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::{List, prelude::*};
24use ui_input::InputField;
25use util::ResultExt;
26use zed_env_vars::{EnvVar, env_var};
27
28use crate::ui::ConfiguredApiCard;
29use crate::{api_key::ApiKeyState, ui::InstructionListItem};
30
31const PROVIDER_ID: LanguageModelProviderId = language_model::OPEN_AI_PROVIDER_ID;
32const PROVIDER_NAME: LanguageModelProviderName = language_model::OPEN_AI_PROVIDER_NAME;
33
34const API_KEY_ENV_VAR_NAME: &str = "OPENAI_API_KEY";
35static API_KEY_ENV_VAR: LazyLock<EnvVar> = env_var!(API_KEY_ENV_VAR_NAME);
36
37#[derive(Default, Clone, Debug, PartialEq)]
38pub struct OpenAiSettings {
39 pub api_url: String,
40 pub available_models: Vec<AvailableModel>,
41}
42
43pub struct OpenAiLanguageModelProvider {
44 http_client: Arc<dyn HttpClient>,
45 state: Entity<State>,
46}
47
48pub struct State {
49 api_key_state: ApiKeyState,
50}
51
52impl State {
53 fn is_authenticated(&self) -> bool {
54 self.api_key_state.has_key()
55 }
56
57 fn set_api_key(&mut self, api_key: Option<String>, cx: &mut Context<Self>) -> Task<Result<()>> {
58 let api_url = OpenAiLanguageModelProvider::api_url(cx);
59 self.api_key_state
60 .store(api_url, api_key, |this| &mut this.api_key_state, cx)
61 }
62
63 fn authenticate(&mut self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
64 let api_url = OpenAiLanguageModelProvider::api_url(cx);
65 self.api_key_state.load_if_needed(
66 api_url,
67 &API_KEY_ENV_VAR,
68 |this| &mut this.api_key_state,
69 cx,
70 )
71 }
72}
73
74impl OpenAiLanguageModelProvider {
75 pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
76 let state = cx.new(|cx| {
77 cx.observe_global::<SettingsStore>(|this: &mut State, cx| {
78 let api_url = Self::api_url(cx);
79 this.api_key_state.handle_url_change(
80 api_url,
81 &API_KEY_ENV_VAR,
82 |this| &mut this.api_key_state,
83 cx,
84 );
85 cx.notify();
86 })
87 .detach();
88 State {
89 api_key_state: ApiKeyState::new(Self::api_url(cx)),
90 }
91 });
92
93 Self { http_client, state }
94 }
95
96 fn create_language_model(&self, model: open_ai::Model) -> Arc<dyn LanguageModel> {
97 Arc::new(OpenAiLanguageModel {
98 id: LanguageModelId::from(model.id().to_string()),
99 model,
100 state: self.state.clone(),
101 http_client: self.http_client.clone(),
102 request_limiter: RateLimiter::new(4),
103 })
104 }
105
106 fn settings(cx: &App) -> &OpenAiSettings {
107 &crate::AllLanguageModelSettings::get_global(cx).openai
108 }
109
110 fn api_url(cx: &App) -> SharedString {
111 let api_url = &Self::settings(cx).api_url;
112 if api_url.is_empty() {
113 open_ai::OPEN_AI_API_URL.into()
114 } else {
115 SharedString::new(api_url.as_str())
116 }
117 }
118}
119
120impl LanguageModelProviderState for OpenAiLanguageModelProvider {
121 type ObservableEntity = State;
122
123 fn observable_entity(&self) -> Option<Entity<Self::ObservableEntity>> {
124 Some(self.state.clone())
125 }
126}
127
128impl LanguageModelProvider for OpenAiLanguageModelProvider {
129 fn id(&self) -> LanguageModelProviderId {
130 PROVIDER_ID
131 }
132
133 fn name(&self) -> LanguageModelProviderName {
134 PROVIDER_NAME
135 }
136
137 fn icon(&self) -> IconName {
138 IconName::AiOpenAi
139 }
140
141 fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
142 Some(self.create_language_model(open_ai::Model::default()))
143 }
144
145 fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
146 Some(self.create_language_model(open_ai::Model::default_fast()))
147 }
148
149 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
150 let mut models = BTreeMap::default();
151
152 // Add base models from open_ai::Model::iter()
153 for model in open_ai::Model::iter() {
154 if !matches!(model, open_ai::Model::Custom { .. }) {
155 models.insert(model.id().to_string(), model);
156 }
157 }
158
159 // Override with available models from settings
160 for model in &OpenAiLanguageModelProvider::settings(cx).available_models {
161 models.insert(
162 model.name.clone(),
163 open_ai::Model::Custom {
164 name: model.name.clone(),
165 display_name: model.display_name.clone(),
166 max_tokens: model.max_tokens,
167 max_output_tokens: model.max_output_tokens,
168 max_completion_tokens: model.max_completion_tokens,
169 reasoning_effort: model.reasoning_effort.clone(),
170 },
171 );
172 }
173
174 models
175 .into_values()
176 .map(|model| self.create_language_model(model))
177 .collect()
178 }
179
180 fn is_authenticated(&self, cx: &App) -> bool {
181 self.state.read(cx).is_authenticated()
182 }
183
184 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
185 self.state.update(cx, |state, cx| state.authenticate(cx))
186 }
187
188 fn configuration_view(
189 &self,
190 _target_agent: language_model::ConfigurationViewTargetAgent,
191 window: &mut Window,
192 cx: &mut App,
193 ) -> AnyView {
194 cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
195 .into()
196 }
197
198 fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
199 self.state
200 .update(cx, |state, cx| state.set_api_key(None, cx))
201 }
202}
203
204pub struct OpenAiLanguageModel {
205 id: LanguageModelId,
206 model: open_ai::Model,
207 state: Entity<State>,
208 http_client: Arc<dyn HttpClient>,
209 request_limiter: RateLimiter,
210}
211
212impl OpenAiLanguageModel {
213 fn stream_completion(
214 &self,
215 request: open_ai::Request,
216 cx: &AsyncApp,
217 ) -> BoxFuture<'static, Result<futures::stream::BoxStream<'static, Result<ResponseStreamEvent>>>>
218 {
219 let http_client = self.http_client.clone();
220
221 let Ok((api_key, api_url)) = self.state.read_with(cx, |state, cx| {
222 let api_url = OpenAiLanguageModelProvider::api_url(cx);
223 (state.api_key_state.key(&api_url), api_url)
224 }) else {
225 return future::ready(Err(anyhow!("App state dropped"))).boxed();
226 };
227
228 let future = self.request_limiter.stream(async move {
229 let provider = PROVIDER_NAME;
230 let Some(api_key) = api_key else {
231 return Err(LanguageModelCompletionError::NoApiKey { provider });
232 };
233 let request = stream_completion(
234 http_client.as_ref(),
235 provider.0.as_str(),
236 &api_url,
237 &api_key,
238 request,
239 );
240 let response = request.await?;
241 Ok(response)
242 });
243
244 async move { Ok(future.await?.boxed()) }.boxed()
245 }
246}
247
248impl LanguageModel for OpenAiLanguageModel {
249 fn id(&self) -> LanguageModelId {
250 self.id.clone()
251 }
252
253 fn name(&self) -> LanguageModelName {
254 LanguageModelName::from(self.model.display_name().to_string())
255 }
256
257 fn provider_id(&self) -> LanguageModelProviderId {
258 PROVIDER_ID
259 }
260
261 fn provider_name(&self) -> LanguageModelProviderName {
262 PROVIDER_NAME
263 }
264
265 fn supports_tools(&self) -> bool {
266 true
267 }
268
269 fn supports_images(&self) -> bool {
270 use open_ai::Model;
271 match &self.model {
272 Model::FourOmni
273 | Model::FourOmniMini
274 | Model::FourPointOne
275 | Model::FourPointOneMini
276 | Model::FourPointOneNano
277 | Model::Five
278 | Model::FiveMini
279 | Model::FiveNano
280 | Model::FivePointOne
281 | Model::O1
282 | Model::O3
283 | Model::O4Mini => true,
284 Model::ThreePointFiveTurbo
285 | Model::Four
286 | Model::FourTurbo
287 | Model::O3Mini
288 | Model::Custom { .. } => false,
289 }
290 }
291
292 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
293 match choice {
294 LanguageModelToolChoice::Auto => true,
295 LanguageModelToolChoice::Any => true,
296 LanguageModelToolChoice::None => true,
297 }
298 }
299
300 fn telemetry_id(&self) -> String {
301 format!("openai/{}", self.model.id())
302 }
303
304 fn max_token_count(&self) -> u64 {
305 self.model.max_token_count()
306 }
307
308 fn max_output_tokens(&self) -> Option<u64> {
309 self.model.max_output_tokens()
310 }
311
312 fn count_tokens(
313 &self,
314 request: LanguageModelRequest,
315 cx: &App,
316 ) -> BoxFuture<'static, Result<u64>> {
317 count_open_ai_tokens(request, self.model.clone(), cx)
318 }
319
320 fn stream_completion(
321 &self,
322 request: LanguageModelRequest,
323 cx: &AsyncApp,
324 ) -> BoxFuture<
325 'static,
326 Result<
327 futures::stream::BoxStream<
328 'static,
329 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
330 >,
331 LanguageModelCompletionError,
332 >,
333 > {
334 let request = into_open_ai(
335 request,
336 self.model.id(),
337 self.model.supports_parallel_tool_calls(),
338 self.model.supports_prompt_cache_key(),
339 self.max_output_tokens(),
340 self.model.reasoning_effort(),
341 );
342 let completions = self.stream_completion(request, cx);
343 async move {
344 let mapper = OpenAiEventMapper::new();
345 Ok(mapper.map_stream(completions.await?).boxed())
346 }
347 .boxed()
348 }
349}
350
351pub fn into_open_ai(
352 request: LanguageModelRequest,
353 model_id: &str,
354 supports_parallel_tool_calls: bool,
355 supports_prompt_cache_key: bool,
356 max_output_tokens: Option<u64>,
357 reasoning_effort: Option<ReasoningEffort>,
358) -> open_ai::Request {
359 let stream = !model_id.starts_with("o1-");
360
361 let mut messages = Vec::new();
362 for message in request.messages {
363 for content in message.content {
364 match content {
365 MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
366 if !text.trim().is_empty() {
367 add_message_content_part(
368 open_ai::MessagePart::Text { text },
369 message.role,
370 &mut messages,
371 );
372 }
373 }
374 MessageContent::RedactedThinking(_) => {}
375 MessageContent::Image(image) => {
376 add_message_content_part(
377 open_ai::MessagePart::Image {
378 image_url: ImageUrl {
379 url: image.to_base64_url(),
380 detail: None,
381 },
382 },
383 message.role,
384 &mut messages,
385 );
386 }
387 MessageContent::ToolUse(tool_use) => {
388 let tool_call = open_ai::ToolCall {
389 id: tool_use.id.to_string(),
390 content: open_ai::ToolCallContent::Function {
391 function: open_ai::FunctionContent {
392 name: tool_use.name.to_string(),
393 arguments: serde_json::to_string(&tool_use.input)
394 .unwrap_or_default(),
395 },
396 },
397 };
398
399 if let Some(open_ai::RequestMessage::Assistant { tool_calls, .. }) =
400 messages.last_mut()
401 {
402 tool_calls.push(tool_call);
403 } else {
404 messages.push(open_ai::RequestMessage::Assistant {
405 content: None,
406 tool_calls: vec![tool_call],
407 });
408 }
409 }
410 MessageContent::ToolResult(tool_result) => {
411 let content = match &tool_result.content {
412 LanguageModelToolResultContent::Text(text) => {
413 vec![open_ai::MessagePart::Text {
414 text: text.to_string(),
415 }]
416 }
417 LanguageModelToolResultContent::Image(image) => {
418 vec![open_ai::MessagePart::Image {
419 image_url: ImageUrl {
420 url: image.to_base64_url(),
421 detail: None,
422 },
423 }]
424 }
425 };
426
427 messages.push(open_ai::RequestMessage::Tool {
428 content: content.into(),
429 tool_call_id: tool_result.tool_use_id.to_string(),
430 });
431 }
432 }
433 }
434 }
435
436 open_ai::Request {
437 model: model_id.into(),
438 messages,
439 stream,
440 stop: request.stop,
441 temperature: request.temperature.unwrap_or(1.0),
442 max_completion_tokens: max_output_tokens,
443 parallel_tool_calls: if supports_parallel_tool_calls && !request.tools.is_empty() {
444 // Disable parallel tool calls, as the Agent currently expects a maximum of one per turn.
445 Some(false)
446 } else {
447 None
448 },
449 prompt_cache_key: if supports_prompt_cache_key {
450 request.thread_id
451 } else {
452 None
453 },
454 tools: request
455 .tools
456 .into_iter()
457 .map(|tool| open_ai::ToolDefinition::Function {
458 function: open_ai::FunctionDefinition {
459 name: tool.name,
460 description: Some(tool.description),
461 parameters: Some(tool.input_schema),
462 },
463 })
464 .collect(),
465 tool_choice: request.tool_choice.map(|choice| match choice {
466 LanguageModelToolChoice::Auto => open_ai::ToolChoice::Auto,
467 LanguageModelToolChoice::Any => open_ai::ToolChoice::Required,
468 LanguageModelToolChoice::None => open_ai::ToolChoice::None,
469 }),
470 reasoning_effort,
471 }
472}
473
474fn add_message_content_part(
475 new_part: open_ai::MessagePart,
476 role: Role,
477 messages: &mut Vec<open_ai::RequestMessage>,
478) {
479 match (role, messages.last_mut()) {
480 (Role::User, Some(open_ai::RequestMessage::User { content }))
481 | (
482 Role::Assistant,
483 Some(open_ai::RequestMessage::Assistant {
484 content: Some(content),
485 ..
486 }),
487 )
488 | (Role::System, Some(open_ai::RequestMessage::System { content, .. })) => {
489 content.push_part(new_part);
490 }
491 _ => {
492 messages.push(match role {
493 Role::User => open_ai::RequestMessage::User {
494 content: open_ai::MessageContent::from(vec![new_part]),
495 },
496 Role::Assistant => open_ai::RequestMessage::Assistant {
497 content: Some(open_ai::MessageContent::from(vec![new_part])),
498 tool_calls: Vec::new(),
499 },
500 Role::System => open_ai::RequestMessage::System {
501 content: open_ai::MessageContent::from(vec![new_part]),
502 },
503 });
504 }
505 }
506}
507
508pub struct OpenAiEventMapper {
509 tool_calls_by_index: HashMap<usize, RawToolCall>,
510}
511
512impl OpenAiEventMapper {
513 pub fn new() -> Self {
514 Self {
515 tool_calls_by_index: HashMap::default(),
516 }
517 }
518
519 pub fn map_stream(
520 mut self,
521 events: Pin<Box<dyn Send + Stream<Item = Result<ResponseStreamEvent>>>>,
522 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
523 {
524 events.flat_map(move |event| {
525 futures::stream::iter(match event {
526 Ok(event) => self.map_event(event),
527 Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
528 })
529 })
530 }
531
532 pub fn map_event(
533 &mut self,
534 event: ResponseStreamEvent,
535 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
536 let mut events = Vec::new();
537 if let Some(usage) = event.usage {
538 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
539 input_tokens: usage.prompt_tokens,
540 output_tokens: usage.completion_tokens,
541 cache_creation_input_tokens: 0,
542 cache_read_input_tokens: 0,
543 })));
544 }
545
546 let Some(choice) = event.choices.first() else {
547 return events;
548 };
549
550 if let Some(delta) = choice.delta.as_ref() {
551 if let Some(content) = delta.content.clone() {
552 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
553 }
554
555 if let Some(tool_calls) = delta.tool_calls.as_ref() {
556 for tool_call in tool_calls {
557 let entry = self.tool_calls_by_index.entry(tool_call.index).or_default();
558
559 if let Some(tool_id) = tool_call.id.clone() {
560 entry.id = tool_id;
561 }
562
563 if let Some(function) = tool_call.function.as_ref() {
564 if let Some(name) = function.name.clone() {
565 entry.name = name;
566 }
567
568 if let Some(arguments) = function.arguments.clone() {
569 entry.arguments.push_str(&arguments);
570 }
571 }
572 }
573 }
574 }
575
576 match choice.finish_reason.as_deref() {
577 Some("stop") => {
578 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
579 }
580 Some("tool_calls") => {
581 events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
582 match serde_json::Value::from_str(&tool_call.arguments) {
583 Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
584 LanguageModelToolUse {
585 id: tool_call.id.clone().into(),
586 name: tool_call.name.as_str().into(),
587 is_input_complete: true,
588 input,
589 raw_input: tool_call.arguments.clone(),
590 thought_signature: None,
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 match model {
649 Model::Custom { max_tokens, .. } => {
650 let model = if max_tokens >= 100_000 {
651 // If the max tokens is 100k or more, it is likely the o200k_base tokenizer from gpt4o
652 "gpt-4o"
653 } else {
654 // Otherwise fallback to gpt-4, since only cl100k_base and o200k_base are
655 // supported with this tiktoken method
656 "gpt-4"
657 };
658 tiktoken_rs::num_tokens_from_messages(model, &messages)
659 }
660 // Currently supported by tiktoken_rs
661 // Sometimes tiktoken-rs is behind on model support. If that is the case, make a new branch
662 // arm with an override. We enumerate all supported models here so that we can check if new
663 // models are supported yet or not.
664 Model::ThreePointFiveTurbo
665 | Model::Four
666 | Model::FourTurbo
667 | Model::FourOmni
668 | Model::FourOmniMini
669 | Model::FourPointOne
670 | Model::FourPointOneMini
671 | Model::FourPointOneNano
672 | Model::O1
673 | Model::O3
674 | Model::O3Mini
675 | Model::O4Mini
676 | Model::Five
677 | Model::FiveMini
678 | Model::FiveNano => tiktoken_rs::num_tokens_from_messages(model.id(), &messages), // GPT-5.1 doesn't have tiktoken support yet; fall back on gpt-4o tokenizer
679 Model::FivePointOne => tiktoken_rs::num_tokens_from_messages("gpt-5", &messages),
680 }
681 .map(|tokens| tokens as u64)
682 })
683 .boxed()
684}
685
686struct ConfigurationView {
687 api_key_editor: Entity<InputField>,
688 state: Entity<State>,
689 load_credentials_task: Option<Task<()>>,
690}
691
692impl ConfigurationView {
693 fn new(state: Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
694 let api_key_editor = cx.new(|cx| {
695 InputField::new(
696 window,
697 cx,
698 "sk-000000000000000000000000000000000000000000000000",
699 )
700 });
701
702 cx.observe(&state, |_, _, cx| {
703 cx.notify();
704 })
705 .detach();
706
707 let load_credentials_task = Some(cx.spawn_in(window, {
708 let state = state.clone();
709 async move |this, cx| {
710 if let Some(task) = state
711 .update(cx, |state, cx| state.authenticate(cx))
712 .log_err()
713 {
714 // We don't log an error, because "not signed in" is also an error.
715 let _ = task.await;
716 }
717 this.update(cx, |this, cx| {
718 this.load_credentials_task = None;
719 cx.notify();
720 })
721 .log_err();
722 }
723 }));
724
725 Self {
726 api_key_editor,
727 state,
728 load_credentials_task,
729 }
730 }
731
732 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
733 let api_key = self.api_key_editor.read(cx).text(cx).trim().to_string();
734 if api_key.is_empty() {
735 return;
736 }
737
738 // url changes can cause the editor to be displayed again
739 self.api_key_editor
740 .update(cx, |editor, cx| editor.set_text("", window, cx));
741
742 let state = self.state.clone();
743 cx.spawn_in(window, async move |_, cx| {
744 state
745 .update(cx, |state, cx| state.set_api_key(Some(api_key), cx))?
746 .await
747 })
748 .detach_and_log_err(cx);
749 }
750
751 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
752 self.api_key_editor
753 .update(cx, |input, cx| input.set_text("", window, cx));
754
755 let state = self.state.clone();
756 cx.spawn_in(window, async move |_, cx| {
757 state
758 .update(cx, |state, cx| state.set_api_key(None, cx))?
759 .await
760 })
761 .detach_and_log_err(cx);
762 }
763
764 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
765 !self.state.read(cx).is_authenticated()
766 }
767}
768
769impl Render for ConfigurationView {
770 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
771 let env_var_set = self.state.read(cx).api_key_state.is_from_env_var();
772 let configured_card_label = if env_var_set {
773 format!("API key set in {API_KEY_ENV_VAR_NAME} environment variable")
774 } else {
775 let api_url = OpenAiLanguageModelProvider::api_url(cx);
776 if api_url == OPEN_AI_API_URL {
777 "API key configured".to_string()
778 } else {
779 format!("API key configured for {}", api_url)
780 }
781 };
782
783 let api_key_section = if self.should_render_editor(cx) {
784 v_flex()
785 .on_action(cx.listener(Self::save_api_key))
786 .child(Label::new("To use Zed's agent with OpenAI, you need to add an API key. Follow these steps:"))
787 .child(
788 List::new()
789 .child(InstructionListItem::new(
790 "Create one by visiting",
791 Some("OpenAI's console"),
792 Some("https://platform.openai.com/api-keys"),
793 ))
794 .child(InstructionListItem::text_only(
795 "Ensure your OpenAI account has credits",
796 ))
797 .child(InstructionListItem::text_only(
798 "Paste your API key below and hit enter to start using the assistant",
799 )),
800 )
801 .child(self.api_key_editor.clone())
802 .child(
803 Label::new(format!(
804 "You can also assign the {API_KEY_ENV_VAR_NAME} environment variable and restart Zed."
805 ))
806 .size(LabelSize::Small)
807 .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_element()
816 } else {
817 ConfiguredApiCard::new(configured_card_label)
818 .disabled(env_var_set)
819 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx)))
820 .when(env_var_set, |this| {
821 this.tooltip_label(format!("To reset your API key, unset the {API_KEY_ENV_VAR_NAME} environment variable."))
822 })
823 .into_any_element()
824 };
825
826 let compatible_api_section = h_flex()
827 .mt_1p5()
828 .gap_0p5()
829 .flex_wrap()
830 .when(self.should_render_editor(cx), |this| {
831 this.pt_1p5()
832 .border_t_1()
833 .border_color(cx.theme().colors().border_variant)
834 })
835 .child(
836 h_flex()
837 .gap_2()
838 .child(
839 Icon::new(IconName::Info)
840 .size(IconSize::XSmall)
841 .color(Color::Muted),
842 )
843 .child(Label::new("Zed also supports OpenAI-compatible models.")),
844 )
845 .child(
846 Button::new("docs", "Learn More")
847 .icon(IconName::ArrowUpRight)
848 .icon_size(IconSize::Small)
849 .icon_color(Color::Muted)
850 .on_click(move |_, _window, cx| {
851 cx.open_url("https://zed.dev/docs/ai/llm-providers#openai-api-compatible")
852 }),
853 );
854
855 if self.load_credentials_task.is_some() {
856 div().child(Label::new("Loading credentials…")).into_any()
857 } else {
858 v_flex()
859 .size_full()
860 .child(api_key_section)
861 .child(compatible_api_section)
862 .into_any()
863 }
864 }
865}
866
867#[cfg(test)]
868mod tests {
869 use gpui::TestAppContext;
870 use language_model::LanguageModelRequestMessage;
871
872 use super::*;
873
874 #[gpui::test]
875 fn tiktoken_rs_support(cx: &TestAppContext) {
876 let request = LanguageModelRequest {
877 thread_id: None,
878 prompt_id: None,
879 intent: None,
880 mode: None,
881 messages: vec![LanguageModelRequestMessage {
882 role: Role::User,
883 content: vec![MessageContent::Text("message".into())],
884 cache: false,
885 reasoning_details: None,
886 }],
887 tools: vec![],
888 tool_choice: None,
889 stop: vec![],
890 temperature: None,
891 thinking_allowed: true,
892 };
893
894 // Validate that all models are supported by tiktoken-rs
895 for model in Model::iter() {
896 let count = cx
897 .executor()
898 .block(count_open_ai_tokens(
899 request.clone(),
900 model,
901 &cx.app.borrow(),
902 ))
903 .unwrap();
904 assert!(count > 0);
905 }
906 }
907}