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