1use super::open_ai::count_open_ai_tokens;
2use crate::{
3 settings::AllLanguageModelSettings, CloudModel, LanguageModel, LanguageModelId,
4 LanguageModelName, LanguageModelProviderId, LanguageModelProviderName,
5 LanguageModelProviderState, LanguageModelRequest, RateLimiter, ZedModel,
6};
7use anthropic::AnthropicError;
8use anyhow::{anyhow, bail, Context as _, Result};
9use client::{Client, PerformCompletionParams, UserStore, EXPIRED_LLM_TOKEN_HEADER_NAME};
10use collections::BTreeMap;
11use feature_flags::{FeatureFlagAppExt, ZedPro};
12use futures::{future::BoxFuture, stream::BoxStream, AsyncBufReadExt, FutureExt, StreamExt};
13use gpui::{
14 AnyElement, AnyView, AppContext, AsyncAppContext, FontWeight, Model, ModelContext,
15 Subscription, Task,
16};
17use http_client::{AsyncBody, HttpClient, Method, Response};
18use schemars::JsonSchema;
19use serde::{Deserialize, Serialize};
20use serde_json::value::RawValue;
21use settings::{Settings, SettingsStore};
22use smol::{
23 io::{AsyncReadExt, BufReader},
24 lock::{RwLock, RwLockUpgradableReadGuard, RwLockWriteGuard},
25};
26use std::{future, sync::Arc};
27use strum::IntoEnumIterator;
28use ui::prelude::*;
29
30use crate::{LanguageModelAvailability, LanguageModelProvider};
31
32use super::anthropic::count_anthropic_tokens;
33
34pub const PROVIDER_ID: &str = "zed.dev";
35pub const PROVIDER_NAME: &str = "Zed";
36
37#[derive(Default, Clone, Debug, PartialEq)]
38pub struct ZedDotDevSettings {
39 pub available_models: Vec<AvailableModel>,
40}
41
42#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
43#[serde(rename_all = "lowercase")]
44pub enum AvailableProvider {
45 Anthropic,
46 OpenAi,
47 Google,
48}
49
50#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
51pub struct AvailableModel {
52 provider: AvailableProvider,
53 name: String,
54 max_tokens: usize,
55 tool_override: Option<String>,
56}
57
58pub struct CloudLanguageModelProvider {
59 client: Arc<Client>,
60 llm_api_token: LlmApiToken,
61 state: gpui::Model<State>,
62 _maintain_client_status: Task<()>,
63}
64
65pub struct State {
66 client: Arc<Client>,
67 user_store: Model<UserStore>,
68 status: client::Status,
69 accept_terms: Option<Task<Result<()>>>,
70 _subscription: Subscription,
71}
72
73impl State {
74 fn is_signed_out(&self) -> bool {
75 self.status.is_signed_out()
76 }
77
78 fn authenticate(&self, cx: &mut ModelContext<Self>) -> Task<Result<()>> {
79 let client = self.client.clone();
80 cx.spawn(move |this, mut cx| async move {
81 client.authenticate_and_connect(true, &cx).await?;
82 this.update(&mut cx, |_, cx| cx.notify())
83 })
84 }
85
86 fn has_accepted_terms_of_service(&self, cx: &AppContext) -> bool {
87 self.user_store
88 .read(cx)
89 .current_user_has_accepted_terms()
90 .unwrap_or(false)
91 }
92
93 fn accept_terms_of_service(&mut self, cx: &mut ModelContext<Self>) {
94 let user_store = self.user_store.clone();
95 self.accept_terms = Some(cx.spawn(move |this, mut cx| async move {
96 let _ = user_store
97 .update(&mut cx, |store, cx| store.accept_terms_of_service(cx))?
98 .await;
99 this.update(&mut cx, |this, cx| {
100 this.accept_terms = None;
101 cx.notify()
102 })
103 }));
104 }
105}
106
107impl CloudLanguageModelProvider {
108 pub fn new(user_store: Model<UserStore>, client: Arc<Client>, cx: &mut AppContext) -> Self {
109 let mut status_rx = client.status();
110 let status = *status_rx.borrow();
111
112 let state = cx.new_model(|cx| State {
113 client: client.clone(),
114 user_store,
115 status,
116 accept_terms: None,
117 _subscription: cx.observe_global::<SettingsStore>(|_, cx| {
118 cx.notify();
119 }),
120 });
121
122 let state_ref = state.downgrade();
123 let maintain_client_status = cx.spawn(|mut cx| async move {
124 while let Some(status) = status_rx.next().await {
125 if let Some(this) = state_ref.upgrade() {
126 _ = this.update(&mut cx, |this, cx| {
127 if this.status != status {
128 this.status = status;
129 cx.notify();
130 }
131 });
132 } else {
133 break;
134 }
135 }
136 });
137
138 Self {
139 client,
140 state,
141 llm_api_token: LlmApiToken::default(),
142 _maintain_client_status: maintain_client_status,
143 }
144 }
145}
146
147impl LanguageModelProviderState for CloudLanguageModelProvider {
148 type ObservableEntity = State;
149
150 fn observable_entity(&self) -> Option<gpui::Model<Self::ObservableEntity>> {
151 Some(self.state.clone())
152 }
153}
154
155impl LanguageModelProvider for CloudLanguageModelProvider {
156 fn id(&self) -> LanguageModelProviderId {
157 LanguageModelProviderId(PROVIDER_ID.into())
158 }
159
160 fn name(&self) -> LanguageModelProviderName {
161 LanguageModelProviderName(PROVIDER_NAME.into())
162 }
163
164 fn icon(&self) -> IconName {
165 IconName::AiZed
166 }
167
168 fn provided_models(&self, cx: &AppContext) -> Vec<Arc<dyn LanguageModel>> {
169 let mut models = BTreeMap::default();
170
171 if cx.is_staff() {
172 for model in anthropic::Model::iter() {
173 if !matches!(model, anthropic::Model::Custom { .. }) {
174 models.insert(model.id().to_string(), CloudModel::Anthropic(model));
175 }
176 }
177 for model in open_ai::Model::iter() {
178 if !matches!(model, open_ai::Model::Custom { .. }) {
179 models.insert(model.id().to_string(), CloudModel::OpenAi(model));
180 }
181 }
182 for model in google_ai::Model::iter() {
183 if !matches!(model, google_ai::Model::Custom { .. }) {
184 models.insert(model.id().to_string(), CloudModel::Google(model));
185 }
186 }
187 for model in ZedModel::iter() {
188 models.insert(model.id().to_string(), CloudModel::Zed(model));
189 }
190
191 // Override with available models from settings
192 for model in &AllLanguageModelSettings::get_global(cx)
193 .zed_dot_dev
194 .available_models
195 {
196 let model = match model.provider {
197 AvailableProvider::Anthropic => {
198 CloudModel::Anthropic(anthropic::Model::Custom {
199 name: model.name.clone(),
200 max_tokens: model.max_tokens,
201 tool_override: model.tool_override.clone(),
202 })
203 }
204 AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {
205 name: model.name.clone(),
206 max_tokens: model.max_tokens,
207 }),
208 AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {
209 name: model.name.clone(),
210 max_tokens: model.max_tokens,
211 }),
212 };
213 models.insert(model.id().to_string(), model.clone());
214 }
215 } else {
216 models.insert(
217 anthropic::Model::Claude3_5Sonnet.id().to_string(),
218 CloudModel::Anthropic(anthropic::Model::Claude3_5Sonnet),
219 );
220 }
221
222 models
223 .into_values()
224 .map(|model| {
225 Arc::new(CloudLanguageModel {
226 id: LanguageModelId::from(model.id().to_string()),
227 model,
228 llm_api_token: self.llm_api_token.clone(),
229 client: self.client.clone(),
230 request_limiter: RateLimiter::new(4),
231 }) as Arc<dyn LanguageModel>
232 })
233 .collect()
234 }
235
236 fn is_authenticated(&self, cx: &AppContext) -> bool {
237 !self.state.read(cx).is_signed_out()
238 }
239
240 fn authenticate(&self, _cx: &mut AppContext) -> Task<Result<()>> {
241 Task::ready(Ok(()))
242 }
243
244 fn configuration_view(&self, cx: &mut WindowContext) -> AnyView {
245 cx.new_view(|_cx| ConfigurationView {
246 state: self.state.clone(),
247 })
248 .into()
249 }
250
251 fn must_accept_terms(&self, cx: &AppContext) -> bool {
252 !self.state.read(cx).has_accepted_terms_of_service(cx)
253 }
254
255 fn render_accept_terms(&self, cx: &mut WindowContext) -> Option<AnyElement> {
256 let state = self.state.read(cx);
257
258 let terms = [(
259 "terms_of_service",
260 "Terms of Service",
261 "https://zed.dev/terms-of-service",
262 )]
263 .map(|(id, label, url)| {
264 Button::new(id, label)
265 .style(ButtonStyle::Subtle)
266 .icon(IconName::ExternalLink)
267 .icon_size(IconSize::XSmall)
268 .icon_color(Color::Muted)
269 .on_click(move |_, cx| cx.open_url(url))
270 });
271
272 if state.has_accepted_terms_of_service(cx) {
273 None
274 } else {
275 let disabled = state.accept_terms.is_some();
276 Some(
277 v_flex()
278 .gap_2()
279 .child(
280 v_flex()
281 .child(Label::new("Terms and Conditions").weight(FontWeight::MEDIUM))
282 .child(
283 Label::new(
284 "Please read and accept our terms and conditions to continue.",
285 )
286 .size(LabelSize::Small),
287 ),
288 )
289 .child(v_flex().gap_1().children(terms))
290 .child(
291 h_flex().justify_end().child(
292 Button::new("accept_terms", "I've read it and accept it")
293 .disabled(disabled)
294 .on_click({
295 let state = self.state.downgrade();
296 move |_, cx| {
297 state
298 .update(cx, |state, cx| {
299 state.accept_terms_of_service(cx)
300 })
301 .ok();
302 }
303 }),
304 ),
305 )
306 .into_any(),
307 )
308 }
309 }
310
311 fn reset_credentials(&self, _cx: &mut AppContext) -> Task<Result<()>> {
312 Task::ready(Ok(()))
313 }
314}
315
316pub struct CloudLanguageModel {
317 id: LanguageModelId,
318 model: CloudModel,
319 llm_api_token: LlmApiToken,
320 client: Arc<Client>,
321 request_limiter: RateLimiter,
322}
323
324#[derive(Clone, Default)]
325struct LlmApiToken(Arc<RwLock<Option<String>>>);
326
327impl CloudLanguageModel {
328 async fn perform_llm_completion(
329 client: Arc<Client>,
330 llm_api_token: LlmApiToken,
331 body: PerformCompletionParams,
332 ) -> Result<Response<AsyncBody>> {
333 let http_client = &client.http_client();
334
335 let mut token = llm_api_token.acquire(&client).await?;
336 let mut did_retry = false;
337
338 let response = loop {
339 let request = http_client::Request::builder()
340 .method(Method::POST)
341 .uri(http_client.build_zed_llm_url("/completion", &[])?.as_ref())
342 .header("Content-Type", "application/json")
343 .header("Authorization", format!("Bearer {token}"))
344 .body(serde_json::to_string(&body)?.into())?;
345 let mut response = http_client.send(request).await?;
346 if response.status().is_success() {
347 break response;
348 } else if !did_retry
349 && response
350 .headers()
351 .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
352 .is_some()
353 {
354 did_retry = true;
355 token = llm_api_token.refresh(&client).await?;
356 } else {
357 let mut body = String::new();
358 response.body_mut().read_to_string(&mut body).await?;
359 break Err(anyhow!(
360 "cloud language model completion failed with status {}: {body}",
361 response.status()
362 ))?;
363 }
364 };
365
366 Ok(response)
367 }
368}
369
370impl LanguageModel for CloudLanguageModel {
371 fn id(&self) -> LanguageModelId {
372 self.id.clone()
373 }
374
375 fn name(&self) -> LanguageModelName {
376 LanguageModelName::from(self.model.display_name().to_string())
377 }
378
379 fn provider_id(&self) -> LanguageModelProviderId {
380 LanguageModelProviderId(PROVIDER_ID.into())
381 }
382
383 fn provider_name(&self) -> LanguageModelProviderName {
384 LanguageModelProviderName(PROVIDER_NAME.into())
385 }
386
387 fn telemetry_id(&self) -> String {
388 format!("zed.dev/{}", self.model.id())
389 }
390
391 fn availability(&self) -> LanguageModelAvailability {
392 self.model.availability()
393 }
394
395 fn max_token_count(&self) -> usize {
396 self.model.max_token_count()
397 }
398
399 fn count_tokens(
400 &self,
401 request: LanguageModelRequest,
402 cx: &AppContext,
403 ) -> BoxFuture<'static, Result<usize>> {
404 match self.model.clone() {
405 CloudModel::Anthropic(_) => count_anthropic_tokens(request, cx),
406 CloudModel::OpenAi(model) => count_open_ai_tokens(request, model, cx),
407 CloudModel::Google(model) => {
408 let client = self.client.clone();
409 let request = request.into_google(model.id().into());
410 let request = google_ai::CountTokensRequest {
411 contents: request.contents,
412 };
413 async move {
414 let request = serde_json::to_string(&request)?;
415 let response = client
416 .request(proto::CountLanguageModelTokens {
417 provider: proto::LanguageModelProvider::Google as i32,
418 request,
419 })
420 .await?;
421 Ok(response.token_count as usize)
422 }
423 .boxed()
424 }
425 CloudModel::Zed(_) => {
426 count_open_ai_tokens(request, open_ai::Model::ThreePointFiveTurbo, cx)
427 }
428 }
429 }
430
431 fn stream_completion(
432 &self,
433 request: LanguageModelRequest,
434 _cx: &AsyncAppContext,
435 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>> {
436 match &self.model {
437 CloudModel::Anthropic(model) => {
438 let request = request.into_anthropic(model.id().into());
439 let client = self.client.clone();
440 let llm_api_token = self.llm_api_token.clone();
441 let future = self.request_limiter.stream(async move {
442 let response = Self::perform_llm_completion(
443 client.clone(),
444 llm_api_token,
445 PerformCompletionParams {
446 provider: client::LanguageModelProvider::Anthropic,
447 model: request.model.clone(),
448 provider_request: RawValue::from_string(serde_json::to_string(
449 &request,
450 )?)?,
451 },
452 )
453 .await?;
454 let body = BufReader::new(response.into_body());
455 let stream = futures::stream::try_unfold(body, move |mut body| async move {
456 let mut buffer = String::new();
457 match body.read_line(&mut buffer).await {
458 Ok(0) => Ok(None),
459 Ok(_) => {
460 let event: anthropic::Event = serde_json::from_str(&buffer)
461 .context("failed to parse Anthropic event")?;
462 Ok(Some((event, body)))
463 }
464 Err(err) => Err(AnthropicError::Other(err.into())),
465 }
466 });
467
468 Ok(anthropic::extract_text_from_events(stream))
469 });
470 async move {
471 Ok(future
472 .await?
473 .map(|result| result.map_err(|err| anyhow!(err)))
474 .boxed())
475 }
476 .boxed()
477 }
478 CloudModel::OpenAi(model) => {
479 let client = self.client.clone();
480 let request = request.into_open_ai(model.id().into());
481 let llm_api_token = self.llm_api_token.clone();
482 let future = self.request_limiter.stream(async move {
483 let response = Self::perform_llm_completion(
484 client.clone(),
485 llm_api_token,
486 PerformCompletionParams {
487 provider: client::LanguageModelProvider::OpenAi,
488 model: request.model.clone(),
489 provider_request: RawValue::from_string(serde_json::to_string(
490 &request,
491 )?)?,
492 },
493 )
494 .await?;
495 let body = BufReader::new(response.into_body());
496 let stream = futures::stream::try_unfold(body, move |mut body| async move {
497 let mut buffer = String::new();
498 match body.read_line(&mut buffer).await {
499 Ok(0) => Ok(None),
500 Ok(_) => {
501 let event: open_ai::ResponseStreamEvent =
502 serde_json::from_str(&buffer)?;
503 Ok(Some((event, body)))
504 }
505 Err(e) => Err(e.into()),
506 }
507 });
508
509 Ok(open_ai::extract_text_from_events(stream))
510 });
511 async move { Ok(future.await?.boxed()) }.boxed()
512 }
513 CloudModel::Google(model) => {
514 let client = self.client.clone();
515 let request = request.into_google(model.id().into());
516 let llm_api_token = self.llm_api_token.clone();
517 let future = self.request_limiter.stream(async move {
518 let response = Self::perform_llm_completion(
519 client.clone(),
520 llm_api_token,
521 PerformCompletionParams {
522 provider: client::LanguageModelProvider::Google,
523 model: request.model.clone(),
524 provider_request: RawValue::from_string(serde_json::to_string(
525 &request,
526 )?)?,
527 },
528 )
529 .await?;
530 let body = BufReader::new(response.into_body());
531 let stream = futures::stream::try_unfold(body, move |mut body| async move {
532 let mut buffer = String::new();
533 match body.read_line(&mut buffer).await {
534 Ok(0) => Ok(None),
535 Ok(_) => {
536 let event: google_ai::GenerateContentResponse =
537 serde_json::from_str(&buffer)?;
538 Ok(Some((event, body)))
539 }
540 Err(e) => Err(e.into()),
541 }
542 });
543
544 Ok(google_ai::extract_text_from_events(stream))
545 });
546 async move { Ok(future.await?.boxed()) }.boxed()
547 }
548 CloudModel::Zed(model) => {
549 let client = self.client.clone();
550 let mut request = request.into_open_ai(model.id().into());
551 request.max_tokens = Some(4000);
552 let llm_api_token = self.llm_api_token.clone();
553 let future = self.request_limiter.stream(async move {
554 let response = Self::perform_llm_completion(
555 client.clone(),
556 llm_api_token,
557 PerformCompletionParams {
558 provider: client::LanguageModelProvider::Zed,
559 model: request.model.clone(),
560 provider_request: RawValue::from_string(serde_json::to_string(
561 &request,
562 )?)?,
563 },
564 )
565 .await?;
566 let body = BufReader::new(response.into_body());
567 let stream = futures::stream::try_unfold(body, move |mut body| async move {
568 let mut buffer = String::new();
569 match body.read_line(&mut buffer).await {
570 Ok(0) => Ok(None),
571 Ok(_) => {
572 let event: open_ai::ResponseStreamEvent =
573 serde_json::from_str(&buffer)?;
574 Ok(Some((event, body)))
575 }
576 Err(e) => Err(e.into()),
577 }
578 });
579
580 Ok(open_ai::extract_text_from_events(stream))
581 });
582 async move { Ok(future.await?.boxed()) }.boxed()
583 }
584 }
585 }
586
587 fn use_any_tool(
588 &self,
589 request: LanguageModelRequest,
590 tool_name: String,
591 tool_description: String,
592 input_schema: serde_json::Value,
593 _cx: &AsyncAppContext,
594 ) -> BoxFuture<'static, Result<serde_json::Value>> {
595 match &self.model {
596 CloudModel::Anthropic(model) => {
597 let client = self.client.clone();
598 let mut request = request.into_anthropic(model.tool_model_id().into());
599 request.tool_choice = Some(anthropic::ToolChoice::Tool {
600 name: tool_name.clone(),
601 });
602 request.tools = vec![anthropic::Tool {
603 name: tool_name.clone(),
604 description: tool_description,
605 input_schema,
606 }];
607
608 let llm_api_token = self.llm_api_token.clone();
609 self.request_limiter
610 .run(async move {
611 let response = Self::perform_llm_completion(
612 client.clone(),
613 llm_api_token,
614 PerformCompletionParams {
615 provider: client::LanguageModelProvider::Anthropic,
616 model: request.model.clone(),
617 provider_request: RawValue::from_string(serde_json::to_string(
618 &request,
619 )?)?,
620 },
621 )
622 .await?;
623
624 let mut tool_use_index = None;
625 let mut tool_input = String::new();
626 let mut body = BufReader::new(response.into_body());
627 let mut line = String::new();
628 while body.read_line(&mut line).await? > 0 {
629 let event: anthropic::Event = serde_json::from_str(&line)?;
630 line.clear();
631
632 match event {
633 anthropic::Event::ContentBlockStart {
634 content_block,
635 index,
636 } => {
637 if let anthropic::Content::ToolUse { name, .. } = content_block
638 {
639 if name == tool_name {
640 tool_use_index = Some(index);
641 }
642 }
643 }
644 anthropic::Event::ContentBlockDelta { index, delta } => match delta
645 {
646 anthropic::ContentDelta::TextDelta { .. } => {}
647 anthropic::ContentDelta::InputJsonDelta { partial_json } => {
648 if Some(index) == tool_use_index {
649 tool_input.push_str(&partial_json);
650 }
651 }
652 },
653 anthropic::Event::ContentBlockStop { index } => {
654 if Some(index) == tool_use_index {
655 return Ok(serde_json::from_str(&tool_input)?);
656 }
657 }
658 _ => {}
659 }
660 }
661
662 if tool_use_index.is_some() {
663 Err(anyhow!("tool content incomplete"))
664 } else {
665 Err(anyhow!("tool not used"))
666 }
667 })
668 .boxed()
669 }
670 CloudModel::OpenAi(model) => {
671 let mut request = request.into_open_ai(model.id().into());
672 let client = self.client.clone();
673 let mut function = open_ai::FunctionDefinition {
674 name: tool_name.clone(),
675 description: None,
676 parameters: None,
677 };
678 let func = open_ai::ToolDefinition::Function {
679 function: function.clone(),
680 };
681 request.tool_choice = Some(open_ai::ToolChoice::Other(func.clone()));
682 // Fill in description and params separately, as they're not needed for tool_choice field.
683 function.description = Some(tool_description);
684 function.parameters = Some(input_schema);
685 request.tools = vec![open_ai::ToolDefinition::Function { function }];
686
687 let llm_api_token = self.llm_api_token.clone();
688 self.request_limiter
689 .run(async move {
690 let response = Self::perform_llm_completion(
691 client.clone(),
692 llm_api_token,
693 PerformCompletionParams {
694 provider: client::LanguageModelProvider::OpenAi,
695 model: request.model.clone(),
696 provider_request: RawValue::from_string(serde_json::to_string(
697 &request,
698 )?)?,
699 },
700 )
701 .await?;
702
703 let mut body = BufReader::new(response.into_body());
704 let mut line = String::new();
705 let mut load_state = None;
706
707 while body.read_line(&mut line).await? > 0 {
708 let part: open_ai::ResponseStreamEvent = serde_json::from_str(&line)?;
709 line.clear();
710
711 for choice in part.choices {
712 let Some(tool_calls) = choice.delta.tool_calls else {
713 continue;
714 };
715
716 for call in tool_calls {
717 if let Some(func) = call.function {
718 if func.name.as_deref() == Some(tool_name.as_str()) {
719 load_state = Some((String::default(), call.index));
720 }
721 if let Some((arguments, (output, index))) =
722 func.arguments.zip(load_state.as_mut())
723 {
724 if call.index == *index {
725 output.push_str(&arguments);
726 }
727 }
728 }
729 }
730 }
731 }
732
733 if let Some((arguments, _)) = load_state {
734 return Ok(serde_json::from_str(&arguments)?);
735 } else {
736 bail!("tool not used");
737 }
738 })
739 .boxed()
740 }
741 CloudModel::Google(_) => {
742 future::ready(Err(anyhow!("tool use not implemented for Google AI"))).boxed()
743 }
744 CloudModel::Zed(model) => {
745 // All Zed models are OpenAI-based at the time of writing.
746 let mut request = request.into_open_ai(model.id().into());
747 let client = self.client.clone();
748 let mut function = open_ai::FunctionDefinition {
749 name: tool_name.clone(),
750 description: None,
751 parameters: None,
752 };
753 let func = open_ai::ToolDefinition::Function {
754 function: function.clone(),
755 };
756 request.tool_choice = Some(open_ai::ToolChoice::Other(func.clone()));
757 // Fill in description and params separately, as they're not needed for tool_choice field.
758 function.description = Some(tool_description);
759 function.parameters = Some(input_schema);
760 request.tools = vec![open_ai::ToolDefinition::Function { function }];
761
762 let llm_api_token = self.llm_api_token.clone();
763 self.request_limiter
764 .run(async move {
765 let response = Self::perform_llm_completion(
766 client.clone(),
767 llm_api_token,
768 PerformCompletionParams {
769 provider: client::LanguageModelProvider::Zed,
770 model: request.model.clone(),
771 provider_request: RawValue::from_string(serde_json::to_string(
772 &request,
773 )?)?,
774 },
775 )
776 .await?;
777
778 let mut body = BufReader::new(response.into_body());
779 let mut line = String::new();
780 let mut load_state = None;
781
782 while body.read_line(&mut line).await? > 0 {
783 let part: open_ai::ResponseStreamEvent = serde_json::from_str(&line)?;
784 line.clear();
785
786 for choice in part.choices {
787 let Some(tool_calls) = choice.delta.tool_calls else {
788 continue;
789 };
790
791 for call in tool_calls {
792 if let Some(func) = call.function {
793 if func.name.as_deref() == Some(tool_name.as_str()) {
794 load_state = Some((String::default(), call.index));
795 }
796 if let Some((arguments, (output, index))) =
797 func.arguments.zip(load_state.as_mut())
798 {
799 if call.index == *index {
800 output.push_str(&arguments);
801 }
802 }
803 }
804 }
805 }
806 }
807 if let Some((arguments, _)) = load_state {
808 return Ok(serde_json::from_str(&arguments)?);
809 } else {
810 bail!("tool not used");
811 }
812 })
813 .boxed()
814 }
815 }
816 }
817}
818
819impl LlmApiToken {
820 async fn acquire(&self, client: &Arc<Client>) -> Result<String> {
821 let lock = self.0.upgradable_read().await;
822 if let Some(token) = lock.as_ref() {
823 Ok(token.to_string())
824 } else {
825 Self::fetch(RwLockUpgradableReadGuard::upgrade(lock).await, &client).await
826 }
827 }
828
829 async fn refresh(&self, client: &Arc<Client>) -> Result<String> {
830 Self::fetch(self.0.write().await, &client).await
831 }
832
833 async fn fetch<'a>(
834 mut lock: RwLockWriteGuard<'a, Option<String>>,
835 client: &Arc<Client>,
836 ) -> Result<String> {
837 let response = client.request(proto::GetLlmToken {}).await?;
838 *lock = Some(response.token.clone());
839 Ok(response.token.clone())
840 }
841}
842
843struct ConfigurationView {
844 state: gpui::Model<State>,
845}
846
847impl ConfigurationView {
848 fn authenticate(&mut self, cx: &mut ViewContext<Self>) {
849 self.state.update(cx, |state, cx| {
850 state.authenticate(cx).detach_and_log_err(cx);
851 });
852 cx.notify();
853 }
854}
855
856impl Render for ConfigurationView {
857 fn render(&mut self, cx: &mut ViewContext<Self>) -> impl IntoElement {
858 const ZED_AI_URL: &str = "https://zed.dev/ai";
859 const ACCOUNT_SETTINGS_URL: &str = "https://zed.dev/account";
860
861 let is_connected = !self.state.read(cx).is_signed_out();
862 let plan = self.state.read(cx).user_store.read(cx).current_plan();
863 let must_accept_terms = !self.state.read(cx).has_accepted_terms_of_service(cx);
864
865 let is_pro = plan == Some(proto::Plan::ZedPro);
866
867 if is_connected {
868 v_flex()
869 .gap_3()
870 .max_w_4_5()
871 .when(must_accept_terms, |this| {
872 this.child(Label::new(
873 "You must accept the terms of service to use this provider.",
874 ))
875 })
876 .child(Label::new(
877 if is_pro {
878 "You have full access to Zed's hosted models from Anthropic, OpenAI, Google with faster speeds and higher limits through Zed Pro."
879 } else {
880 "You have basic access to models from Anthropic through the Zed AI Free plan."
881 }))
882 .children(if is_pro {
883 Some(
884 h_flex().child(
885 Button::new("manage_settings", "Manage Subscription")
886 .style(ButtonStyle::Filled)
887 .on_click(
888 cx.listener(|_, _, cx| cx.open_url(ACCOUNT_SETTINGS_URL)),
889 ),
890 ),
891 )
892 } else if cx.has_flag::<ZedPro>() {
893 Some(
894 h_flex()
895 .gap_2()
896 .child(
897 Button::new("learn_more", "Learn more")
898 .style(ButtonStyle::Subtle)
899 .on_click(cx.listener(|_, _, cx| cx.open_url(ZED_AI_URL))),
900 )
901 .child(
902 Button::new("upgrade", "Upgrade")
903 .style(ButtonStyle::Subtle)
904 .color(Color::Accent)
905 .on_click(
906 cx.listener(|_, _, cx| cx.open_url(ACCOUNT_SETTINGS_URL)),
907 ),
908 ),
909 )
910 } else {
911 None
912 })
913 } else {
914 v_flex()
915 .gap_6()
916 .child(Label::new("Use the zed.dev to access language models."))
917 .child(
918 v_flex()
919 .gap_2()
920 .child(
921 Button::new("sign_in", "Sign in")
922 .icon_color(Color::Muted)
923 .icon(IconName::Github)
924 .icon_position(IconPosition::Start)
925 .style(ButtonStyle::Filled)
926 .full_width()
927 .on_click(cx.listener(move |this, _, cx| this.authenticate(cx))),
928 )
929 .child(
930 div().flex().w_full().items_center().child(
931 Label::new("Sign in to enable collaboration.")
932 .color(Color::Muted)
933 .size(LabelSize::Small),
934 ),
935 ),
936 )
937 }
938 }
939}