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