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 Some(api_key) = api_key else {
230 return Err(LanguageModelCompletionError::NoApiKey {
231 provider: PROVIDER_NAME,
232 });
233 };
234 let request = stream_completion(http_client.as_ref(), &api_url, &api_key, request);
235 let response = request.await?;
236 Ok(response)
237 });
238
239 async move { Ok(future.await?.boxed()) }.boxed()
240 }
241}
242
243impl LanguageModel for OpenAiLanguageModel {
244 fn id(&self) -> LanguageModelId {
245 self.id.clone()
246 }
247
248 fn name(&self) -> LanguageModelName {
249 LanguageModelName::from(self.model.display_name().to_string())
250 }
251
252 fn provider_id(&self) -> LanguageModelProviderId {
253 PROVIDER_ID
254 }
255
256 fn provider_name(&self) -> LanguageModelProviderName {
257 PROVIDER_NAME
258 }
259
260 fn supports_tools(&self) -> bool {
261 true
262 }
263
264 fn supports_images(&self) -> bool {
265 use open_ai::Model;
266 match &self.model {
267 Model::FourOmni
268 | Model::FourOmniMini
269 | Model::FourPointOne
270 | Model::FourPointOneMini
271 | Model::FourPointOneNano
272 | Model::Five
273 | Model::FiveMini
274 | Model::FiveNano
275 | Model::O1
276 | Model::O3
277 | Model::O4Mini => true,
278 Model::ThreePointFiveTurbo
279 | Model::Four
280 | Model::FourTurbo
281 | Model::O3Mini
282 | Model::Custom { .. } => false,
283 }
284 }
285
286 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
287 match choice {
288 LanguageModelToolChoice::Auto => true,
289 LanguageModelToolChoice::Any => true,
290 LanguageModelToolChoice::None => true,
291 }
292 }
293
294 fn telemetry_id(&self) -> String {
295 format!("openai/{}", self.model.id())
296 }
297
298 fn max_token_count(&self) -> u64 {
299 self.model.max_token_count()
300 }
301
302 fn max_output_tokens(&self) -> Option<u64> {
303 self.model.max_output_tokens()
304 }
305
306 fn count_tokens(
307 &self,
308 request: LanguageModelRequest,
309 cx: &App,
310 ) -> BoxFuture<'static, Result<u64>> {
311 count_open_ai_tokens(request, self.model.clone(), cx)
312 }
313
314 fn stream_completion(
315 &self,
316 request: LanguageModelRequest,
317 cx: &AsyncApp,
318 ) -> BoxFuture<
319 'static,
320 Result<
321 futures::stream::BoxStream<
322 'static,
323 Result<LanguageModelCompletionEvent, LanguageModelCompletionError>,
324 >,
325 LanguageModelCompletionError,
326 >,
327 > {
328 let request = into_open_ai(
329 request,
330 self.model.id(),
331 self.model.supports_parallel_tool_calls(),
332 self.model.supports_prompt_cache_key(),
333 self.max_output_tokens(),
334 self.model.reasoning_effort(),
335 );
336 let completions = self.stream_completion(request, cx);
337 async move {
338 let mapper = OpenAiEventMapper::new();
339 Ok(mapper.map_stream(completions.await?).boxed())
340 }
341 .boxed()
342 }
343}
344
345pub fn into_open_ai(
346 request: LanguageModelRequest,
347 model_id: &str,
348 supports_parallel_tool_calls: bool,
349 supports_prompt_cache_key: bool,
350 max_output_tokens: Option<u64>,
351 reasoning_effort: Option<ReasoningEffort>,
352) -> open_ai::Request {
353 let stream = !model_id.starts_with("o1-");
354
355 let mut messages = Vec::new();
356 for message in request.messages {
357 for content in message.content {
358 match content {
359 MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
360 if !text.trim().is_empty() {
361 add_message_content_part(
362 open_ai::MessagePart::Text { text },
363 message.role,
364 &mut messages,
365 );
366 }
367 }
368 MessageContent::RedactedThinking(_) => {}
369 MessageContent::Image(image) => {
370 add_message_content_part(
371 open_ai::MessagePart::Image {
372 image_url: ImageUrl {
373 url: image.to_base64_url(),
374 detail: None,
375 },
376 },
377 message.role,
378 &mut messages,
379 );
380 }
381 MessageContent::ToolUse(tool_use) => {
382 let tool_call = open_ai::ToolCall {
383 id: tool_use.id.to_string(),
384 content: open_ai::ToolCallContent::Function {
385 function: open_ai::FunctionContent {
386 name: tool_use.name.to_string(),
387 arguments: serde_json::to_string(&tool_use.input)
388 .unwrap_or_default(),
389 },
390 },
391 };
392
393 if let Some(open_ai::RequestMessage::Assistant { tool_calls, .. }) =
394 messages.last_mut()
395 {
396 tool_calls.push(tool_call);
397 } else {
398 messages.push(open_ai::RequestMessage::Assistant {
399 content: None,
400 tool_calls: vec![tool_call],
401 });
402 }
403 }
404 MessageContent::ToolResult(tool_result) => {
405 let content = match &tool_result.content {
406 LanguageModelToolResultContent::Text(text) => {
407 vec![open_ai::MessagePart::Text {
408 text: text.to_string(),
409 }]
410 }
411 LanguageModelToolResultContent::Image(image) => {
412 vec![open_ai::MessagePart::Image {
413 image_url: ImageUrl {
414 url: image.to_base64_url(),
415 detail: None,
416 },
417 }]
418 }
419 };
420
421 messages.push(open_ai::RequestMessage::Tool {
422 content: content.into(),
423 tool_call_id: tool_result.tool_use_id.to_string(),
424 });
425 }
426 }
427 }
428 }
429
430 open_ai::Request {
431 model: model_id.into(),
432 messages,
433 stream,
434 stop: request.stop,
435 temperature: request.temperature.unwrap_or(1.0),
436 max_completion_tokens: max_output_tokens,
437 parallel_tool_calls: if supports_parallel_tool_calls && !request.tools.is_empty() {
438 // Disable parallel tool calls, as the Agent currently expects a maximum of one per turn.
439 Some(false)
440 } else {
441 None
442 },
443 prompt_cache_key: if supports_prompt_cache_key {
444 request.thread_id
445 } else {
446 None
447 },
448 tools: request
449 .tools
450 .into_iter()
451 .map(|tool| open_ai::ToolDefinition::Function {
452 function: open_ai::FunctionDefinition {
453 name: tool.name,
454 description: Some(tool.description),
455 parameters: Some(tool.input_schema),
456 },
457 })
458 .collect(),
459 tool_choice: request.tool_choice.map(|choice| match choice {
460 LanguageModelToolChoice::Auto => open_ai::ToolChoice::Auto,
461 LanguageModelToolChoice::Any => open_ai::ToolChoice::Required,
462 LanguageModelToolChoice::None => open_ai::ToolChoice::None,
463 }),
464 reasoning_effort,
465 }
466}
467
468fn add_message_content_part(
469 new_part: open_ai::MessagePart,
470 role: Role,
471 messages: &mut Vec<open_ai::RequestMessage>,
472) {
473 match (role, messages.last_mut()) {
474 (Role::User, Some(open_ai::RequestMessage::User { content }))
475 | (
476 Role::Assistant,
477 Some(open_ai::RequestMessage::Assistant {
478 content: Some(content),
479 ..
480 }),
481 )
482 | (Role::System, Some(open_ai::RequestMessage::System { content, .. })) => {
483 content.push_part(new_part);
484 }
485 _ => {
486 messages.push(match role {
487 Role::User => open_ai::RequestMessage::User {
488 content: open_ai::MessageContent::from(vec![new_part]),
489 },
490 Role::Assistant => open_ai::RequestMessage::Assistant {
491 content: Some(open_ai::MessageContent::from(vec![new_part])),
492 tool_calls: Vec::new(),
493 },
494 Role::System => open_ai::RequestMessage::System {
495 content: open_ai::MessageContent::from(vec![new_part]),
496 },
497 });
498 }
499 }
500}
501
502pub struct OpenAiEventMapper {
503 tool_calls_by_index: HashMap<usize, RawToolCall>,
504}
505
506impl OpenAiEventMapper {
507 pub fn new() -> Self {
508 Self {
509 tool_calls_by_index: HashMap::default(),
510 }
511 }
512
513 pub fn map_stream(
514 mut self,
515 events: Pin<Box<dyn Send + Stream<Item = Result<ResponseStreamEvent>>>>,
516 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
517 {
518 events.flat_map(move |event| {
519 futures::stream::iter(match event {
520 Ok(event) => self.map_event(event),
521 Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
522 })
523 })
524 }
525
526 pub fn map_event(
527 &mut self,
528 event: ResponseStreamEvent,
529 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
530 let mut events = Vec::new();
531 if let Some(usage) = event.usage {
532 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
533 input_tokens: usage.prompt_tokens,
534 output_tokens: usage.completion_tokens,
535 cache_creation_input_tokens: 0,
536 cache_read_input_tokens: 0,
537 })));
538 }
539
540 let Some(choice) = event.choices.first() else {
541 return events;
542 };
543
544 if let Some(delta) = choice.delta.as_ref() {
545 if let Some(content) = delta.content.clone() {
546 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
547 }
548
549 if let Some(tool_calls) = delta.tool_calls.as_ref() {
550 for tool_call in tool_calls {
551 let entry = self.tool_calls_by_index.entry(tool_call.index).or_default();
552
553 if let Some(tool_id) = tool_call.id.clone() {
554 entry.id = tool_id;
555 }
556
557 if let Some(function) = tool_call.function.as_ref() {
558 if let Some(name) = function.name.clone() {
559 entry.name = name;
560 }
561
562 if let Some(arguments) = function.arguments.clone() {
563 entry.arguments.push_str(&arguments);
564 }
565 }
566 }
567 }
568 }
569
570 match choice.finish_reason.as_deref() {
571 Some("stop") => {
572 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
573 }
574 Some("tool_calls") => {
575 events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
576 match serde_json::Value::from_str(&tool_call.arguments) {
577 Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
578 LanguageModelToolUse {
579 id: tool_call.id.clone().into(),
580 name: tool_call.name.as_str().into(),
581 is_input_complete: true,
582 input,
583 raw_input: tool_call.arguments.clone(),
584 },
585 )),
586 Err(error) => Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
587 id: tool_call.id.into(),
588 tool_name: tool_call.name.into(),
589 raw_input: tool_call.arguments.clone().into(),
590 json_parse_error: error.to_string(),
591 }),
592 }
593 }));
594
595 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
596 }
597 Some(stop_reason) => {
598 log::error!("Unexpected OpenAI stop_reason: {stop_reason:?}",);
599 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
600 }
601 None => {}
602 }
603
604 events
605 }
606}
607
608#[derive(Default)]
609struct RawToolCall {
610 id: String,
611 name: String,
612 arguments: String,
613}
614
615pub(crate) fn collect_tiktoken_messages(
616 request: LanguageModelRequest,
617) -> Vec<tiktoken_rs::ChatCompletionRequestMessage> {
618 request
619 .messages
620 .into_iter()
621 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
622 role: match message.role {
623 Role::User => "user".into(),
624 Role::Assistant => "assistant".into(),
625 Role::System => "system".into(),
626 },
627 content: Some(message.string_contents()),
628 name: None,
629 function_call: None,
630 })
631 .collect::<Vec<_>>()
632}
633
634pub fn count_open_ai_tokens(
635 request: LanguageModelRequest,
636 model: Model,
637 cx: &App,
638) -> BoxFuture<'static, Result<u64>> {
639 cx.background_spawn(async move {
640 let messages = collect_tiktoken_messages(request);
641
642 match model {
643 Model::Custom { max_tokens, .. } => {
644 let model = if max_tokens >= 100_000 {
645 // If the max tokens is 100k or more, it is likely the o200k_base tokenizer from gpt4o
646 "gpt-4o"
647 } else {
648 // Otherwise fallback to gpt-4, since only cl100k_base and o200k_base are
649 // supported with this tiktoken method
650 "gpt-4"
651 };
652 tiktoken_rs::num_tokens_from_messages(model, &messages)
653 }
654 // Currently supported by tiktoken_rs
655 // Sometimes tiktoken-rs is behind on model support. If that is the case, make a new branch
656 // arm with an override. We enumerate all supported models here so that we can check if new
657 // models are supported yet or not.
658 Model::ThreePointFiveTurbo
659 | Model::Four
660 | Model::FourTurbo
661 | Model::FourOmni
662 | Model::FourOmniMini
663 | Model::FourPointOne
664 | Model::FourPointOneMini
665 | Model::FourPointOneNano
666 | Model::O1
667 | Model::O3
668 | Model::O3Mini
669 | Model::O4Mini => tiktoken_rs::num_tokens_from_messages(model.id(), &messages),
670 // GPT-5 models don't have tiktoken support yet; fall back on gpt-4o tokenizer
671 Model::Five | Model::FiveMini | Model::FiveNano => {
672 tiktoken_rs::num_tokens_from_messages("gpt-4o", &messages)
673 }
674 }
675 .map(|tokens| tokens as u64)
676 })
677 .boxed()
678}
679
680struct ConfigurationView {
681 api_key_editor: Entity<InputField>,
682 state: Entity<State>,
683 load_credentials_task: Option<Task<()>>,
684}
685
686impl ConfigurationView {
687 fn new(state: Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
688 let api_key_editor = cx.new(|cx| {
689 InputField::new(
690 window,
691 cx,
692 "sk-000000000000000000000000000000000000000000000000",
693 )
694 });
695
696 cx.observe(&state, |_, _, cx| {
697 cx.notify();
698 })
699 .detach();
700
701 let load_credentials_task = Some(cx.spawn_in(window, {
702 let state = state.clone();
703 async move |this, cx| {
704 if let Some(task) = state
705 .update(cx, |state, cx| state.authenticate(cx))
706 .log_err()
707 {
708 // We don't log an error, because "not signed in" is also an error.
709 let _ = task.await;
710 }
711 this.update(cx, |this, cx| {
712 this.load_credentials_task = None;
713 cx.notify();
714 })
715 .log_err();
716 }
717 }));
718
719 Self {
720 api_key_editor,
721 state,
722 load_credentials_task,
723 }
724 }
725
726 fn save_api_key(&mut self, _: &menu::Confirm, window: &mut Window, cx: &mut Context<Self>) {
727 let api_key = self.api_key_editor.read(cx).text(cx).trim().to_string();
728 if api_key.is_empty() {
729 return;
730 }
731
732 // url changes can cause the editor to be displayed again
733 self.api_key_editor
734 .update(cx, |editor, cx| editor.set_text("", window, cx));
735
736 let state = self.state.clone();
737 cx.spawn_in(window, async move |_, cx| {
738 state
739 .update(cx, |state, cx| state.set_api_key(Some(api_key), cx))?
740 .await
741 })
742 .detach_and_log_err(cx);
743 }
744
745 fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
746 self.api_key_editor
747 .update(cx, |input, cx| input.set_text("", window, cx));
748
749 let state = self.state.clone();
750 cx.spawn_in(window, async move |_, cx| {
751 state
752 .update(cx, |state, cx| state.set_api_key(None, cx))?
753 .await
754 })
755 .detach_and_log_err(cx);
756 }
757
758 fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
759 !self.state.read(cx).is_authenticated()
760 }
761}
762
763impl Render for ConfigurationView {
764 fn render(&mut self, _: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
765 let env_var_set = self.state.read(cx).api_key_state.is_from_env_var();
766 let configured_card_label = if env_var_set {
767 format!("API key set in {API_KEY_ENV_VAR_NAME} environment variable")
768 } else {
769 let api_url = OpenAiLanguageModelProvider::api_url(cx);
770 if api_url == OPEN_AI_API_URL {
771 "API key configured".to_string()
772 } else {
773 format!("API key configured for {}", api_url)
774 }
775 };
776
777 let api_key_section = if self.should_render_editor(cx) {
778 v_flex()
779 .on_action(cx.listener(Self::save_api_key))
780 .child(Label::new("To use Zed's agent with OpenAI, you need to add an API key. Follow these steps:"))
781 .child(
782 List::new()
783 .child(InstructionListItem::new(
784 "Create one by visiting",
785 Some("OpenAI's console"),
786 Some("https://platform.openai.com/api-keys"),
787 ))
788 .child(InstructionListItem::text_only(
789 "Ensure your OpenAI account has credits",
790 ))
791 .child(InstructionListItem::text_only(
792 "Paste your API key below and hit enter to start using the assistant",
793 )),
794 )
795 .child(self.api_key_editor.clone())
796 .child(
797 Label::new(format!(
798 "You can also assign the {API_KEY_ENV_VAR_NAME} environment variable and restart Zed."
799 ))
800 .size(LabelSize::Small)
801 .color(Color::Muted),
802 )
803 .child(
804 Label::new(
805 "Note that having a subscription for another service like GitHub Copilot won't work.",
806 )
807 .size(LabelSize::Small).color(Color::Muted),
808 )
809 .into_any_element()
810 } else {
811 ConfiguredApiCard::new(configured_card_label)
812 .disabled(env_var_set)
813 .on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx)))
814 .when(env_var_set, |this| {
815 this.tooltip_label(format!("To reset your API key, unset the {API_KEY_ENV_VAR_NAME} environment variable."))
816 })
817 .into_any_element()
818 };
819
820 let compatible_api_section = h_flex()
821 .mt_1p5()
822 .gap_0p5()
823 .flex_wrap()
824 .when(self.should_render_editor(cx), |this| {
825 this.pt_1p5()
826 .border_t_1()
827 .border_color(cx.theme().colors().border_variant)
828 })
829 .child(
830 h_flex()
831 .gap_2()
832 .child(
833 Icon::new(IconName::Info)
834 .size(IconSize::XSmall)
835 .color(Color::Muted),
836 )
837 .child(Label::new("Zed also supports OpenAI-compatible models.")),
838 )
839 .child(
840 Button::new("docs", "Learn More")
841 .icon(IconName::ArrowUpRight)
842 .icon_size(IconSize::Small)
843 .icon_color(Color::Muted)
844 .on_click(move |_, _window, cx| {
845 cx.open_url("https://zed.dev/docs/ai/llm-providers#openai-api-compatible")
846 }),
847 );
848
849 if self.load_credentials_task.is_some() {
850 div().child(Label::new("Loading credentials…")).into_any()
851 } else {
852 v_flex()
853 .size_full()
854 .child(api_key_section)
855 .child(compatible_api_section)
856 .into_any()
857 }
858 }
859}
860
861#[cfg(test)]
862mod tests {
863 use gpui::TestAppContext;
864 use language_model::LanguageModelRequestMessage;
865
866 use super::*;
867
868 #[gpui::test]
869 fn tiktoken_rs_support(cx: &TestAppContext) {
870 let request = LanguageModelRequest {
871 thread_id: None,
872 prompt_id: None,
873 intent: None,
874 mode: None,
875 messages: vec![LanguageModelRequestMessage {
876 role: Role::User,
877 content: vec![MessageContent::Text("message".into())],
878 cache: false,
879 }],
880 tools: vec![],
881 tool_choice: None,
882 stop: vec![],
883 temperature: None,
884 thinking_allowed: true,
885 };
886
887 // Validate that all models are supported by tiktoken-rs
888 for model in Model::iter() {
889 let count = cx
890 .executor()
891 .block(count_open_ai_tokens(
892 request.clone(),
893 model,
894 &cx.app.borrow(),
895 ))
896 .unwrap();
897 assert!(count > 0);
898 }
899 }
900}