1use anyhow::{Context as _, Result, anyhow};
2use collections::{BTreeMap, HashMap};
3use credentials_provider::CredentialsProvider;
4
5use futures::Stream;
6use futures::{FutureExt, StreamExt, future::BoxFuture};
7use gpui::{AnyView, App, AsyncApp, Context, Entity, Subscription, Task, Window};
8use http_client::HttpClient;
9use language_model::{
10 AuthenticateError, LanguageModel, LanguageModelCompletionError, LanguageModelCompletionEvent,
11 LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
12 LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
13 LanguageModelToolChoice, LanguageModelToolResultContent, LanguageModelToolUse, MessageContent,
14 RateLimiter, Role, StopReason, TokenUsage,
15};
16use menu;
17use open_ai::{ImageUrl, Model, ResponseStreamEvent, stream_completion};
18use schemars::JsonSchema;
19use serde::{Deserialize, Serialize};
20use settings::{Settings, SettingsStore};
21use std::pin::Pin;
22use std::str::FromStr as _;
23use std::sync::Arc;
24use strum::IntoEnumIterator;
25
26use ui::{ElevationIndex, List, Tooltip, prelude::*};
27use ui_input::SingleLineInput;
28use util::ResultExt;
29
30use crate::{AllLanguageModelSettings, ui::InstructionListItem};
31
32const PROVIDER_ID: LanguageModelProviderId = language_model::OPEN_AI_PROVIDER_ID;
33const PROVIDER_NAME: LanguageModelProviderName = language_model::OPEN_AI_PROVIDER_NAME;
34
35#[derive(Default, Clone, Debug, PartialEq)]
36pub struct OpenAiSettings {
37 pub api_url: String,
38 pub available_models: Vec<AvailableModel>,
39}
40
41#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
42pub struct AvailableModel {
43 pub name: String,
44 pub display_name: Option<String>,
45 pub max_tokens: u64,
46 pub max_output_tokens: Option<u64>,
47 pub max_completion_tokens: Option<u64>,
48}
49
50pub struct OpenAiLanguageModelProvider {
51 http_client: Arc<dyn HttpClient>,
52 state: gpui::Entity<State>,
53}
54
55pub struct State {
56 api_key: Option<String>,
57 api_key_from_env: bool,
58 _subscription: Subscription,
59}
60
61const OPENAI_API_KEY_VAR: &str = "OPENAI_API_KEY";
62
63impl State {
64 //
65 fn is_authenticated(&self) -> bool {
66 self.api_key.is_some()
67 }
68
69 fn reset_api_key(&self, cx: &mut Context<Self>) -> Task<Result<()>> {
70 let credentials_provider = <dyn CredentialsProvider>::global(cx);
71 let api_url = AllLanguageModelSettings::get_global(cx)
72 .openai
73 .api_url
74 .clone();
75 cx.spawn(async move |this, cx| {
76 credentials_provider
77 .delete_credentials(&api_url, &cx)
78 .await
79 .log_err();
80 this.update(cx, |this, cx| {
81 this.api_key = None;
82 this.api_key_from_env = false;
83 cx.notify();
84 })
85 })
86 }
87
88 fn set_api_key(&mut self, api_key: String, cx: &mut Context<Self>) -> Task<Result<()>> {
89 let credentials_provider = <dyn CredentialsProvider>::global(cx);
90 let api_url = AllLanguageModelSettings::get_global(cx)
91 .openai
92 .api_url
93 .clone();
94 cx.spawn(async move |this, cx| {
95 credentials_provider
96 .write_credentials(&api_url, "Bearer", api_key.as_bytes(), &cx)
97 .await
98 .log_err();
99 this.update(cx, |this, cx| {
100 this.api_key = Some(api_key);
101 cx.notify();
102 })
103 })
104 }
105
106 fn authenticate(&self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
107 if self.is_authenticated() {
108 return Task::ready(Ok(()));
109 }
110
111 let credentials_provider = <dyn CredentialsProvider>::global(cx);
112 let api_url = AllLanguageModelSettings::get_global(cx)
113 .openai
114 .api_url
115 .clone();
116 cx.spawn(async move |this, cx| {
117 let (api_key, from_env) = if let Ok(api_key) = std::env::var(OPENAI_API_KEY_VAR) {
118 (api_key, true)
119 } else {
120 let (_, api_key) = credentials_provider
121 .read_credentials(&api_url, &cx)
122 .await?
123 .ok_or(AuthenticateError::CredentialsNotFound)?;
124 (
125 String::from_utf8(api_key).context("invalid {PROVIDER_NAME} API key")?,
126 false,
127 )
128 };
129 this.update(cx, |this, cx| {
130 this.api_key = Some(api_key);
131 this.api_key_from_env = from_env;
132 cx.notify();
133 })?;
134
135 Ok(())
136 })
137 }
138}
139
140impl OpenAiLanguageModelProvider {
141 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
142 let state = cx.new(|cx| State {
143 api_key: None,
144 api_key_from_env: false,
145 _subscription: cx.observe_global::<SettingsStore>(|_this: &mut State, cx| {
146 cx.notify();
147 }),
148 });
149
150 Self { http_client, state }
151 }
152
153 fn create_language_model(&self, model: open_ai::Model) -> Arc<dyn LanguageModel> {
154 Arc::new(OpenAiLanguageModel {
155 id: LanguageModelId::from(model.id().to_string()),
156 model,
157 state: self.state.clone(),
158 http_client: self.http_client.clone(),
159 request_limiter: RateLimiter::new(4),
160 })
161 }
162}
163
164impl LanguageModelProviderState for OpenAiLanguageModelProvider {
165 type ObservableEntity = State;
166
167 fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>> {
168 Some(self.state.clone())
169 }
170}
171
172impl LanguageModelProvider for OpenAiLanguageModelProvider {
173 fn id(&self) -> LanguageModelProviderId {
174 PROVIDER_ID
175 }
176
177 fn name(&self) -> LanguageModelProviderName {
178 PROVIDER_NAME
179 }
180
181 fn icon(&self) -> IconName {
182 IconName::AiOpenAi
183 }
184
185 fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
186 Some(self.create_language_model(open_ai::Model::default()))
187 }
188
189 fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
190 Some(self.create_language_model(open_ai::Model::default_fast()))
191 }
192
193 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
194 let mut models = BTreeMap::default();
195
196 // Add base models from open_ai::Model::iter()
197 for model in open_ai::Model::iter() {
198 if !matches!(model, open_ai::Model::Custom { .. }) {
199 models.insert(model.id().to_string(), model);
200 }
201 }
202
203 // Override with available models from settings
204 for model in &AllLanguageModelSettings::get_global(cx)
205 .openai
206 .available_models
207 {
208 models.insert(
209 model.name.clone(),
210 open_ai::Model::Custom {
211 name: model.name.clone(),
212 display_name: model.display_name.clone(),
213 max_tokens: model.max_tokens,
214 max_output_tokens: model.max_output_tokens,
215 max_completion_tokens: model.max_completion_tokens,
216 },
217 );
218 }
219
220 models
221 .into_values()
222 .map(|model| self.create_language_model(model))
223 .collect()
224 }
225
226 fn is_authenticated(&self, cx: &App) -> bool {
227 self.state.read(cx).is_authenticated()
228 }
229
230 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
231 self.state.update(cx, |state, cx| state.authenticate(cx))
232 }
233
234 fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView {
235 cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
236 .into()
237 }
238
239 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
240 self.state.update(cx, |state, cx| state.reset_api_key(cx))
241 }
242}
243
244pub struct OpenAiLanguageModel {
245 id: LanguageModelId,
246 model: open_ai::Model,
247 state: gpui::Entity<State>,
248 http_client: Arc<dyn HttpClient>,
249 request_limiter: RateLimiter,
250}
251
252impl OpenAiLanguageModel {
253 fn stream_completion(
254 &self,
255 request: open_ai::Request,
256 cx: &AsyncApp,
257 ) -> BoxFuture<'static, Result<futures::stream::BoxStream<'static, Result<ResponseStreamEvent>>>>
258 {
259 let http_client = self.http_client.clone();
260 let Ok((api_key, api_url)) = cx.read_entity(&self.state, |state, cx| {
261 let settings = &AllLanguageModelSettings::get_global(cx).openai;
262 (state.api_key.clone(), settings.api_url.clone())
263 }) else {
264 return futures::future::ready(Err(anyhow!("App state dropped"))).boxed();
265 };
266
267 let future = self.request_limiter.stream(async move {
268 let Some(api_key) = api_key else {
269 return Err(LanguageModelCompletionError::NoApiKey {
270 provider: PROVIDER_NAME,
271 });
272 };
273 let request = stream_completion(http_client.as_ref(), &api_url, &api_key, request);
274 let response = request.await?;
275 Ok(response)
276 });
277
278 async move { Ok(future.await?.boxed()) }.boxed()
279 }
280}
281
282impl LanguageModel for OpenAiLanguageModel {
283 fn id(&self) -> LanguageModelId {
284 self.id.clone()
285 }
286
287 fn name(&self) -> LanguageModelName {
288 LanguageModelName::from(self.model.display_name().to_string())
289 }
290
291 fn provider_id(&self) -> LanguageModelProviderId {
292 PROVIDER_ID
293 }
294
295 fn provider_name(&self) -> LanguageModelProviderName {
296 PROVIDER_NAME
297 }
298
299 fn supports_tools(&self) -> bool {
300 true
301 }
302
303 fn supports_images(&self) -> bool {
304 false
305 }
306
307 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
308 match choice {
309 LanguageModelToolChoice::Auto => true,
310 LanguageModelToolChoice::Any => true,
311 LanguageModelToolChoice::None => true,
312 }
313 }
314
315 fn telemetry_id(&self) -> String {
316 format!("openai/{}", self.model.id())
317 }
318
319 fn max_token_count(&self) -> u64 {
320 self.model.max_token_count()
321 }
322
323 fn max_output_tokens(&self) -> Option<u64> {
324 self.model.max_output_tokens()
325 }
326
327 fn count_tokens(
328 &self,
329 request: LanguageModelRequest,
330 cx: &App,
331 ) -> BoxFuture<'static, Result<u64>> {
332 count_open_ai_tokens(request, self.model.clone(), cx)
333 }
334
335 fn stream_completion(
336 &self,
337 request: LanguageModelRequest,
338 cx: &AsyncApp,
339 ) -> BoxFuture<
340 'static,
341 Result<
342 futures::stream::BoxStream<
343 'static,
344 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
345 >,
346 LanguageModelCompletionError,
347 >,
348 > {
349 let request = into_open_ai(
350 request,
351 self.model.id(),
352 self.model.supports_parallel_tool_calls(),
353 self.max_output_tokens(),
354 );
355 let completions = self.stream_completion(request, cx);
356 async move {
357 let mapper = OpenAiEventMapper::new();
358 Ok(mapper.map_stream(completions.await?).boxed())
359 }
360 .boxed()
361 }
362}
363
364pub fn into_open_ai(
365 request: LanguageModelRequest,
366 model_id: &str,
367 supports_parallel_tool_calls: bool,
368 max_output_tokens: Option<u64>,
369) -> open_ai::Request {
370 let stream = !model_id.starts_with("o1-");
371
372 let mut messages = Vec::new();
373 for message in request.messages {
374 for content in message.content {
375 match content {
376 MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
377 add_message_content_part(
378 open_ai::MessagePart::Text { text: text },
379 message.role,
380 &mut messages,
381 )
382 }
383 MessageContent::RedactedThinking(_) => {}
384 MessageContent::Image(image) => {
385 add_message_content_part(
386 open_ai::MessagePart::Image {
387 image_url: ImageUrl {
388 url: image.to_base64_url(),
389 detail: None,
390 },
391 },
392 message.role,
393 &mut messages,
394 );
395 }
396 MessageContent::ToolUse(tool_use) => {
397 let tool_call = open_ai::ToolCall {
398 id: tool_use.id.to_string(),
399 content: open_ai::ToolCallContent::Function {
400 function: open_ai::FunctionContent {
401 name: tool_use.name.to_string(),
402 arguments: serde_json::to_string(&tool_use.input)
403 .unwrap_or_default(),
404 },
405 },
406 };
407
408 if let Some(open_ai::RequestMessage::Assistant { tool_calls, .. }) =
409 messages.last_mut()
410 {
411 tool_calls.push(tool_call);
412 } else {
413 messages.push(open_ai::RequestMessage::Assistant {
414 content: None,
415 tool_calls: vec![tool_call],
416 });
417 }
418 }
419 MessageContent::ToolResult(tool_result) => {
420 let content = match &tool_result.content {
421 LanguageModelToolResultContent::Text(text) => {
422 vec![open_ai::MessagePart::Text {
423 text: text.to_string(),
424 }]
425 }
426 LanguageModelToolResultContent::Image(image) => {
427 vec![open_ai::MessagePart::Image {
428 image_url: ImageUrl {
429 url: image.to_base64_url(),
430 detail: None,
431 },
432 }]
433 }
434 };
435
436 messages.push(open_ai::RequestMessage::Tool {
437 content: content.into(),
438 tool_call_id: tool_result.tool_use_id.to_string(),
439 });
440 }
441 }
442 }
443 }
444
445 open_ai::Request {
446 model: model_id.into(),
447 messages,
448 stream,
449 stop: request.stop,
450 temperature: request.temperature.unwrap_or(1.0),
451 max_completion_tokens: max_output_tokens,
452 parallel_tool_calls: if supports_parallel_tool_calls && !request.tools.is_empty() {
453 // Disable parallel tool calls, as the Agent currently expects a maximum of one per turn.
454 Some(false)
455 } else {
456 None
457 },
458 tools: request
459 .tools
460 .into_iter()
461 .map(|tool| open_ai::ToolDefinition::Function {
462 function: open_ai::FunctionDefinition {
463 name: tool.name,
464 description: Some(tool.description),
465 parameters: Some(tool.input_schema),
466 },
467 })
468 .collect(),
469 tool_choice: request.tool_choice.map(|choice| match choice {
470 LanguageModelToolChoice::Auto => open_ai::ToolChoice::Auto,
471 LanguageModelToolChoice::Any => open_ai::ToolChoice::Required,
472 LanguageModelToolChoice::None => open_ai::ToolChoice::None,
473 }),
474 }
475}
476
477fn add_message_content_part(
478 new_part: open_ai::MessagePart,
479 role: Role,
480 messages: &mut Vec<open_ai::RequestMessage>,
481) {
482 match (role, messages.last_mut()) {
483 (Role::User, Some(open_ai::RequestMessage::User { content }))
484 | (
485 Role::Assistant,
486 Some(open_ai::RequestMessage::Assistant {
487 content: Some(content),
488 ..
489 }),
490 )
491 | (Role::System, Some(open_ai::RequestMessage::System { content, .. })) => {
492 content.push_part(new_part);
493 }
494 _ => {
495 messages.push(match role {
496 Role::User => open_ai::RequestMessage::User {
497 content: open_ai::MessageContent::from(vec![new_part]),
498 },
499 Role::Assistant => open_ai::RequestMessage::Assistant {
500 content: Some(open_ai::MessageContent::from(vec![new_part])),
501 tool_calls: Vec::new(),
502 },
503 Role::System => open_ai::RequestMessage::System {
504 content: open_ai::MessageContent::from(vec![new_part]),
505 },
506 });
507 }
508 }
509}
510
511pub struct OpenAiEventMapper {
512 tool_calls_by_index: HashMap<usize, RawToolCall>,
513}
514
515impl OpenAiEventMapper {
516 pub fn new() -> Self {
517 Self {
518 tool_calls_by_index: HashMap::default(),
519 }
520 }
521
522 pub fn map_stream(
523 mut self,
524 events: Pin<Box<dyn Send + Stream<Item = Result<ResponseStreamEvent>>>>,
525 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
526 {
527 events.flat_map(move |event| {
528 futures::stream::iter(match event {
529 Ok(event) => self.map_event(event),
530 Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
531 })
532 })
533 }
534
535 pub fn map_event(
536 &mut self,
537 event: ResponseStreamEvent,
538 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
539 let mut events = Vec::new();
540 if let Some(usage) = event.usage {
541 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
542 input_tokens: usage.prompt_tokens,
543 output_tokens: usage.completion_tokens,
544 cache_creation_input_tokens: 0,
545 cache_read_input_tokens: 0,
546 })));
547 }
548
549 let Some(choice) = event.choices.first() else {
550 return events;
551 };
552
553 if let Some(content) = choice.delta.content.clone() {
554 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
555 }
556
557 if let Some(tool_calls) = choice.delta.tool_calls.as_ref() {
558 for tool_call in tool_calls {
559 let entry = self.tool_calls_by_index.entry(tool_call.index).or_default();
560
561 if let Some(tool_id) = tool_call.id.clone() {
562 entry.id = tool_id;
563 }
564
565 if let Some(function) = tool_call.function.as_ref() {
566 if let Some(name) = function.name.clone() {
567 entry.name = name;
568 }
569
570 if let Some(arguments) = function.arguments.clone() {
571 entry.arguments.push_str(&arguments);
572 }
573 }
574 }
575 }
576
577 match choice.finish_reason.as_deref() {
578 Some("stop") => {
579 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
580 }
581 Some("tool_calls") => {
582 events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
583 match serde_json::Value::from_str(&tool_call.arguments) {
584 Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
585 LanguageModelToolUse {
586 id: tool_call.id.clone().into(),
587 name: tool_call.name.as_str().into(),
588 is_input_complete: true,
589 input,
590 raw_input: tool_call.arguments.clone(),
591 },
592 )),
593 Err(error) => Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
594 id: tool_call.id.into(),
595 tool_name: tool_call.name.into(),
596 raw_input: tool_call.arguments.clone().into(),
597 json_parse_error: error.to_string(),
598 }),
599 }
600 }));
601
602 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
603 }
604 Some(stop_reason) => {
605 log::error!("Unexpected OpenAI stop_reason: {stop_reason:?}",);
606 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
607 }
608 None => {}
609 }
610
611 events
612 }
613}
614
615#[derive(Default)]
616struct RawToolCall {
617 id: String,
618 name: String,
619 arguments: String,
620}
621
622pub(crate) fn collect_tiktoken_messages(
623 request: LanguageModelRequest,
624) -> Vec<tiktoken_rs::ChatCompletionRequestMessage> {
625 request
626 .messages
627 .into_iter()
628 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
629 role: match message.role {
630 Role::User => "user".into(),
631 Role::Assistant => "assistant".into(),
632 Role::System => "system".into(),
633 },
634 content: Some(message.string_contents()),
635 name: None,
636 function_call: None,
637 })
638 .collect::<Vec<_>>()
639}
640
641pub fn count_open_ai_tokens(
642 request: LanguageModelRequest,
643 model: Model,
644 cx: &App,
645) -> BoxFuture<'static, Result<u64>> {
646 cx.background_spawn(async move {
647 let messages = collect_tiktoken_messages(request);
648
649 match model {
650 Model::Custom { max_tokens, .. } => {
651 let model = if max_tokens >= 100_000 {
652 // If the max tokens is 100k or more, it is likely the o200k_base tokenizer from gpt4o
653 "gpt-4o"
654 } else {
655 // Otherwise fallback to gpt-4, since only cl100k_base and o200k_base are
656 // supported with this tiktoken method
657 "gpt-4"
658 };
659 tiktoken_rs::num_tokens_from_messages(model, &messages)
660 }
661 // Currently supported by tiktoken_rs
662 // Sometimes tiktoken-rs is behind on model support. If that is the case, make a new branch
663 // arm with an override. We enumerate all supported models here so that we can check if new
664 // models are supported yet or not.
665 Model::ThreePointFiveTurbo
666 | Model::Four
667 | Model::FourTurbo
668 | Model::FourOmni
669 | Model::FourOmniMini
670 | Model::FourPointOne
671 | Model::FourPointOneMini
672 | Model::FourPointOneNano
673 | Model::O1
674 | Model::O3
675 | Model::O3Mini
676 | Model::O4Mini => tiktoken_rs::num_tokens_from_messages(model.id(), &messages),
677 // GPT-5 models don't have tiktoken support yet; fall back on gpt-4o tokenizer
678 Model::Five | Model::FiveMini | Model::FiveNano => {
679 tiktoken_rs::num_tokens_from_messages("gpt-4o", &messages)
680 }
681 }
682 .map(|tokens| tokens as u64)
683 })
684 .boxed()
685}
686
687struct ConfigurationView {
688 api_key_editor: Entity<SingleLineInput>,
689 state: gpui::Entity<State>,
690 load_credentials_task: Option<Task<()>>,
691}
692
693impl ConfigurationView {
694 fn new(state: gpui::Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
695 let api_key_editor = cx.new(|cx| {
696 SingleLineInput::new(
697 window,
698 cx,
699 "sk-000000000000000000000000000000000000000000000000",
700 )
701 });
702
703 cx.observe(&state, |_, _, cx| {
704 cx.notify();
705 })
706 .detach();
707
708 let load_credentials_task = Some(cx.spawn_in(window, {
709 let state = state.clone();
710 async move |this, cx| {
711 if let Some(task) = state
712 .update(cx, |state, cx| state.authenticate(cx))
713 .log_err()
714 {
715 // We don't log an error, because "not signed in" is also an error.
716 let _ = task.await;
717 }
718 this.update(cx, |this, cx| {
719 this.load_credentials_task = None;
720 cx.notify();
721 })
722 .log_err();
723 }
724 }));
725
726 Self {
727 api_key_editor,
728 state,
729 load_credentials_task,
730 }
731 }
732
733 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
734 let api_key = self
735 .api_key_editor
736 .read(cx)
737 .editor()
738 .read(cx)
739 .text(cx)
740 .trim()
741 .to_string();
742
743 // Don't proceed if no API key is provided and we're not authenticated
744 if api_key.is_empty() && !self.state.read(cx).is_authenticated() {
745 return;
746 }
747
748 let state = self.state.clone();
749 cx.spawn_in(window, async move |_, cx| {
750 state
751 .update(cx, |state, cx| state.set_api_key(api_key, cx))?
752 .await
753 })
754 .detach_and_log_err(cx);
755
756 cx.notify();
757 }
758
759 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
760 self.api_key_editor.update(cx, |input, cx| {
761 input.editor.update(cx, |editor, cx| {
762 editor.set_text("", window, cx);
763 });
764 });
765
766 let state = self.state.clone();
767 cx.spawn_in(window, async move |_, cx| {
768 state.update(cx, |state, cx| state.reset_api_key(cx))?.await
769 })
770 .detach_and_log_err(cx);
771
772 cx.notify();
773 }
774
775 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
776 !self.state.read(cx).is_authenticated()
777 }
778}
779
780impl Render for ConfigurationView {
781 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
782 let env_var_set = self.state.read(cx).api_key_from_env;
783
784 let api_key_section = if self.should_render_editor(cx) {
785 v_flex()
786 .on_action(cx.listener(Self::save_api_key))
787 .child(Label::new("To use Zed's agent with OpenAI, you need to add an API key. Follow these steps:"))
788 .child(
789 List::new()
790 .child(InstructionListItem::new(
791 "Create one by visiting",
792 Some("OpenAI's console"),
793 Some("https://platform.openai.com/api-keys"),
794 ))
795 .child(InstructionListItem::text_only(
796 "Ensure your OpenAI account has credits",
797 ))
798 .child(InstructionListItem::text_only(
799 "Paste your API key below and hit enter to start using the assistant",
800 )),
801 )
802 .child(self.api_key_editor.clone())
803 .child(
804 Label::new(
805 format!("You can also assign the {OPENAI_API_KEY_VAR} environment variable and restart Zed."),
806 )
807 .size(LabelSize::Small).color(Color::Muted),
808 )
809 .child(
810 Label::new(
811 "Note that having a subscription for another service like GitHub Copilot won't work.",
812 )
813 .size(LabelSize::Small).color(Color::Muted),
814 )
815 .into_any()
816 } else {
817 h_flex()
818 .mt_1()
819 .p_1()
820 .justify_between()
821 .rounded_md()
822 .border_1()
823 .border_color(cx.theme().colors().border)
824 .bg(cx.theme().colors().background)
825 .child(
826 h_flex()
827 .gap_1()
828 .child(Icon::new(IconName::Check).color(Color::Success))
829 .child(Label::new(if env_var_set {
830 format!("API key set in {OPENAI_API_KEY_VAR} environment variable.")
831 } else {
832 "API key configured.".to_string()
833 })),
834 )
835 .child(
836 Button::new("reset-api-key", "Reset API Key")
837 .label_size(LabelSize::Small)
838 .icon(IconName::Undo)
839 .icon_size(IconSize::Small)
840 .icon_position(IconPosition::Start)
841 .layer(ElevationIndex::ModalSurface)
842 .when(env_var_set, |this| {
843 this.tooltip(Tooltip::text(format!("To reset your API key, unset the {OPENAI_API_KEY_VAR} environment variable.")))
844 })
845 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx))),
846 )
847 .into_any()
848 };
849
850 let compatible_api_section = h_flex()
851 .mt_1p5()
852 .gap_0p5()
853 .flex_wrap()
854 .when(self.should_render_editor(cx), |this| {
855 this.pt_1p5()
856 .border_t_1()
857 .border_color(cx.theme().colors().border_variant)
858 })
859 .child(
860 h_flex()
861 .gap_2()
862 .child(
863 Icon::new(IconName::Info)
864 .size(IconSize::XSmall)
865 .color(Color::Muted),
866 )
867 .child(Label::new("Zed also supports OpenAI-compatible models.")),
868 )
869 .child(
870 Button::new("docs", "Learn More")
871 .icon(IconName::ArrowUpRight)
872 .icon_size(IconSize::XSmall)
873 .icon_color(Color::Muted)
874 .on_click(move |_, _window, cx| {
875 cx.open_url("https://zed.dev/docs/ai/llm-providers#openai-api-compatible")
876 }),
877 );
878
879 if self.load_credentials_task.is_some() {
880 div().child(Label::new("Loading credentials…")).into_any()
881 } else {
882 v_flex()
883 .size_full()
884 .child(api_key_section)
885 .child(compatible_api_section)
886 .into_any()
887 }
888 }
889}
890
891#[cfg(test)]
892mod tests {
893 use gpui::TestAppContext;
894 use language_model::LanguageModelRequestMessage;
895
896 use super::*;
897
898 #[gpui::test]
899 fn tiktoken_rs_support(cx: &TestAppContext) {
900 let request = LanguageModelRequest {
901 thread_id: None,
902 prompt_id: None,
903 intent: None,
904 mode: None,
905 messages: vec![LanguageModelRequestMessage {
906 role: Role::User,
907 content: vec![MessageContent::Text("message".into())],
908 cache: false,
909 }],
910 tools: vec![],
911 tool_choice: None,
912 stop: vec![],
913 temperature: None,
914 thinking_allowed: true,
915 };
916
917 // Validate that all models are supported by tiktoken-rs
918 for model in Model::iter() {
919 let count = cx
920 .executor()
921 .block(count_open_ai_tokens(
922 request.clone(),
923 model,
924 &cx.app.borrow(),
925 ))
926 .unwrap();
927 assert!(count > 0);
928 }
929 }
930}