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, LanguageModels};
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 let is_user = !cx.has_flag::<LanguageModels>();
172 if is_user {
173 models.insert(
174 anthropic::Model::Claude3_5Sonnet.id().to_string(),
175 CloudModel::Anthropic(anthropic::Model::Claude3_5Sonnet),
176 );
177 } else {
178 for model in anthropic::Model::iter() {
179 if !matches!(model, anthropic::Model::Custom { .. }) {
180 models.insert(model.id().to_string(), CloudModel::Anthropic(model));
181 }
182 }
183 for model in open_ai::Model::iter() {
184 if !matches!(model, open_ai::Model::Custom { .. }) {
185 models.insert(model.id().to_string(), CloudModel::OpenAi(model));
186 }
187 }
188 for model in google_ai::Model::iter() {
189 if !matches!(model, google_ai::Model::Custom { .. }) {
190 models.insert(model.id().to_string(), CloudModel::Google(model));
191 }
192 }
193 for model in ZedModel::iter() {
194 models.insert(model.id().to_string(), CloudModel::Zed(model));
195 }
196
197 // Override with available models from settings
198 for model in &AllLanguageModelSettings::get_global(cx)
199 .zed_dot_dev
200 .available_models
201 {
202 let model = match model.provider {
203 AvailableProvider::Anthropic => {
204 CloudModel::Anthropic(anthropic::Model::Custom {
205 name: model.name.clone(),
206 max_tokens: model.max_tokens,
207 tool_override: model.tool_override.clone(),
208 })
209 }
210 AvailableProvider::OpenAi => CloudModel::OpenAi(open_ai::Model::Custom {
211 name: model.name.clone(),
212 max_tokens: model.max_tokens,
213 }),
214 AvailableProvider::Google => CloudModel::Google(google_ai::Model::Custom {
215 name: model.name.clone(),
216 max_tokens: model.max_tokens,
217 }),
218 };
219 models.insert(model.id().to_string(), model.clone());
220 }
221 }
222
223 models
224 .into_values()
225 .map(|model| {
226 Arc::new(CloudLanguageModel {
227 id: LanguageModelId::from(model.id().to_string()),
228 model,
229 llm_api_token: self.llm_api_token.clone(),
230 client: self.client.clone(),
231 request_limiter: RateLimiter::new(4),
232 }) as Arc<dyn LanguageModel>
233 })
234 .collect()
235 }
236
237 fn is_authenticated(&self, cx: &AppContext) -> bool {
238 !self.state.read(cx).is_signed_out()
239 }
240
241 fn authenticate(&self, _cx: &mut AppContext) -> Task<Result<()>> {
242 Task::ready(Ok(()))
243 }
244
245 fn configuration_view(&self, cx: &mut WindowContext) -> AnyView {
246 cx.new_view(|_cx| ConfigurationView {
247 state: self.state.clone(),
248 })
249 .into()
250 }
251
252 fn must_accept_terms(&self, cx: &AppContext) -> bool {
253 !self.state.read(cx).has_accepted_terms_of_service(cx)
254 }
255
256 fn render_accept_terms(&self, cx: &mut WindowContext) -> Option<AnyElement> {
257 let state = self.state.read(cx);
258
259 let terms = [(
260 "anthropic_terms_of_service",
261 "Anthropic Terms of Service",
262 "https://www.anthropic.com/legal/consumer-terms",
263 )]
264 .map(|(id, label, url)| {
265 Button::new(id, label)
266 .style(ButtonStyle::Subtle)
267 .icon(IconName::ExternalLink)
268 .icon_size(IconSize::XSmall)
269 .icon_color(Color::Muted)
270 .on_click(move |_, cx| cx.open_url(url))
271 });
272
273 if state.has_accepted_terms_of_service(cx) {
274 None
275 } else {
276 let disabled = state.accept_terms.is_some();
277 Some(
278 v_flex()
279 .child(Label::new("Terms & Conditions").weight(FontWeight::SEMIBOLD))
280 .child("Please read and accept the terms and conditions of Zed AI and our provider partners to continue.")
281 .child(v_flex().m_2().gap_1().children(terms))
282 .child(
283 h_flex().justify_end().mt_1().child(
284 Button::new("accept_terms", "Accept")
285 .disabled(disabled)
286 .on_click({
287 let state = self.state.downgrade();
288 move |_, cx| {
289 state
290 .update(cx, |state, cx| {
291 state.accept_terms_of_service(cx)
292 })
293 .ok();
294 }
295 }),
296 ),
297 )
298 .into_any(),
299 )
300 }
301 }
302
303 fn reset_credentials(&self, _cx: &mut AppContext) -> Task<Result<()>> {
304 Task::ready(Ok(()))
305 }
306}
307
308pub struct CloudLanguageModel {
309 id: LanguageModelId,
310 model: CloudModel,
311 llm_api_token: LlmApiToken,
312 client: Arc<Client>,
313 request_limiter: RateLimiter,
314}
315
316#[derive(Clone, Default)]
317struct LlmApiToken(Arc<RwLock<Option<String>>>);
318
319impl CloudLanguageModel {
320 async fn perform_llm_completion(
321 client: Arc<Client>,
322 llm_api_token: LlmApiToken,
323 body: PerformCompletionParams,
324 ) -> Result<Response<AsyncBody>> {
325 let http_client = &client.http_client();
326
327 let mut token = llm_api_token.acquire(&client).await?;
328 let mut did_retry = false;
329
330 let response = loop {
331 let request = http_client::Request::builder()
332 .method(Method::POST)
333 .uri(http_client.build_zed_llm_url("/completion", &[])?.as_ref())
334 .header("Content-Type", "application/json")
335 .header("Authorization", format!("Bearer {token}"))
336 .body(serde_json::to_string(&body)?.into())?;
337 let mut response = http_client.send(request).await?;
338 if response.status().is_success() {
339 break response;
340 } else if !did_retry
341 && response
342 .headers()
343 .get(EXPIRED_LLM_TOKEN_HEADER_NAME)
344 .is_some()
345 {
346 did_retry = true;
347 token = llm_api_token.refresh(&client).await?;
348 } else {
349 let mut body = String::new();
350 response.body_mut().read_to_string(&mut body).await?;
351 break Err(anyhow!(
352 "cloud language model completion failed with status {}: {body}",
353 response.status()
354 ))?;
355 }
356 };
357
358 Ok(response)
359 }
360}
361
362impl LanguageModel for CloudLanguageModel {
363 fn id(&self) -> LanguageModelId {
364 self.id.clone()
365 }
366
367 fn name(&self) -> LanguageModelName {
368 LanguageModelName::from(self.model.display_name().to_string())
369 }
370
371 fn provider_id(&self) -> LanguageModelProviderId {
372 LanguageModelProviderId(PROVIDER_ID.into())
373 }
374
375 fn provider_name(&self) -> LanguageModelProviderName {
376 LanguageModelProviderName(PROVIDER_NAME.into())
377 }
378
379 fn telemetry_id(&self) -> String {
380 format!("zed.dev/{}", self.model.id())
381 }
382
383 fn availability(&self) -> LanguageModelAvailability {
384 self.model.availability()
385 }
386
387 fn max_token_count(&self) -> usize {
388 self.model.max_token_count()
389 }
390
391 fn count_tokens(
392 &self,
393 request: LanguageModelRequest,
394 cx: &AppContext,
395 ) -> BoxFuture<'static, Result<usize>> {
396 match self.model.clone() {
397 CloudModel::Anthropic(_) => count_anthropic_tokens(request, cx),
398 CloudModel::OpenAi(model) => count_open_ai_tokens(request, model, cx),
399 CloudModel::Google(model) => {
400 let client = self.client.clone();
401 let request = request.into_google(model.id().into());
402 let request = google_ai::CountTokensRequest {
403 contents: request.contents,
404 };
405 async move {
406 let request = serde_json::to_string(&request)?;
407 let response = client
408 .request(proto::CountLanguageModelTokens {
409 provider: proto::LanguageModelProvider::Google as i32,
410 request,
411 })
412 .await?;
413 Ok(response.token_count as usize)
414 }
415 .boxed()
416 }
417 CloudModel::Zed(_) => {
418 count_open_ai_tokens(request, open_ai::Model::ThreePointFiveTurbo, cx)
419 }
420 }
421 }
422
423 fn stream_completion(
424 &self,
425 request: LanguageModelRequest,
426 _cx: &AsyncAppContext,
427 ) -> BoxFuture<'static, Result<BoxStream<'static, Result<String>>>> {
428 match &self.model {
429 CloudModel::Anthropic(model) => {
430 let request = request.into_anthropic(model.id().into());
431 let client = self.client.clone();
432 let llm_api_token = self.llm_api_token.clone();
433 let future = self.request_limiter.stream(async move {
434 let response = Self::perform_llm_completion(
435 client.clone(),
436 llm_api_token,
437 PerformCompletionParams {
438 provider: client::LanguageModelProvider::Anthropic,
439 model: request.model.clone(),
440 provider_request: RawValue::from_string(serde_json::to_string(
441 &request,
442 )?)?,
443 },
444 )
445 .await?;
446 let body = BufReader::new(response.into_body());
447 let stream = futures::stream::try_unfold(body, move |mut body| async move {
448 let mut buffer = String::new();
449 match body.read_line(&mut buffer).await {
450 Ok(0) => Ok(None),
451 Ok(_) => {
452 let event: anthropic::Event = serde_json::from_str(&buffer)
453 .context("failed to parse Anthropic event")?;
454 Ok(Some((event, body)))
455 }
456 Err(err) => Err(AnthropicError::Other(err.into())),
457 }
458 });
459
460 Ok(anthropic::extract_text_from_events(stream))
461 });
462 async move {
463 Ok(future
464 .await?
465 .map(|result| result.map_err(|err| anyhow!(err)))
466 .boxed())
467 }
468 .boxed()
469 }
470 CloudModel::OpenAi(model) => {
471 let client = self.client.clone();
472 let request = request.into_open_ai(model.id().into());
473 let llm_api_token = self.llm_api_token.clone();
474 let future = self.request_limiter.stream(async move {
475 let response = Self::perform_llm_completion(
476 client.clone(),
477 llm_api_token,
478 PerformCompletionParams {
479 provider: client::LanguageModelProvider::OpenAi,
480 model: request.model.clone(),
481 provider_request: RawValue::from_string(serde_json::to_string(
482 &request,
483 )?)?,
484 },
485 )
486 .await?;
487 let body = BufReader::new(response.into_body());
488 let stream = futures::stream::try_unfold(body, move |mut body| async move {
489 let mut buffer = String::new();
490 match body.read_line(&mut buffer).await {
491 Ok(0) => Ok(None),
492 Ok(_) => {
493 let event: open_ai::ResponseStreamEvent =
494 serde_json::from_str(&buffer)?;
495 Ok(Some((event, body)))
496 }
497 Err(e) => Err(e.into()),
498 }
499 });
500
501 Ok(open_ai::extract_text_from_events(stream))
502 });
503 async move { Ok(future.await?.boxed()) }.boxed()
504 }
505 CloudModel::Google(model) => {
506 let client = self.client.clone();
507 let request = request.into_google(model.id().into());
508 let llm_api_token = self.llm_api_token.clone();
509 let future = self.request_limiter.stream(async move {
510 let response = Self::perform_llm_completion(
511 client.clone(),
512 llm_api_token,
513 PerformCompletionParams {
514 provider: client::LanguageModelProvider::Google,
515 model: request.model.clone(),
516 provider_request: RawValue::from_string(serde_json::to_string(
517 &request,
518 )?)?,
519 },
520 )
521 .await?;
522 let body = BufReader::new(response.into_body());
523 let stream = futures::stream::try_unfold(body, move |mut body| async move {
524 let mut buffer = String::new();
525 match body.read_line(&mut buffer).await {
526 Ok(0) => Ok(None),
527 Ok(_) => {
528 let event: google_ai::GenerateContentResponse =
529 serde_json::from_str(&buffer)?;
530 Ok(Some((event, body)))
531 }
532 Err(e) => Err(e.into()),
533 }
534 });
535
536 Ok(google_ai::extract_text_from_events(stream))
537 });
538 async move { Ok(future.await?.boxed()) }.boxed()
539 }
540 CloudModel::Zed(model) => {
541 let client = self.client.clone();
542 let mut request = request.into_open_ai(model.id().into());
543 request.max_tokens = Some(4000);
544 let llm_api_token = self.llm_api_token.clone();
545 let future = self.request_limiter.stream(async move {
546 let response = Self::perform_llm_completion(
547 client.clone(),
548 llm_api_token,
549 PerformCompletionParams {
550 provider: client::LanguageModelProvider::Zed,
551 model: request.model.clone(),
552 provider_request: RawValue::from_string(serde_json::to_string(
553 &request,
554 )?)?,
555 },
556 )
557 .await?;
558 let body = BufReader::new(response.into_body());
559 let stream = futures::stream::try_unfold(body, move |mut body| async move {
560 let mut buffer = String::new();
561 match body.read_line(&mut buffer).await {
562 Ok(0) => Ok(None),
563 Ok(_) => {
564 let event: open_ai::ResponseStreamEvent =
565 serde_json::from_str(&buffer)?;
566 Ok(Some((event, body)))
567 }
568 Err(e) => Err(e.into()),
569 }
570 });
571
572 Ok(open_ai::extract_text_from_events(stream))
573 });
574 async move { Ok(future.await?.boxed()) }.boxed()
575 }
576 }
577 }
578
579 fn use_any_tool(
580 &self,
581 request: LanguageModelRequest,
582 tool_name: String,
583 tool_description: String,
584 input_schema: serde_json::Value,
585 _cx: &AsyncAppContext,
586 ) -> BoxFuture<'static, Result<serde_json::Value>> {
587 match &self.model {
588 CloudModel::Anthropic(model) => {
589 let client = self.client.clone();
590 let mut request = request.into_anthropic(model.tool_model_id().into());
591 request.tool_choice = Some(anthropic::ToolChoice::Tool {
592 name: tool_name.clone(),
593 });
594 request.tools = vec![anthropic::Tool {
595 name: tool_name.clone(),
596 description: tool_description,
597 input_schema,
598 }];
599
600 let llm_api_token = self.llm_api_token.clone();
601 self.request_limiter
602 .run(async move {
603 let response = Self::perform_llm_completion(
604 client.clone(),
605 llm_api_token,
606 PerformCompletionParams {
607 provider: client::LanguageModelProvider::Anthropic,
608 model: request.model.clone(),
609 provider_request: RawValue::from_string(serde_json::to_string(
610 &request,
611 )?)?,
612 },
613 )
614 .await?;
615
616 let mut tool_use_index = None;
617 let mut tool_input = String::new();
618 let mut body = BufReader::new(response.into_body());
619 let mut line = String::new();
620 while body.read_line(&mut line).await? > 0 {
621 let event: anthropic::Event = serde_json::from_str(&line)?;
622 line.clear();
623
624 match event {
625 anthropic::Event::ContentBlockStart {
626 content_block,
627 index,
628 } => {
629 if let anthropic::Content::ToolUse { name, .. } = content_block
630 {
631 if name == tool_name {
632 tool_use_index = Some(index);
633 }
634 }
635 }
636 anthropic::Event::ContentBlockDelta { index, delta } => match delta
637 {
638 anthropic::ContentDelta::TextDelta { .. } => {}
639 anthropic::ContentDelta::InputJsonDelta { partial_json } => {
640 if Some(index) == tool_use_index {
641 tool_input.push_str(&partial_json);
642 }
643 }
644 },
645 anthropic::Event::ContentBlockStop { index } => {
646 if Some(index) == tool_use_index {
647 return Ok(serde_json::from_str(&tool_input)?);
648 }
649 }
650 _ => {}
651 }
652 }
653
654 if tool_use_index.is_some() {
655 Err(anyhow!("tool content incomplete"))
656 } else {
657 Err(anyhow!("tool not used"))
658 }
659 })
660 .boxed()
661 }
662 CloudModel::OpenAi(model) => {
663 let mut request = request.into_open_ai(model.id().into());
664 let client = self.client.clone();
665 let mut function = open_ai::FunctionDefinition {
666 name: tool_name.clone(),
667 description: None,
668 parameters: None,
669 };
670 let func = open_ai::ToolDefinition::Function {
671 function: function.clone(),
672 };
673 request.tool_choice = Some(open_ai::ToolChoice::Other(func.clone()));
674 // Fill in description and params separately, as they're not needed for tool_choice field.
675 function.description = Some(tool_description);
676 function.parameters = Some(input_schema);
677 request.tools = vec![open_ai::ToolDefinition::Function { function }];
678
679 let llm_api_token = self.llm_api_token.clone();
680 self.request_limiter
681 .run(async move {
682 let response = Self::perform_llm_completion(
683 client.clone(),
684 llm_api_token,
685 PerformCompletionParams {
686 provider: client::LanguageModelProvider::OpenAi,
687 model: request.model.clone(),
688 provider_request: RawValue::from_string(serde_json::to_string(
689 &request,
690 )?)?,
691 },
692 )
693 .await?;
694
695 let mut body = BufReader::new(response.into_body());
696 let mut line = String::new();
697 let mut load_state = None;
698
699 while body.read_line(&mut line).await? > 0 {
700 let part: open_ai::ResponseStreamEvent = serde_json::from_str(&line)?;
701 line.clear();
702
703 for choice in part.choices {
704 let Some(tool_calls) = choice.delta.tool_calls else {
705 continue;
706 };
707
708 for call in tool_calls {
709 if let Some(func) = call.function {
710 if func.name.as_deref() == Some(tool_name.as_str()) {
711 load_state = Some((String::default(), call.index));
712 }
713 if let Some((arguments, (output, index))) =
714 func.arguments.zip(load_state.as_mut())
715 {
716 if call.index == *index {
717 output.push_str(&arguments);
718 }
719 }
720 }
721 }
722 }
723 }
724
725 if let Some((arguments, _)) = load_state {
726 return Ok(serde_json::from_str(&arguments)?);
727 } else {
728 bail!("tool not used");
729 }
730 })
731 .boxed()
732 }
733 CloudModel::Google(_) => {
734 future::ready(Err(anyhow!("tool use not implemented for Google AI"))).boxed()
735 }
736 CloudModel::Zed(model) => {
737 // All Zed models are OpenAI-based at the time of writing.
738 let mut request = request.into_open_ai(model.id().into());
739 let client = self.client.clone();
740 let mut function = open_ai::FunctionDefinition {
741 name: tool_name.clone(),
742 description: None,
743 parameters: None,
744 };
745 let func = open_ai::ToolDefinition::Function {
746 function: function.clone(),
747 };
748 request.tool_choice = Some(open_ai::ToolChoice::Other(func.clone()));
749 // Fill in description and params separately, as they're not needed for tool_choice field.
750 function.description = Some(tool_description);
751 function.parameters = Some(input_schema);
752 request.tools = vec![open_ai::ToolDefinition::Function { function }];
753
754 let llm_api_token = self.llm_api_token.clone();
755 self.request_limiter
756 .run(async move {
757 let response = Self::perform_llm_completion(
758 client.clone(),
759 llm_api_token,
760 PerformCompletionParams {
761 provider: client::LanguageModelProvider::Zed,
762 model: request.model.clone(),
763 provider_request: RawValue::from_string(serde_json::to_string(
764 &request,
765 )?)?,
766 },
767 )
768 .await?;
769
770 let mut body = BufReader::new(response.into_body());
771 let mut line = String::new();
772 let mut load_state = None;
773
774 while body.read_line(&mut line).await? > 0 {
775 let part: open_ai::ResponseStreamEvent = serde_json::from_str(&line)?;
776 line.clear();
777
778 for choice in part.choices {
779 let Some(tool_calls) = choice.delta.tool_calls else {
780 continue;
781 };
782
783 for call in tool_calls {
784 if let Some(func) = call.function {
785 if func.name.as_deref() == Some(tool_name.as_str()) {
786 load_state = Some((String::default(), call.index));
787 }
788 if let Some((arguments, (output, index))) =
789 func.arguments.zip(load_state.as_mut())
790 {
791 if call.index == *index {
792 output.push_str(&arguments);
793 }
794 }
795 }
796 }
797 }
798 }
799 if let Some((arguments, _)) = load_state {
800 return Ok(serde_json::from_str(&arguments)?);
801 } else {
802 bail!("tool not used");
803 }
804 })
805 .boxed()
806 }
807 }
808 }
809}
810
811impl LlmApiToken {
812 async fn acquire(&self, client: &Arc<Client>) -> Result<String> {
813 let lock = self.0.upgradable_read().await;
814 if let Some(token) = lock.as_ref() {
815 Ok(token.to_string())
816 } else {
817 Self::fetch(RwLockUpgradableReadGuard::upgrade(lock).await, &client).await
818 }
819 }
820
821 async fn refresh(&self, client: &Arc<Client>) -> Result<String> {
822 Self::fetch(self.0.write().await, &client).await
823 }
824
825 async fn fetch<'a>(
826 mut lock: RwLockWriteGuard<'a, Option<String>>,
827 client: &Arc<Client>,
828 ) -> Result<String> {
829 let response = client.request(proto::GetLlmToken {}).await?;
830 *lock = Some(response.token.clone());
831 Ok(response.token.clone())
832 }
833}
834
835struct ConfigurationView {
836 state: gpui::Model<State>,
837}
838
839impl ConfigurationView {
840 fn authenticate(&mut self, cx: &mut ViewContext<Self>) {
841 self.state.update(cx, |state, cx| {
842 state.authenticate(cx).detach_and_log_err(cx);
843 });
844 cx.notify();
845 }
846}
847
848impl Render for ConfigurationView {
849 fn render(&mut self, cx: &mut ViewContext<Self>) -> impl IntoElement {
850 const ZED_AI_URL: &str = "https://zed.dev/ai";
851 const ACCOUNT_SETTINGS_URL: &str = "https://zed.dev/account";
852
853 let is_connected = !self.state.read(cx).is_signed_out();
854 let plan = self.state.read(cx).user_store.read(cx).current_plan();
855 let must_accept_terms = !self.state.read(cx).has_accepted_terms_of_service(cx);
856
857 let is_pro = plan == Some(proto::Plan::ZedPro);
858
859 if is_connected {
860 v_flex()
861 .gap_3()
862 .max_w_4_5()
863 .when(must_accept_terms, |this| {
864 this.child(Label::new(
865 "You must accept the terms of service to use this provider.",
866 ))
867 })
868 .child(Label::new(
869 if is_pro {
870 "You have full access to Zed's hosted models from Anthropic, OpenAI, Google with faster speeds and higher limits through Zed Pro."
871 } else {
872 "You have basic access to models from Anthropic, OpenAI, Google and more through the Zed AI Free plan."
873 }))
874 .child(
875 if is_pro {
876 h_flex().child(
877 Button::new("manage_settings", "Manage Subscription")
878 .style(ButtonStyle::Filled)
879 .on_click(cx.listener(|_, _, cx| {
880 cx.open_url(ACCOUNT_SETTINGS_URL)
881 })))
882 } else {
883 h_flex()
884 .gap_2()
885 .child(
886 Button::new("learn_more", "Learn more")
887 .style(ButtonStyle::Subtle)
888 .on_click(cx.listener(|_, _, cx| {
889 cx.open_url(ZED_AI_URL)
890 })))
891 .child(
892 Button::new("upgrade", "Upgrade")
893 .style(ButtonStyle::Subtle)
894 .color(Color::Accent)
895 .on_click(cx.listener(|_, _, cx| {
896 cx.open_url(ACCOUNT_SETTINGS_URL)
897 })))
898 },
899 )
900 } else {
901 v_flex()
902 .gap_6()
903 .child(Label::new("Use the zed.dev to access language models."))
904 .child(
905 v_flex()
906 .gap_2()
907 .child(
908 Button::new("sign_in", "Sign in")
909 .icon_color(Color::Muted)
910 .icon(IconName::Github)
911 .icon_position(IconPosition::Start)
912 .style(ButtonStyle::Filled)
913 .full_width()
914 .on_click(cx.listener(move |this, _, cx| this.authenticate(cx))),
915 )
916 .child(
917 div().flex().w_full().items_center().child(
918 Label::new("Sign in to enable collaboration.")
919 .color(Color::Muted)
920 .size(LabelSize::Small),
921 ),
922 ),
923 )
924 }
925 }
926}