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