  40    SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME,
  41    TOOL_USE_LIMIT_REACHED_HEADER_NAME, ZED_VERSION_HEADER_NAME,
  42};
  43
  44use crate::provider::anthropic::{AnthropicEventMapper, count_anthropic_tokens, into_anthropic};
  45use crate::provider::google::{GoogleEventMapper, into_google};
  46use crate::provider::open_ai::{OpenAiEventMapper, count_open_ai_tokens, into_open_ai};
  47
  48const PROVIDER_ID: LanguageModelProviderId = language_model::ZED_CLOUD_PROVIDER_ID;
  49const PROVIDER_NAME: LanguageModelProviderName = language_model::ZED_CLOUD_PROVIDER_NAME;
  50
  51#[derive(Default, Clone, Debug, PartialEq)]
  52pub struct ZedDotDevSettings {
  53    pub available_models: Vec<AvailableModel>,
  54}
  55
  56#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
  57#[serde(rename_all = "lowercase")]
  58pub enum AvailableProvider {
  59    Anthropic,
  60    OpenAi,
  61    Google,
  62}
  63
  64#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
  65pub struct AvailableModel {
  66    /// The provider of the language model.
  67    pub provider: AvailableProvider,
  68    /// The model's name in the provider's API. e.g. claude-3-5-sonnet-20240620
  69    pub name: String,
  70    /// The name displayed in the UI, such as in the assistant panel model dropdown menu.
  71    pub display_name: Option<String>,
  72    /// The size of the context window, indicating the maximum number of tokens the model can process.
  73    pub max_tokens: usize,
  74    /// The maximum number of output tokens allowed by the model.
  75    pub max_output_tokens: Option<u64>,
  76    /// The maximum number of completion tokens allowed by the model (o1-* only)
  77    pub max_completion_tokens: Option<u64>,
  78    /// Override this model with a different Anthropic model for tool calls.
  79    pub tool_override: Option<String>,
  80    /// Indicates whether this custom model supports caching.
  81    pub cache_configuration: Option<LanguageModelCacheConfiguration>,
  82    /// The default temperature to use for this model.
  83    pub default_temperature: Option<f32>,
  84    /// Any extra beta headers to provide when using the model.
  85    #[serde(default)]
  86    pub extra_beta_headers: Vec<String>,
  87    /// The model's mode (e.g. thinking)
  88    pub mode: Option<ModelMode>,
  89}
  90
  91#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
  92#[serde(tag = "type", rename_all = "lowercase")]
  93pub enum ModelMode {
  94    #[default]
  95    Default,
  96    Thinking {
  97        /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
  98        budget_tokens: Option<u32>,
  99    },
 100}
 101
 102impl From<ModelMode> for AnthropicModelMode {
 103    fn from(value: ModelMode) -> Self {
 104        match value {
 105            ModelMode::Default => AnthropicModelMode::Default,
 106            ModelMode::Thinking { budget_tokens } => AnthropicModelMode::Thinking { budget_tokens },
 107        }
 108    }
 109}
 110
 111pub struct CloudLanguageModelProvider {
 112    client: Arc<Client>,
 113    state: gpui::Entity<State>,
 114    _maintain_client_status: Task<()>,
 115}
 116
 117pub struct State {
 118    client: Arc<Client>,
 119    llm_api_token: LlmApiToken,
 120    user_store: Entity<UserStore>,
 121    status: client::Status,
 122    accept_terms_of_service_task: Option<Task<Result<()>>>,
 123    models: Vec<Arc<zed_llm_client::LanguageModel>>,
 124    default_model: Option<Arc<zed_llm_client::LanguageModel>>,
 125    default_fast_model: Option<Arc<zed_llm_client::LanguageModel>>,
 126    recommended_models: Vec<Arc<zed_llm_client::LanguageModel>>,
 127    _fetch_models_task: Task<()>,
 128    _settings_subscription: Subscription,
 129    _llm_token_subscription: Subscription,
 130}
 131
 132impl State {
 133    fn new(
 134        client: Arc<Client>,
 135        user_store: Entity<UserStore>,
 136        status: client::Status,
 137        cx: &mut Context<Self>,
 138    ) -> Self {
 139        let refresh_llm_token_listener = RefreshLlmTokenListener::global(cx);
 140
 141        Self {
 142            client: client.clone(),
 143            llm_api_token: LlmApiToken::default(),
 144            user_store,
 145            status,
 146            accept_terms_of_service_task: None,
 147            models: Vec::new(),
 148            default_model: None,
 149            default_fast_model: None,
 150            recommended_models: Vec::new(),
 151            _fetch_models_task: cx.spawn(async move |this, cx| {
 152                maybe!(async move {
 153                    let (client, llm_api_token) = this
 154                        .read_with(cx, |this, _cx| (client.clone(), this.llm_api_token.clone()))?;
 155
 156                    loop {
 157                        let status = this.read_with(cx, |this, _cx| this.status)?;
 158                        if matches!(status, client::Status::Connected { .. }) {
 159                            break;
 160                        }
 161
 162                        cx.background_executor()
 163                            .timer(Duration::from_millis(100))
 164                            .await;
 165                    }
 166
 167                    let response = Self::fetch_models(client, llm_api_token).await?;
 168                    this.update(cx, |this, cx| {
 169                        this.update_models(response, cx);
 170                    })
 171                })
 172                .await
 173                .context("failed to fetch Zed models")
 174                .log_err();
 175            }),
 176            _settings_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
 177                cx.notify();
 178            }),
 179            _llm_token_subscription: cx.subscribe(
 180                &refresh_llm_token_listener,
 181                move |this, _listener, _event, cx| {
 182                    let client = this.client.clone();
 183                    let llm_api_token = this.llm_api_token.clone();
 184                    cx.spawn(async move |this, cx| {
 185                        llm_api_token.refresh(&client).await?;
 186                        let response = Self::fetch_models(client, llm_api_token).await?;
 187                        this.update(cx, |this, cx| {
 188                            this.update_models(response, cx);
 189                        })
 190                    })
 191                    .detach_and_log_err(cx);
 192                },
 193            ),
 194        }
 195    }
 196
 197    fn is_signed_out(&self) -> bool {
 198        self.status.is_signed_out()
 199    }
 200
 201    fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
 202        let client = self.client.clone();
 203        cx.spawn(async move |state, cx| {
 204            client
 205                .authenticate_and_connect(true, &cx)
 206                .await
 207                .into_response()?;
 208            state.update(cx, |_, cx| cx.notify())
 209        })
 210    }
 211
 212    fn has_accepted_terms_of_service(&self, cx: &App) -> bool {
 213        self.user_store
 214            .read(cx)
 215            .current_user_has_accepted_terms()
 216            .unwrap_or(false)
 217    }
 218
 219    fn accept_terms_of_service(&mut self, cx: &mut Context<Self>) {
 220        let user_store = self.user_store.clone();
 221        self.accept_terms_of_service_task = Some(cx.spawn(async move |this, cx| {
 222            let _ = user_store
 223                .update(cx, |store, cx| store.accept_terms_of_service(cx))?
 224                .await;
 225            this.update(cx, |this, cx| {
 226                this.accept_terms_of_service_task = None;
 227                cx.notify()
 228            })
 229        }));
 230    }
 231
 232    fn update_models(&mut self, response: ListModelsResponse, cx: &mut Context<Self>) {
 233        let mut models = Vec::new();
 234
 235        for model in response.models {
 236            models.push(Arc::new(model.clone()));
 237
 238            // Right now we represent thinking variants of models as separate models on the client,
 239            // so we need to insert variants for any model that supports thinking.
 240            if model.supports_thinking {
 241                models.push(Arc::new(zed_llm_client::LanguageModel {
 242                    id: zed_llm_client::LanguageModelId(format!("{}-thinking", model.id).into()),
 243                    display_name: format!("{} Thinking", model.display_name),
 244                    ..model
 245                }));
 246            }
 247        }
 248
 249        self.default_model = models
 250            .iter()
 251            .find(|model| model.id == response.default_model)
 252            .cloned();
 253        self.default_fast_model = models
 254            .iter()
 255            .find(|model| model.id == response.default_fast_model)
 256            .cloned();
 257        self.recommended_models = response
 258            .recommended_models
 259            .iter()
 260            .filter_map(|id| models.iter().find(|model| &model.id == id))
 261            .cloned()
 262            .collect();
 263        self.models = models;
 264        cx.notify();
 265    }
 266
 267    async fn fetch_models(
 268        client: Arc<Client>,
 269        llm_api_token: LlmApiToken,
 270    ) -> Result<ListModelsResponse> {
 271        let http_client = &client.http_client();
 272        let token = llm_api_token.acquire(&client).await?;
 273
 274        let request = http_client::Request::builder()
 275            .method(Method::GET)
 276            .uri(http_client.build_zed_llm_url("/models", &[])?.as_ref())
 277            .header("Authorization", format!("Bearer {token}"))
 278            .body(AsyncBody::empty())?;
 279        let mut response = http_client
 280            .send(request)
 281            .await
 282            .context("failed to send list models request")?;
 283
 284        if response.status().is_success() {
 285            let mut body = String::new();
 286            response.body_mut().read_to_string(&mut body).await?;
 287            return Ok(serde_json::from_str(&body)?);
 288        } else {
 289            let mut body = String::new();
 290            response.body_mut().read_to_string(&mut body).await?;
 291            anyhow::bail!(
 292                "error listing models.\nStatus: {:?}\nBody: {body}",
 293                response.status(),
 294            );
 295        }
 296    }
 297}
 298
 299impl CloudLanguageModelProvider {
 300    pub fn new(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) -> Self {
 301        let mut status_rx = client.status();
 302        let status = *status_rx.borrow();
 303
 304        let state = cx.new(|cx| State::new(client.clone(), user_store.clone(), status, cx));
 305
 306        let state_ref = state.downgrade();
 307        let maintain_client_status = cx.spawn(async move |cx| {
 308            while let Some(status) = status_rx.next().await {
 309                if let Some(this) = state_ref.upgrade() {
 310                    _ = this.update(cx, |this, cx| {
 311                        if this.status != status {
 312                            this.status = status;
 313                            cx.notify();
 314                        }
 315                    });
 316                } else {
 317                    break;
 318                }
 319            }
 320        });
 321
 322        Self {
 323            client,
 324            state: state.clone(),
 325            _maintain_client_status: maintain_client_status,
 326        }
 327    }
 328
 329    fn create_language_model(
 330        &self,
 331        model: Arc<zed_llm_client::LanguageModel>,
 332        llm_api_token: LlmApiToken,
 333    ) -> Arc<dyn LanguageModel> {
 334        Arc::new(CloudLanguageModel {
 335            id: LanguageModelId(SharedString::from(model.id.0.clone())),
 336            model,
 337            llm_api_token: llm_api_token.clone(),
 338            client: self.client.clone(),
 339            request_limiter: RateLimiter::new(4),
 340        })
 341    }
 342}
 343
 344impl LanguageModelProviderState for CloudLanguageModelProvider {
 345    type ObservableEntity = State;
 346
 347    fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
 348        Some(self.state.clone())
 349    }
 350}
 351
 352impl LanguageModelProvider for CloudLanguageModelProvider {
 353    fn id(&self) -> LanguageModelProviderId {
 354        PROVIDER_ID
 355    }
 356
 357    fn name(&self) -> LanguageModelProviderName {
 358        PROVIDER_NAME
 359    }
 360
 361    fn icon(&self) -> IconName {
 362        IconName::AiZed
 363    }
 364
 365    fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
 366        let default_model = self.state.read(cx).default_model.clone()?;
 367        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 368        Some(self.create_language_model(default_model, llm_api_token))
 369    }
 370
 371    fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
 372        let default_fast_model = self.state.read(cx).default_fast_model.clone()?;
 373        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 374        Some(self.create_language_model(default_fast_model, llm_api_token))
 375    }
 376
 377    fn recommended_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
 378        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 379        self.state
 380            .read(cx)
 381            .recommended_models
 382            .iter()
 383            .cloned()
 384            .map(|model| self.create_language_model(model, llm_api_token.clone()))
 385            .collect()
 386    }
 387
 388    fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
 389        let llm_api_token = self.state.read(cx).llm_api_token.clone();
 390        self.state
 391            .read(cx)
 392            .models
 393            .iter()
 394            .cloned()
 395            .map(|model| self.create_language_model(model, llm_api_token.clone()))
 396            .collect()
 397    }
 398
 399    fn is_authenticated(&self, cx: &App) -> bool {
 400        let state = self.state.read(cx);
 401        !state.is_signed_out() && state.has_accepted_terms_of_service(cx)
 402    }
 403
 404    fn authenticate(&self, _cx: &mut App) -> Task<Result<(), AuthenticateError>> {
 405        Task::ready(Ok(()))
 406    }
 407
 408    fn configuration_view(&self, _: &mut Window, cx: &mut App) -> AnyView {
 409        cx.new(|_| ConfigurationView::new(self.state.clone()))
 410            .into()
 411    }
 412
 413    fn must_accept_terms(&self, cx: &App) -> bool {
 414        !self.state.read(cx).has_accepted_terms_of_service(cx)
 415    }
 416
 417    fn render_accept_terms(
 418        &self,
 419        view: LanguageModelProviderTosView,
 420        cx: &mut App,
 421    ) -> Option<AnyElement> {
 422        let state = self.state.read(cx);
 423        if state.has_accepted_terms_of_service(cx) {
 424            return None;
 425        }
 426        Some(
 427            render_accept_terms(view, state.accept_terms_of_service_task.is_some(), {
 428                let state = self.state.clone();
 429                move |_window, cx| {
 430                    state.update(cx, |state, cx| state.accept_terms_of_service(cx));
 431                }
 432            })
 433            .into_any_element(),
 434        )
 435    }
 436
 437    fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
 438        Task::ready(Ok(()))
 439    }
 440}
 441
 442fn render_accept_terms(
 443    view_kind: LanguageModelProviderTosView,
 444    accept_terms_of_service_in_progress: bool,
 445    accept_terms_callback: impl Fn(&mut Window, &mut App) + 'static,
 446) -> impl IntoElement {
 447    let thread_fresh_start = matches!(view_kind, LanguageModelProviderTosView::ThreadFreshStart);
 448    let thread_empty_state = matches!(view_kind, LanguageModelProviderTosView::ThreadEmptyState);
 449
 450    let terms_button = Button::new("terms_of_service", "Terms of Service")
 451        .style(ButtonStyle::Subtle)
 452        .icon(IconName::ArrowUpRight)
 453        .icon_color(Color::Muted)
 454        .icon_size(IconSize::XSmall)
 455        .when(thread_empty_state, |this| this.label_size(LabelSize::Small))
 456        .on_click(move |_, _window, cx| cx.open_url("https://zed.dev/terms-of-service"));
 457
 458    let button_container = h_flex().child(
 459        Button::new("accept_terms", "I accept the Terms of Service")
 460            .when(!thread_empty_state, |this| {
 461                this.full_width()
 462                    .style(ButtonStyle::Tinted(TintColor::Accent))
 463                    .icon(IconName::Check)
 464                    .icon_position(IconPosition::Start)
 465                    .icon_size(IconSize::Small)
 466            })
 467            .when(thread_empty_state, |this| {
 468                this.style(ButtonStyle::Tinted(TintColor::Warning))
 469                    .label_size(LabelSize::Small)
 470            })
 471            .disabled(accept_terms_of_service_in_progress)
 472            .on_click(move |_, window, cx| (accept_terms_callback)(window, cx)),
 473    );
 474
 475    if thread_empty_state {
 476        h_flex()
 477            .w_full()
 478            .flex_wrap()
 479            .justify_between()
 480            .child(
 481                h_flex()
 482                    .child(
 483                        Label::new("To start using Zed AI, please read and accept the")
 484                            .size(LabelSize::Small),
 485                    )
 486                    .child(terms_button),
 487            )
 488            .child(button_container)
 489    } else {
 490        v_flex()
 491            .w_full()
 492            .gap_2()
 493            .child(
 494                h_flex()
 495                    .flex_wrap()
 496                    .when(thread_fresh_start, |this| this.justify_center())
 497                    .child(Label::new(
 498                        "To start using Zed AI, please read and accept the",
 499                    ))
 500                    .child(terms_button),
 501            )
 502            .child({
 503                match view_kind {
 504                    LanguageModelProviderTosView::TextThreadPopup => {
 505                        button_container.w_full().justify_end()
 506                    }
 507                    LanguageModelProviderTosView::Configuration => {
 508                        button_container.w_full().justify_start()
 509                    }
 510                    LanguageModelProviderTosView::ThreadFreshStart => {
 511                        button_container.w_full().justify_center()
 512                    }
 513                    LanguageModelProviderTosView::ThreadEmptyState => div().w_0(),
 514                }
 515            })
 516    }
 517}
 518
 519pub struct CloudLanguageModel {
 520    id: LanguageModelId,
 521    model: Arc<zed_llm_client::LanguageModel>,
 522    llm_api_token: LlmApiToken,
 523    client: Arc<Client>,
 524    request_limiter: RateLimiter,
 525}
 526
 527struct PerformLlmCompletionResponse {
 528    response: Response<AsyncBody>,
 529    usage: Option<ModelRequestUsage>,
 530    tool_use_limit_reached: bool,
 531    includes_status_messages: bool,
 532}
 533
 534impl CloudLanguageModel {
 535    async fn perform_llm_completion(
 536        client: Arc<Client>,
 537        llm_api_token: LlmApiToken,
 538        app_version: Option<SemanticVersion>,
 539        body: CompletionBody,
 540    ) -> Result<PerformLlmCompletionResponse> {
 541        let http_client = &client.http_client();
 542
 543        let mut token = llm_api_token.acquire(&client).await?;
 544        let mut refreshed_token = false;
 545
 546        loop {
 547            let request_builder = http_client::Request::builder()
 548                .method(Method::POST)
 549                .uri(http_client.build_zed_llm_url("/completions", &[])?.as_ref());
 550            let request_builder = if let Some(app_version) = app_version {
 551                request_builder.header(ZED_VERSION_HEADER_NAME, app_version.to_string())
 552            } else {
 553                request_builder
 554            };
 555
 556            let request = request_builder
 557                .header("Content-Type", "application/json")
 558                .header("Authorization", format!("Bearer {token}"))
 559                .header(CLIENT_SUPPORTS_STATUS_MESSAGES_HEADER_NAME, "true")
 560                .body(serde_json::to_string(&body)?.into())?;
 561            let mut response = http_client.send(request).await?;
 562            let status = response.status();
 563            if status.is_success() {
 564                let includes_status_messages = response
 565                    .headers()
 566                    .get(SERVER_SUPPORTS_STATUS_MESSAGES_HEADER_NAME)
 567                    .is_some();
 568
 569                let tool_use_limit_reached = response
 570                    .headers()
 571                    .get(TOOL_USE_LIMIT_REACHED_HEADER_NAME)
 572                    .is_some();
 573
 574                let usage = if includes_status_messages {
 575                    None
 576                } else {
 577                    ModelRequestUsage::from_headers(response.headers()).ok()
 578                };
 579
 580                return Ok(PerformLlmCompletionResponse {
 581                    response,
 582                    usage,
 583                    includes_status_messages,
 584                    tool_use_limit_reached,
 585                });
 586            }
 587
 588            if !refreshed_token
 589                && response
 590                    .headers()
 591                    .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
 592                    .is_some()
 593            {
 594                token = llm_api_token.refresh(&client).await?;
 595                refreshed_token = true;
 596                continue;
 597            }
 598
 599            if status == StatusCode::FORBIDDEN
 600                && response
 601                    .headers()
 602                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 603                    .is_some()
 604            {
 605                if let Some(MODEL_REQUESTS_RESOURCE_HEADER_VALUE) = response
 606                    .headers()
 607                    .get(SUBSCRIPTION_LIMIT_RESOURCE_HEADER_NAME)
 608                    .and_then(|resource| resource.to_str().ok())
 609                {
 610                    if let Some(plan) = response
 611                        .headers()
 612                        .get(CURRENT_PLAN_HEADER_NAME)
 613                        .and_then(|plan| plan.to_str().ok())
 614                        .and_then(|plan| zed_llm_client::Plan::from_str(plan).ok())
 615                    {
 616                        let plan = match plan {
 617                            zed_llm_client::Plan::ZedFree => Plan::Free,
 618                            zed_llm_client::Plan::ZedPro => Plan::ZedPro,
 619                            zed_llm_client::Plan::ZedProTrial => Plan::ZedProTrial,
 620                        };
 621                        return Err(anyhow!(ModelRequestLimitReachedError { plan }));
 622                    }
 623                }
 624            } else if status == StatusCode::PAYMENT_REQUIRED {
 625                return Err(anyhow!(PaymentRequiredError));
 626            }
 627
 628            let mut body = String::new();
 629            let headers = response.headers().clone();
 630            response.body_mut().read_to_string(&mut body).await?;
 631            return Err(anyhow!(ApiError {
 632                status,
 633                body,
 634                headers
 635            }));
 636        }
 637    }
 638}
 639
 640#[derive(Debug, Error)]
 641#[error("cloud language model request failed with status {status}: {body}")]
 642struct ApiError {
 643    status: StatusCode,
 644    body: String,
 645    headers: HeaderMap<HeaderValue>,
 646}
 647
 648/// Represents error responses from Zed's cloud API.
 649///
 650/// Example JSON for an upstream HTTP error:
 651/// ```json
 652/// {
 653///   "code": "upstream_http_error",
 654///   "message": "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout",
 655///   "upstream_status": 503
 656/// }
 657/// ```
 658#[derive(Debug, serde::Deserialize)]
 659struct CloudApiError {
 660    code: String,
 661    message: String,
 662    #[serde(default)]
 663    #[serde(deserialize_with = "deserialize_optional_status_code")]
 664    upstream_status: Option<StatusCode>,
 665    #[serde(default)]
 666    retry_after: Option<f64>,
 667}
 668
 669fn deserialize_optional_status_code<'de, D>(deserializer: D) -> Result<Option<StatusCode>, D::Error>
 670where
 671    D: serde::Deserializer<'de>,
 672{
 673    let opt: Option<u16> = Option::deserialize(deserializer)?;
 674    Ok(opt.and_then(|code| StatusCode::from_u16(code).ok()))
 675}
 676
 677impl From<ApiError> for LanguageModelCompletionError {
 678    fn from(error: ApiError) -> Self {
 679        if let Ok(cloud_error) = serde_json::from_str::<CloudApiError>(&error.body) {
 680            if cloud_error.code.starts_with("upstream_http_") {
 681                let status = if let Some(status) = cloud_error.upstream_status {
 682                    status
 683                } else if cloud_error.code.ends_with("_error") {
 684                    error.status
 685                } else {
 686                    // If there's a status code in the code string (e.g. "upstream_http_429")
 687                    // then use that; otherwise, see if the JSON contains a status code.
 688                    cloud_error
 689                        .code
 690                        .strip_prefix("upstream_http_")
 691                        .and_then(|code_str| code_str.parse::<u16>().ok())
 692                        .and_then(|code| StatusCode::from_u16(code).ok())
 693                        .unwrap_or(error.status)
 694                };
 695
 696                return LanguageModelCompletionError::UpstreamProviderError {
 697                    message: cloud_error.message,
 698                    status,
 699                    retry_after: cloud_error.retry_after.map(Duration::from_secs_f64),
 700                };
 701            }
 702        }
 703
 704        let retry_after = None;
 705        LanguageModelCompletionError::from_http_status(
 706            PROVIDER_NAME,
 707            error.status,
 708            error.body,
 709            retry_after,
 710        )
 711    }
 712}
 713
 714impl LanguageModel for CloudLanguageModel {
 715    fn id(&self) -> LanguageModelId {
 716        self.id.clone()
 717    }
 718
 719    fn name(&self) -> LanguageModelName {
 720        LanguageModelName::from(self.model.display_name.clone())
 721    }
 722
 723    fn provider_id(&self) -> LanguageModelProviderId {
 724        PROVIDER_ID
 725    }
 726
 727    fn provider_name(&self) -> LanguageModelProviderName {
 728        PROVIDER_NAME
 729    }
 730
 731    fn upstream_provider_id(&self) -> LanguageModelProviderId {
 732        use zed_llm_client::LanguageModelProvider::*;
 733        match self.model.provider {
 734            Anthropic => language_model::ANTHROPIC_PROVIDER_ID,
 735            OpenAi => language_model::OPEN_AI_PROVIDER_ID,
 736            Google => language_model::GOOGLE_PROVIDER_ID,
 737        }
 738    }
 739
 740    fn upstream_provider_name(&self) -> LanguageModelProviderName {
 741        use zed_llm_client::LanguageModelProvider::*;
 742        match self.model.provider {
 743            Anthropic => language_model::ANTHROPIC_PROVIDER_NAME,
 744            OpenAi => language_model::OPEN_AI_PROVIDER_NAME,
 745            Google => language_model::GOOGLE_PROVIDER_NAME,
 746        }
 747    }
 748
 749    fn supports_tools(&self) -> bool {
 750        self.model.supports_tools
 751    }
 752
 753    fn supports_images(&self) -> bool {
 754        self.model.supports_images
 755    }
 756
 757    fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
 758        match choice {
 759            LanguageModelToolChoice::Auto
 760            | LanguageModelToolChoice::Any
 761            | LanguageModelToolChoice::None => true,
 762        }
 763    }
 764
 765    fn supports_burn_mode(&self) -> bool {
 766        self.model.supports_max_mode
 767    }
 768
 769    fn telemetry_id(&self) -> String {
 770        format!("zed.dev/{}", self.model.id)
 771    }
 772
 773    fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
 774        match self.model.provider {
 775            zed_llm_client::LanguageModelProvider::Anthropic
 776            | zed_llm_client::LanguageModelProvider::OpenAi => {
 777                LanguageModelToolSchemaFormat::JsonSchema
 778            }
 779            zed_llm_client::LanguageModelProvider::Google => {
 780                LanguageModelToolSchemaFormat::JsonSchemaSubset
 781            }
 782        }
 783    }
 784
 785    fn max_token_count(&self) -> u64 {
 786        self.model.max_token_count as u64
 787    }
 788
 789    fn max_token_count_in_burn_mode(&self) -> Option<u64> {
 790        self.model
 791            .max_token_count_in_max_mode
 792            .filter(|_| self.model.supports_max_mode)
 793            .map(|max_token_count| max_token_count as u64)
 794    }
 795
 796    fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
 797        match &self.model.provider {
 798            zed_llm_client::LanguageModelProvider::Anthropic => {
 799                Some(LanguageModelCacheConfiguration {
 800                    min_total_token: 2_048,
 801                    should_speculate: true,
 802                    max_cache_anchors: 4,
 803                })
 804            }
 805            zed_llm_client::LanguageModelProvider::OpenAi
 806            | zed_llm_client::LanguageModelProvider::Google => None,
 807        }
 808    }
 809
 810    fn count_tokens(
 811        &self,
 812        request: LanguageModelRequest,
 813        cx: &App,
 814    ) -> BoxFuture<'static, Result<u64>> {
 815        match self.model.provider {
 816            zed_llm_client::LanguageModelProvider::Anthropic => count_anthropic_tokens(request, cx),
 817            zed_llm_client::LanguageModelProvider::OpenAi => {
 818                let model = match open_ai::Model::from_id(&self.model.id.0) {
 819                    Ok(model) => model,
 820                    Err(err) => return async move { Err(anyhow!(err)) }.boxed(),
 821                };
 822                count_open_ai_tokens(request, model, cx)
 823            }
 824            zed_llm_client::LanguageModelProvider::Google => {
 825                let client = self.client.clone();
 826                let llm_api_token = self.llm_api_token.clone();
 827                let model_id = self.model.id.to_string();
 828                let generate_content_request =
 829                    into_google(request, model_id.clone(), GoogleModelMode::Default);
 830                async move {
 831                    let http_client = &client.http_client();
 832                    let token = llm_api_token.acquire(&client).await?;
 833
 834                    let request_body = CountTokensBody {
 835                        provider: zed_llm_client::LanguageModelProvider::Google,
 836                        model: model_id,
 837                        provider_request: serde_json::to_value(&google_ai::CountTokensRequest {
 838                            generate_content_request,
 839                        })?,
 840                    };
 841                    let request = http_client::Request::builder()
 842                        .method(Method::POST)
 843                        .uri(
 844                            http_client
 845                                .build_zed_llm_url("/count_tokens", &[])?
 846                                .as_ref(),
 847                        )
 848                        .header("Content-Type", "application/json")
 849                        .header("Authorization", format!("Bearer {token}"))
 850                        .body(serde_json::to_string(&request_body)?.into())?;
 851                    let mut response = http_client.send(request).await?;
 852                    let status = response.status();
 853                    let headers = response.headers().clone();
 854                    let mut response_body = String::new();
 855                    response
 856                        .body_mut()
 857                        .read_to_string(&mut response_body)
 858                        .await?;
 859
 860                    if status.is_success() {
 861                        let response_body: CountTokensResponse =
 862                            serde_json::from_str(&response_body)?;
 863
 864                        Ok(response_body.tokens as u64)
 865                    } else {
 866                        Err(anyhow!(ApiError {
 867                            status,
 868                            body: response_body,
 869                            headers
 870                        }))
 871                    }
 872                }
 873                .boxed()
 874            }
 875        }
 876    }
 877
 878    fn stream_completion(
 879        &self,
 880        request: LanguageModelRequest,
 881        cx: &AsyncApp,
 882    ) -> BoxFuture<
 883        'static,
 884        Result<
 885            BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
 886            LanguageModelCompletionError,
 887        >,
 888    > {
 889        let thread_id = request.thread_id.clone();
 890        let prompt_id = request.prompt_id.clone();
 891        let intent = request.intent;
 892        let mode = request.mode;
 893        let app_version = cx.update(|cx| AppVersion::global(cx)).ok();
 894        let thinking_allowed = request.thinking_allowed;
 895        match self.model.provider {
 896            zed_llm_client::LanguageModelProvider::Anthropic => {
 897                let request = into_anthropic(
 898                    request,
 899                    self.model.id.to_string(),
 900                    1.0,
 901                    self.model.max_output_tokens as u64,
 902                    if thinking_allowed && self.model.id.0.ends_with("-thinking") {
 903                        AnthropicModelMode::Thinking {
 904                            budget_tokens: Some(4_096),
 905                        }
 906                    } else {
 907                        AnthropicModelMode::Default
 908                    },
 909                );
 910                let client = self.client.clone();
 911                let llm_api_token = self.llm_api_token.clone();
 912                let future = self.request_limiter.stream(async move {
 913                    let PerformLlmCompletionResponse {
 914                        response,
 915                        usage,
 916                        includes_status_messages,
 917                        tool_use_limit_reached,
 918                    } = Self::perform_llm_completion(
 919                        client.clone(),
 920                        llm_api_token,
 921                        app_version,
 922                        CompletionBody {
 923                            thread_id,
 924                            prompt_id,
 925                            intent,
 926                            mode,
 927                            provider: zed_llm_client::LanguageModelProvider::Anthropic,
 928                            model: request.model.clone(),
 929                            provider_request: serde_json::to_value(&request)
 930                                .map_err(|e| anyhow!(e))?,
 931                        },
 932                    )
 933                    .await
 934                    .map_err(|err| match err.downcast::<ApiError>() {
 935                        Ok(api_err) => anyhow!(LanguageModelCompletionError::from(api_err)),
 936                        Err(err) => anyhow!(err),
 937                    })?;
 938
 939                    let mut mapper = AnthropicEventMapper::new();
 940                    Ok(map_cloud_completion_events(
 941                        Box::pin(
 942                            response_lines(response, includes_status_messages)
 943                                .chain(usage_updated_event(usage))
 944                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
 945                        ),
 946                        move |event| mapper.map_event(event),
 947                    ))
 948                });
 949                async move { Ok(future.await?.boxed()) }.boxed()
 950            }
 951            zed_llm_client::LanguageModelProvider::OpenAi => {
 952                let client = self.client.clone();
 953                let model = match open_ai::Model::from_id(&self.model.id.0) {
 954                    Ok(model) => model,
 955                    Err(err) => return async move { Err(anyhow!(err).into()) }.boxed(),
 956                };
 957                let request = into_open_ai(
 958                    request,
 959                    model.id(),
 960                    model.supports_parallel_tool_calls(),
 961                    None,
 962                );
 963                let llm_api_token = self.llm_api_token.clone();
 964                let future = self.request_limiter.stream(async move {
 965                    let PerformLlmCompletionResponse {
 966                        response,
 967                        usage,
 968                        includes_status_messages,
 969                        tool_use_limit_reached,
 970                    } = Self::perform_llm_completion(
 971                        client.clone(),
 972                        llm_api_token,
 973                        app_version,
 974                        CompletionBody {
 975                            thread_id,
 976                            prompt_id,
 977                            intent,
 978                            mode,
 979                            provider: zed_llm_client::LanguageModelProvider::OpenAi,
 980                            model: request.model.clone(),
 981                            provider_request: serde_json::to_value(&request)
 982                                .map_err(|e| anyhow!(e))?,
 983                        },
 984                    )
 985                    .await?;
 986
 987                    let mut mapper = OpenAiEventMapper::new();
 988                    Ok(map_cloud_completion_events(
 989                        Box::pin(
 990                            response_lines(response, includes_status_messages)
 991                                .chain(usage_updated_event(usage))
 992                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
 993                        ),
 994                        move |event| mapper.map_event(event),
 995                    ))
 996                });
 997                async move { Ok(future.await?.boxed()) }.boxed()
 998            }
 999            zed_llm_client::LanguageModelProvider::Google => {
1000                let client = self.client.clone();
1001                let request =
1002                    into_google(request, self.model.id.to_string(), GoogleModelMode::Default);
1003                let llm_api_token = self.llm_api_token.clone();
1004                let future = self.request_limiter.stream(async move {
1005                    let PerformLlmCompletionResponse {
1006                        response,
1007                        usage,
1008                        includes_status_messages,
1009                        tool_use_limit_reached,
1010                    } = Self::perform_llm_completion(
1011                        client.clone(),
1012                        llm_api_token,
1013                        app_version,
1014                        CompletionBody {
1015                            thread_id,
1016                            prompt_id,
1017                            intent,
1018                            mode,
1019                            provider: zed_llm_client::LanguageModelProvider::Google,
1020                            model: request.model.model_id.clone(),
1021                            provider_request: serde_json::to_value(&request)
1022                                .map_err(|e| anyhow!(e))?,
1023                        },
1024                    )
1025                    .await?;
1026
1027                    let mut mapper = GoogleEventMapper::new();
1028                    Ok(map_cloud_completion_events(
1029                        Box::pin(
1030                            response_lines(response, includes_status_messages)
1031                                .chain(usage_updated_event(usage))
1032                                .chain(tool_use_limit_reached_event(tool_use_limit_reached)),
1033                        ),
1034                        move |event| mapper.map_event(event),
1035                    ))
1036                });
1037                async move { Ok(future.await?.boxed()) }.boxed()
1038            }
1039        }
1040    }
1041}
1042
1043fn map_cloud_completion_events<T, F>(
1044    stream: Pin<Box<dyn Stream<Item = Result<CompletionEvent<T>>> + Send>>,
1045    mut map_callback: F,
1046) -> BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
1047where
1048    T: DeserializeOwned + 'static,
1049    F: FnMut(T) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
1050        + Send
1051        + 'static,
1052{
1053    stream
1054        .flat_map(move |event| {
1055            futures::stream::iter(match event {
1056                Err(error) => {
1057                    vec![Err(LanguageModelCompletionError::from(error))]
1058                }
1059                Ok(CompletionEvent::Status(event)) => {
1060                    vec![Ok(LanguageModelCompletionEvent::StatusUpdate(event))]
1061                }
1062                Ok(CompletionEvent::Event(event)) => map_callback(event),
1063            })
1064        })
1065        .boxed()
1066}
1067
1068fn usage_updated_event<T>(
1069    usage: Option<ModelRequestUsage>,
1070) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1071    futures::stream::iter(usage.map(|usage| {
1072        Ok(CompletionEvent::Status(
1073            CompletionRequestStatus::UsageUpdated {
1074                amount: usage.amount as usize,
1075                limit: usage.limit,
1076            },
1077        ))
1078    }))
1079}
1080
1081fn tool_use_limit_reached_event<T>(
1082    tool_use_limit_reached: bool,
1083) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1084    futures::stream::iter(tool_use_limit_reached.then(|| {
1085        Ok(CompletionEvent::Status(
1086            CompletionRequestStatus::ToolUseLimitReached,
1087        ))
1088    }))
1089}
1090
1091fn response_lines<T: DeserializeOwned>(
1092    response: Response<AsyncBody>,
1093    includes_status_messages: bool,
1094) -> impl Stream<Item = Result<CompletionEvent<T>>> {
1095    futures::stream::try_unfold(
1096        (String::new(), BufReader::new(response.into_body())),
1097        move |(mut line, mut body)| async move {
1098            match body.read_line(&mut line).await {
1099                Ok(0) => Ok(None),
1100                Ok(_) => {
1101                    let event = if includes_status_messages {
1102                        serde_json::from_str::<CompletionEvent<T>>(&line)?
1103                    } else {
1104                        CompletionEvent::Event(serde_json::from_str::<T>(&line)?)
1105                    };
1106
1107                    line.clear();
1108                    Ok(Some((event, (line, body))))
1109                }
1110                Err(e) => Err(e.into()),
1111            }
1112        },
1113    )
1114}
1115
1116#[derive(IntoElement, RegisterComponent)]
1117struct ZedAiConfiguration {
1118    is_connected: bool,
1119    plan: Option<proto::Plan>,
1120    subscription_period: Option<(DateTime<Utc>, DateTime<Utc>)>,
1121    eligible_for_trial: bool,
1122    has_accepted_terms_of_service: bool,
1123    account_too_young: bool,
1124    accept_terms_of_service_in_progress: bool,
1125    accept_terms_of_service_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1126    sign_in_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1127}
1128
1129impl RenderOnce for ZedAiConfiguration {
1130    fn render(self, _window: &mut Window, _cx: &mut App) -> impl IntoElement {
1131        let young_account_banner = YoungAccountBanner;
1132
1133        let is_pro = self.plan == Some(proto::Plan::ZedPro);
1134        let subscription_text = match (self.plan, self.subscription_period) {
1135            (Some(proto::Plan::ZedPro), Some(_)) => {
1136                "You have access to Zed's hosted models through your Pro subscription."
1137            }
1138            (Some(proto::Plan::ZedProTrial), Some(_)) => {
1139                "You have access to Zed's hosted models through your Pro trial."
1140            }
1141            (Some(proto::Plan::Free), Some(_)) => {
1142                "You have basic access to Zed's hosted models through the Free plan."
1143            }
1144            _ => {
1145                if self.eligible_for_trial {
1146                    "Subscribe for access to Zed's hosted models. Start with a 14 day free trial."
1147                } else {
1148                    "Subscribe for access to Zed's hosted models."
1149                }
1150            }
1151        };
1152
1153        let manage_subscription_buttons = if is_pro {
1154            Button::new("manage_settings", "Manage Subscription")
1155                .full_width()
1156                .style(ButtonStyle::Tinted(TintColor::Accent))
1157                .on_click(|_, _, cx| cx.open_url(&zed_urls::account_url(cx)))
1158                .into_any_element()
1159        } else if self.plan.is_none() || self.eligible_for_trial {
1160            Button::new("start_trial", "Start 14-day Free Pro Trial")
1161                .full_width()
1162                .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1163                .on_click(|_, _, cx| cx.open_url(&zed_urls::start_trial_url(cx)))
1164                .into_any_element()
1165        } else {
1166            Button::new("upgrade", "Upgrade to Pro")
1167                .full_width()
1168                .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1169                .on_click(|_, _, cx| cx.open_url(&zed_urls::upgrade_to_zed_pro_url(cx)))
1170                .into_any_element()
1171        };
1172
1173        if !self.is_connected {
1174            return v_flex()
1175                .gap_2()
1176                .child(Label::new("Sign in to have access to Zed's complete agentic experience with hosted models."))
1177                .child(
1178                    Button::new("sign_in", "Sign In to use Zed AI")
1179                        .icon_color(Color::Muted)
1180                        .icon(IconName::Github)
1181                        .icon_size(IconSize::Small)
1182                        .icon_position(IconPosition::Start)
1183                        .full_width()
1184                        .on_click({
1185                            let callback = self.sign_in_callback.clone();
1186                            move |_, window, cx| (callback)(window, cx)
1187                        }),
1188                );
1189        }
1190
1191        v_flex()
1192            .gap_2()
1193            .w_full()
1194            .when(!self.has_accepted_terms_of_service, |this| {
1195                this.child(render_accept_terms(
1196                    LanguageModelProviderTosView::Configuration,
1197                    self.accept_terms_of_service_in_progress,
1198                    {
1199                        let callback = self.accept_terms_of_service_callback.clone();
1200                        move |window, cx| (callback)(window, cx)
1201                    },
1202                ))
1203            })
1204            .map(|this| {
1205                if self.has_accepted_terms_of_service && self.account_too_young {
1206                    this.child(young_account_banner).child(
1207                        Button::new("upgrade", "Upgrade to Pro")
1208                            .style(ui::ButtonStyle::Tinted(ui::TintColor::Accent))
1209                            .full_width()
1210                            .on_click(|_, _, cx| {
1211                                cx.open_url(&zed_urls::upgrade_to_zed_pro_url(cx))
1212                            }),
1213                    )
1214                } else if self.has_accepted_terms_of_service {
1215                    this.text_sm()
1216                        .child(subscription_text)
1217                        .child(manage_subscription_buttons)
1218                } else {
1219                    this
1220                }
1221            })
1222            .when(self.has_accepted_terms_of_service, |this| this)
1223    }
1224}
1225
1226struct ConfigurationView {
1227    state: Entity<State>,
1228    accept_terms_of_service_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1229    sign_in_callback: Arc<dyn Fn(&mut Window, &mut App) + Send + Sync>,
1230}
1231
1232impl ConfigurationView {
1233    fn new(state: Entity<State>) -> Self {
1234        let accept_terms_of_service_callback = Arc::new({
1235            let state = state.clone();
1236            move |_window: &mut Window, cx: &mut App| {
1237                state.update(cx, |state, cx| {
1238                    state.accept_terms_of_service(cx);
1239                });
1240            }
1241        });
1242
1243        let sign_in_callback = Arc::new({
1244            let state = state.clone();
1245            move |_window: &mut Window, cx: &mut App| {
1246                state.update(cx, |state, cx| {
1247                    state.authenticate(cx).detach_and_log_err(cx);
1248                });
1249            }
1250        });
1251
1252        Self {
1253            state,
1254            accept_terms_of_service_callback,
1255            sign_in_callback,
1256        }
1257    }
1258}
1259
1260impl Render for ConfigurationView {
1261    fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
1262        let state = self.state.read(cx);
1263        let user_store = state.user_store.read(cx);
1264
1265        ZedAiConfiguration {
1266            is_connected: !state.is_signed_out(),
1267            plan: user_store.current_plan(),
1268            subscription_period: user_store.subscription_period(),
1269            eligible_for_trial: user_store.trial_started_at().is_none(),
1270            has_accepted_terms_of_service: state.has_accepted_terms_of_service(cx),
1271            account_too_young: user_store.account_too_young(),
1272            accept_terms_of_service_in_progress: state.accept_terms_of_service_task.is_some(),
1273            accept_terms_of_service_callback: self.accept_terms_of_service_callback.clone(),
1274            sign_in_callback: self.sign_in_callback.clone(),
1275        }
1276    }
1277}
1278
1279impl Component for ZedAiConfiguration {
1280    fn scope() -> ComponentScope {
1281        ComponentScope::Agent
1282    }
1283
1284    fn preview(_window: &mut Window, _cx: &mut App) -> Option<AnyElement> {
1285        fn configuration(
1286            is_connected: bool,
1287            plan: Option<proto::Plan>,
1288            eligible_for_trial: bool,
1289            account_too_young: bool,
1290            has_accepted_terms_of_service: bool,
1291        ) -> AnyElement {
1292            ZedAiConfiguration {
1293                is_connected,
1294                plan,
1295                subscription_period: plan
1296                    .is_some()
1297                    .then(|| (Utc::now(), Utc::now() + chrono::Duration::days(7))),
1298                eligible_for_trial,
1299                has_accepted_terms_of_service,
1300                account_too_young,
1301                accept_terms_of_service_in_progress: false,
1302                accept_terms_of_service_callback: Arc::new(|_, _| {}),
1303                sign_in_callback: Arc::new(|_, _| {}),
1304            }
1305            .into_any_element()
1306        }
1307
1308        Some(
1309            v_flex()
1310                .p_4()
1311                .gap_4()
1312                .children(vec![
1313                    single_example(
1314                        "Not connected",
1315                        configuration(false, None, false, false, true),
1316                    ),
1317                    single_example(
1318                        "Accept Terms of Service",
1319                        configuration(true, None, true, false, false),
1320                    ),
1321                    single_example(
1322                        "No Plan - Not eligible for trial",
1323                        configuration(true, None, false, false, true),
1324                    ),
1325                    single_example(
1326                        "No Plan - Eligible for trial",
1327                        configuration(true, None, true, false, true),
1328                    ),
1329                    single_example(
1330                        "Free Plan",
1331                        configuration(true, Some(proto::Plan::Free), true, false, true),
1332                    ),
1333                    single_example(
1334                        "Zed Pro Trial Plan",
1335                        configuration(true, Some(proto::Plan::ZedProTrial), true, false, true),
1336                    ),
1337                    single_example(
1338                        "Zed Pro Plan",
1339                        configuration(true, Some(proto::Plan::ZedPro), true, false, true),
1340                    ),
1341                ])
1342                .into_any_element(),
1343        )
1344    }
1345}
1346
1347#[cfg(test)]
1348mod tests {
1349    use super::*;
1350    use http_client::http::{HeaderMap, StatusCode};
1351    use language_model::LanguageModelCompletionError;
1352
1353    #[test]
1354    fn test_api_error_conversion_with_upstream_http_error() {
1355        // upstream_http_error with 503 status should become ServerOverloaded
1356        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}"#;
1357
1358        let api_error = ApiError {
1359            status: StatusCode::INTERNAL_SERVER_ERROR,
1360            body: error_body.to_string(),
1361            headers: HeaderMap::new(),
1362        };
1363
1364        let completion_error: LanguageModelCompletionError = api_error.into();
1365
1366        match completion_error {
1367            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1368                assert_eq!(
1369                    message,
1370                    "Received an error from the Anthropic API: upstream connect error or disconnect/reset before headers, reset reason: connection timeout"
1371                );
1372            }
1373            _ => panic!(
1374                "Expected UpstreamProviderError for upstream 503, got: {:?}",
1375                completion_error
1376            ),
1377        }
1378
1379        // upstream_http_error with 500 status should become ApiInternalServerError
1380        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the OpenAI API: internal server error","upstream_status":500}"#;
1381
1382        let api_error = ApiError {
1383            status: StatusCode::INTERNAL_SERVER_ERROR,
1384            body: error_body.to_string(),
1385            headers: HeaderMap::new(),
1386        };
1387
1388        let completion_error: LanguageModelCompletionError = api_error.into();
1389
1390        match completion_error {
1391            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1392                assert_eq!(
1393                    message,
1394                    "Received an error from the OpenAI API: internal server error"
1395                );
1396            }
1397            _ => panic!(
1398                "Expected UpstreamProviderError for upstream 500, got: {:?}",
1399                completion_error
1400            ),
1401        }
1402
1403        // upstream_http_error with 429 status should become RateLimitExceeded
1404        let error_body = r#"{"code":"upstream_http_error","message":"Received an error from the Google API: rate limit exceeded","upstream_status":429}"#;
1405
1406        let api_error = ApiError {
1407            status: StatusCode::INTERNAL_SERVER_ERROR,
1408            body: error_body.to_string(),
1409            headers: HeaderMap::new(),
1410        };
1411
1412        let completion_error: LanguageModelCompletionError = api_error.into();
1413
1414        match completion_error {
1415            LanguageModelCompletionError::UpstreamProviderError { message, .. } => {
1416                assert_eq!(
1417                    message,
1418                    "Received an error from the Google API: rate limit exceeded"
1419                );
1420            }
1421            _ => panic!(
1422                "Expected UpstreamProviderError for upstream 429, got: {:?}",
1423                completion_error
1424            ),
1425        }
1426
1427        // Regular 500 error without upstream_http_error should remain ApiInternalServerError for Zed
1428        let error_body = "Regular internal server error";
1429
1430        let api_error = ApiError {
1431            status: StatusCode::INTERNAL_SERVER_ERROR,
1432            body: error_body.to_string(),
1433            headers: HeaderMap::new(),
1434        };
1435
1436        let completion_error: LanguageModelCompletionError = api_error.into();
1437
1438        match completion_error {
1439            LanguageModelCompletionError::ApiInternalServerError { provider, message } => {
1440                assert_eq!(provider, PROVIDER_NAME);
1441                assert_eq!(message, "Regular internal server error");
1442            }
1443            _ => panic!(
1444                "Expected ApiInternalServerError for regular 500, got: {:?}",
1445                completion_error
1446            ),
1447        }
1448
1449        // upstream_http_429 format should be converted to UpstreamProviderError
1450        let error_body = r#"{"code":"upstream_http_429","message":"Upstream Anthropic rate limit exceeded.","retry_after":30.5}"#;
1451
1452        let api_error = ApiError {
1453            status: StatusCode::INTERNAL_SERVER_ERROR,
1454            body: error_body.to_string(),
1455            headers: HeaderMap::new(),
1456        };
1457
1458        let completion_error: LanguageModelCompletionError = api_error.into();
1459
1460        match completion_error {
1461            LanguageModelCompletionError::UpstreamProviderError {
1462                message,
1463                status,
1464                retry_after,
1465            } => {
1466                assert_eq!(message, "Upstream Anthropic rate limit exceeded.");
1467                assert_eq!(status, StatusCode::TOO_MANY_REQUESTS);
1468                assert_eq!(retry_after, Some(Duration::from_secs_f64(30.5)));
1469            }
1470            _ => panic!(
1471                "Expected UpstreamProviderError for upstream_http_429, got: {:?}",
1472                completion_error
1473            ),
1474        }
1475
1476        // Invalid JSON in error body should fall back to regular error handling
1477        let error_body = "Not JSON at all";
1478
1479        let api_error = ApiError {
1480            status: StatusCode::INTERNAL_SERVER_ERROR,
1481            body: error_body.to_string(),
1482            headers: HeaderMap::new(),
1483        };
1484
1485        let completion_error: LanguageModelCompletionError = api_error.into();
1486
1487        match completion_error {
1488            LanguageModelCompletionError::ApiInternalServerError { provider, .. } => {
1489                assert_eq!(provider, PROVIDER_NAME);
1490            }
1491            _ => panic!(
1492                "Expected ApiInternalServerError for invalid JSON, got: {:?}",
1493                completion_error
1494            ),
1495        }
1496    }
1497}