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 }
267
268 let llm_closed_beta_models = if cx.has_flag::<LlmClosedBeta>() {
269 zed_cloud_provider_additional_models()
270 } else {
271 &[]
272 };
273
274 // Override with available models from settings
275 for model in AllLanguageModelSettings::get_global(cx)
276 .zed_dot_dev
277 .available_models
278 .iter()
279 .chain(llm_closed_beta_models)
280 .cloned()
281 {
282 let model = match model.provider {
283 AvailableProvider::Anthropic => CloudModel::Anthropic(anthropic::Model::Custom {
284 name: model.name.clone(),
285 display_name: model.display_name.clone(),
286 max_tokens: model.max_tokens,
287 tool_override: model.tool_override.clone(),
288 cache_configuration: model.cache_configuration.as_ref().map(|config| {
289 anthropic::AnthropicModelCacheConfiguration {
290 max_cache_anchors: config.max_cache_anchors,
291 should_speculate: config.should_speculate,
292 min_total_token: config.min_total_token,
293 }
294 }),
295 default_temperature: model.default_temperature,
296 max_output_tokens: model.max_output_tokens,
297 extra_beta_headers: model.extra_beta_headers.clone(),
298 }),
299 AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {
300 name: model.name.clone(),
301 display_name: model.display_name.clone(),
302 max_tokens: model.max_tokens,
303 max_output_tokens: model.max_output_tokens,
304 max_completion_tokens: model.max_completion_tokens,
305 }),
306 AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {
307 name: model.name.clone(),
308 display_name: model.display_name.clone(),
309 max_tokens: model.max_tokens,
310 }),
311 };
312 models.insert(model.id().to_string(), model.clone());
313 }
314
315 let llm_api_token = self.state.read(cx).llm_api_token.clone();
316 models
317 .into_values()
318 .map(|model| {
319 Arc::new(CloudLanguageModel {
320 id: LanguageModelId::from(model.id().to_string()),
321 model,
322 llm_api_token: llm_api_token.clone(),
323 client: self.client.clone(),
324 request_limiter: RateLimiter::new(4),
325 }) as Arc<dyn LanguageModel>
326 })
327 .collect()
328 }
329
330 fn is_authenticated(&self, cx: &App) -> bool {
331 !self.state.read(cx).is_signed_out()
332 }
333
334 fn authenticate(&self, _cx: &mut App) -> Task<Result<(), AuthenticateError>> {
335 Task::ready(Ok(()))
336 }
337
338 fn configuration_view(&self, _: &mut Window, cx: &mut App) -> AnyView {
339 cx.new(|_| ConfigurationView {
340 state: self.state.clone(),
341 })
342 .into()
343 }
344
345 fn must_accept_terms(&self, cx: &App) -> bool {
346 !self.state.read(cx).has_accepted_terms_of_service(cx)
347 }
348
349 fn render_accept_terms(
350 &self,
351 view: LanguageModelProviderTosView,
352 cx: &mut App,
353 ) -> Option<AnyElement> {
354 render_accept_terms(self.state.clone(), view, cx)
355 }
356
357 fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
358 Task::ready(Ok(()))
359 }
360}
361
362fn render_accept_terms(
363 state: Entity<State>,
364 view_kind: LanguageModelProviderTosView,
365 cx: &mut App,
366) -> Option<AnyElement> {
367 if state.read(cx).has_accepted_terms_of_service(cx) {
368 return None;
369 }
370
371 let accept_terms_disabled = state.read(cx).accept_terms.is_some();
372
373 let terms_button = Button::new("terms_of_service", "Terms of Service")
374 .style(ButtonStyle::Subtle)
375 .icon(IconName::ArrowUpRight)
376 .icon_color(Color::Muted)
377 .icon_size(IconSize::XSmall)
378 .on_click(move |_, _window, cx| cx.open_url("https://zed.dev/terms-of-service"));
379
380 let text = "To start using Zed AI, please read and accept the";
381
382 let form = v_flex()
383 .w_full()
384 .gap_2()
385 .when(
386 view_kind == LanguageModelProviderTosView::ThreadEmptyState,
387 |form| form.items_center(),
388 )
389 .child(
390 h_flex()
391 .flex_wrap()
392 .when(
393 view_kind == LanguageModelProviderTosView::ThreadEmptyState,
394 |form| form.justify_center(),
395 )
396 .child(Label::new(text))
397 .child(terms_button),
398 )
399 .child({
400 let button_container = h_flex().w_full().child(
401 Button::new("accept_terms", "I accept the Terms of Service")
402 .style(ButtonStyle::Tinted(TintColor::Accent))
403 .disabled(accept_terms_disabled)
404 .on_click({
405 let state = state.downgrade();
406 move |_, _window, cx| {
407 state
408 .update(cx, |state, cx| state.accept_terms_of_service(cx))
409 .ok();
410 }
411 }),
412 );
413
414 match view_kind {
415 LanguageModelProviderTosView::ThreadEmptyState => button_container.justify_center(),
416 LanguageModelProviderTosView::PromptEditorPopup => button_container.justify_end(),
417 LanguageModelProviderTosView::Configuration => button_container.justify_start(),
418 }
419 });
420
421 Some(form.into_any())
422}
423
424pub struct CloudLanguageModel {
425 id: LanguageModelId,
426 model: CloudModel,
427 llm_api_token: LlmApiToken,
428 client: Arc<Client>,
429 request_limiter: RateLimiter,
430}
431
432impl CloudLanguageModel {
433 async fn perform_llm_completion(
434 client: Arc<Client>,
435 llm_api_token: LlmApiToken,
436 body: PerformCompletionParams,
437 ) -> Result<Response<AsyncBody>> {
438 let http_client = &client.http_client();
439
440 let mut token = llm_api_token.acquire(&client).await?;
441 let mut did_retry = false;
442
443 let response = loop {
444 let request_builder = http_client::Request::builder();
445 let request = request_builder
446 .method(Method::POST)
447 .uri(http_client.build_zed_llm_url("/completion", &[])?.as_ref())
448 .header("Content-Type", "application/json")
449 .header("Authorization", format!("Bearer {token}"))
450 .body(serde_json::to_string(&body)?.into())?;
451 let mut response = http_client.send(request).await?;
452 if response.status().is_success() {
453 break response;
454 } else if !did_retry
455 && response
456 .headers()
457 .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
458 .is_some()
459 {
460 did_retry = true;
461 token = llm_api_token.refresh(&client).await?;
462 } else if response.status() == StatusCode::FORBIDDEN
463 && response
464 .headers()
465 .get(MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME)
466 .is_some()
467 {
468 break Err(anyhow!(MaxMonthlySpendReachedError))?;
469 } else if response.status() == StatusCode::PAYMENT_REQUIRED {
470 break Err(anyhow!(PaymentRequiredError))?;
471 } else {
472 let mut body = String::new();
473 response.body_mut().read_to_string(&mut body).await?;
474 break Err(anyhow!(
475 "cloud language model completion failed with status {}: {body}",
476 response.status()
477 ))?;
478 }
479 };
480
481 Ok(response)
482 }
483}
484
485impl LanguageModel for CloudLanguageModel {
486 fn id(&self) -> LanguageModelId {
487 self.id.clone()
488 }
489
490 fn name(&self) -> LanguageModelName {
491 LanguageModelName::from(self.model.display_name().to_string())
492 }
493
494 fn icon(&self) -> Option<IconName> {
495 self.model.icon()
496 }
497
498 fn provider_id(&self) -> LanguageModelProviderId {
499 LanguageModelProviderId(ZED_CLOUD_PROVIDER_ID.into())
500 }
501
502 fn provider_name(&self) -> LanguageModelProviderName {
503 LanguageModelProviderName(PROVIDER_NAME.into())
504 }
505
506 fn telemetry_id(&self) -> String {
507 format!("zed.dev/{}", self.model.id())
508 }
509
510 fn availability(&self) -> LanguageModelAvailability {
511 self.model.availability()
512 }
513
514 fn max_token_count(&self) -> usize {
515 self.model.max_token_count()
516 }
517
518 fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
519 match &self.model {
520 CloudModel::Anthropic(model) => {
521 model
522 .cache_configuration()
523 .map(|cache| LanguageModelCacheConfiguration {
524 max_cache_anchors: cache.max_cache_anchors,
525 should_speculate: cache.should_speculate,
526 min_total_token: cache.min_total_token,
527 })
528 }
529 CloudModel::OpenAi(_) | CloudModel::Google(_) => None,
530 }
531 }
532
533 fn count_tokens(
534 &self,
535 request: LanguageModelRequest,
536 cx: &App,
537 ) -> BoxFuture<'static, Result<usize>> {
538 match self.model.clone() {
539 CloudModel::Anthropic(_) => count_anthropic_tokens(request, cx),
540 CloudModel::OpenAi(model) => count_open_ai_tokens(request, model, cx),
541 CloudModel::Google(model) => {
542 let client = self.client.clone();
543 let request = into_google(request, model.id().into());
544 let request = google_ai::CountTokensRequest {
545 contents: request.contents,
546 };
547 async move {
548 let request = serde_json::to_string(&request)?;
549 let response = client
550 .request(proto::CountLanguageModelTokens {
551 provider: proto::LanguageModelProvider::Google as i32,
552 request,
553 })
554 .await?;
555 Ok(response.token_count as usize)
556 }
557 .boxed()
558 }
559 }
560 }
561
562 fn stream_completion(
563 &self,
564 request: LanguageModelRequest,
565 _cx: &AsyncApp,
566 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<LanguageModelCompletionEvent>>>> {
567 match &self.model {
568 CloudModel::Anthropic(model) => {
569 let request = into_anthropic(
570 request,
571 model.id().into(),
572 model.default_temperature(),
573 model.max_output_tokens(),
574 );
575 let client = self.client.clone();
576 let llm_api_token = self.llm_api_token.clone();
577 let future = self.request_limiter.stream(async move {
578 let response = Self::perform_llm_completion(
579 client.clone(),
580 llm_api_token,
581 PerformCompletionParams {
582 provider: client::LanguageModelProvider::Anthropic,
583 model: request.model.clone(),
584 provider_request: RawValue::from_string(serde_json::to_string(
585 &request,
586 )?)?,
587 },
588 )
589 .await?;
590 Ok(map_to_language_model_completion_events(Box::pin(
591 response_lines(response).map_err(AnthropicError::Other),
592 )))
593 });
594 async move { Ok(future.await?.boxed()) }.boxed()
595 }
596 CloudModel::OpenAi(model) => {
597 let client = self.client.clone();
598 let request = into_open_ai(request, model.id().into(), model.max_output_tokens());
599 let llm_api_token = self.llm_api_token.clone();
600 let future = self.request_limiter.stream(async move {
601 let response = Self::perform_llm_completion(
602 client.clone(),
603 llm_api_token,
604 PerformCompletionParams {
605 provider: client::LanguageModelProvider::OpenAi,
606 model: request.model.clone(),
607 provider_request: RawValue::from_string(serde_json::to_string(
608 &request,
609 )?)?,
610 },
611 )
612 .await?;
613 Ok(open_ai::extract_text_from_events(response_lines(response)))
614 });
615 async move {
616 Ok(future
617 .await?
618 .map(|result| result.map(LanguageModelCompletionEvent::Text))
619 .boxed())
620 }
621 .boxed()
622 }
623 CloudModel::Google(model) => {
624 let client = self.client.clone();
625 let request = into_google(request, model.id().into());
626 let llm_api_token = self.llm_api_token.clone();
627 let future = self.request_limiter.stream(async move {
628 let response = Self::perform_llm_completion(
629 client.clone(),
630 llm_api_token,
631 PerformCompletionParams {
632 provider: client::LanguageModelProvider::Google,
633 model: request.model.clone(),
634 provider_request: RawValue::from_string(serde_json::to_string(
635 &request,
636 )?)?,
637 },
638 )
639 .await?;
640 Ok(google_ai::extract_text_from_events(response_lines(
641 response,
642 )))
643 });
644 async move {
645 Ok(future
646 .await?
647 .map(|result| result.map(LanguageModelCompletionEvent::Text))
648 .boxed())
649 }
650 .boxed()
651 }
652 }
653 }
654
655 fn use_any_tool(
656 &self,
657 request: LanguageModelRequest,
658 tool_name: String,
659 tool_description: String,
660 input_schema: serde_json::Value,
661 _cx: &AsyncApp,
662 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>> {
663 let client = self.client.clone();
664 let llm_api_token = self.llm_api_token.clone();
665
666 match &self.model {
667 CloudModel::Anthropic(model) => {
668 let mut request = into_anthropic(
669 request,
670 model.tool_model_id().into(),
671 model.default_temperature(),
672 model.max_output_tokens(),
673 );
674 request.tool_choice = Some(anthropic::ToolChoice::Tool {
675 name: tool_name.clone(),
676 });
677 request.tools = vec![anthropic::Tool {
678 name: tool_name.clone(),
679 description: tool_description,
680 input_schema,
681 }];
682
683 self.request_limiter
684 .run(async move {
685 let response = Self::perform_llm_completion(
686 client.clone(),
687 llm_api_token,
688 PerformCompletionParams {
689 provider: client::LanguageModelProvider::Anthropic,
690 model: request.model.clone(),
691 provider_request: RawValue::from_string(serde_json::to_string(
692 &request,
693 )?)?,
694 },
695 )
696 .await?;
697
698 Ok(anthropic::extract_tool_args_from_events(
699 tool_name,
700 Box::pin(response_lines(response)),
701 )
702 .await?
703 .boxed())
704 })
705 .boxed()
706 }
707 CloudModel::OpenAi(model) => {
708 let mut request =
709 into_open_ai(request, model.id().into(), model.max_output_tokens());
710 request.tool_choice = Some(open_ai::ToolChoice::Other(
711 open_ai::ToolDefinition::Function {
712 function: open_ai::FunctionDefinition {
713 name: tool_name.clone(),
714 description: None,
715 parameters: None,
716 },
717 },
718 ));
719 request.tools = vec![open_ai::ToolDefinition::Function {
720 function: open_ai::FunctionDefinition {
721 name: tool_name.clone(),
722 description: Some(tool_description),
723 parameters: Some(input_schema),
724 },
725 }];
726
727 self.request_limiter
728 .run(async move {
729 let response = Self::perform_llm_completion(
730 client.clone(),
731 llm_api_token,
732 PerformCompletionParams {
733 provider: client::LanguageModelProvider::OpenAi,
734 model: request.model.clone(),
735 provider_request: RawValue::from_string(serde_json::to_string(
736 &request,
737 )?)?,
738 },
739 )
740 .await?;
741
742 Ok(open_ai::extract_tool_args_from_events(
743 tool_name,
744 Box::pin(response_lines(response)),
745 )
746 .await?
747 .boxed())
748 })
749 .boxed()
750 }
751 CloudModel::Google(_) => {
752 future::ready(Err(anyhow!("tool use not implemented for Google AI"))).boxed()
753 }
754 }
755 }
756}
757
758fn response_lines<T: DeserializeOwned>(
759 response: Response<AsyncBody>,
760) -> impl Stream<Item = Result<T>> {
761 futures::stream::try_unfold(
762 (String::new(), BufReader::new(response.into_body())),
763 move |(mut line, mut body)| async {
764 match body.read_line(&mut line).await {
765 Ok(0) => Ok(None),
766 Ok(_) => {
767 let event: T = serde_json::from_str(&line)?;
768 line.clear();
769 Ok(Some((event, (line, body))))
770 }
771 Err(e) => Err(e.into()),
772 }
773 },
774 )
775}
776
777struct ConfigurationView {
778 state: gpui::Entity<State>,
779}
780
781impl ConfigurationView {
782 fn authenticate(&mut self, cx: &mut Context<Self>) {
783 self.state.update(cx, |state, cx| {
784 state.authenticate(cx).detach_and_log_err(cx);
785 });
786 cx.notify();
787 }
788}
789
790impl Render for ConfigurationView {
791 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
792 const ZED_AI_URL: &str = "https://zed.dev/ai";
793
794 let is_connected = !self.state.read(cx).is_signed_out();
795 let plan = self.state.read(cx).user_store.read(cx).current_plan();
796 let has_accepted_terms = self.state.read(cx).has_accepted_terms_of_service(cx);
797
798 let is_pro = plan == Some(proto::Plan::ZedPro);
799 let subscription_text = Label::new(if is_pro {
800 "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."
801 } else {
802 "You have basic access to models from Anthropic through the Zed AI Free plan."
803 });
804 let manage_subscription_button = if is_pro {
805 Some(
806 h_flex().child(
807 Button::new("manage_settings", "Manage Subscription")
808 .style(ButtonStyle::Tinted(TintColor::Accent))
809 .on_click(
810 cx.listener(|_, _, _, cx| cx.open_url(&zed_urls::account_url(cx))),
811 ),
812 ),
813 )
814 } else if cx.has_flag::<ZedPro>() {
815 Some(
816 h_flex()
817 .gap_2()
818 .child(
819 Button::new("learn_more", "Learn more")
820 .style(ButtonStyle::Subtle)
821 .on_click(cx.listener(|_, _, _, cx| cx.open_url(ZED_AI_URL))),
822 )
823 .child(
824 Button::new("upgrade", "Upgrade")
825 .style(ButtonStyle::Subtle)
826 .color(Color::Accent)
827 .on_click(
828 cx.listener(|_, _, _, cx| cx.open_url(&zed_urls::account_url(cx))),
829 ),
830 ),
831 )
832 } else {
833 None
834 };
835
836 if is_connected {
837 v_flex()
838 .gap_3()
839 .w_full()
840 .children(render_accept_terms(
841 self.state.clone(),
842 LanguageModelProviderTosView::Configuration,
843 cx,
844 ))
845 .when(has_accepted_terms, |this| {
846 this.child(subscription_text)
847 .children(manage_subscription_button)
848 })
849 } else {
850 v_flex()
851 .gap_2()
852 .child(Label::new("Use Zed AI to access hosted language models."))
853 .child(
854 Button::new("sign_in", "Sign In")
855 .icon_color(Color::Muted)
856 .icon(IconName::Github)
857 .icon_position(IconPosition::Start)
858 .on_click(cx.listener(move |this, _, _, cx| this.authenticate(cx))),
859 )
860 }
861 }
862}