1use anthropic::{AnthropicError, AnthropicModelMode};
2use anyhow::{anyhow, Result};
3use client::{
4 zed_urls, Client, PerformCompletionParams, UserStore, EXPIRED_LLM_TOKEN_HEADER_NAME,
5 MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME,
6};
7use collections::BTreeMap;
8use feature_flags::{FeatureFlagAppExt, LlmClosedBeta, ZedPro};
9use futures::{
10 future::BoxFuture, stream::BoxStream, AsyncBufReadExt, FutureExt, Stream, StreamExt,
11 TryStreamExt as _,
12};
13use gpui::{AnyElement, AnyView, App, AsyncApp, Context, Entity, Subscription, Task};
14use http_client::{AsyncBody, HttpClient, Method, Response, StatusCode};
15use language_model::{
16 AuthenticateError, CloudModel, LanguageModel, LanguageModelCacheConfiguration, LanguageModelId,
17 LanguageModelName, LanguageModelProviderId, LanguageModelProviderName,
18 LanguageModelProviderState, LanguageModelProviderTosView, LanguageModelRequest, RateLimiter,
19 ZED_CLOUD_PROVIDER_ID,
20};
21use language_model::{
22 LanguageModelAvailability, LanguageModelCompletionEvent, LanguageModelProvider, LlmApiToken,
23 MaxMonthlySpendReachedError, PaymentRequiredError, RefreshLlmTokenListener,
24};
25use schemars::JsonSchema;
26use serde::{de::DeserializeOwned, Deserialize, Serialize};
27use serde_json::value::RawValue;
28use settings::{Settings, SettingsStore};
29use smol::io::{AsyncReadExt, BufReader};
30use smol::Timer;
31use std::{
32 future,
33 sync::{Arc, LazyLock},
34 time::Duration,
35};
36use strum::IntoEnumIterator;
37use ui::{prelude::*, TintColor};
38
39use crate::provider::anthropic::{
40 count_anthropic_tokens, into_anthropic, map_to_language_model_completion_events,
41};
42use crate::provider::google::into_google;
43use crate::provider::open_ai::{count_open_ai_tokens, into_open_ai};
44use crate::AllLanguageModelSettings;
45
46pub const PROVIDER_NAME: &str = "Zed";
47
48const ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON: Option<&str> =
49 option_env!("ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON");
50
51fn zed_cloud_provider_additional_models() -> &'static [AvailableModel] {
52 static ADDITIONAL_MODELS: LazyLock<Vec<AvailableModel>> = LazyLock::new(|| {
53 ZED_CLOUD_PROVIDER_ADDITIONAL_MODELS_JSON
54 .map(|json| serde_json::from_str(json).unwrap())
55 .unwrap_or_default()
56 });
57 ADDITIONAL_MODELS.as_slice()
58}
59
60#[derive(Default, Clone, Debug, PartialEq)]
61pub struct ZedDotDevSettings {
62 pub available_models: Vec<AvailableModel>,
63}
64
65#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
66#[serde(rename_all = "lowercase")]
67pub enum AvailableProvider {
68 Anthropic,
69 OpenAi,
70 Google,
71}
72
73#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
74pub struct AvailableModel {
75 /// The provider of the language model.
76 pub provider: AvailableProvider,
77 /// The model's name in the provider's API. e.g. claude-3-5-sonnet-20240620
78 pub name: String,
79 /// The name displayed in the UI, such as in the assistant panel model dropdown menu.
80 pub display_name: Option<String>,
81 /// The size of the context window, indicating the maximum number of tokens the model can process.
82 pub max_tokens: usize,
83 /// The maximum number of output tokens allowed by the model.
84 pub max_output_tokens: Option<u32>,
85 /// The maximum number of completion tokens allowed by the model (o1-* only)
86 pub max_completion_tokens: Option<u32>,
87 /// Override this model with a different Anthropic model for tool calls.
88 pub tool_override: Option<String>,
89 /// Indicates whether this custom model supports caching.
90 pub cache_configuration: Option<LanguageModelCacheConfiguration>,
91 /// The default temperature to use for this model.
92 pub default_temperature: Option<f32>,
93 /// Any extra beta headers to provide when using the model.
94 #[serde(default)]
95 pub extra_beta_headers: Vec<String>,
96 /// The model's mode (e.g. thinking)
97 pub mode: Option<ModelMode>,
98}
99
100#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
101#[serde(tag = "type", rename_all = "lowercase")]
102pub enum ModelMode {
103 #[default]
104 Default,
105 Thinking {
106 /// The maximum number of tokens to use for reasoning. Must be lower than the model's `max_output_tokens`.
107 budget_tokens: Option<u32>,
108 },
109}
110
111impl From<ModelMode> for AnthropicModelMode {
112 fn from(value: ModelMode) -> Self {
113 match value {
114 ModelMode::Default => AnthropicModelMode::Default,
115 ModelMode::Thinking { budget_tokens } => AnthropicModelMode::Thinking { budget_tokens },
116 }
117 }
118}
119
120pub struct CloudLanguageModelProvider {
121 client: Arc<Client>,
122 state: gpui::Entity<State>,
123 _maintain_client_status: Task<()>,
124}
125
126pub struct State {
127 client: Arc<Client>,
128 llm_api_token: LlmApiToken,
129 user_store: Entity<UserStore>,
130 status: client::Status,
131 accept_terms: Option<Task<Result<()>>>,
132 _settings_subscription: Subscription,
133 _llm_token_subscription: Subscription,
134}
135
136impl State {
137 fn new(
138 client: Arc<Client>,
139 user_store: Entity<UserStore>,
140 status: client::Status,
141 cx: &mut Context<Self>,
142 ) -> Self {
143 let refresh_llm_token_listener = RefreshLlmTokenListener::global(cx);
144
145 Self {
146 client: client.clone(),
147 llm_api_token: LlmApiToken::default(),
148 user_store,
149 status,
150 accept_terms: None,
151 _settings_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
152 cx.notify();
153 }),
154 _llm_token_subscription: cx.subscribe(
155 &refresh_llm_token_listener,
156 |this, _listener, _event, cx| {
157 let client = this.client.clone();
158 let llm_api_token = this.llm_api_token.clone();
159 cx.spawn(async move |_this, _cx| {
160 llm_api_token.refresh(&client).await?;
161 anyhow::Ok(())
162 })
163 .detach_and_log_err(cx);
164 },
165 ),
166 }
167 }
168
169 fn is_signed_out(&self) -> bool {
170 self.status.is_signed_out()
171 }
172
173 fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
174 let client = self.client.clone();
175 cx.spawn(async move |this, cx| {
176 client.authenticate_and_connect(true, &cx).await?;
177 this.update(cx, |_, cx| cx.notify())
178 })
179 }
180
181 fn has_accepted_terms_of_service(&self, cx: &App) -> bool {
182 self.user_store
183 .read(cx)
184 .current_user_has_accepted_terms()
185 .unwrap_or(false)
186 }
187
188 fn accept_terms_of_service(&mut self, cx: &mut Context<Self>) {
189 let user_store = self.user_store.clone();
190 self.accept_terms = Some(cx.spawn(async move |this, cx| {
191 let _ = user_store
192 .update(cx, |store, cx| store.accept_terms_of_service(cx))?
193 .await;
194 this.update(cx, |this, cx| {
195 this.accept_terms = None;
196 cx.notify()
197 })
198 }));
199 }
200}
201
202impl CloudLanguageModelProvider {
203 pub fn new(user_store: Entity<UserStore>, client: Arc<Client>, cx: &mut App) -> Self {
204 let mut status_rx = client.status();
205 let status = *status_rx.borrow();
206
207 let state = cx.new(|cx| State::new(client.clone(), user_store.clone(), status, cx));
208
209 let state_ref = state.downgrade();
210 let maintain_client_status = cx.spawn(async move |cx| {
211 while let Some(status) = status_rx.next().await {
212 if let Some(this) = state_ref.upgrade() {
213 _ = this.update(cx, |this, cx| {
214 if this.status != status {
215 this.status = status;
216 cx.notify();
217 }
218 });
219 } else {
220 break;
221 }
222 }
223 });
224
225 Self {
226 client,
227 state: state.clone(),
228 _maintain_client_status: maintain_client_status,
229 }
230 }
231}
232
233impl LanguageModelProviderState for CloudLanguageModelProvider {
234 type ObservableEntity = State;
235
236 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
237 Some(self.state.clone())
238 }
239}
240
241impl LanguageModelProvider for CloudLanguageModelProvider {
242 fn id(&self) -> LanguageModelProviderId {
243 LanguageModelProviderId(ZED_CLOUD_PROVIDER_ID.into())
244 }
245
246 fn name(&self) -> LanguageModelProviderName {
247 LanguageModelProviderName(PROVIDER_NAME.into())
248 }
249
250 fn icon(&self) -> IconName {
251 IconName::AiZed
252 }
253
254 fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
255 let llm_api_token = self.state.read(cx).llm_api_token.clone();
256 let model = CloudModel::Anthropic(anthropic::Model::default());
257 Some(Arc::new(CloudLanguageModel {
258 id: LanguageModelId::from(model.id().to_string()),
259 model,
260 llm_api_token: llm_api_token.clone(),
261 client: self.client.clone(),
262 request_limiter: RateLimiter::new(4),
263 }))
264 }
265
266 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
267 let mut models = BTreeMap::default();
268
269 if cx.is_staff() {
270 for model in anthropic::Model::iter() {
271 if !matches!(model, anthropic::Model::Custom { .. }) {
272 models.insert(model.id().to_string(), CloudModel::Anthropic(model));
273 }
274 }
275 for model in open_ai::Model::iter() {
276 if !matches!(model, open_ai::Model::Custom { .. }) {
277 models.insert(model.id().to_string(), CloudModel::OpenAi(model));
278 }
279 }
280 for model in google_ai::Model::iter() {
281 if !matches!(model, google_ai::Model::Custom { .. }) {
282 models.insert(model.id().to_string(), CloudModel::Google(model));
283 }
284 }
285 } else {
286 models.insert(
287 anthropic::Model::Claude3_5Sonnet.id().to_string(),
288 CloudModel::Anthropic(anthropic::Model::Claude3_5Sonnet),
289 );
290 models.insert(
291 anthropic::Model::Claude3_7Sonnet.id().to_string(),
292 CloudModel::Anthropic(anthropic::Model::Claude3_7Sonnet),
293 );
294 models.insert(
295 anthropic::Model::Claude3_7SonnetThinking.id().to_string(),
296 CloudModel::Anthropic(anthropic::Model::Claude3_7SonnetThinking),
297 );
298 }
299
300 let llm_closed_beta_models = if cx.has_flag::<LlmClosedBeta>() {
301 zed_cloud_provider_additional_models()
302 } else {
303 &[]
304 };
305
306 // Override with available models from settings
307 for model in AllLanguageModelSettings::get_global(cx)
308 .zed_dot_dev
309 .available_models
310 .iter()
311 .chain(llm_closed_beta_models)
312 .cloned()
313 {
314 let model = match model.provider {
315 AvailableProvider::Anthropic => CloudModel::Anthropic(anthropic::Model::Custom {
316 name: model.name.clone(),
317 display_name: model.display_name.clone(),
318 max_tokens: model.max_tokens,
319 tool_override: model.tool_override.clone(),
320 cache_configuration: model.cache_configuration.as_ref().map(|config| {
321 anthropic::AnthropicModelCacheConfiguration {
322 max_cache_anchors: config.max_cache_anchors,
323 should_speculate: config.should_speculate,
324 min_total_token: config.min_total_token,
325 }
326 }),
327 default_temperature: model.default_temperature,
328 max_output_tokens: model.max_output_tokens,
329 extra_beta_headers: model.extra_beta_headers.clone(),
330 mode: model.mode.unwrap_or_default().into(),
331 }),
332 AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {
333 name: model.name.clone(),
334 display_name: model.display_name.clone(),
335 max_tokens: model.max_tokens,
336 max_output_tokens: model.max_output_tokens,
337 max_completion_tokens: model.max_completion_tokens,
338 }),
339 AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {
340 name: model.name.clone(),
341 display_name: model.display_name.clone(),
342 max_tokens: model.max_tokens,
343 }),
344 };
345 models.insert(model.id().to_string(), model.clone());
346 }
347
348 let llm_api_token = self.state.read(cx).llm_api_token.clone();
349 models
350 .into_values()
351 .map(|model| {
352 Arc::new(CloudLanguageModel {
353 id: LanguageModelId::from(model.id().to_string()),
354 model,
355 llm_api_token: llm_api_token.clone(),
356 client: self.client.clone(),
357 request_limiter: RateLimiter::new(4),
358 }) as Arc<dyn LanguageModel>
359 })
360 .collect()
361 }
362
363 fn is_authenticated(&self, cx: &App) -> bool {
364 !self.state.read(cx).is_signed_out()
365 }
366
367 fn authenticate(&self, _cx: &mut App) -> Task<Result<(), AuthenticateError>> {
368 Task::ready(Ok(()))
369 }
370
371 fn configuration_view(&self, _: &mut Window, cx: &mut App) -> AnyView {
372 cx.new(|_| ConfigurationView {
373 state: self.state.clone(),
374 })
375 .into()
376 }
377
378 fn must_accept_terms(&self, cx: &App) -> bool {
379 !self.state.read(cx).has_accepted_terms_of_service(cx)
380 }
381
382 fn render_accept_terms(
383 &self,
384 view: LanguageModelProviderTosView,
385 cx: &mut App,
386 ) -> Option<AnyElement> {
387 render_accept_terms(self.state.clone(), view, cx)
388 }
389
390 fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
391 Task::ready(Ok(()))
392 }
393}
394
395fn render_accept_terms(
396 state: Entity<State>,
397 view_kind: LanguageModelProviderTosView,
398 cx: &mut App,
399) -> Option<AnyElement> {
400 if state.read(cx).has_accepted_terms_of_service(cx) {
401 return None;
402 }
403
404 let accept_terms_disabled = state.read(cx).accept_terms.is_some();
405
406 let terms_button = Button::new("terms_of_service", "Terms of Service")
407 .style(ButtonStyle::Subtle)
408 .icon(IconName::ArrowUpRight)
409 .icon_color(Color::Muted)
410 .icon_size(IconSize::XSmall)
411 .on_click(move |_, _window, cx| cx.open_url("https://zed.dev/terms-of-service"));
412
413 let text = "To start using Zed AI, please read and accept the";
414
415 let form = v_flex()
416 .w_full()
417 .gap_2()
418 .child(
419 h_flex()
420 .flex_wrap()
421 .items_start()
422 .child(Label::new(text))
423 .child(terms_button),
424 )
425 .child({
426 let button_container = h_flex().w_full().child(
427 Button::new("accept_terms", "I accept the Terms of Service")
428 .style(ButtonStyle::Tinted(TintColor::Accent))
429 .disabled(accept_terms_disabled)
430 .on_click({
431 let state = state.downgrade();
432 move |_, _window, cx| {
433 state
434 .update(cx, |state, cx| state.accept_terms_of_service(cx))
435 .ok();
436 }
437 }),
438 );
439
440 match view_kind {
441 LanguageModelProviderTosView::PromptEditorPopup => button_container.justify_end(),
442 LanguageModelProviderTosView::Configuration
443 | LanguageModelProviderTosView::ThreadEmptyState => {
444 button_container.justify_start()
445 }
446 }
447 });
448
449 Some(form.into_any())
450}
451
452pub struct CloudLanguageModel {
453 id: LanguageModelId,
454 model: CloudModel,
455 llm_api_token: LlmApiToken,
456 client: Arc<Client>,
457 request_limiter: RateLimiter,
458}
459
460impl CloudLanguageModel {
461 const MAX_RETRIES: usize = 3;
462
463 async fn perform_llm_completion(
464 client: Arc<Client>,
465 llm_api_token: LlmApiToken,
466 body: PerformCompletionParams,
467 ) -> Result<Response<AsyncBody>> {
468 let http_client = &client.http_client();
469
470 let mut token = llm_api_token.acquire(&client).await?;
471 let mut retries_remaining = Self::MAX_RETRIES;
472 let mut retry_delay = Duration::from_secs(1);
473
474 loop {
475 let request_builder = http_client::Request::builder();
476 let request = request_builder
477 .method(Method::POST)
478 .uri(http_client.build_zed_llm_url("/completion", &[])?.as_ref())
479 .header("Content-Type", "application/json")
480 .header("Authorization", format!("Bearer {token}"))
481 .body(serde_json::to_string(&body)?.into())?;
482 let mut response = http_client.send(request).await?;
483 let status = response.status();
484 if status.is_success() {
485 return Ok(response);
486 } else if response
487 .headers()
488 .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
489 .is_some()
490 {
491 retries_remaining -= 1;
492 token = llm_api_token.refresh(&client).await?;
493 } else if status == StatusCode::FORBIDDEN
494 && response
495 .headers()
496 .get(MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME)
497 .is_some()
498 {
499 return Err(anyhow!(MaxMonthlySpendReachedError));
500 } else if status.as_u16() >= 500 && status.as_u16() < 600 {
501 // If we encounter an error in the 500 range, retry after a delay.
502 // We've seen at least these in the wild from API providers:
503 // * 500 Internal Server Error
504 // * 502 Bad Gateway
505 // * 529 Service Overloaded
506
507 if retries_remaining == 0 {
508 let mut body = String::new();
509 response.body_mut().read_to_string(&mut body).await?;
510 return Err(anyhow!(
511 "cloud language model completion failed after {} retries with status {status}: {body}",
512 Self::MAX_RETRIES
513 ));
514 }
515
516 Timer::after(retry_delay).await;
517
518 retries_remaining -= 1;
519 retry_delay *= 2; // If it fails again, wait longer.
520 } else if status == StatusCode::PAYMENT_REQUIRED {
521 return Err(anyhow!(PaymentRequiredError));
522 } else {
523 let mut body = String::new();
524 response.body_mut().read_to_string(&mut body).await?;
525 return Err(anyhow!(
526 "cloud language model completion failed with status {status}: {body}",
527 ));
528 }
529 }
530 }
531}
532
533impl LanguageModel for CloudLanguageModel {
534 fn id(&self) -> LanguageModelId {
535 self.id.clone()
536 }
537
538 fn name(&self) -> LanguageModelName {
539 LanguageModelName::from(self.model.display_name().to_string())
540 }
541
542 fn icon(&self) -> Option<IconName> {
543 self.model.icon()
544 }
545
546 fn provider_id(&self) -> LanguageModelProviderId {
547 LanguageModelProviderId(ZED_CLOUD_PROVIDER_ID.into())
548 }
549
550 fn provider_name(&self) -> LanguageModelProviderName {
551 LanguageModelProviderName(PROVIDER_NAME.into())
552 }
553
554 fn telemetry_id(&self) -> String {
555 format!("zed.dev/{}", self.model.id())
556 }
557
558 fn availability(&self) -> LanguageModelAvailability {
559 self.model.availability()
560 }
561
562 fn max_token_count(&self) -> usize {
563 self.model.max_token_count()
564 }
565
566 fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
567 match &self.model {
568 CloudModel::Anthropic(model) => {
569 model
570 .cache_configuration()
571 .map(|cache| LanguageModelCacheConfiguration {
572 max_cache_anchors: cache.max_cache_anchors,
573 should_speculate: cache.should_speculate,
574 min_total_token: cache.min_total_token,
575 })
576 }
577 CloudModel::OpenAi(_) | CloudModel::Google(_) => None,
578 }
579 }
580
581 fn count_tokens(
582 &self,
583 request: LanguageModelRequest,
584 cx: &App,
585 ) -> BoxFuture<'static, Result<usize>> {
586 match self.model.clone() {
587 CloudModel::Anthropic(_) => count_anthropic_tokens(request, cx),
588 CloudModel::OpenAi(model) => count_open_ai_tokens(request, model, cx),
589 CloudModel::Google(model) => {
590 let client = self.client.clone();
591 let request = into_google(request, model.id().into());
592 let request = google_ai::CountTokensRequest {
593 contents: request.contents,
594 };
595 async move {
596 let request = serde_json::to_string(&request)?;
597 let response = client
598 .request(proto::CountLanguageModelTokens {
599 provider: proto::LanguageModelProvider::Google as i32,
600 request,
601 })
602 .await?;
603 Ok(response.token_count as usize)
604 }
605 .boxed()
606 }
607 }
608 }
609
610 fn stream_completion(
611 &self,
612 request: LanguageModelRequest,
613 _cx: &AsyncApp,
614 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<LanguageModelCompletionEvent>>>> {
615 match &self.model {
616 CloudModel::Anthropic(model) => {
617 let request = into_anthropic(
618 request,
619 model.request_id().into(),
620 model.default_temperature(),
621 model.max_output_tokens(),
622 model.mode(),
623 );
624 let client = self.client.clone();
625 let llm_api_token = self.llm_api_token.clone();
626 let future = self.request_limiter.stream(async move {
627 let response = Self::perform_llm_completion(
628 client.clone(),
629 llm_api_token,
630 PerformCompletionParams {
631 provider: client::LanguageModelProvider::Anthropic,
632 model: request.model.clone(),
633 provider_request: RawValue::from_string(serde_json::to_string(
634 &request,
635 )?)?,
636 },
637 )
638 .await?;
639 Ok(map_to_language_model_completion_events(Box::pin(
640 response_lines(response).map_err(AnthropicError::Other),
641 )))
642 });
643 async move { Ok(future.await?.boxed()) }.boxed()
644 }
645 CloudModel::OpenAi(model) => {
646 let client = self.client.clone();
647 let request = into_open_ai(request, model.id().into(), model.max_output_tokens());
648 let llm_api_token = self.llm_api_token.clone();
649 let future = self.request_limiter.stream(async move {
650 let response = Self::perform_llm_completion(
651 client.clone(),
652 llm_api_token,
653 PerformCompletionParams {
654 provider: client::LanguageModelProvider::OpenAi,
655 model: request.model.clone(),
656 provider_request: RawValue::from_string(serde_json::to_string(
657 &request,
658 )?)?,
659 },
660 )
661 .await?;
662 Ok(open_ai::extract_text_from_events(response_lines(response)))
663 });
664 async move {
665 Ok(future
666 .await?
667 .map(|result| result.map(LanguageModelCompletionEvent::Text))
668 .boxed())
669 }
670 .boxed()
671 }
672 CloudModel::Google(model) => {
673 let client = self.client.clone();
674 let request = into_google(request, model.id().into());
675 let llm_api_token = self.llm_api_token.clone();
676 let future = self.request_limiter.stream(async move {
677 let response = Self::perform_llm_completion(
678 client.clone(),
679 llm_api_token,
680 PerformCompletionParams {
681 provider: client::LanguageModelProvider::Google,
682 model: request.model.clone(),
683 provider_request: RawValue::from_string(serde_json::to_string(
684 &request,
685 )?)?,
686 },
687 )
688 .await?;
689 Ok(google_ai::extract_text_from_events(response_lines(
690 response,
691 )))
692 });
693 async move {
694 Ok(future
695 .await?
696 .map(|result| result.map(LanguageModelCompletionEvent::Text))
697 .boxed())
698 }
699 .boxed()
700 }
701 }
702 }
703
704 fn use_any_tool(
705 &self,
706 request: LanguageModelRequest,
707 tool_name: String,
708 tool_description: String,
709 input_schema: serde_json::Value,
710 _cx: &AsyncApp,
711 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>> {
712 let client = self.client.clone();
713 let llm_api_token = self.llm_api_token.clone();
714
715 match &self.model {
716 CloudModel::Anthropic(model) => {
717 let mut request = into_anthropic(
718 request,
719 model.tool_model_id().into(),
720 model.default_temperature(),
721 model.max_output_tokens(),
722 model.mode(),
723 );
724 request.tool_choice = Some(anthropic::ToolChoice::Tool {
725 name: tool_name.clone(),
726 });
727 request.tools = vec![anthropic::Tool {
728 name: tool_name.clone(),
729 description: tool_description,
730 input_schema,
731 }];
732
733 self.request_limiter
734 .run(async move {
735 let response = Self::perform_llm_completion(
736 client.clone(),
737 llm_api_token,
738 PerformCompletionParams {
739 provider: client::LanguageModelProvider::Anthropic,
740 model: request.model.clone(),
741 provider_request: RawValue::from_string(serde_json::to_string(
742 &request,
743 )?)?,
744 },
745 )
746 .await?;
747
748 Ok(anthropic::extract_tool_args_from_events(
749 tool_name,
750 Box::pin(response_lines(response)),
751 )
752 .await?
753 .boxed())
754 })
755 .boxed()
756 }
757 CloudModel::OpenAi(model) => {
758 let mut request =
759 into_open_ai(request, model.id().into(), model.max_output_tokens());
760 request.tool_choice = Some(open_ai::ToolChoice::Other(
761 open_ai::ToolDefinition::Function {
762 function: open_ai::FunctionDefinition {
763 name: tool_name.clone(),
764 description: None,
765 parameters: None,
766 },
767 },
768 ));
769 request.tools = vec![open_ai::ToolDefinition::Function {
770 function: open_ai::FunctionDefinition {
771 name: tool_name.clone(),
772 description: Some(tool_description),
773 parameters: Some(input_schema),
774 },
775 }];
776
777 self.request_limiter
778 .run(async move {
779 let response = Self::perform_llm_completion(
780 client.clone(),
781 llm_api_token,
782 PerformCompletionParams {
783 provider: client::LanguageModelProvider::OpenAi,
784 model: request.model.clone(),
785 provider_request: RawValue::from_string(serde_json::to_string(
786 &request,
787 )?)?,
788 },
789 )
790 .await?;
791
792 Ok(open_ai::extract_tool_args_from_events(
793 tool_name,
794 Box::pin(response_lines(response)),
795 )
796 .await?
797 .boxed())
798 })
799 .boxed()
800 }
801 CloudModel::Google(_) => {
802 future::ready(Err(anyhow!("tool use not implemented for Google AI"))).boxed()
803 }
804 }
805 }
806}
807
808fn response_lines<T: DeserializeOwned>(
809 response: Response<AsyncBody>,
810) -> impl Stream<Item = Result<T>> {
811 futures::stream::try_unfold(
812 (String::new(), BufReader::new(response.into_body())),
813 move |(mut line, mut body)| async {
814 match body.read_line(&mut line).await {
815 Ok(0) => Ok(None),
816 Ok(_) => {
817 let event: T = serde_json::from_str(&line)?;
818 line.clear();
819 Ok(Some((event, (line, body))))
820 }
821 Err(e) => Err(e.into()),
822 }
823 },
824 )
825}
826
827struct ConfigurationView {
828 state: gpui::Entity<State>,
829}
830
831impl ConfigurationView {
832 fn authenticate(&mut self, cx: &mut Context<Self>) {
833 self.state.update(cx, |state, cx| {
834 state.authenticate(cx).detach_and_log_err(cx);
835 });
836 cx.notify();
837 }
838}
839
840impl Render for ConfigurationView {
841 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
842 const ZED_AI_URL: &str = "https://zed.dev/ai";
843
844 let is_connected = !self.state.read(cx).is_signed_out();
845 let plan = self.state.read(cx).user_store.read(cx).current_plan();
846 let has_accepted_terms = self.state.read(cx).has_accepted_terms_of_service(cx);
847
848 let is_pro = plan == Some(proto::Plan::ZedPro);
849 let subscription_text = Label::new(if is_pro {
850 "You have full access to Zed's hosted LLMs, which include models from Anthropic, OpenAI, and Google. They come with faster speeds and higher limits through Zed Pro."
851 } else {
852 "You have basic access to models from Anthropic through the Zed AI Free plan."
853 });
854 let manage_subscription_button = if is_pro {
855 Some(
856 h_flex().child(
857 Button::new("manage_settings", "Manage Subscription")
858 .style(ButtonStyle::Tinted(TintColor::Accent))
859 .on_click(
860 cx.listener(|_, _, _, cx| cx.open_url(&zed_urls::account_url(cx))),
861 ),
862 ),
863 )
864 } else if cx.has_flag::<ZedPro>() {
865 Some(
866 h_flex()
867 .gap_2()
868 .child(
869 Button::new("learn_more", "Learn more")
870 .style(ButtonStyle::Subtle)
871 .on_click(cx.listener(|_, _, _, cx| cx.open_url(ZED_AI_URL))),
872 )
873 .child(
874 Button::new("upgrade", "Upgrade")
875 .style(ButtonStyle::Subtle)
876 .color(Color::Accent)
877 .on_click(
878 cx.listener(|_, _, _, cx| cx.open_url(&zed_urls::account_url(cx))),
879 ),
880 ),
881 )
882 } else {
883 None
884 };
885
886 if is_connected {
887 v_flex()
888 .gap_3()
889 .w_full()
890 .children(render_accept_terms(
891 self.state.clone(),
892 LanguageModelProviderTosView::Configuration,
893 cx,
894 ))
895 .when(has_accepted_terms, |this| {
896 this.child(subscription_text)
897 .children(manage_subscription_button)
898 })
899 } else {
900 v_flex()
901 .gap_2()
902 .child(Label::new("Use Zed AI to access hosted language models."))
903 .child(
904 Button::new("sign_in", "Sign In")
905 .icon_color(Color::Muted)
906 .icon(IconName::Github)
907 .icon_position(IconPosition::Start)
908 .on_click(cx.listener(move |this, _, _, cx| this.authenticate(cx))),
909 )
910 }
911 }
912}