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