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(async move |_this, _cx| {
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(async move |this, cx| {
152 client.authenticate_and_connect(true, &cx).await?;
153 this.update(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(async move |this, cx| {
167 let _ = user_store
168 .update(cx, |store, cx| store.accept_terms_of_service(cx))?
169 .await;
170 this.update(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(async move |cx| {
187 while let Some(status) = status_rx.next().await {
188 if let Some(this) = state_ref.upgrade() {
189 _ = this.update(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 .child(
390 h_flex()
391 .flex_wrap()
392 .items_start()
393 .child(Label::new(text))
394 .child(terms_button),
395 )
396 .child({
397 let button_container = h_flex().w_full().child(
398 Button::new("accept_terms", "I accept the Terms of Service")
399 .style(ButtonStyle::Tinted(TintColor::Accent))
400 .disabled(accept_terms_disabled)
401 .on_click({
402 let state = state.downgrade();
403 move |_, _window, cx| {
404 state
405 .update(cx, |state, cx| state.accept_terms_of_service(cx))
406 .ok();
407 }
408 }),
409 );
410
411 match view_kind {
412 LanguageModelProviderTosView::PromptEditorPopup => button_container.justify_end(),
413 LanguageModelProviderTosView::Configuration
414 | LanguageModelProviderTosView::ThreadEmptyState => {
415 button_container.justify_start()
416 }
417 }
418 });
419
420 Some(form.into_any())
421}
422
423pub struct CloudLanguageModel {
424 id: LanguageModelId,
425 model: CloudModel,
426 llm_api_token: LlmApiToken,
427 client: Arc<Client>,
428 request_limiter: RateLimiter,
429}
430
431impl CloudLanguageModel {
432 async fn perform_llm_completion(
433 client: Arc<Client>,
434 llm_api_token: LlmApiToken,
435 body: PerformCompletionParams,
436 ) -> Result<Response<AsyncBody>> {
437 let http_client = &client.http_client();
438
439 let mut token = llm_api_token.acquire(&client).await?;
440 let mut did_retry = false;
441
442 let response = loop {
443 let request_builder = http_client::Request::builder();
444 let request = request_builder
445 .method(Method::POST)
446 .uri(http_client.build_zed_llm_url("/completion", &[])?.as_ref())
447 .header("Content-Type", "application/json")
448 .header("Authorization", format!("Bearer {token}"))
449 .body(serde_json::to_string(&body)?.into())?;
450 let mut response = http_client.send(request).await?;
451 if response.status().is_success() {
452 break response;
453 } else if !did_retry
454 && response
455 .headers()
456 .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
457 .is_some()
458 {
459 did_retry = true;
460 token = llm_api_token.refresh(&client).await?;
461 } else if response.status() == StatusCode::FORBIDDEN
462 && response
463 .headers()
464 .get(MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME)
465 .is_some()
466 {
467 break Err(anyhow!(MaxMonthlySpendReachedError))?;
468 } else if response.status() == StatusCode::PAYMENT_REQUIRED {
469 break Err(anyhow!(PaymentRequiredError))?;
470 } else {
471 let mut body = String::new();
472 response.body_mut().read_to_string(&mut body).await?;
473 break Err(anyhow!(
474 "cloud language model completion failed with status {}: {body}",
475 response.status()
476 ))?;
477 }
478 };
479
480 Ok(response)
481 }
482}
483
484impl LanguageModel for CloudLanguageModel {
485 fn id(&self) -> LanguageModelId {
486 self.id.clone()
487 }
488
489 fn name(&self) -> LanguageModelName {
490 LanguageModelName::from(self.model.display_name().to_string())
491 }
492
493 fn icon(&self) -> Option<IconName> {
494 self.model.icon()
495 }
496
497 fn provider_id(&self) -> LanguageModelProviderId {
498 LanguageModelProviderId(ZED_CLOUD_PROVIDER_ID.into())
499 }
500
501 fn provider_name(&self) -> LanguageModelProviderName {
502 LanguageModelProviderName(PROVIDER_NAME.into())
503 }
504
505 fn telemetry_id(&self) -> String {
506 format!("zed.dev/{}", self.model.id())
507 }
508
509 fn availability(&self) -> LanguageModelAvailability {
510 self.model.availability()
511 }
512
513 fn max_token_count(&self) -> usize {
514 self.model.max_token_count()
515 }
516
517 fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
518 match &self.model {
519 CloudModel::Anthropic(model) => {
520 model
521 .cache_configuration()
522 .map(|cache| LanguageModelCacheConfiguration {
523 max_cache_anchors: cache.max_cache_anchors,
524 should_speculate: cache.should_speculate,
525 min_total_token: cache.min_total_token,
526 })
527 }
528 CloudModel::OpenAi(_) | CloudModel::Google(_) => None,
529 }
530 }
531
532 fn count_tokens(
533 &self,
534 request: LanguageModelRequest,
535 cx: &App,
536 ) -> BoxFuture<'static, Result<usize>> {
537 match self.model.clone() {
538 CloudModel::Anthropic(_) => count_anthropic_tokens(request, cx),
539 CloudModel::OpenAi(model) => count_open_ai_tokens(request, model, cx),
540 CloudModel::Google(model) => {
541 let client = self.client.clone();
542 let request = into_google(request, model.id().into());
543 let request = google_ai::CountTokensRequest {
544 contents: request.contents,
545 };
546 async move {
547 let request = serde_json::to_string(&request)?;
548 let response = client
549 .request(proto::CountLanguageModelTokens {
550 provider: proto::LanguageModelProvider::Google as i32,
551 request,
552 })
553 .await?;
554 Ok(response.token_count as usize)
555 }
556 .boxed()
557 }
558 }
559 }
560
561 fn stream_completion(
562 &self,
563 request: LanguageModelRequest,
564 _cx: &AsyncApp,
565 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<LanguageModelCompletionEvent>>>> {
566 match &self.model {
567 CloudModel::Anthropic(model) => {
568 let request = into_anthropic(
569 request,
570 model.id().into(),
571 model.default_temperature(),
572 model.max_output_tokens(),
573 );
574 let client = self.client.clone();
575 let llm_api_token = self.llm_api_token.clone();
576 let future = self.request_limiter.stream(async move {
577 let response = Self::perform_llm_completion(
578 client.clone(),
579 llm_api_token,
580 PerformCompletionParams {
581 provider: client::LanguageModelProvider::Anthropic,
582 model: request.model.clone(),
583 provider_request: RawValue::from_string(serde_json::to_string(
584 &request,
585 )?)?,
586 },
587 )
588 .await?;
589 Ok(map_to_language_model_completion_events(Box::pin(
590 response_lines(response).map_err(AnthropicError::Other),
591 )))
592 });
593 async move { Ok(future.await?.boxed()) }.boxed()
594 }
595 CloudModel::OpenAi(model) => {
596 let client = self.client.clone();
597 let request = into_open_ai(request, model.id().into(), model.max_output_tokens());
598 let llm_api_token = self.llm_api_token.clone();
599 let future = self.request_limiter.stream(async move {
600 let response = Self::perform_llm_completion(
601 client.clone(),
602 llm_api_token,
603 PerformCompletionParams {
604 provider: client::LanguageModelProvider::OpenAi,
605 model: request.model.clone(),
606 provider_request: RawValue::from_string(serde_json::to_string(
607 &request,
608 )?)?,
609 },
610 )
611 .await?;
612 Ok(open_ai::extract_text_from_events(response_lines(response)))
613 });
614 async move {
615 Ok(future
616 .await?
617 .map(|result| result.map(LanguageModelCompletionEvent::Text))
618 .boxed())
619 }
620 .boxed()
621 }
622 CloudModel::Google(model) => {
623 let client = self.client.clone();
624 let request = into_google(request, model.id().into());
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::Google,
632 model: request.model.clone(),
633 provider_request: RawValue::from_string(serde_json::to_string(
634 &request,
635 )?)?,
636 },
637 )
638 .await?;
639 Ok(google_ai::extract_text_from_events(response_lines(
640 response,
641 )))
642 });
643 async move {
644 Ok(future
645 .await?
646 .map(|result| result.map(LanguageModelCompletionEvent::Text))
647 .boxed())
648 }
649 .boxed()
650 }
651 }
652 }
653
654 fn use_any_tool(
655 &self,
656 request: LanguageModelRequest,
657 tool_name: String,
658 tool_description: String,
659 input_schema: serde_json::Value,
660 _cx: &AsyncApp,
661 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>> {
662 let client = self.client.clone();
663 let llm_api_token = self.llm_api_token.clone();
664
665 match &self.model {
666 CloudModel::Anthropic(model) => {
667 let mut request = into_anthropic(
668 request,
669 model.tool_model_id().into(),
670 model.default_temperature(),
671 model.max_output_tokens(),
672 );
673 request.tool_choice = Some(anthropic::ToolChoice::Tool {
674 name: tool_name.clone(),
675 });
676 request.tools = vec![anthropic::Tool {
677 name: tool_name.clone(),
678 description: tool_description,
679 input_schema,
680 }];
681
682 self.request_limiter
683 .run(async move {
684 let response = Self::perform_llm_completion(
685 client.clone(),
686 llm_api_token,
687 PerformCompletionParams {
688 provider: client::LanguageModelProvider::Anthropic,
689 model: request.model.clone(),
690 provider_request: RawValue::from_string(serde_json::to_string(
691 &request,
692 )?)?,
693 },
694 )
695 .await?;
696
697 Ok(anthropic::extract_tool_args_from_events(
698 tool_name,
699 Box::pin(response_lines(response)),
700 )
701 .await?
702 .boxed())
703 })
704 .boxed()
705 }
706 CloudModel::OpenAi(model) => {
707 let mut request =
708 into_open_ai(request, model.id().into(), model.max_output_tokens());
709 request.tool_choice = Some(open_ai::ToolChoice::Other(
710 open_ai::ToolDefinition::Function {
711 function: open_ai::FunctionDefinition {
712 name: tool_name.clone(),
713 description: None,
714 parameters: None,
715 },
716 },
717 ));
718 request.tools = vec![open_ai::ToolDefinition::Function {
719 function: open_ai::FunctionDefinition {
720 name: tool_name.clone(),
721 description: Some(tool_description),
722 parameters: Some(input_schema),
723 },
724 }];
725
726 self.request_limiter
727 .run(async move {
728 let response = Self::perform_llm_completion(
729 client.clone(),
730 llm_api_token,
731 PerformCompletionParams {
732 provider: client::LanguageModelProvider::OpenAi,
733 model: request.model.clone(),
734 provider_request: RawValue::from_string(serde_json::to_string(
735 &request,
736 )?)?,
737 },
738 )
739 .await?;
740
741 Ok(open_ai::extract_tool_args_from_events(
742 tool_name,
743 Box::pin(response_lines(response)),
744 )
745 .await?
746 .boxed())
747 })
748 .boxed()
749 }
750 CloudModel::Google(_) => {
751 future::ready(Err(anyhow!("tool use not implemented for Google AI"))).boxed()
752 }
753 }
754 }
755}
756
757fn response_lines<T: DeserializeOwned>(
758 response: Response<AsyncBody>,
759) -> impl Stream<Item = Result<T>> {
760 futures::stream::try_unfold(
761 (String::new(), BufReader::new(response.into_body())),
762 move |(mut line, mut body)| async {
763 match body.read_line(&mut line).await {
764 Ok(0) => Ok(None),
765 Ok(_) => {
766 let event: T = serde_json::from_str(&line)?;
767 line.clear();
768 Ok(Some((event, (line, body))))
769 }
770 Err(e) => Err(e.into()),
771 }
772 },
773 )
774}
775
776struct ConfigurationView {
777 state: gpui::Entity<State>,
778}
779
780impl ConfigurationView {
781 fn authenticate(&mut self, cx: &mut Context<Self>) {
782 self.state.update(cx, |state, cx| {
783 state.authenticate(cx).detach_and_log_err(cx);
784 });
785 cx.notify();
786 }
787}
788
789impl Render for ConfigurationView {
790 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
791 const ZED_AI_URL: &str = "https://zed.dev/ai";
792
793 let is_connected = !self.state.read(cx).is_signed_out();
794 let plan = self.state.read(cx).user_store.read(cx).current_plan();
795 let has_accepted_terms = self.state.read(cx).has_accepted_terms_of_service(cx);
796
797 let is_pro = plan == Some(proto::Plan::ZedPro);
798 let subscription_text = Label::new(if is_pro {
799 "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."
800 } else {
801 "You have basic access to models from Anthropic through the Zed AI Free plan."
802 });
803 let manage_subscription_button = if is_pro {
804 Some(
805 h_flex().child(
806 Button::new("manage_settings", "Manage Subscription")
807 .style(ButtonStyle::Tinted(TintColor::Accent))
808 .on_click(
809 cx.listener(|_, _, _, cx| cx.open_url(&zed_urls::account_url(cx))),
810 ),
811 ),
812 )
813 } else if cx.has_flag::<ZedPro>() {
814 Some(
815 h_flex()
816 .gap_2()
817 .child(
818 Button::new("learn_more", "Learn more")
819 .style(ButtonStyle::Subtle)
820 .on_click(cx.listener(|_, _, _, cx| cx.open_url(ZED_AI_URL))),
821 )
822 .child(
823 Button::new("upgrade", "Upgrade")
824 .style(ButtonStyle::Subtle)
825 .color(Color::Accent)
826 .on_click(
827 cx.listener(|_, _, _, cx| cx.open_url(&zed_urls::account_url(cx))),
828 ),
829 ),
830 )
831 } else {
832 None
833 };
834
835 if is_connected {
836 v_flex()
837 .gap_3()
838 .w_full()
839 .children(render_accept_terms(
840 self.state.clone(),
841 LanguageModelProviderTosView::Configuration,
842 cx,
843 ))
844 .when(has_accepted_terms, |this| {
845 this.child(subscription_text)
846 .children(manage_subscription_button)
847 })
848 } else {
849 v_flex()
850 .gap_2()
851 .child(Label::new("Use Zed AI to access hosted language models."))
852 .child(
853 Button::new("sign_in", "Sign In")
854 .icon_color(Color::Muted)
855 .icon(IconName::Github)
856 .icon_position(IconPosition::Start)
857 .on_click(cx.listener(move |this, _, _, cx| this.authenticate(cx))),
858 )
859 }
860 }
861}