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