1use std::pin::Pin;
2use std::str::FromStr as _;
3use std::sync::Arc;
4
5use anyhow::{Result, anyhow};
6use cloud_llm_client::CompletionIntent;
7use collections::HashMap;
8use copilot::{Copilot, Status};
9use copilot_chat::responses as copilot_responses;
10use copilot_chat::{
11 ChatMessage, ChatMessageContent, ChatMessagePart, CopilotChat, CopilotChatConfiguration,
12 Function, FunctionContent, ImageUrl, Model as CopilotChatModel, ModelVendor,
13 Request as CopilotChatRequest, ResponseEvent, Tool, ToolCall, ToolCallContent, ToolChoice,
14};
15use futures::future::BoxFuture;
16use futures::stream::BoxStream;
17use futures::{FutureExt, Stream, StreamExt};
18use gpui::{AnyView, App, AsyncApp, Entity, Subscription, Task};
19use http_client::StatusCode;
20use language::language_settings::all_language_settings;
21use language_model::{
22 AuthenticateError, IconOrSvg, LanguageModel, LanguageModelCompletionError,
23 LanguageModelCompletionEvent, LanguageModelId, LanguageModelName, LanguageModelProvider,
24 LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
25 LanguageModelRequest, LanguageModelRequestMessage, LanguageModelToolChoice,
26 LanguageModelToolResultContent, LanguageModelToolSchemaFormat, LanguageModelToolUse,
27 MessageContent, RateLimiter, Role, StopReason, TokenUsage,
28};
29use settings::SettingsStore;
30use ui::prelude::*;
31use util::debug_panic;
32
33const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("copilot_chat");
34const PROVIDER_NAME: LanguageModelProviderName =
35 LanguageModelProviderName::new("GitHub Copilot Chat");
36
37pub struct CopilotChatLanguageModelProvider {
38 state: Entity<State>,
39}
40
41pub struct State {
42 _copilot_chat_subscription: Option<Subscription>,
43 _settings_subscription: Subscription,
44}
45
46impl State {
47 fn is_authenticated(&self, cx: &App) -> bool {
48 CopilotChat::global(cx)
49 .map(|m| m.read(cx).is_authenticated())
50 .unwrap_or(false)
51 }
52}
53
54impl CopilotChatLanguageModelProvider {
55 pub fn new(cx: &mut App) -> Self {
56 let state = cx.new(|cx| {
57 let copilot_chat_subscription = CopilotChat::global(cx)
58 .map(|copilot_chat| cx.observe(&copilot_chat, |_, _, cx| cx.notify()));
59 State {
60 _copilot_chat_subscription: copilot_chat_subscription,
61 _settings_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
62 if let Some(copilot_chat) = CopilotChat::global(cx) {
63 let language_settings = all_language_settings(None, cx);
64 let configuration = CopilotChatConfiguration {
65 enterprise_uri: language_settings
66 .edit_predictions
67 .copilot
68 .enterprise_uri
69 .clone(),
70 };
71 copilot_chat.update(cx, |chat, cx| {
72 chat.set_configuration(configuration, cx);
73 });
74 }
75 cx.notify();
76 }),
77 }
78 });
79
80 Self { state }
81 }
82
83 fn create_language_model(&self, model: CopilotChatModel) -> Arc<dyn LanguageModel> {
84 Arc::new(CopilotChatLanguageModel {
85 model,
86 request_limiter: RateLimiter::new(4),
87 })
88 }
89}
90
91impl LanguageModelProviderState for CopilotChatLanguageModelProvider {
92 type ObservableEntity = State;
93
94 fn observable_entity(&self) -> Option<Entity<Self::ObservableEntity>> {
95 Some(self.state.clone())
96 }
97}
98
99impl LanguageModelProvider for CopilotChatLanguageModelProvider {
100 fn id(&self) -> LanguageModelProviderId {
101 PROVIDER_ID
102 }
103
104 fn name(&self) -> LanguageModelProviderName {
105 PROVIDER_NAME
106 }
107
108 fn icon(&self) -> IconOrSvg {
109 IconOrSvg::Icon(IconName::Copilot)
110 }
111
112 fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
113 let models = CopilotChat::global(cx).and_then(|m| m.read(cx).models())?;
114 models
115 .first()
116 .map(|model| self.create_language_model(model.clone()))
117 }
118
119 fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
120 // The default model should be Copilot Chat's 'base model', which is likely a relatively fast
121 // model (e.g. 4o) and a sensible choice when considering premium requests
122 self.default_model(cx)
123 }
124
125 fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
126 let Some(models) = CopilotChat::global(cx).and_then(|m| m.read(cx).models()) else {
127 return Vec::new();
128 };
129 models
130 .iter()
131 .map(|model| self.create_language_model(model.clone()))
132 .collect()
133 }
134
135 fn is_authenticated(&self, cx: &App) -> bool {
136 self.state.read(cx).is_authenticated(cx)
137 }
138
139 fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
140 if self.is_authenticated(cx) {
141 return Task::ready(Ok(()));
142 };
143
144 let Some(copilot) = Copilot::global(cx) else {
145 return Task::ready(Err(anyhow!(concat!(
146 "Copilot must be enabled for Copilot Chat to work. ",
147 "Please enable Copilot and try again."
148 ))
149 .into()));
150 };
151
152 let err = match copilot.read(cx).status() {
153 Status::Authorized => return Task::ready(Ok(())),
154 Status::Disabled => anyhow!(
155 "Copilot must be enabled for Copilot Chat to work. Please enable Copilot and try again."
156 ),
157 Status::Error(err) => anyhow!(format!(
158 "Received the following error while signing into Copilot: {err}"
159 )),
160 Status::Starting { task: _ } => anyhow!(
161 "Copilot is still starting, please wait for Copilot to start then try again"
162 ),
163 Status::Unauthorized => anyhow!(
164 "Unable to authorize with Copilot. Please make sure that you have an active Copilot and Copilot Chat subscription."
165 ),
166 Status::SignedOut { .. } => {
167 anyhow!("You have signed out of Copilot. Please sign in to Copilot and try again.")
168 }
169 Status::SigningIn { prompt: _ } => anyhow!("Still signing into Copilot..."),
170 };
171
172 Task::ready(Err(err.into()))
173 }
174
175 fn configuration_view(
176 &self,
177 _target_agent: language_model::ConfigurationViewTargetAgent,
178 _: &mut Window,
179 cx: &mut App,
180 ) -> AnyView {
181 cx.new(|cx| {
182 copilot_ui::ConfigurationView::new(
183 |cx| {
184 CopilotChat::global(cx)
185 .map(|m| m.read(cx).is_authenticated())
186 .unwrap_or(false)
187 },
188 copilot_ui::ConfigurationMode::Chat,
189 cx,
190 )
191 })
192 .into()
193 }
194
195 fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
196 Task::ready(Err(anyhow!(
197 "Signing out of GitHub Copilot Chat is currently not supported."
198 )))
199 }
200}
201
202fn collect_tiktoken_messages(
203 request: LanguageModelRequest,
204) -> Vec<tiktoken_rs::ChatCompletionRequestMessage> {
205 request
206 .messages
207 .into_iter()
208 .map(|message| tiktoken_rs::ChatCompletionRequestMessage {
209 role: match message.role {
210 Role::User => "user".into(),
211 Role::Assistant => "assistant".into(),
212 Role::System => "system".into(),
213 },
214 content: Some(message.string_contents()),
215 name: None,
216 function_call: None,
217 })
218 .collect::<Vec<_>>()
219}
220
221pub struct CopilotChatLanguageModel {
222 model: CopilotChatModel,
223 request_limiter: RateLimiter,
224}
225
226impl LanguageModel for CopilotChatLanguageModel {
227 fn id(&self) -> LanguageModelId {
228 LanguageModelId::from(self.model.id().to_string())
229 }
230
231 fn name(&self) -> LanguageModelName {
232 LanguageModelName::from(self.model.display_name().to_string())
233 }
234
235 fn provider_id(&self) -> LanguageModelProviderId {
236 PROVIDER_ID
237 }
238
239 fn provider_name(&self) -> LanguageModelProviderName {
240 PROVIDER_NAME
241 }
242
243 fn supports_tools(&self) -> bool {
244 self.model.supports_tools()
245 }
246
247 fn supports_images(&self) -> bool {
248 self.model.supports_vision()
249 }
250
251 fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
252 match self.model.vendor() {
253 ModelVendor::OpenAI | ModelVendor::Anthropic => {
254 LanguageModelToolSchemaFormat::JsonSchema
255 }
256 ModelVendor::Google | ModelVendor::XAI | ModelVendor::Unknown => {
257 LanguageModelToolSchemaFormat::JsonSchemaSubset
258 }
259 }
260 }
261
262 fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
263 match choice {
264 LanguageModelToolChoice::Auto
265 | LanguageModelToolChoice::Any
266 | LanguageModelToolChoice::None => self.supports_tools(),
267 }
268 }
269
270 fn telemetry_id(&self) -> String {
271 format!("copilot_chat/{}", self.model.id())
272 }
273
274 fn max_token_count(&self) -> u64 {
275 self.model.max_token_count()
276 }
277
278 fn count_tokens(
279 &self,
280 request: LanguageModelRequest,
281 cx: &App,
282 ) -> BoxFuture<'static, Result<u64>> {
283 let model = self.model.clone();
284 cx.background_spawn(async move {
285 let messages = collect_tiktoken_messages(request);
286 // Copilot uses OpenAI tiktoken tokenizer for all it's model irrespective of the underlying provider(vendor).
287 let tokenizer_model = match model.tokenizer() {
288 Some("o200k_base") => "gpt-4o",
289 Some("cl100k_base") => "gpt-4",
290 _ => "gpt-4o",
291 };
292
293 tiktoken_rs::num_tokens_from_messages(tokenizer_model, &messages)
294 .map(|tokens| tokens as u64)
295 })
296 .boxed()
297 }
298
299 fn stream_completion(
300 &self,
301 request: LanguageModelRequest,
302 cx: &AsyncApp,
303 ) -> BoxFuture<
304 'static,
305 Result<
306 BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
307 LanguageModelCompletionError,
308 >,
309 > {
310 let is_user_initiated = request.intent.is_none_or(|intent| match intent {
311 CompletionIntent::UserPrompt
312 | CompletionIntent::ThreadContextSummarization
313 | CompletionIntent::InlineAssist
314 | CompletionIntent::TerminalInlineAssist
315 | CompletionIntent::GenerateGitCommitMessage => true,
316
317 CompletionIntent::ToolResults
318 | CompletionIntent::ThreadSummarization
319 | CompletionIntent::CreateFile
320 | CompletionIntent::EditFile => false,
321 });
322
323 if self.model.supports_response() {
324 let responses_request = into_copilot_responses(&self.model, request);
325 let request_limiter = self.request_limiter.clone();
326 let future = cx.spawn(async move |cx| {
327 let request =
328 CopilotChat::stream_response(responses_request, is_user_initiated, cx.clone());
329 request_limiter
330 .stream(async move {
331 let stream = request.await?;
332 let mapper = CopilotResponsesEventMapper::new();
333 Ok(mapper.map_stream(stream).boxed())
334 })
335 .await
336 });
337 return async move { Ok(future.await?.boxed()) }.boxed();
338 }
339
340 let copilot_request = match into_copilot_chat(&self.model, request) {
341 Ok(request) => request,
342 Err(err) => return futures::future::ready(Err(err.into())).boxed(),
343 };
344 let is_streaming = copilot_request.stream;
345
346 let request_limiter = self.request_limiter.clone();
347 let future = cx.spawn(async move |cx| {
348 let request =
349 CopilotChat::stream_completion(copilot_request, is_user_initiated, cx.clone());
350 request_limiter
351 .stream(async move {
352 let response = request.await?;
353 Ok(map_to_language_model_completion_events(
354 response,
355 is_streaming,
356 ))
357 })
358 .await
359 });
360 async move { Ok(future.await?.boxed()) }.boxed()
361 }
362}
363
364pub fn map_to_language_model_completion_events(
365 events: Pin<Box<dyn Send + Stream<Item = Result<ResponseEvent>>>>,
366 is_streaming: bool,
367) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
368 #[derive(Default)]
369 struct RawToolCall {
370 id: String,
371 name: String,
372 arguments: String,
373 thought_signature: Option<String>,
374 }
375
376 struct State {
377 events: Pin<Box<dyn Send + Stream<Item = Result<ResponseEvent>>>>,
378 tool_calls_by_index: HashMap<usize, RawToolCall>,
379 reasoning_opaque: Option<String>,
380 reasoning_text: Option<String>,
381 }
382
383 futures::stream::unfold(
384 State {
385 events,
386 tool_calls_by_index: HashMap::default(),
387 reasoning_opaque: None,
388 reasoning_text: None,
389 },
390 move |mut state| async move {
391 if let Some(event) = state.events.next().await {
392 match event {
393 Ok(event) => {
394 let Some(choice) = event.choices.first() else {
395 return Some((
396 vec![Err(anyhow!("Response contained no choices").into())],
397 state,
398 ));
399 };
400
401 let delta = if is_streaming {
402 choice.delta.as_ref()
403 } else {
404 choice.message.as_ref()
405 };
406
407 let Some(delta) = delta else {
408 return Some((
409 vec![Err(anyhow!("Response contained no delta").into())],
410 state,
411 ));
412 };
413
414 let mut events = Vec::new();
415 if let Some(content) = delta.content.clone() {
416 events.push(Ok(LanguageModelCompletionEvent::Text(content)));
417 }
418
419 // Capture reasoning data from the delta (e.g. for Gemini 3)
420 if let Some(opaque) = delta.reasoning_opaque.clone() {
421 state.reasoning_opaque = Some(opaque);
422 }
423 if let Some(text) = delta.reasoning_text.clone() {
424 state.reasoning_text = Some(text);
425 }
426
427 for (index, tool_call) in delta.tool_calls.iter().enumerate() {
428 let tool_index = tool_call.index.unwrap_or(index);
429 let entry = state.tool_calls_by_index.entry(tool_index).or_default();
430
431 if let Some(tool_id) = tool_call.id.clone() {
432 entry.id = tool_id;
433 }
434
435 if let Some(function) = tool_call.function.as_ref() {
436 if let Some(name) = function.name.clone() {
437 entry.name = name;
438 }
439
440 if let Some(arguments) = function.arguments.clone() {
441 entry.arguments.push_str(&arguments);
442 }
443
444 if let Some(thought_signature) = function.thought_signature.clone()
445 {
446 entry.thought_signature = Some(thought_signature);
447 }
448 }
449 }
450
451 if let Some(usage) = event.usage {
452 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
453 TokenUsage {
454 input_tokens: usage.prompt_tokens,
455 output_tokens: usage.completion_tokens,
456 cache_creation_input_tokens: 0,
457 cache_read_input_tokens: 0,
458 },
459 )));
460 }
461
462 match choice.finish_reason.as_deref() {
463 Some("stop") => {
464 events.push(Ok(LanguageModelCompletionEvent::Stop(
465 StopReason::EndTurn,
466 )));
467 }
468 Some("tool_calls") => {
469 // Gemini 3 models send reasoning_opaque/reasoning_text that must
470 // be preserved and sent back in subsequent requests. Emit as
471 // ReasoningDetails so the agent stores it in the message.
472 if state.reasoning_opaque.is_some()
473 || state.reasoning_text.is_some()
474 {
475 let mut details = serde_json::Map::new();
476 if let Some(opaque) = state.reasoning_opaque.take() {
477 details.insert(
478 "reasoning_opaque".to_string(),
479 serde_json::Value::String(opaque),
480 );
481 }
482 if let Some(text) = state.reasoning_text.take() {
483 details.insert(
484 "reasoning_text".to_string(),
485 serde_json::Value::String(text),
486 );
487 }
488 events.push(Ok(
489 LanguageModelCompletionEvent::ReasoningDetails(
490 serde_json::Value::Object(details),
491 ),
492 ));
493 }
494
495 events.extend(state.tool_calls_by_index.drain().map(
496 |(_, tool_call)| {
497 // The model can output an empty string
498 // to indicate the absence of arguments.
499 // When that happens, create an empty
500 // object instead.
501 let arguments = if tool_call.arguments.is_empty() {
502 Ok(serde_json::Value::Object(Default::default()))
503 } else {
504 serde_json::Value::from_str(&tool_call.arguments)
505 };
506 match arguments {
507 Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
508 LanguageModelToolUse {
509 id: tool_call.id.into(),
510 name: tool_call.name.as_str().into(),
511 is_input_complete: true,
512 input,
513 raw_input: tool_call.arguments,
514 thought_signature: tool_call.thought_signature,
515 },
516 )),
517 Err(error) => Ok(
518 LanguageModelCompletionEvent::ToolUseJsonParseError {
519 id: tool_call.id.into(),
520 tool_name: tool_call.name.as_str().into(),
521 raw_input: tool_call.arguments.into(),
522 json_parse_error: error.to_string(),
523 },
524 ),
525 }
526 },
527 ));
528
529 events.push(Ok(LanguageModelCompletionEvent::Stop(
530 StopReason::ToolUse,
531 )));
532 }
533 Some(stop_reason) => {
534 log::error!("Unexpected Copilot Chat stop_reason: {stop_reason:?}");
535 events.push(Ok(LanguageModelCompletionEvent::Stop(
536 StopReason::EndTurn,
537 )));
538 }
539 None => {}
540 }
541
542 return Some((events, state));
543 }
544 Err(err) => return Some((vec![Err(anyhow!(err).into())], state)),
545 }
546 }
547
548 None
549 },
550 )
551 .flat_map(futures::stream::iter)
552}
553
554pub struct CopilotResponsesEventMapper {
555 pending_stop_reason: Option<StopReason>,
556}
557
558impl CopilotResponsesEventMapper {
559 pub fn new() -> Self {
560 Self {
561 pending_stop_reason: None,
562 }
563 }
564
565 pub fn map_stream(
566 mut self,
567 events: Pin<Box<dyn Send + Stream<Item = Result<copilot_responses::StreamEvent>>>>,
568 ) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
569 {
570 events.flat_map(move |event| {
571 futures::stream::iter(match event {
572 Ok(event) => self.map_event(event),
573 Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
574 })
575 })
576 }
577
578 fn map_event(
579 &mut self,
580 event: copilot_responses::StreamEvent,
581 ) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
582 match event {
583 copilot_responses::StreamEvent::OutputItemAdded { item, .. } => match item {
584 copilot_responses::ResponseOutputItem::Message { id, .. } => {
585 vec![Ok(LanguageModelCompletionEvent::StartMessage {
586 message_id: id,
587 })]
588 }
589 _ => Vec::new(),
590 },
591
592 copilot_responses::StreamEvent::OutputTextDelta { delta, .. } => {
593 if delta.is_empty() {
594 Vec::new()
595 } else {
596 vec![Ok(LanguageModelCompletionEvent::Text(delta))]
597 }
598 }
599
600 copilot_responses::StreamEvent::OutputItemDone { item, .. } => match item {
601 copilot_responses::ResponseOutputItem::Message { .. } => Vec::new(),
602 copilot_responses::ResponseOutputItem::FunctionCall {
603 call_id,
604 name,
605 arguments,
606 thought_signature,
607 ..
608 } => {
609 let mut events = Vec::new();
610 match serde_json::from_str::<serde_json::Value>(&arguments) {
611 Ok(input) => events.push(Ok(LanguageModelCompletionEvent::ToolUse(
612 LanguageModelToolUse {
613 id: call_id.into(),
614 name: name.as_str().into(),
615 is_input_complete: true,
616 input,
617 raw_input: arguments.clone(),
618 thought_signature,
619 },
620 ))),
621 Err(error) => {
622 events.push(Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
623 id: call_id.into(),
624 tool_name: name.as_str().into(),
625 raw_input: arguments.clone().into(),
626 json_parse_error: error.to_string(),
627 }))
628 }
629 }
630 // Record that we already emitted a tool-use stop so we can avoid duplicating
631 // a Stop event on Completed.
632 self.pending_stop_reason = Some(StopReason::ToolUse);
633 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
634 events
635 }
636 copilot_responses::ResponseOutputItem::Reasoning {
637 summary,
638 encrypted_content,
639 ..
640 } => {
641 let mut events = Vec::new();
642
643 if let Some(blocks) = summary {
644 let mut text = String::new();
645 for block in blocks {
646 text.push_str(&block.text);
647 }
648 if !text.is_empty() {
649 events.push(Ok(LanguageModelCompletionEvent::Thinking {
650 text,
651 signature: None,
652 }));
653 }
654 }
655
656 if let Some(data) = encrypted_content {
657 events.push(Ok(LanguageModelCompletionEvent::RedactedThinking { data }));
658 }
659
660 events
661 }
662 },
663
664 copilot_responses::StreamEvent::Completed { response } => {
665 let mut events = Vec::new();
666 if let Some(usage) = response.usage {
667 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
668 input_tokens: usage.input_tokens.unwrap_or(0),
669 output_tokens: usage.output_tokens.unwrap_or(0),
670 cache_creation_input_tokens: 0,
671 cache_read_input_tokens: 0,
672 })));
673 }
674 if self.pending_stop_reason.take() != Some(StopReason::ToolUse) {
675 events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
676 }
677 events
678 }
679
680 copilot_responses::StreamEvent::Incomplete { response } => {
681 let reason = response
682 .incomplete_details
683 .as_ref()
684 .and_then(|details| details.reason.as_ref());
685 let stop_reason = match reason {
686 Some(copilot_responses::IncompleteReason::MaxOutputTokens) => {
687 StopReason::MaxTokens
688 }
689 Some(copilot_responses::IncompleteReason::ContentFilter) => StopReason::Refusal,
690 _ => self
691 .pending_stop_reason
692 .take()
693 .unwrap_or(StopReason::EndTurn),
694 };
695
696 let mut events = Vec::new();
697 if let Some(usage) = response.usage {
698 events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
699 input_tokens: usage.input_tokens.unwrap_or(0),
700 output_tokens: usage.output_tokens.unwrap_or(0),
701 cache_creation_input_tokens: 0,
702 cache_read_input_tokens: 0,
703 })));
704 }
705 events.push(Ok(LanguageModelCompletionEvent::Stop(stop_reason)));
706 events
707 }
708
709 copilot_responses::StreamEvent::Failed { response } => {
710 let provider = PROVIDER_NAME;
711 let (status_code, message) = match response.error {
712 Some(error) => {
713 let status_code = StatusCode::from_str(&error.code)
714 .unwrap_or(StatusCode::INTERNAL_SERVER_ERROR);
715 (status_code, error.message)
716 }
717 None => (
718 StatusCode::INTERNAL_SERVER_ERROR,
719 "response.failed".to_string(),
720 ),
721 };
722 vec![Err(LanguageModelCompletionError::HttpResponseError {
723 provider,
724 status_code,
725 message,
726 })]
727 }
728
729 copilot_responses::StreamEvent::GenericError { error } => vec![Err(
730 LanguageModelCompletionError::Other(anyhow!(format!("{error:?}"))),
731 )],
732
733 copilot_responses::StreamEvent::Created { .. }
734 | copilot_responses::StreamEvent::Unknown => Vec::new(),
735 }
736 }
737}
738
739fn into_copilot_chat(
740 model: &CopilotChatModel,
741 request: LanguageModelRequest,
742) -> Result<CopilotChatRequest> {
743 let mut request_messages: Vec<LanguageModelRequestMessage> = Vec::new();
744 for message in request.messages {
745 if let Some(last_message) = request_messages.last_mut() {
746 if last_message.role == message.role {
747 last_message.content.extend(message.content);
748 } else {
749 request_messages.push(message);
750 }
751 } else {
752 request_messages.push(message);
753 }
754 }
755
756 let mut messages: Vec<ChatMessage> = Vec::new();
757 for message in request_messages {
758 match message.role {
759 Role::User => {
760 for content in &message.content {
761 if let MessageContent::ToolResult(tool_result) = content {
762 let content = match &tool_result.content {
763 LanguageModelToolResultContent::Text(text) => text.to_string().into(),
764 LanguageModelToolResultContent::Image(image) => {
765 if model.supports_vision() {
766 ChatMessageContent::Multipart(vec![ChatMessagePart::Image {
767 image_url: ImageUrl {
768 url: image.to_base64_url(),
769 },
770 }])
771 } else {
772 debug_panic!(
773 "This should be caught at {} level",
774 tool_result.tool_name
775 );
776 "[Tool responded with an image, but this model does not support vision]".to_string().into()
777 }
778 }
779 };
780
781 messages.push(ChatMessage::Tool {
782 tool_call_id: tool_result.tool_use_id.to_string(),
783 content,
784 });
785 }
786 }
787
788 let mut content_parts = Vec::new();
789 for content in &message.content {
790 match content {
791 MessageContent::Text(text) | MessageContent::Thinking { text, .. }
792 if !text.is_empty() =>
793 {
794 if let Some(ChatMessagePart::Text { text: text_content }) =
795 content_parts.last_mut()
796 {
797 text_content.push_str(text);
798 } else {
799 content_parts.push(ChatMessagePart::Text {
800 text: text.to_string(),
801 });
802 }
803 }
804 MessageContent::Image(image) if model.supports_vision() => {
805 content_parts.push(ChatMessagePart::Image {
806 image_url: ImageUrl {
807 url: image.to_base64_url(),
808 },
809 });
810 }
811 _ => {}
812 }
813 }
814
815 if !content_parts.is_empty() {
816 messages.push(ChatMessage::User {
817 content: content_parts.into(),
818 });
819 }
820 }
821 Role::Assistant => {
822 let mut tool_calls = Vec::new();
823 for content in &message.content {
824 if let MessageContent::ToolUse(tool_use) = content {
825 tool_calls.push(ToolCall {
826 id: tool_use.id.to_string(),
827 content: ToolCallContent::Function {
828 function: FunctionContent {
829 name: tool_use.name.to_string(),
830 arguments: serde_json::to_string(&tool_use.input)?,
831 thought_signature: tool_use.thought_signature.clone(),
832 },
833 },
834 });
835 }
836 }
837
838 let text_content = {
839 let mut buffer = String::new();
840 for string in message.content.iter().filter_map(|content| match content {
841 MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
842 Some(text.as_str())
843 }
844 MessageContent::ToolUse(_)
845 | MessageContent::RedactedThinking(_)
846 | MessageContent::ToolResult(_)
847 | MessageContent::Image(_) => None,
848 }) {
849 buffer.push_str(string);
850 }
851
852 buffer
853 };
854
855 // Extract reasoning_opaque and reasoning_text from reasoning_details
856 let (reasoning_opaque, reasoning_text) =
857 if let Some(details) = &message.reasoning_details {
858 let opaque = details
859 .get("reasoning_opaque")
860 .and_then(|v| v.as_str())
861 .map(|s| s.to_string());
862 let text = details
863 .get("reasoning_text")
864 .and_then(|v| v.as_str())
865 .map(|s| s.to_string());
866 (opaque, text)
867 } else {
868 (None, None)
869 };
870
871 messages.push(ChatMessage::Assistant {
872 content: if text_content.is_empty() {
873 ChatMessageContent::empty()
874 } else {
875 text_content.into()
876 },
877 tool_calls,
878 reasoning_opaque,
879 reasoning_text,
880 });
881 }
882 Role::System => messages.push(ChatMessage::System {
883 content: message.string_contents(),
884 }),
885 }
886 }
887
888 let tools = request
889 .tools
890 .iter()
891 .map(|tool| Tool::Function {
892 function: Function {
893 name: tool.name.clone(),
894 description: tool.description.clone(),
895 parameters: tool.input_schema.clone(),
896 },
897 })
898 .collect::<Vec<_>>();
899
900 Ok(CopilotChatRequest {
901 intent: true,
902 n: 1,
903 stream: model.uses_streaming(),
904 temperature: 0.1,
905 model: model.id().to_string(),
906 messages,
907 tools,
908 tool_choice: request.tool_choice.map(|choice| match choice {
909 LanguageModelToolChoice::Auto => ToolChoice::Auto,
910 LanguageModelToolChoice::Any => ToolChoice::Any,
911 LanguageModelToolChoice::None => ToolChoice::None,
912 }),
913 })
914}
915
916fn into_copilot_responses(
917 model: &CopilotChatModel,
918 request: LanguageModelRequest,
919) -> copilot_responses::Request {
920 use copilot_responses as responses;
921
922 let LanguageModelRequest {
923 thread_id: _,
924 prompt_id: _,
925 intent: _,
926 messages,
927 tools,
928 tool_choice,
929 stop: _,
930 temperature,
931 thinking_allowed: _,
932 } = request;
933
934 let mut input_items: Vec<responses::ResponseInputItem> = Vec::new();
935
936 for message in messages {
937 match message.role {
938 Role::User => {
939 for content in &message.content {
940 if let MessageContent::ToolResult(tool_result) = content {
941 let output = if let Some(out) = &tool_result.output {
942 match out {
943 serde_json::Value::String(s) => {
944 responses::ResponseFunctionOutput::Text(s.clone())
945 }
946 serde_json::Value::Null => {
947 responses::ResponseFunctionOutput::Text(String::new())
948 }
949 other => responses::ResponseFunctionOutput::Text(other.to_string()),
950 }
951 } else {
952 match &tool_result.content {
953 LanguageModelToolResultContent::Text(text) => {
954 responses::ResponseFunctionOutput::Text(text.to_string())
955 }
956 LanguageModelToolResultContent::Image(image) => {
957 if model.supports_vision() {
958 responses::ResponseFunctionOutput::Content(vec![
959 responses::ResponseInputContent::InputImage {
960 image_url: Some(image.to_base64_url()),
961 detail: Default::default(),
962 },
963 ])
964 } else {
965 debug_panic!(
966 "This should be caught at {} level",
967 tool_result.tool_name
968 );
969 responses::ResponseFunctionOutput::Text(
970 "[Tool responded with an image, but this model does not support vision]".into(),
971 )
972 }
973 }
974 }
975 };
976
977 input_items.push(responses::ResponseInputItem::FunctionCallOutput {
978 call_id: tool_result.tool_use_id.to_string(),
979 output,
980 status: None,
981 });
982 }
983 }
984
985 let mut parts: Vec<responses::ResponseInputContent> = Vec::new();
986 for content in &message.content {
987 match content {
988 MessageContent::Text(text) => {
989 parts.push(responses::ResponseInputContent::InputText {
990 text: text.clone(),
991 });
992 }
993
994 MessageContent::Image(image) => {
995 if model.supports_vision() {
996 parts.push(responses::ResponseInputContent::InputImage {
997 image_url: Some(image.to_base64_url()),
998 detail: Default::default(),
999 });
1000 }
1001 }
1002 _ => {}
1003 }
1004 }
1005
1006 if !parts.is_empty() {
1007 input_items.push(responses::ResponseInputItem::Message {
1008 role: "user".into(),
1009 content: Some(parts),
1010 status: None,
1011 });
1012 }
1013 }
1014
1015 Role::Assistant => {
1016 for content in &message.content {
1017 if let MessageContent::ToolUse(tool_use) = content {
1018 input_items.push(responses::ResponseInputItem::FunctionCall {
1019 call_id: tool_use.id.to_string(),
1020 name: tool_use.name.to_string(),
1021 arguments: tool_use.raw_input.clone(),
1022 status: None,
1023 thought_signature: tool_use.thought_signature.clone(),
1024 });
1025 }
1026 }
1027
1028 for content in &message.content {
1029 if let MessageContent::RedactedThinking(data) = content {
1030 input_items.push(responses::ResponseInputItem::Reasoning {
1031 id: None,
1032 summary: Vec::new(),
1033 encrypted_content: data.clone(),
1034 });
1035 }
1036 }
1037
1038 let mut parts: Vec<responses::ResponseInputContent> = Vec::new();
1039 for content in &message.content {
1040 match content {
1041 MessageContent::Text(text) => {
1042 parts.push(responses::ResponseInputContent::OutputText {
1043 text: text.clone(),
1044 });
1045 }
1046 MessageContent::Image(_) => {
1047 parts.push(responses::ResponseInputContent::OutputText {
1048 text: "[image omitted]".to_string(),
1049 });
1050 }
1051 _ => {}
1052 }
1053 }
1054
1055 if !parts.is_empty() {
1056 input_items.push(responses::ResponseInputItem::Message {
1057 role: "assistant".into(),
1058 content: Some(parts),
1059 status: Some("completed".into()),
1060 });
1061 }
1062 }
1063
1064 Role::System => {
1065 let mut parts: Vec<responses::ResponseInputContent> = Vec::new();
1066 for content in &message.content {
1067 if let MessageContent::Text(text) = content {
1068 parts.push(responses::ResponseInputContent::InputText {
1069 text: text.clone(),
1070 });
1071 }
1072 }
1073
1074 if !parts.is_empty() {
1075 input_items.push(responses::ResponseInputItem::Message {
1076 role: "system".into(),
1077 content: Some(parts),
1078 status: None,
1079 });
1080 }
1081 }
1082 }
1083 }
1084
1085 let converted_tools: Vec<responses::ToolDefinition> = tools
1086 .into_iter()
1087 .map(|tool| responses::ToolDefinition::Function {
1088 name: tool.name,
1089 description: Some(tool.description),
1090 parameters: Some(tool.input_schema),
1091 strict: None,
1092 })
1093 .collect();
1094
1095 let mapped_tool_choice = tool_choice.map(|choice| match choice {
1096 LanguageModelToolChoice::Auto => responses::ToolChoice::Auto,
1097 LanguageModelToolChoice::Any => responses::ToolChoice::Any,
1098 LanguageModelToolChoice::None => responses::ToolChoice::None,
1099 });
1100
1101 responses::Request {
1102 model: model.id().to_string(),
1103 input: input_items,
1104 stream: model.uses_streaming(),
1105 temperature,
1106 tools: converted_tools,
1107 tool_choice: mapped_tool_choice,
1108 reasoning: None, // We would need to add support for setting from user settings.
1109 include: Some(vec![
1110 copilot_responses::ResponseIncludable::ReasoningEncryptedContent,
1111 ]),
1112 }
1113}
1114
1115#[cfg(test)]
1116mod tests {
1117 use super::*;
1118 use copilot_chat::responses;
1119 use futures::StreamExt;
1120
1121 fn map_events(events: Vec<responses::StreamEvent>) -> Vec<LanguageModelCompletionEvent> {
1122 futures::executor::block_on(async {
1123 CopilotResponsesEventMapper::new()
1124 .map_stream(Box::pin(futures::stream::iter(events.into_iter().map(Ok))))
1125 .collect::<Vec<_>>()
1126 .await
1127 .into_iter()
1128 .map(Result::unwrap)
1129 .collect()
1130 })
1131 }
1132
1133 #[test]
1134 fn responses_stream_maps_text_and_usage() {
1135 let events = vec![
1136 responses::StreamEvent::OutputItemAdded {
1137 output_index: 0,
1138 sequence_number: None,
1139 item: responses::ResponseOutputItem::Message {
1140 id: "msg_1".into(),
1141 role: "assistant".into(),
1142 content: Some(Vec::new()),
1143 },
1144 },
1145 responses::StreamEvent::OutputTextDelta {
1146 item_id: "msg_1".into(),
1147 output_index: 0,
1148 delta: "Hello".into(),
1149 },
1150 responses::StreamEvent::Completed {
1151 response: responses::Response {
1152 usage: Some(responses::ResponseUsage {
1153 input_tokens: Some(5),
1154 output_tokens: Some(3),
1155 total_tokens: Some(8),
1156 }),
1157 ..Default::default()
1158 },
1159 },
1160 ];
1161
1162 let mapped = map_events(events);
1163 assert!(matches!(
1164 mapped[0],
1165 LanguageModelCompletionEvent::StartMessage { ref message_id } if message_id == "msg_1"
1166 ));
1167 assert!(matches!(
1168 mapped[1],
1169 LanguageModelCompletionEvent::Text(ref text) if text == "Hello"
1170 ));
1171 assert!(matches!(
1172 mapped[2],
1173 LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
1174 input_tokens: 5,
1175 output_tokens: 3,
1176 ..
1177 })
1178 ));
1179 assert!(matches!(
1180 mapped[3],
1181 LanguageModelCompletionEvent::Stop(StopReason::EndTurn)
1182 ));
1183 }
1184
1185 #[test]
1186 fn responses_stream_maps_tool_calls() {
1187 let events = vec![responses::StreamEvent::OutputItemDone {
1188 output_index: 0,
1189 sequence_number: None,
1190 item: responses::ResponseOutputItem::FunctionCall {
1191 id: Some("fn_1".into()),
1192 call_id: "call_1".into(),
1193 name: "do_it".into(),
1194 arguments: "{\"x\":1}".into(),
1195 status: None,
1196 thought_signature: None,
1197 },
1198 }];
1199
1200 let mapped = map_events(events);
1201 assert!(matches!(
1202 mapped[0],
1203 LanguageModelCompletionEvent::ToolUse(ref use_) if use_.id.to_string() == "call_1" && use_.name.as_ref() == "do_it"
1204 ));
1205 assert!(matches!(
1206 mapped[1],
1207 LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
1208 ));
1209 }
1210
1211 #[test]
1212 fn responses_stream_handles_json_parse_error() {
1213 let events = vec![responses::StreamEvent::OutputItemDone {
1214 output_index: 0,
1215 sequence_number: None,
1216 item: responses::ResponseOutputItem::FunctionCall {
1217 id: Some("fn_1".into()),
1218 call_id: "call_1".into(),
1219 name: "do_it".into(),
1220 arguments: "{not json}".into(),
1221 status: None,
1222 thought_signature: None,
1223 },
1224 }];
1225
1226 let mapped = map_events(events);
1227 assert!(matches!(
1228 mapped[0],
1229 LanguageModelCompletionEvent::ToolUseJsonParseError { ref id, ref tool_name, .. }
1230 if id.to_string() == "call_1" && tool_name.as_ref() == "do_it"
1231 ));
1232 assert!(matches!(
1233 mapped[1],
1234 LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
1235 ));
1236 }
1237
1238 #[test]
1239 fn responses_stream_maps_reasoning_summary_and_encrypted_content() {
1240 let events = vec![responses::StreamEvent::OutputItemDone {
1241 output_index: 0,
1242 sequence_number: None,
1243 item: responses::ResponseOutputItem::Reasoning {
1244 id: "r1".into(),
1245 summary: Some(vec![responses::ResponseReasoningItem {
1246 kind: "summary_text".into(),
1247 text: "Chain".into(),
1248 }]),
1249 encrypted_content: Some("ENC".into()),
1250 },
1251 }];
1252
1253 let mapped = map_events(events);
1254 assert!(matches!(
1255 mapped[0],
1256 LanguageModelCompletionEvent::Thinking { ref text, signature: None } if text == "Chain"
1257 ));
1258 assert!(matches!(
1259 mapped[1],
1260 LanguageModelCompletionEvent::RedactedThinking { ref data } if data == "ENC"
1261 ));
1262 }
1263
1264 #[test]
1265 fn responses_stream_handles_incomplete_max_tokens() {
1266 let events = vec![responses::StreamEvent::Incomplete {
1267 response: responses::Response {
1268 usage: Some(responses::ResponseUsage {
1269 input_tokens: Some(10),
1270 output_tokens: Some(0),
1271 total_tokens: Some(10),
1272 }),
1273 incomplete_details: Some(responses::IncompleteDetails {
1274 reason: Some(responses::IncompleteReason::MaxOutputTokens),
1275 }),
1276 ..Default::default()
1277 },
1278 }];
1279
1280 let mapped = map_events(events);
1281 assert!(matches!(
1282 mapped[0],
1283 LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
1284 input_tokens: 10,
1285 output_tokens: 0,
1286 ..
1287 })
1288 ));
1289 assert!(matches!(
1290 mapped[1],
1291 LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
1292 ));
1293 }
1294
1295 #[test]
1296 fn responses_stream_handles_incomplete_content_filter() {
1297 let events = vec![responses::StreamEvent::Incomplete {
1298 response: responses::Response {
1299 usage: None,
1300 incomplete_details: Some(responses::IncompleteDetails {
1301 reason: Some(responses::IncompleteReason::ContentFilter),
1302 }),
1303 ..Default::default()
1304 },
1305 }];
1306
1307 let mapped = map_events(events);
1308 assert!(matches!(
1309 mapped.last().unwrap(),
1310 LanguageModelCompletionEvent::Stop(StopReason::Refusal)
1311 ));
1312 }
1313
1314 #[test]
1315 fn responses_stream_completed_no_duplicate_after_tool_use() {
1316 let events = vec![
1317 responses::StreamEvent::OutputItemDone {
1318 output_index: 0,
1319 sequence_number: None,
1320 item: responses::ResponseOutputItem::FunctionCall {
1321 id: Some("fn_1".into()),
1322 call_id: "call_1".into(),
1323 name: "do_it".into(),
1324 arguments: "{}".into(),
1325 status: None,
1326 thought_signature: None,
1327 },
1328 },
1329 responses::StreamEvent::Completed {
1330 response: responses::Response::default(),
1331 },
1332 ];
1333
1334 let mapped = map_events(events);
1335
1336 let mut stop_count = 0usize;
1337 let mut saw_tool_use_stop = false;
1338 for event in mapped {
1339 if let LanguageModelCompletionEvent::Stop(reason) = event {
1340 stop_count += 1;
1341 if matches!(reason, StopReason::ToolUse) {
1342 saw_tool_use_stop = true;
1343 }
1344 }
1345 }
1346 assert_eq!(stop_count, 1, "should emit exactly one Stop event");
1347 assert!(saw_tool_use_stop, "Stop reason should be ToolUse");
1348 }
1349
1350 #[test]
1351 fn responses_stream_failed_maps_http_response_error() {
1352 let events = vec![responses::StreamEvent::Failed {
1353 response: responses::Response {
1354 error: Some(responses::ResponseError {
1355 code: "429".into(),
1356 message: "too many requests".into(),
1357 }),
1358 ..Default::default()
1359 },
1360 }];
1361
1362 let mapped_results = futures::executor::block_on(async {
1363 CopilotResponsesEventMapper::new()
1364 .map_stream(Box::pin(futures::stream::iter(events.into_iter().map(Ok))))
1365 .collect::<Vec<_>>()
1366 .await
1367 });
1368
1369 assert_eq!(mapped_results.len(), 1);
1370 match &mapped_results[0] {
1371 Err(LanguageModelCompletionError::HttpResponseError {
1372 status_code,
1373 message,
1374 ..
1375 }) => {
1376 assert_eq!(*status_code, http_client::StatusCode::TOO_MANY_REQUESTS);
1377 assert_eq!(message, "too many requests");
1378 }
1379 other => panic!("expected HttpResponseError, got {:?}", other),
1380 }
1381 }
1382
1383 #[test]
1384 fn chat_completions_stream_maps_reasoning_data() {
1385 use copilot_chat::{
1386 FunctionChunk, ResponseChoice, ResponseDelta, ResponseEvent, Role, ToolCallChunk,
1387 };
1388
1389 let events = vec![
1390 ResponseEvent {
1391 choices: vec![ResponseChoice {
1392 index: Some(0),
1393 finish_reason: None,
1394 delta: Some(ResponseDelta {
1395 content: None,
1396 role: Some(Role::Assistant),
1397 tool_calls: vec![ToolCallChunk {
1398 index: Some(0),
1399 id: Some("call_abc123".to_string()),
1400 function: Some(FunctionChunk {
1401 name: Some("list_directory".to_string()),
1402 arguments: Some("{\"path\":\"test\"}".to_string()),
1403 thought_signature: None,
1404 }),
1405 }],
1406 reasoning_opaque: Some("encrypted_reasoning_token_xyz".to_string()),
1407 reasoning_text: Some("Let me check the directory".to_string()),
1408 }),
1409 message: None,
1410 }],
1411 id: "chatcmpl-123".to_string(),
1412 usage: None,
1413 },
1414 ResponseEvent {
1415 choices: vec![ResponseChoice {
1416 index: Some(0),
1417 finish_reason: Some("tool_calls".to_string()),
1418 delta: Some(ResponseDelta {
1419 content: None,
1420 role: None,
1421 tool_calls: vec![],
1422 reasoning_opaque: None,
1423 reasoning_text: None,
1424 }),
1425 message: None,
1426 }],
1427 id: "chatcmpl-123".to_string(),
1428 usage: None,
1429 },
1430 ];
1431
1432 let mapped = futures::executor::block_on(async {
1433 map_to_language_model_completion_events(
1434 Box::pin(futures::stream::iter(events.into_iter().map(Ok))),
1435 true,
1436 )
1437 .collect::<Vec<_>>()
1438 .await
1439 });
1440
1441 let mut has_reasoning_details = false;
1442 let mut has_tool_use = false;
1443 let mut reasoning_opaque_value: Option<String> = None;
1444 let mut reasoning_text_value: Option<String> = None;
1445
1446 for event_result in mapped {
1447 match event_result {
1448 Ok(LanguageModelCompletionEvent::ReasoningDetails(details)) => {
1449 has_reasoning_details = true;
1450 reasoning_opaque_value = details
1451 .get("reasoning_opaque")
1452 .and_then(|v| v.as_str())
1453 .map(|s| s.to_string());
1454 reasoning_text_value = details
1455 .get("reasoning_text")
1456 .and_then(|v| v.as_str())
1457 .map(|s| s.to_string());
1458 }
1459 Ok(LanguageModelCompletionEvent::ToolUse(tool_use)) => {
1460 has_tool_use = true;
1461 assert_eq!(tool_use.id.to_string(), "call_abc123");
1462 assert_eq!(tool_use.name.as_ref(), "list_directory");
1463 }
1464 _ => {}
1465 }
1466 }
1467
1468 assert!(
1469 has_reasoning_details,
1470 "Should emit ReasoningDetails event for Gemini 3 reasoning"
1471 );
1472 assert!(has_tool_use, "Should emit ToolUse event");
1473 assert_eq!(
1474 reasoning_opaque_value,
1475 Some("encrypted_reasoning_token_xyz".to_string()),
1476 "Should capture reasoning_opaque"
1477 );
1478 assert_eq!(
1479 reasoning_text_value,
1480 Some("Let me check the directory".to_string()),
1481 "Should capture reasoning_text"
1482 );
1483 }
1484}