1use super::open_ai::count_open_ai_tokens;
2use crate::{
3 settings::AllLanguageModelSettings, CloudModel, LanguageModel, LanguageModelCacheConfiguration,
4 LanguageModelId, LanguageModelName, LanguageModelProviderId, LanguageModelProviderName,
5 LanguageModelProviderState, LanguageModelRequest, RateLimiter, ZedModel,
6};
7use anthropic::AnthropicError;
8use anyhow::{anyhow, Result};
9use client::{Client, PerformCompletionParams, UserStore, EXPIRED_LLM_TOKEN_HEADER_NAME};
10use collections::BTreeMap;
11use feature_flags::{FeatureFlagAppExt, LlmClosedBeta, ZedPro};
12use futures::{
13 future::BoxFuture, stream::BoxStream, AsyncBufReadExt, FutureExt, Stream, StreamExt,
14 TryStreamExt as _,
15};
16use gpui::{
17 AnyElement, AnyView, AppContext, AsyncAppContext, FontWeight, Model, ModelContext,
18 Subscription, Task,
19};
20use http_client::{AsyncBody, HttpClient, Method, Response};
21use schemars::JsonSchema;
22use serde::{de::DeserializeOwned, Deserialize, Serialize};
23use serde_json::value::RawValue;
24use settings::{Settings, SettingsStore};
25use smol::{
26 io::{AsyncReadExt, BufReader},
27 lock::{RwLock, RwLockUpgradableReadGuard, RwLockWriteGuard},
28};
29use std::{
30 future,
31 sync::{Arc, LazyLock},
32};
33use strum::IntoEnumIterator;
34use ui::{prelude::*, TintColor};
35
36use crate::{
37 LanguageModelAvailability, LanguageModelCompletionEvent, LanguageModelProvider,
38 LanguageModelToolUse,
39};
40
41use super::anthropic::count_anthropic_tokens;
42
43pub const PROVIDER_ID: &str = "zed.dev";
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(Vec::new())
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 /// Override this model with a different Anthropic model for tool calls.
84 pub tool_override: Option<String>,
85 /// Indicates whether this custom model supports caching.
86 pub cache_configuration: Option<LanguageModelCacheConfiguration>,
87}
88
89pub struct CloudLanguageModelProvider {
90 client: Arc<Client>,
91 llm_api_token: LlmApiToken,
92 state: gpui::Model<State>,
93 _maintain_client_status: Task<()>,
94}
95
96pub struct State {
97 client: Arc<Client>,
98 user_store: Model<UserStore>,
99 status: client::Status,
100 accept_terms: Option<Task<Result<()>>>,
101 _subscription: Subscription,
102}
103
104impl State {
105 fn is_signed_out(&self) -> bool {
106 self.status.is_signed_out()
107 }
108
109 fn authenticate(&self, cx: &mut ModelContext<Self>) -> Task<Result<()>> {
110 let client = self.client.clone();
111 cx.spawn(move |this, mut cx| async move {
112 client.authenticate_and_connect(true, &cx).await?;
113 this.update(&mut cx, |_, cx| cx.notify())
114 })
115 }
116
117 fn has_accepted_terms_of_service(&self, cx: &AppContext) -> bool {
118 self.user_store
119 .read(cx)
120 .current_user_has_accepted_terms()
121 .unwrap_or(false)
122 }
123
124 fn accept_terms_of_service(&mut self, cx: &mut ModelContext<Self>) {
125 let user_store = self.user_store.clone();
126 self.accept_terms = Some(cx.spawn(move |this, mut cx| async move {
127 let _ = user_store
128 .update(&mut cx, |store, cx| store.accept_terms_of_service(cx))?
129 .await;
130 this.update(&mut cx, |this, cx| {
131 this.accept_terms = None;
132 cx.notify()
133 })
134 }));
135 }
136}
137
138impl CloudLanguageModelProvider {
139 pub fn new(user_store: Model<UserStore>, client: Arc<Client>, cx: &mut AppContext) -> Self {
140 let mut status_rx = client.status();
141 let status = *status_rx.borrow();
142
143 let state = cx.new_model(|cx| State {
144 client: client.clone(),
145 user_store,
146 status,
147 accept_terms: None,
148 _subscription: cx.observe_global::<SettingsStore>(|_, cx| {
149 cx.notify();
150 }),
151 });
152
153 let state_ref = state.downgrade();
154 let maintain_client_status = cx.spawn(|mut cx| async move {
155 while let Some(status) = status_rx.next().await {
156 if let Some(this) = state_ref.upgrade() {
157 _ = this.update(&mut cx, |this, cx| {
158 if this.status != status {
159 this.status = status;
160 cx.notify();
161 }
162 });
163 } else {
164 break;
165 }
166 }
167 });
168
169 Self {
170 client,
171 state,
172 llm_api_token: LlmApiToken::default(),
173 _maintain_client_status: maintain_client_status,
174 }
175 }
176}
177
178impl LanguageModelProviderState for CloudLanguageModelProvider {
179 type ObservableEntity = State;
180
181 fn observable_entity(&self) -> Option<gpui::Model<Self::ObservableEntity>> {
182 Some(self.state.clone())
183 }
184}
185
186impl LanguageModelProvider for CloudLanguageModelProvider {
187 fn id(&self) -> LanguageModelProviderId {
188 LanguageModelProviderId(PROVIDER_ID.into())
189 }
190
191 fn name(&self) -> LanguageModelProviderName {
192 LanguageModelProviderName(PROVIDER_NAME.into())
193 }
194
195 fn icon(&self) -> IconName {
196 IconName::AiZed
197 }
198
199 fn provided_models(&self, cx: &AppContext) -> Vec<Arc<dyn LanguageModel>> {
200 let mut models = BTreeMap::default();
201
202 if cx.is_staff() {
203 for model in anthropic::Model::iter() {
204 if !matches!(model, anthropic::Model::Custom { .. }) {
205 models.insert(model.id().to_string(), CloudModel::Anthropic(model));
206 }
207 }
208 for model in open_ai::Model::iter() {
209 if !matches!(model, open_ai::Model::Custom { .. }) {
210 models.insert(model.id().to_string(), CloudModel::OpenAi(model));
211 }
212 }
213 for model in google_ai::Model::iter() {
214 if !matches!(model, google_ai::Model::Custom { .. }) {
215 models.insert(model.id().to_string(), CloudModel::Google(model));
216 }
217 }
218 for model in ZedModel::iter() {
219 models.insert(model.id().to_string(), CloudModel::Zed(model));
220 }
221 } else {
222 models.insert(
223 anthropic::Model::Claude3_5Sonnet.id().to_string(),
224 CloudModel::Anthropic(anthropic::Model::Claude3_5Sonnet),
225 );
226 }
227
228 let llm_closed_beta_models = if cx.has_flag::<LlmClosedBeta>() {
229 zed_cloud_provider_additional_models()
230 } else {
231 &[]
232 };
233
234 // Override with available models from settings
235 for model in AllLanguageModelSettings::get_global(cx)
236 .zed_dot_dev
237 .available_models
238 .iter()
239 .chain(llm_closed_beta_models)
240 .cloned()
241 {
242 let model = match model.provider {
243 AvailableProvider::Anthropic => CloudModel::Anthropic(anthropic::Model::Custom {
244 name: model.name.clone(),
245 display_name: model.display_name.clone(),
246 max_tokens: model.max_tokens,
247 tool_override: model.tool_override.clone(),
248 cache_configuration: model.cache_configuration.as_ref().map(|config| {
249 anthropic::AnthropicModelCacheConfiguration {
250 max_cache_anchors: config.max_cache_anchors,
251 should_speculate: config.should_speculate,
252 min_total_token: config.min_total_token,
253 }
254 }),
255 max_output_tokens: model.max_output_tokens,
256 }),
257 AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {
258 name: model.name.clone(),
259 max_tokens: model.max_tokens,
260 max_output_tokens: model.max_output_tokens,
261 }),
262 AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {
263 name: model.name.clone(),
264 max_tokens: model.max_tokens,
265 }),
266 };
267 models.insert(model.id().to_string(), model.clone());
268 }
269
270 models
271 .into_values()
272 .map(|model| {
273 Arc::new(CloudLanguageModel {
274 id: LanguageModelId::from(model.id().to_string()),
275 model,
276 llm_api_token: self.llm_api_token.clone(),
277 client: self.client.clone(),
278 request_limiter: RateLimiter::new(4),
279 }) as Arc<dyn LanguageModel>
280 })
281 .collect()
282 }
283
284 fn is_authenticated(&self, cx: &AppContext) -> bool {
285 !self.state.read(cx).is_signed_out()
286 }
287
288 fn authenticate(&self, _cx: &mut AppContext) -> Task<Result<()>> {
289 Task::ready(Ok(()))
290 }
291
292 fn configuration_view(&self, cx: &mut WindowContext) -> AnyView {
293 cx.new_view(|_cx| ConfigurationView {
294 state: self.state.clone(),
295 })
296 .into()
297 }
298
299 fn must_accept_terms(&self, cx: &AppContext) -> bool {
300 !self.state.read(cx).has_accepted_terms_of_service(cx)
301 }
302
303 fn render_accept_terms(&self, cx: &mut WindowContext) -> Option<AnyElement> {
304 let state = self.state.read(cx);
305
306 let terms = [(
307 "terms_of_service",
308 "Terms of Service",
309 "https://zed.dev/terms-of-service",
310 )]
311 .map(|(id, label, url)| {
312 Button::new(id, label)
313 .style(ButtonStyle::Subtle)
314 .icon(IconName::ExternalLink)
315 .icon_size(IconSize::XSmall)
316 .icon_color(Color::Muted)
317 .on_click(move |_, cx| cx.open_url(url))
318 });
319
320 if state.has_accepted_terms_of_service(cx) {
321 None
322 } else {
323 let disabled = state.accept_terms.is_some();
324 Some(
325 v_flex()
326 .gap_2()
327 .child(
328 v_flex()
329 .child(Label::new("Terms and Conditions").weight(FontWeight::MEDIUM))
330 .child(
331 Label::new(
332 "Please read and accept our terms and conditions to continue.",
333 )
334 .size(LabelSize::Small),
335 ),
336 )
337 .child(v_flex().gap_1().children(terms))
338 .child(
339 h_flex().justify_end().child(
340 Button::new("accept_terms", "I've read it and accept it")
341 .disabled(disabled)
342 .on_click({
343 let state = self.state.downgrade();
344 move |_, cx| {
345 state
346 .update(cx, |state, cx| {
347 state.accept_terms_of_service(cx)
348 })
349 .ok();
350 }
351 }),
352 ),
353 )
354 .into_any(),
355 )
356 }
357 }
358
359 fn reset_credentials(&self, _cx: &mut AppContext) -> Task<Result<()>> {
360 Task::ready(Ok(()))
361 }
362}
363
364pub struct CloudLanguageModel {
365 id: LanguageModelId,
366 model: CloudModel,
367 llm_api_token: LlmApiToken,
368 client: Arc<Client>,
369 request_limiter: RateLimiter,
370}
371
372#[derive(Clone, Default)]
373struct LlmApiToken(Arc<RwLock<Option<String>>>);
374
375impl CloudLanguageModel {
376 async fn perform_llm_completion(
377 client: Arc<Client>,
378 llm_api_token: LlmApiToken,
379 body: PerformCompletionParams,
380 ) -> Result<Response<AsyncBody>> {
381 let http_client = &client.http_client();
382
383 let mut token = llm_api_token.acquire(&client).await?;
384 let mut did_retry = false;
385
386 let response = loop {
387 let request = http_client::Request::builder()
388 .method(Method::POST)
389 .uri(http_client.build_zed_llm_url("/completion", &[])?.as_ref())
390 .header("Content-Type", "application/json")
391 .header("Authorization", format!("Bearer {token}"))
392 .body(serde_json::to_string(&body)?.into())?;
393 let mut response = http_client.send(request).await?;
394 if response.status().is_success() {
395 break response;
396 } else if !did_retry
397 && response
398 .headers()
399 .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
400 .is_some()
401 {
402 did_retry = true;
403 token = llm_api_token.refresh(&client).await?;
404 } else {
405 let mut body = String::new();
406 response.body_mut().read_to_string(&mut body).await?;
407 break Err(anyhow!(
408 "cloud language model completion failed with status {}: {body}",
409 response.status()
410 ))?;
411 }
412 };
413
414 Ok(response)
415 }
416}
417
418impl LanguageModel for CloudLanguageModel {
419 fn id(&self) -> LanguageModelId {
420 self.id.clone()
421 }
422
423 fn name(&self) -> LanguageModelName {
424 LanguageModelName::from(self.model.display_name().to_string())
425 }
426
427 fn icon(&self) -> Option<IconName> {
428 self.model.icon()
429 }
430
431 fn provider_id(&self) -> LanguageModelProviderId {
432 LanguageModelProviderId(PROVIDER_ID.into())
433 }
434
435 fn provider_name(&self) -> LanguageModelProviderName {
436 LanguageModelProviderName(PROVIDER_NAME.into())
437 }
438
439 fn telemetry_id(&self) -> String {
440 format!("zed.dev/{}", self.model.id())
441 }
442
443 fn availability(&self) -> LanguageModelAvailability {
444 self.model.availability()
445 }
446
447 fn max_token_count(&self) -> usize {
448 self.model.max_token_count()
449 }
450
451 fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
452 match &self.model {
453 CloudModel::Anthropic(model) => {
454 model
455 .cache_configuration()
456 .map(|cache| LanguageModelCacheConfiguration {
457 max_cache_anchors: cache.max_cache_anchors,
458 should_speculate: cache.should_speculate,
459 min_total_token: cache.min_total_token,
460 })
461 }
462 CloudModel::OpenAi(_) | CloudModel::Google(_) | CloudModel::Zed(_) => None,
463 }
464 }
465
466 fn count_tokens(
467 &self,
468 request: LanguageModelRequest,
469 cx: &AppContext,
470 ) -> BoxFuture<'static, Result<usize>> {
471 match self.model.clone() {
472 CloudModel::Anthropic(_) => count_anthropic_tokens(request, cx),
473 CloudModel::OpenAi(model) => count_open_ai_tokens(request, model, cx),
474 CloudModel::Google(model) => {
475 let client = self.client.clone();
476 let request = request.into_google(model.id().into());
477 let request = google_ai::CountTokensRequest {
478 contents: request.contents,
479 };
480 async move {
481 let request = serde_json::to_string(&request)?;
482 let response = client
483 .request(proto::CountLanguageModelTokens {
484 provider: proto::LanguageModelProvider::Google as i32,
485 request,
486 })
487 .await?;
488 Ok(response.token_count as usize)
489 }
490 .boxed()
491 }
492 CloudModel::Zed(_) => {
493 count_open_ai_tokens(request, open_ai::Model::ThreePointFiveTurbo, cx)
494 }
495 }
496 }
497
498 fn stream_completion(
499 &self,
500 request: LanguageModelRequest,
501 _cx: &AsyncAppContext,
502 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<LanguageModelCompletionEvent>>>> {
503 match &self.model {
504 CloudModel::Anthropic(model) => {
505 let request = request.into_anthropic(model.id().into(), model.max_output_tokens());
506 let client = self.client.clone();
507 let llm_api_token = self.llm_api_token.clone();
508 let future = self.request_limiter.stream(async move {
509 let response = Self::perform_llm_completion(
510 client.clone(),
511 llm_api_token,
512 PerformCompletionParams {
513 provider: client::LanguageModelProvider::Anthropic,
514 model: request.model.clone(),
515 provider_request: RawValue::from_string(serde_json::to_string(
516 &request,
517 )?)?,
518 },
519 )
520 .await?;
521 Ok(anthropic::extract_content_from_events(Box::pin(
522 response_lines(response).map_err(AnthropicError::Other),
523 )))
524 });
525 async move {
526 Ok(future
527 .await?
528 .map(|result| {
529 result
530 .map(|content| match content {
531 anthropic::ResponseContent::Text { text } => {
532 LanguageModelCompletionEvent::Text(text)
533 }
534 anthropic::ResponseContent::ToolUse { id, name, input } => {
535 LanguageModelCompletionEvent::ToolUse(
536 LanguageModelToolUse { id, name, input },
537 )
538 }
539 })
540 .map_err(|err| anyhow!(err))
541 })
542 .boxed())
543 }
544 .boxed()
545 }
546 CloudModel::OpenAi(model) => {
547 let client = self.client.clone();
548 let request = request.into_open_ai(model.id().into(), model.max_output_tokens());
549 let llm_api_token = self.llm_api_token.clone();
550 let future = self.request_limiter.stream(async move {
551 let response = Self::perform_llm_completion(
552 client.clone(),
553 llm_api_token,
554 PerformCompletionParams {
555 provider: client::LanguageModelProvider::OpenAi,
556 model: request.model.clone(),
557 provider_request: RawValue::from_string(serde_json::to_string(
558 &request,
559 )?)?,
560 },
561 )
562 .await?;
563 Ok(open_ai::extract_text_from_events(response_lines(response)))
564 });
565 async move {
566 Ok(future
567 .await?
568 .map(|result| result.map(LanguageModelCompletionEvent::Text))
569 .boxed())
570 }
571 .boxed()
572 }
573 CloudModel::Google(model) => {
574 let client = self.client.clone();
575 let request = request.into_google(model.id().into());
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::Google,
583 model: request.model.clone(),
584 provider_request: RawValue::from_string(serde_json::to_string(
585 &request,
586 )?)?,
587 },
588 )
589 .await?;
590 Ok(google_ai::extract_text_from_events(response_lines(
591 response,
592 )))
593 });
594 async move {
595 Ok(future
596 .await?
597 .map(|result| result.map(LanguageModelCompletionEvent::Text))
598 .boxed())
599 }
600 .boxed()
601 }
602 CloudModel::Zed(model) => {
603 let client = self.client.clone();
604 let mut request = request.into_open_ai(model.id().into(), None);
605 request.max_tokens = Some(4000);
606 let llm_api_token = self.llm_api_token.clone();
607 let future = self.request_limiter.stream(async move {
608 let response = Self::perform_llm_completion(
609 client.clone(),
610 llm_api_token,
611 PerformCompletionParams {
612 provider: client::LanguageModelProvider::Zed,
613 model: request.model.clone(),
614 provider_request: RawValue::from_string(serde_json::to_string(
615 &request,
616 )?)?,
617 },
618 )
619 .await?;
620 Ok(open_ai::extract_text_from_events(response_lines(response)))
621 });
622 async move {
623 Ok(future
624 .await?
625 .map(|result| result.map(LanguageModelCompletionEvent::Text))
626 .boxed())
627 }
628 .boxed()
629 }
630 }
631 }
632
633 fn use_any_tool(
634 &self,
635 request: LanguageModelRequest,
636 tool_name: String,
637 tool_description: String,
638 input_schema: serde_json::Value,
639 _cx: &AsyncAppContext,
640 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>> {
641 let client = self.client.clone();
642 let llm_api_token = self.llm_api_token.clone();
643
644 match &self.model {
645 CloudModel::Anthropic(model) => {
646 let mut request =
647 request.into_anthropic(model.tool_model_id().into(), model.max_output_tokens());
648 request.tool_choice = Some(anthropic::ToolChoice::Tool {
649 name: tool_name.clone(),
650 });
651 request.tools = vec![anthropic::Tool {
652 name: tool_name.clone(),
653 description: tool_description,
654 input_schema,
655 }];
656
657 self.request_limiter
658 .run(async move {
659 let response = Self::perform_llm_completion(
660 client.clone(),
661 llm_api_token,
662 PerformCompletionParams {
663 provider: client::LanguageModelProvider::Anthropic,
664 model: request.model.clone(),
665 provider_request: RawValue::from_string(serde_json::to_string(
666 &request,
667 )?)?,
668 },
669 )
670 .await?;
671
672 Ok(anthropic::extract_tool_args_from_events(
673 tool_name,
674 Box::pin(response_lines(response)),
675 )
676 .await?
677 .boxed())
678 })
679 .boxed()
680 }
681 CloudModel::OpenAi(model) => {
682 let mut request =
683 request.into_open_ai(model.id().into(), model.max_output_tokens());
684 request.tool_choice = Some(open_ai::ToolChoice::Other(
685 open_ai::ToolDefinition::Function {
686 function: open_ai::FunctionDefinition {
687 name: tool_name.clone(),
688 description: None,
689 parameters: None,
690 },
691 },
692 ));
693 request.tools = vec![open_ai::ToolDefinition::Function {
694 function: open_ai::FunctionDefinition {
695 name: tool_name.clone(),
696 description: Some(tool_description),
697 parameters: Some(input_schema),
698 },
699 }];
700
701 self.request_limiter
702 .run(async move {
703 let response = Self::perform_llm_completion(
704 client.clone(),
705 llm_api_token,
706 PerformCompletionParams {
707 provider: client::LanguageModelProvider::OpenAi,
708 model: request.model.clone(),
709 provider_request: RawValue::from_string(serde_json::to_string(
710 &request,
711 )?)?,
712 },
713 )
714 .await?;
715
716 Ok(open_ai::extract_tool_args_from_events(
717 tool_name,
718 Box::pin(response_lines(response)),
719 )
720 .await?
721 .boxed())
722 })
723 .boxed()
724 }
725 CloudModel::Google(_) => {
726 future::ready(Err(anyhow!("tool use not implemented for Google AI"))).boxed()
727 }
728 CloudModel::Zed(model) => {
729 // All Zed models are OpenAI-based at the time of writing.
730 let mut request = request.into_open_ai(model.id().into(), None);
731 request.tool_choice = Some(open_ai::ToolChoice::Other(
732 open_ai::ToolDefinition::Function {
733 function: open_ai::FunctionDefinition {
734 name: tool_name.clone(),
735 description: None,
736 parameters: None,
737 },
738 },
739 ));
740 request.tools = vec![open_ai::ToolDefinition::Function {
741 function: open_ai::FunctionDefinition {
742 name: tool_name.clone(),
743 description: Some(tool_description),
744 parameters: Some(input_schema),
745 },
746 }];
747
748 self.request_limiter
749 .run(async move {
750 let response = Self::perform_llm_completion(
751 client.clone(),
752 llm_api_token,
753 PerformCompletionParams {
754 provider: client::LanguageModelProvider::Zed,
755 model: request.model.clone(),
756 provider_request: RawValue::from_string(serde_json::to_string(
757 &request,
758 )?)?,
759 },
760 )
761 .await?;
762
763 Ok(open_ai::extract_tool_args_from_events(
764 tool_name,
765 Box::pin(response_lines(response)),
766 )
767 .await?
768 .boxed())
769 })
770 .boxed()
771 }
772 }
773 }
774}
775
776fn response_lines<T: DeserializeOwned>(
777 response: Response<AsyncBody>,
778) -> impl Stream<Item = Result<T>> {
779 futures::stream::try_unfold(
780 (String::new(), BufReader::new(response.into_body())),
781 move |(mut line, mut body)| async {
782 match body.read_line(&mut line).await {
783 Ok(0) => Ok(None),
784 Ok(_) => {
785 let event: T = serde_json::from_str(&line)?;
786 line.clear();
787 Ok(Some((event, (line, body))))
788 }
789 Err(e) => Err(e.into()),
790 }
791 },
792 )
793}
794
795impl LlmApiToken {
796 async fn acquire(&self, client: &Arc<Client>) -> Result<String> {
797 let lock = self.0.upgradable_read().await;
798 if let Some(token) = lock.as_ref() {
799 Ok(token.to_string())
800 } else {
801 Self::fetch(RwLockUpgradableReadGuard::upgrade(lock).await, &client).await
802 }
803 }
804
805 async fn refresh(&self, client: &Arc<Client>) -> Result<String> {
806 Self::fetch(self.0.write().await, &client).await
807 }
808
809 async fn fetch<'a>(
810 mut lock: RwLockWriteGuard<'a, Option<String>>,
811 client: &Arc<Client>,
812 ) -> Result<String> {
813 let response = client.request(proto::GetLlmToken {}).await?;
814 *lock = Some(response.token.clone());
815 Ok(response.token.clone())
816 }
817}
818
819struct ConfigurationView {
820 state: gpui::Model<State>,
821}
822
823impl ConfigurationView {
824 fn authenticate(&mut self, cx: &mut ViewContext<Self>) {
825 self.state.update(cx, |state, cx| {
826 state.authenticate(cx).detach_and_log_err(cx);
827 });
828 cx.notify();
829 }
830
831 fn render_accept_terms(&mut self, cx: &mut ViewContext<Self>) -> Option<AnyElement> {
832 if self.state.read(cx).has_accepted_terms_of_service(cx) {
833 return None;
834 }
835
836 let accept_terms_disabled = self.state.read(cx).accept_terms.is_some();
837
838 let terms_button = Button::new("terms_of_service", "Terms of Service")
839 .style(ButtonStyle::Subtle)
840 .icon(IconName::ExternalLink)
841 .icon_color(Color::Muted)
842 .on_click(move |_, cx| cx.open_url("https://zed.dev/terms-of-service"));
843
844 let text =
845 "In order to use Zed AI, please read and accept our terms and conditions to continue:";
846
847 let form = v_flex()
848 .gap_2()
849 .child(Label::new("Terms and Conditions"))
850 .child(Label::new(text))
851 .child(h_flex().justify_center().child(terms_button))
852 .child(
853 h_flex().justify_center().child(
854 Button::new("accept_terms", "I've read and accept the terms of service")
855 .style(ButtonStyle::Tinted(TintColor::Accent))
856 .disabled(accept_terms_disabled)
857 .on_click({
858 let state = self.state.downgrade();
859 move |_, cx| {
860 state
861 .update(cx, |state, cx| state.accept_terms_of_service(cx))
862 .ok();
863 }
864 }),
865 ),
866 );
867
868 Some(form.into_any())
869 }
870}
871
872impl Render for ConfigurationView {
873 fn render(&mut self, cx: &mut ViewContext<Self>) -> impl IntoElement {
874 const ZED_AI_URL: &str = "https://zed.dev/ai";
875 const ACCOUNT_SETTINGS_URL: &str = "https://zed.dev/account";
876
877 let is_connected = !self.state.read(cx).is_signed_out();
878 let plan = self.state.read(cx).user_store.read(cx).current_plan();
879 let has_accepted_terms = self.state.read(cx).has_accepted_terms_of_service(cx);
880
881 let is_pro = plan == Some(proto::Plan::ZedPro);
882 let subscription_text = Label::new(if is_pro {
883 "You have full access to Zed's hosted models from Anthropic, OpenAI, Google with faster speeds and higher limits through Zed Pro."
884 } else {
885 "You have basic access to models from Anthropic through the Zed AI Free plan."
886 });
887 let manage_subscription_button = if is_pro {
888 Some(
889 h_flex().child(
890 Button::new("manage_settings", "Manage Subscription")
891 .style(ButtonStyle::Tinted(TintColor::Accent))
892 .on_click(cx.listener(|_, _, cx| cx.open_url(ACCOUNT_SETTINGS_URL))),
893 ),
894 )
895 } else if cx.has_flag::<ZedPro>() {
896 Some(
897 h_flex()
898 .gap_2()
899 .child(
900 Button::new("learn_more", "Learn more")
901 .style(ButtonStyle::Subtle)
902 .on_click(cx.listener(|_, _, cx| cx.open_url(ZED_AI_URL))),
903 )
904 .child(
905 Button::new("upgrade", "Upgrade")
906 .style(ButtonStyle::Subtle)
907 .color(Color::Accent)
908 .on_click(cx.listener(|_, _, cx| cx.open_url(ACCOUNT_SETTINGS_URL))),
909 ),
910 )
911 } else {
912 None
913 };
914
915 if is_connected {
916 v_flex()
917 .gap_3()
918 .max_w_4_5()
919 .children(self.render_accept_terms(cx))
920 .when(has_accepted_terms, |this| {
921 this.child(subscription_text)
922 .children(manage_subscription_button)
923 })
924 } else {
925 v_flex()
926 .gap_6()
927 .child(Label::new("Use the zed.dev to access language models."))
928 .child(
929 v_flex()
930 .gap_2()
931 .child(
932 Button::new("sign_in", "Sign in")
933 .icon_color(Color::Muted)
934 .icon(IconName::Github)
935 .icon_position(IconPosition::Start)
936 .style(ButtonStyle::Filled)
937 .full_width()
938 .on_click(cx.listener(move |this, _, cx| this.authenticate(cx))),
939 )
940 .child(
941 div().flex().w_full().items_center().child(
942 Label::new("Sign in to enable collaboration.")
943 .color(Color::Muted)
944 .size(LabelSize::Small),
945 ),
946 ),
947 )
948 }
949 }
950}