Richard Feldman
c0fadae881
Implement Gemini API's [thought signatures](https://ai.google.dev/gemini-api/docs/thinking#signatures) Release Notes: - Added thought signatures for Gemini tool calls
1398 lines
54 KiB
Rust
1398 lines
54 KiB
Rust
use std::pin::Pin;
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use std::str::FromStr as _;
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use std::sync::Arc;
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use anyhow::{Result, anyhow};
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use cloud_llm_client::CompletionIntent;
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use collections::HashMap;
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use copilot::copilot_chat::{
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ChatMessage, ChatMessageContent, ChatMessagePart, CopilotChat, ImageUrl,
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Model as CopilotChatModel, ModelVendor, Request as CopilotChatRequest, ResponseEvent, Tool,
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ToolCall,
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};
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use copilot::{Copilot, Status};
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use futures::future::BoxFuture;
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use futures::stream::BoxStream;
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use futures::{FutureExt, Stream, StreamExt};
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use gpui::{Action, AnyView, App, AsyncApp, Entity, Render, Subscription, Task, svg};
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use http_client::StatusCode;
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use language::language_settings::all_language_settings;
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use language_model::{
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AuthenticateError, LanguageModel, LanguageModelCompletionError, LanguageModelCompletionEvent,
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LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
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LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
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LanguageModelRequestMessage, LanguageModelToolChoice, LanguageModelToolResultContent,
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LanguageModelToolSchemaFormat, LanguageModelToolUse, MessageContent, RateLimiter, Role,
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StopReason, TokenUsage,
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};
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use settings::SettingsStore;
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use ui::{CommonAnimationExt, prelude::*};
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use util::debug_panic;
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use crate::ui::ConfiguredApiCard;
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const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("copilot_chat");
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const PROVIDER_NAME: LanguageModelProviderName =
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LanguageModelProviderName::new("GitHub Copilot Chat");
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pub struct CopilotChatLanguageModelProvider {
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state: Entity<State>,
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}
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pub struct State {
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_copilot_chat_subscription: Option<Subscription>,
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_settings_subscription: Subscription,
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}
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impl State {
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fn is_authenticated(&self, cx: &App) -> bool {
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CopilotChat::global(cx)
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.map(|m| m.read(cx).is_authenticated())
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.unwrap_or(false)
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}
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}
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impl CopilotChatLanguageModelProvider {
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pub fn new(cx: &mut App) -> Self {
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let state = cx.new(|cx| {
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let copilot_chat_subscription = CopilotChat::global(cx)
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.map(|copilot_chat| cx.observe(&copilot_chat, |_, _, cx| cx.notify()));
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State {
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_copilot_chat_subscription: copilot_chat_subscription,
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_settings_subscription: cx.observe_global::<SettingsStore>(|_, cx| {
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if let Some(copilot_chat) = CopilotChat::global(cx) {
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let language_settings = all_language_settings(None, cx);
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let configuration = copilot::copilot_chat::CopilotChatConfiguration {
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enterprise_uri: language_settings
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.edit_predictions
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.copilot
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.enterprise_uri
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.clone(),
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};
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copilot_chat.update(cx, |chat, cx| {
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chat.set_configuration(configuration, cx);
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});
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}
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cx.notify();
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}),
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}
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});
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Self { state }
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}
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fn create_language_model(&self, model: CopilotChatModel) -> Arc<dyn LanguageModel> {
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Arc::new(CopilotChatLanguageModel {
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model,
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request_limiter: RateLimiter::new(4),
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})
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}
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}
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impl LanguageModelProviderState for CopilotChatLanguageModelProvider {
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type ObservableEntity = State;
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fn observable_entity(&self) -> Option<Entity<Self::ObservableEntity>> {
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Some(self.state.clone())
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}
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}
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impl LanguageModelProvider for CopilotChatLanguageModelProvider {
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fn id(&self) -> LanguageModelProviderId {
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PROVIDER_ID
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}
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fn name(&self) -> LanguageModelProviderName {
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PROVIDER_NAME
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}
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fn icon(&self) -> IconName {
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IconName::Copilot
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}
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fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
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let models = CopilotChat::global(cx).and_then(|m| m.read(cx).models())?;
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models
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.first()
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.map(|model| self.create_language_model(model.clone()))
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}
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fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>> {
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// The default model should be Copilot Chat's 'base model', which is likely a relatively fast
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// model (e.g. 4o) and a sensible choice when considering premium requests
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self.default_model(cx)
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}
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fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
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let Some(models) = CopilotChat::global(cx).and_then(|m| m.read(cx).models()) else {
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return Vec::new();
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};
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models
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.iter()
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.map(|model| self.create_language_model(model.clone()))
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.collect()
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}
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fn is_authenticated(&self, cx: &App) -> bool {
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self.state.read(cx).is_authenticated(cx)
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}
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fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
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if self.is_authenticated(cx) {
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return Task::ready(Ok(()));
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};
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let Some(copilot) = Copilot::global(cx) else {
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return Task::ready(Err(anyhow!(concat!(
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"Copilot must be enabled for Copilot Chat to work. ",
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"Please enable Copilot and try again."
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))
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.into()));
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};
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let err = match copilot.read(cx).status() {
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Status::Authorized => return Task::ready(Ok(())),
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Status::Disabled => anyhow!(
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"Copilot must be enabled for Copilot Chat to work. Please enable Copilot and try again."
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),
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Status::Error(err) => anyhow!(format!(
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"Received the following error while signing into Copilot: {err}"
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)),
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Status::Starting { task: _ } => anyhow!(
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"Copilot is still starting, please wait for Copilot to start then try again"
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),
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Status::Unauthorized => anyhow!(
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"Unable to authorize with Copilot. Please make sure that you have an active Copilot and Copilot Chat subscription."
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),
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Status::SignedOut { .. } => {
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anyhow!("You have signed out of Copilot. Please sign in to Copilot and try again.")
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}
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Status::SigningIn { prompt: _ } => anyhow!("Still signing into Copilot..."),
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};
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Task::ready(Err(err.into()))
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}
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fn configuration_view(
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&self,
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_target_agent: language_model::ConfigurationViewTargetAgent,
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_: &mut Window,
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cx: &mut App,
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) -> AnyView {
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let state = self.state.clone();
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cx.new(|cx| ConfigurationView::new(state, cx)).into()
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}
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fn reset_credentials(&self, _cx: &mut App) -> Task<Result<()>> {
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Task::ready(Err(anyhow!(
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"Signing out of GitHub Copilot Chat is currently not supported."
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)))
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}
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}
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fn collect_tiktoken_messages(
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request: LanguageModelRequest,
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) -> Vec<tiktoken_rs::ChatCompletionRequestMessage> {
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request
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.messages
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.into_iter()
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.map(|message| tiktoken_rs::ChatCompletionRequestMessage {
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role: match message.role {
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Role::User => "user".into(),
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Role::Assistant => "assistant".into(),
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Role::System => "system".into(),
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},
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content: Some(message.string_contents()),
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name: None,
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function_call: None,
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})
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.collect::<Vec<_>>()
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}
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pub struct CopilotChatLanguageModel {
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model: CopilotChatModel,
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request_limiter: RateLimiter,
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}
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impl LanguageModel for CopilotChatLanguageModel {
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fn id(&self) -> LanguageModelId {
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LanguageModelId::from(self.model.id().to_string())
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}
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fn name(&self) -> LanguageModelName {
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LanguageModelName::from(self.model.display_name().to_string())
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}
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fn provider_id(&self) -> LanguageModelProviderId {
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PROVIDER_ID
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}
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fn provider_name(&self) -> LanguageModelProviderName {
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PROVIDER_NAME
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}
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fn supports_tools(&self) -> bool {
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self.model.supports_tools()
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}
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fn supports_images(&self) -> bool {
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self.model.supports_vision()
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}
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fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
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match self.model.vendor() {
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ModelVendor::OpenAI | ModelVendor::Anthropic => {
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LanguageModelToolSchemaFormat::JsonSchema
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}
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ModelVendor::Google | ModelVendor::XAI | ModelVendor::Unknown => {
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LanguageModelToolSchemaFormat::JsonSchemaSubset
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}
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}
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}
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fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
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match choice {
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LanguageModelToolChoice::Auto
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| LanguageModelToolChoice::Any
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| LanguageModelToolChoice::None => self.supports_tools(),
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}
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}
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fn telemetry_id(&self) -> String {
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format!("copilot_chat/{}", self.model.id())
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}
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fn max_token_count(&self) -> u64 {
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self.model.max_token_count()
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}
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fn count_tokens(
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&self,
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request: LanguageModelRequest,
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cx: &App,
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) -> BoxFuture<'static, Result<u64>> {
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let model = self.model.clone();
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cx.background_spawn(async move {
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let messages = collect_tiktoken_messages(request);
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// Copilot uses OpenAI tiktoken tokenizer for all it's model irrespective of the underlying provider(vendor).
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let tokenizer_model = match model.tokenizer() {
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Some("o200k_base") => "gpt-4o",
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Some("cl100k_base") => "gpt-4",
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_ => "gpt-4o",
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};
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tiktoken_rs::num_tokens_from_messages(tokenizer_model, &messages)
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.map(|tokens| tokens as u64)
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})
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.boxed()
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}
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fn stream_completion(
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&self,
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request: LanguageModelRequest,
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cx: &AsyncApp,
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) -> BoxFuture<
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'static,
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Result<
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BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
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LanguageModelCompletionError,
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>,
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> {
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let is_user_initiated = request.intent.is_none_or(|intent| match intent {
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CompletionIntent::UserPrompt
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| CompletionIntent::ThreadContextSummarization
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| CompletionIntent::InlineAssist
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| CompletionIntent::TerminalInlineAssist
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| CompletionIntent::GenerateGitCommitMessage => true,
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CompletionIntent::ToolResults
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| CompletionIntent::ThreadSummarization
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| CompletionIntent::CreateFile
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| CompletionIntent::EditFile => false,
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});
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if self.model.supports_response() {
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let responses_request = into_copilot_responses(&self.model, request);
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let request_limiter = self.request_limiter.clone();
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let future = cx.spawn(async move |cx| {
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let request =
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CopilotChat::stream_response(responses_request, is_user_initiated, cx.clone());
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request_limiter
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.stream(async move {
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let stream = request.await?;
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let mapper = CopilotResponsesEventMapper::new();
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Ok(mapper.map_stream(stream).boxed())
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})
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.await
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});
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return async move { Ok(future.await?.boxed()) }.boxed();
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}
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let copilot_request = match into_copilot_chat(&self.model, request) {
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Ok(request) => request,
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Err(err) => return futures::future::ready(Err(err.into())).boxed(),
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};
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let is_streaming = copilot_request.stream;
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let request_limiter = self.request_limiter.clone();
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let future = cx.spawn(async move |cx| {
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let request =
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CopilotChat::stream_completion(copilot_request, is_user_initiated, cx.clone());
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request_limiter
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.stream(async move {
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let response = request.await?;
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Ok(map_to_language_model_completion_events(
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response,
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is_streaming,
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))
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})
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.await
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});
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async move { Ok(future.await?.boxed()) }.boxed()
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}
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}
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pub fn map_to_language_model_completion_events(
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events: Pin<Box<dyn Send + Stream<Item = Result<ResponseEvent>>>>,
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is_streaming: bool,
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) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
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#[derive(Default)]
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struct RawToolCall {
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id: String,
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name: String,
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arguments: String,
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}
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struct State {
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events: Pin<Box<dyn Send + Stream<Item = Result<ResponseEvent>>>>,
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tool_calls_by_index: HashMap<usize, RawToolCall>,
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}
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futures::stream::unfold(
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State {
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events,
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tool_calls_by_index: HashMap::default(),
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},
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move |mut state| async move {
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if let Some(event) = state.events.next().await {
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match event {
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Ok(event) => {
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let Some(choice) = event.choices.first() else {
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return Some((
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vec![Err(anyhow!("Response contained no choices").into())],
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state,
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));
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};
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let delta = if is_streaming {
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choice.delta.as_ref()
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} else {
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choice.message.as_ref()
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};
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let Some(delta) = delta else {
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return Some((
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vec![Err(anyhow!("Response contained no delta").into())],
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state,
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));
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};
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let mut events = Vec::new();
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if let Some(content) = delta.content.clone() {
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events.push(Ok(LanguageModelCompletionEvent::Text(content)));
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}
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for (index, tool_call) in delta.tool_calls.iter().enumerate() {
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let tool_index = tool_call.index.unwrap_or(index);
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let entry = state.tool_calls_by_index.entry(tool_index).or_default();
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if let Some(tool_id) = tool_call.id.clone() {
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entry.id = tool_id;
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}
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if let Some(function) = tool_call.function.as_ref() {
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if let Some(name) = function.name.clone() {
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entry.name = name;
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}
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if let Some(arguments) = function.arguments.clone() {
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entry.arguments.push_str(&arguments);
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}
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}
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}
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if let Some(usage) = event.usage {
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events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(
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TokenUsage {
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input_tokens: usage.prompt_tokens,
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output_tokens: usage.completion_tokens,
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cache_creation_input_tokens: 0,
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cache_read_input_tokens: 0,
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},
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)));
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}
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match choice.finish_reason.as_deref() {
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Some("stop") => {
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events.push(Ok(LanguageModelCompletionEvent::Stop(
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StopReason::EndTurn,
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)));
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}
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Some("tool_calls") => {
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events.extend(state.tool_calls_by_index.drain().map(
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|(_, tool_call)| {
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// The model can output an empty string
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// to indicate the absence of arguments.
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// When that happens, create an empty
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// object instead.
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let arguments = if tool_call.arguments.is_empty() {
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Ok(serde_json::Value::Object(Default::default()))
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} else {
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serde_json::Value::from_str(&tool_call.arguments)
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};
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match arguments {
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Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
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LanguageModelToolUse {
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id: tool_call.id.into(),
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name: tool_call.name.as_str().into(),
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is_input_complete: true,
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input,
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raw_input: tool_call.arguments,
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thought_signature: None,
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},
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)),
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Err(error) => Ok(
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LanguageModelCompletionEvent::ToolUseJsonParseError {
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id: tool_call.id.into(),
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tool_name: tool_call.name.as_str().into(),
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raw_input: tool_call.arguments.into(),
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json_parse_error: error.to_string(),
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},
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),
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}
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},
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));
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|
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events.push(Ok(LanguageModelCompletionEvent::Stop(
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StopReason::ToolUse,
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)));
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}
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Some(stop_reason) => {
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log::error!("Unexpected Copilot Chat stop_reason: {stop_reason:?}");
|
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events.push(Ok(LanguageModelCompletionEvent::Stop(
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StopReason::EndTurn,
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)));
|
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}
|
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None => {}
|
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}
|
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|
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return Some((events, state));
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}
|
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Err(err) => return Some((vec![Err(anyhow!(err).into())], state)),
|
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}
|
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}
|
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|
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None
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},
|
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)
|
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.flat_map(futures::stream::iter)
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}
|
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|
|
pub struct CopilotResponsesEventMapper {
|
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pending_stop_reason: Option<StopReason>,
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}
|
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|
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impl CopilotResponsesEventMapper {
|
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pub fn new() -> Self {
|
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Self {
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pending_stop_reason: None,
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}
|
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}
|
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|
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pub fn map_stream(
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mut self,
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events: Pin<Box<dyn Send + Stream<Item = Result<copilot::copilot_responses::StreamEvent>>>>,
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) -> impl Stream<Item = Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>
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{
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events.flat_map(move |event| {
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futures::stream::iter(match event {
|
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Ok(event) => self.map_event(event),
|
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Err(error) => vec![Err(LanguageModelCompletionError::from(anyhow!(error)))],
|
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})
|
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})
|
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}
|
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|
|
fn map_event(
|
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&mut self,
|
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event: copilot::copilot_responses::StreamEvent,
|
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) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
|
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match event {
|
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copilot::copilot_responses::StreamEvent::OutputItemAdded { item, .. } => match item {
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copilot::copilot_responses::ResponseOutputItem::Message { id, .. } => {
|
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vec![Ok(LanguageModelCompletionEvent::StartMessage {
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message_id: id,
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|
})]
|
|
}
|
|
_ => Vec::new(),
|
|
},
|
|
|
|
copilot::copilot_responses::StreamEvent::OutputTextDelta { delta, .. } => {
|
|
if delta.is_empty() {
|
|
Vec::new()
|
|
} else {
|
|
vec![Ok(LanguageModelCompletionEvent::Text(delta))]
|
|
}
|
|
}
|
|
|
|
copilot::copilot_responses::StreamEvent::OutputItemDone { item, .. } => match item {
|
|
copilot::copilot_responses::ResponseOutputItem::Message { .. } => Vec::new(),
|
|
copilot::copilot_responses::ResponseOutputItem::FunctionCall {
|
|
call_id,
|
|
name,
|
|
arguments,
|
|
..
|
|
} => {
|
|
let mut events = Vec::new();
|
|
match serde_json::from_str::<serde_json::Value>(&arguments) {
|
|
Ok(input) => events.push(Ok(LanguageModelCompletionEvent::ToolUse(
|
|
LanguageModelToolUse {
|
|
id: call_id.into(),
|
|
name: name.as_str().into(),
|
|
is_input_complete: true,
|
|
input,
|
|
raw_input: arguments.clone(),
|
|
thought_signature: None,
|
|
},
|
|
))),
|
|
Err(error) => {
|
|
events.push(Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
|
|
id: call_id.into(),
|
|
tool_name: name.as_str().into(),
|
|
raw_input: arguments.clone().into(),
|
|
json_parse_error: error.to_string(),
|
|
}))
|
|
}
|
|
}
|
|
// Record that we already emitted a tool-use stop so we can avoid duplicating
|
|
// a Stop event on Completed.
|
|
self.pending_stop_reason = Some(StopReason::ToolUse);
|
|
events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
|
|
events
|
|
}
|
|
copilot::copilot_responses::ResponseOutputItem::Reasoning {
|
|
summary,
|
|
encrypted_content,
|
|
..
|
|
} => {
|
|
let mut events = Vec::new();
|
|
|
|
if let Some(blocks) = summary {
|
|
let mut text = String::new();
|
|
for block in blocks {
|
|
text.push_str(&block.text);
|
|
}
|
|
if !text.is_empty() {
|
|
events.push(Ok(LanguageModelCompletionEvent::Thinking {
|
|
text,
|
|
signature: None,
|
|
}));
|
|
}
|
|
}
|
|
|
|
if let Some(data) = encrypted_content {
|
|
events.push(Ok(LanguageModelCompletionEvent::RedactedThinking { data }));
|
|
}
|
|
|
|
events
|
|
}
|
|
},
|
|
|
|
copilot::copilot_responses::StreamEvent::Completed { response } => {
|
|
let mut events = Vec::new();
|
|
if let Some(usage) = response.usage {
|
|
events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
|
|
input_tokens: usage.input_tokens.unwrap_or(0),
|
|
output_tokens: usage.output_tokens.unwrap_or(0),
|
|
cache_creation_input_tokens: 0,
|
|
cache_read_input_tokens: 0,
|
|
})));
|
|
}
|
|
if self.pending_stop_reason.take() != Some(StopReason::ToolUse) {
|
|
events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
|
|
}
|
|
events
|
|
}
|
|
|
|
copilot::copilot_responses::StreamEvent::Incomplete { response } => {
|
|
let reason = response
|
|
.incomplete_details
|
|
.as_ref()
|
|
.and_then(|details| details.reason.as_ref());
|
|
let stop_reason = match reason {
|
|
Some(copilot::copilot_responses::IncompleteReason::MaxOutputTokens) => {
|
|
StopReason::MaxTokens
|
|
}
|
|
Some(copilot::copilot_responses::IncompleteReason::ContentFilter) => {
|
|
StopReason::Refusal
|
|
}
|
|
_ => self
|
|
.pending_stop_reason
|
|
.take()
|
|
.unwrap_or(StopReason::EndTurn),
|
|
};
|
|
|
|
let mut events = Vec::new();
|
|
if let Some(usage) = response.usage {
|
|
events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
|
|
input_tokens: usage.input_tokens.unwrap_or(0),
|
|
output_tokens: usage.output_tokens.unwrap_or(0),
|
|
cache_creation_input_tokens: 0,
|
|
cache_read_input_tokens: 0,
|
|
})));
|
|
}
|
|
events.push(Ok(LanguageModelCompletionEvent::Stop(stop_reason)));
|
|
events
|
|
}
|
|
|
|
copilot::copilot_responses::StreamEvent::Failed { response } => {
|
|
let provider = PROVIDER_NAME;
|
|
let (status_code, message) = match response.error {
|
|
Some(error) => {
|
|
let status_code = StatusCode::from_str(&error.code)
|
|
.unwrap_or(StatusCode::INTERNAL_SERVER_ERROR);
|
|
(status_code, error.message)
|
|
}
|
|
None => (
|
|
StatusCode::INTERNAL_SERVER_ERROR,
|
|
"response.failed".to_string(),
|
|
),
|
|
};
|
|
vec![Err(LanguageModelCompletionError::HttpResponseError {
|
|
provider,
|
|
status_code,
|
|
message,
|
|
})]
|
|
}
|
|
|
|
copilot::copilot_responses::StreamEvent::GenericError { error } => vec![Err(
|
|
LanguageModelCompletionError::Other(anyhow!(format!("{error:?}"))),
|
|
)],
|
|
|
|
copilot::copilot_responses::StreamEvent::Created { .. }
|
|
| copilot::copilot_responses::StreamEvent::Unknown => Vec::new(),
|
|
}
|
|
}
|
|
}
|
|
|
|
fn into_copilot_chat(
|
|
model: &copilot::copilot_chat::Model,
|
|
request: LanguageModelRequest,
|
|
) -> Result<CopilotChatRequest> {
|
|
let mut request_messages: Vec<LanguageModelRequestMessage> = Vec::new();
|
|
for message in request.messages {
|
|
if let Some(last_message) = request_messages.last_mut() {
|
|
if last_message.role == message.role {
|
|
last_message.content.extend(message.content);
|
|
} else {
|
|
request_messages.push(message);
|
|
}
|
|
} else {
|
|
request_messages.push(message);
|
|
}
|
|
}
|
|
|
|
let mut messages: Vec<ChatMessage> = Vec::new();
|
|
for message in request_messages {
|
|
match message.role {
|
|
Role::User => {
|
|
for content in &message.content {
|
|
if let MessageContent::ToolResult(tool_result) = content {
|
|
let content = match &tool_result.content {
|
|
LanguageModelToolResultContent::Text(text) => text.to_string().into(),
|
|
LanguageModelToolResultContent::Image(image) => {
|
|
if model.supports_vision() {
|
|
ChatMessageContent::Multipart(vec![ChatMessagePart::Image {
|
|
image_url: ImageUrl {
|
|
url: image.to_base64_url(),
|
|
},
|
|
}])
|
|
} else {
|
|
debug_panic!(
|
|
"This should be caught at {} level",
|
|
tool_result.tool_name
|
|
);
|
|
"[Tool responded with an image, but this model does not support vision]".to_string().into()
|
|
}
|
|
}
|
|
};
|
|
|
|
messages.push(ChatMessage::Tool {
|
|
tool_call_id: tool_result.tool_use_id.to_string(),
|
|
content,
|
|
});
|
|
}
|
|
}
|
|
|
|
let mut content_parts = Vec::new();
|
|
for content in &message.content {
|
|
match content {
|
|
MessageContent::Text(text) | MessageContent::Thinking { text, .. }
|
|
if !text.is_empty() =>
|
|
{
|
|
if let Some(ChatMessagePart::Text { text: text_content }) =
|
|
content_parts.last_mut()
|
|
{
|
|
text_content.push_str(text);
|
|
} else {
|
|
content_parts.push(ChatMessagePart::Text {
|
|
text: text.to_string(),
|
|
});
|
|
}
|
|
}
|
|
MessageContent::Image(image) if model.supports_vision() => {
|
|
content_parts.push(ChatMessagePart::Image {
|
|
image_url: ImageUrl {
|
|
url: image.to_base64_url(),
|
|
},
|
|
});
|
|
}
|
|
_ => {}
|
|
}
|
|
}
|
|
|
|
if !content_parts.is_empty() {
|
|
messages.push(ChatMessage::User {
|
|
content: content_parts.into(),
|
|
});
|
|
}
|
|
}
|
|
Role::Assistant => {
|
|
let mut tool_calls = Vec::new();
|
|
for content in &message.content {
|
|
if let MessageContent::ToolUse(tool_use) = content {
|
|
tool_calls.push(ToolCall {
|
|
id: tool_use.id.to_string(),
|
|
content: copilot::copilot_chat::ToolCallContent::Function {
|
|
function: copilot::copilot_chat::FunctionContent {
|
|
name: tool_use.name.to_string(),
|
|
arguments: serde_json::to_string(&tool_use.input)?,
|
|
},
|
|
},
|
|
});
|
|
}
|
|
}
|
|
|
|
let text_content = {
|
|
let mut buffer = String::new();
|
|
for string in message.content.iter().filter_map(|content| match content {
|
|
MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
|
|
Some(text.as_str())
|
|
}
|
|
MessageContent::ToolUse(_)
|
|
| MessageContent::RedactedThinking(_)
|
|
| MessageContent::ToolResult(_)
|
|
| MessageContent::Image(_) => None,
|
|
}) {
|
|
buffer.push_str(string);
|
|
}
|
|
|
|
buffer
|
|
};
|
|
|
|
messages.push(ChatMessage::Assistant {
|
|
content: if text_content.is_empty() {
|
|
ChatMessageContent::empty()
|
|
} else {
|
|
text_content.into()
|
|
},
|
|
tool_calls,
|
|
});
|
|
}
|
|
Role::System => messages.push(ChatMessage::System {
|
|
content: message.string_contents(),
|
|
}),
|
|
}
|
|
}
|
|
|
|
let tools = request
|
|
.tools
|
|
.iter()
|
|
.map(|tool| Tool::Function {
|
|
function: copilot::copilot_chat::Function {
|
|
name: tool.name.clone(),
|
|
description: tool.description.clone(),
|
|
parameters: tool.input_schema.clone(),
|
|
},
|
|
})
|
|
.collect::<Vec<_>>();
|
|
|
|
Ok(CopilotChatRequest {
|
|
intent: true,
|
|
n: 1,
|
|
stream: model.uses_streaming(),
|
|
temperature: 0.1,
|
|
model: model.id().to_string(),
|
|
messages,
|
|
tools,
|
|
tool_choice: request.tool_choice.map(|choice| match choice {
|
|
LanguageModelToolChoice::Auto => copilot::copilot_chat::ToolChoice::Auto,
|
|
LanguageModelToolChoice::Any => copilot::copilot_chat::ToolChoice::Any,
|
|
LanguageModelToolChoice::None => copilot::copilot_chat::ToolChoice::None,
|
|
}),
|
|
})
|
|
}
|
|
|
|
fn into_copilot_responses(
|
|
model: &copilot::copilot_chat::Model,
|
|
request: LanguageModelRequest,
|
|
) -> copilot::copilot_responses::Request {
|
|
use copilot::copilot_responses as responses;
|
|
|
|
let LanguageModelRequest {
|
|
thread_id: _,
|
|
prompt_id: _,
|
|
intent: _,
|
|
mode: _,
|
|
messages,
|
|
tools,
|
|
tool_choice,
|
|
stop: _,
|
|
temperature,
|
|
thinking_allowed: _,
|
|
} = request;
|
|
|
|
let mut input_items: Vec<responses::ResponseInputItem> = Vec::new();
|
|
|
|
for message in messages {
|
|
match message.role {
|
|
Role::User => {
|
|
for content in &message.content {
|
|
if let MessageContent::ToolResult(tool_result) = content {
|
|
let output = if let Some(out) = &tool_result.output {
|
|
match out {
|
|
serde_json::Value::String(s) => {
|
|
responses::ResponseFunctionOutput::Text(s.clone())
|
|
}
|
|
serde_json::Value::Null => {
|
|
responses::ResponseFunctionOutput::Text(String::new())
|
|
}
|
|
other => responses::ResponseFunctionOutput::Text(other.to_string()),
|
|
}
|
|
} else {
|
|
match &tool_result.content {
|
|
LanguageModelToolResultContent::Text(text) => {
|
|
responses::ResponseFunctionOutput::Text(text.to_string())
|
|
}
|
|
LanguageModelToolResultContent::Image(image) => {
|
|
if model.supports_vision() {
|
|
responses::ResponseFunctionOutput::Content(vec![
|
|
responses::ResponseInputContent::InputImage {
|
|
image_url: Some(image.to_base64_url()),
|
|
detail: Default::default(),
|
|
},
|
|
])
|
|
} else {
|
|
debug_panic!(
|
|
"This should be caught at {} level",
|
|
tool_result.tool_name
|
|
);
|
|
responses::ResponseFunctionOutput::Text(
|
|
"[Tool responded with an image, but this model does not support vision]".into(),
|
|
)
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
input_items.push(responses::ResponseInputItem::FunctionCallOutput {
|
|
call_id: tool_result.tool_use_id.to_string(),
|
|
output,
|
|
status: None,
|
|
});
|
|
}
|
|
}
|
|
|
|
let mut parts: Vec<responses::ResponseInputContent> = Vec::new();
|
|
for content in &message.content {
|
|
match content {
|
|
MessageContent::Text(text) => {
|
|
parts.push(responses::ResponseInputContent::InputText {
|
|
text: text.clone(),
|
|
});
|
|
}
|
|
|
|
MessageContent::Image(image) => {
|
|
if model.supports_vision() {
|
|
parts.push(responses::ResponseInputContent::InputImage {
|
|
image_url: Some(image.to_base64_url()),
|
|
detail: Default::default(),
|
|
});
|
|
}
|
|
}
|
|
_ => {}
|
|
}
|
|
}
|
|
|
|
if !parts.is_empty() {
|
|
input_items.push(responses::ResponseInputItem::Message {
|
|
role: "user".into(),
|
|
content: Some(parts),
|
|
status: None,
|
|
});
|
|
}
|
|
}
|
|
|
|
Role::Assistant => {
|
|
for content in &message.content {
|
|
if let MessageContent::ToolUse(tool_use) = content {
|
|
input_items.push(responses::ResponseInputItem::FunctionCall {
|
|
call_id: tool_use.id.to_string(),
|
|
name: tool_use.name.to_string(),
|
|
arguments: tool_use.raw_input.clone(),
|
|
status: None,
|
|
});
|
|
}
|
|
}
|
|
|
|
for content in &message.content {
|
|
if let MessageContent::RedactedThinking(data) = content {
|
|
input_items.push(responses::ResponseInputItem::Reasoning {
|
|
id: None,
|
|
summary: Vec::new(),
|
|
encrypted_content: data.clone(),
|
|
});
|
|
}
|
|
}
|
|
|
|
let mut parts: Vec<responses::ResponseInputContent> = Vec::new();
|
|
for content in &message.content {
|
|
match content {
|
|
MessageContent::Text(text) => {
|
|
parts.push(responses::ResponseInputContent::OutputText {
|
|
text: text.clone(),
|
|
});
|
|
}
|
|
MessageContent::Image(_) => {
|
|
parts.push(responses::ResponseInputContent::OutputText {
|
|
text: "[image omitted]".to_string(),
|
|
});
|
|
}
|
|
_ => {}
|
|
}
|
|
}
|
|
|
|
if !parts.is_empty() {
|
|
input_items.push(responses::ResponseInputItem::Message {
|
|
role: "assistant".into(),
|
|
content: Some(parts),
|
|
status: Some("completed".into()),
|
|
});
|
|
}
|
|
}
|
|
|
|
Role::System => {
|
|
let mut parts: Vec<responses::ResponseInputContent> = Vec::new();
|
|
for content in &message.content {
|
|
if let MessageContent::Text(text) = content {
|
|
parts.push(responses::ResponseInputContent::InputText {
|
|
text: text.clone(),
|
|
});
|
|
}
|
|
}
|
|
|
|
if !parts.is_empty() {
|
|
input_items.push(responses::ResponseInputItem::Message {
|
|
role: "system".into(),
|
|
content: Some(parts),
|
|
status: None,
|
|
});
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
let converted_tools: Vec<responses::ToolDefinition> = tools
|
|
.into_iter()
|
|
.map(|tool| responses::ToolDefinition::Function {
|
|
name: tool.name,
|
|
description: Some(tool.description),
|
|
parameters: Some(tool.input_schema),
|
|
strict: None,
|
|
})
|
|
.collect();
|
|
|
|
let mapped_tool_choice = tool_choice.map(|choice| match choice {
|
|
LanguageModelToolChoice::Auto => responses::ToolChoice::Auto,
|
|
LanguageModelToolChoice::Any => responses::ToolChoice::Any,
|
|
LanguageModelToolChoice::None => responses::ToolChoice::None,
|
|
});
|
|
|
|
responses::Request {
|
|
model: model.id().to_string(),
|
|
input: input_items,
|
|
stream: model.uses_streaming(),
|
|
temperature,
|
|
tools: converted_tools,
|
|
tool_choice: mapped_tool_choice,
|
|
reasoning: None, // We would need to add support for setting from user settings.
|
|
include: Some(vec![
|
|
copilot::copilot_responses::ResponseIncludable::ReasoningEncryptedContent,
|
|
]),
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
use copilot::copilot_responses as responses;
|
|
use futures::StreamExt;
|
|
|
|
fn map_events(events: Vec<responses::StreamEvent>) -> Vec<LanguageModelCompletionEvent> {
|
|
futures::executor::block_on(async {
|
|
CopilotResponsesEventMapper::new()
|
|
.map_stream(Box::pin(futures::stream::iter(events.into_iter().map(Ok))))
|
|
.collect::<Vec<_>>()
|
|
.await
|
|
.into_iter()
|
|
.map(Result::unwrap)
|
|
.collect()
|
|
})
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_maps_text_and_usage() {
|
|
let events = vec![
|
|
responses::StreamEvent::OutputItemAdded {
|
|
output_index: 0,
|
|
sequence_number: None,
|
|
item: responses::ResponseOutputItem::Message {
|
|
id: "msg_1".into(),
|
|
role: "assistant".into(),
|
|
content: Some(Vec::new()),
|
|
},
|
|
},
|
|
responses::StreamEvent::OutputTextDelta {
|
|
item_id: "msg_1".into(),
|
|
output_index: 0,
|
|
delta: "Hello".into(),
|
|
},
|
|
responses::StreamEvent::Completed {
|
|
response: responses::Response {
|
|
usage: Some(responses::ResponseUsage {
|
|
input_tokens: Some(5),
|
|
output_tokens: Some(3),
|
|
total_tokens: Some(8),
|
|
}),
|
|
..Default::default()
|
|
},
|
|
},
|
|
];
|
|
|
|
let mapped = map_events(events);
|
|
assert!(matches!(
|
|
mapped[0],
|
|
LanguageModelCompletionEvent::StartMessage { ref message_id } if message_id == "msg_1"
|
|
));
|
|
assert!(matches!(
|
|
mapped[1],
|
|
LanguageModelCompletionEvent::Text(ref text) if text == "Hello"
|
|
));
|
|
assert!(matches!(
|
|
mapped[2],
|
|
LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
|
|
input_tokens: 5,
|
|
output_tokens: 3,
|
|
..
|
|
})
|
|
));
|
|
assert!(matches!(
|
|
mapped[3],
|
|
LanguageModelCompletionEvent::Stop(StopReason::EndTurn)
|
|
));
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_maps_tool_calls() {
|
|
let events = vec![responses::StreamEvent::OutputItemDone {
|
|
output_index: 0,
|
|
sequence_number: None,
|
|
item: responses::ResponseOutputItem::FunctionCall {
|
|
id: Some("fn_1".into()),
|
|
call_id: "call_1".into(),
|
|
name: "do_it".into(),
|
|
arguments: "{\"x\":1}".into(),
|
|
status: None,
|
|
},
|
|
}];
|
|
|
|
let mapped = map_events(events);
|
|
assert!(matches!(
|
|
mapped[0],
|
|
LanguageModelCompletionEvent::ToolUse(ref use_) if use_.id.to_string() == "call_1" && use_.name.as_ref() == "do_it"
|
|
));
|
|
assert!(matches!(
|
|
mapped[1],
|
|
LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
|
|
));
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_handles_json_parse_error() {
|
|
let events = vec![responses::StreamEvent::OutputItemDone {
|
|
output_index: 0,
|
|
sequence_number: None,
|
|
item: responses::ResponseOutputItem::FunctionCall {
|
|
id: Some("fn_1".into()),
|
|
call_id: "call_1".into(),
|
|
name: "do_it".into(),
|
|
arguments: "{not json}".into(),
|
|
status: None,
|
|
},
|
|
}];
|
|
|
|
let mapped = map_events(events);
|
|
assert!(matches!(
|
|
mapped[0],
|
|
LanguageModelCompletionEvent::ToolUseJsonParseError { ref id, ref tool_name, .. }
|
|
if id.to_string() == "call_1" && tool_name.as_ref() == "do_it"
|
|
));
|
|
assert!(matches!(
|
|
mapped[1],
|
|
LanguageModelCompletionEvent::Stop(StopReason::ToolUse)
|
|
));
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_maps_reasoning_summary_and_encrypted_content() {
|
|
let events = vec![responses::StreamEvent::OutputItemDone {
|
|
output_index: 0,
|
|
sequence_number: None,
|
|
item: responses::ResponseOutputItem::Reasoning {
|
|
id: "r1".into(),
|
|
summary: Some(vec![responses::ResponseReasoningItem {
|
|
kind: "summary_text".into(),
|
|
text: "Chain".into(),
|
|
}]),
|
|
encrypted_content: Some("ENC".into()),
|
|
},
|
|
}];
|
|
|
|
let mapped = map_events(events);
|
|
assert!(matches!(
|
|
mapped[0],
|
|
LanguageModelCompletionEvent::Thinking { ref text, signature: None } if text == "Chain"
|
|
));
|
|
assert!(matches!(
|
|
mapped[1],
|
|
LanguageModelCompletionEvent::RedactedThinking { ref data } if data == "ENC"
|
|
));
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_handles_incomplete_max_tokens() {
|
|
let events = vec![responses::StreamEvent::Incomplete {
|
|
response: responses::Response {
|
|
usage: Some(responses::ResponseUsage {
|
|
input_tokens: Some(10),
|
|
output_tokens: Some(0),
|
|
total_tokens: Some(10),
|
|
}),
|
|
incomplete_details: Some(responses::IncompleteDetails {
|
|
reason: Some(responses::IncompleteReason::MaxOutputTokens),
|
|
}),
|
|
..Default::default()
|
|
},
|
|
}];
|
|
|
|
let mapped = map_events(events);
|
|
assert!(matches!(
|
|
mapped[0],
|
|
LanguageModelCompletionEvent::UsageUpdate(TokenUsage {
|
|
input_tokens: 10,
|
|
output_tokens: 0,
|
|
..
|
|
})
|
|
));
|
|
assert!(matches!(
|
|
mapped[1],
|
|
LanguageModelCompletionEvent::Stop(StopReason::MaxTokens)
|
|
));
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_handles_incomplete_content_filter() {
|
|
let events = vec![responses::StreamEvent::Incomplete {
|
|
response: responses::Response {
|
|
usage: None,
|
|
incomplete_details: Some(responses::IncompleteDetails {
|
|
reason: Some(responses::IncompleteReason::ContentFilter),
|
|
}),
|
|
..Default::default()
|
|
},
|
|
}];
|
|
|
|
let mapped = map_events(events);
|
|
assert!(matches!(
|
|
mapped.last().unwrap(),
|
|
LanguageModelCompletionEvent::Stop(StopReason::Refusal)
|
|
));
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_completed_no_duplicate_after_tool_use() {
|
|
let events = vec![
|
|
responses::StreamEvent::OutputItemDone {
|
|
output_index: 0,
|
|
sequence_number: None,
|
|
item: responses::ResponseOutputItem::FunctionCall {
|
|
id: Some("fn_1".into()),
|
|
call_id: "call_1".into(),
|
|
name: "do_it".into(),
|
|
arguments: "{}".into(),
|
|
status: None,
|
|
},
|
|
},
|
|
responses::StreamEvent::Completed {
|
|
response: responses::Response::default(),
|
|
},
|
|
];
|
|
|
|
let mapped = map_events(events);
|
|
|
|
let mut stop_count = 0usize;
|
|
let mut saw_tool_use_stop = false;
|
|
for event in mapped {
|
|
if let LanguageModelCompletionEvent::Stop(reason) = event {
|
|
stop_count += 1;
|
|
if matches!(reason, StopReason::ToolUse) {
|
|
saw_tool_use_stop = true;
|
|
}
|
|
}
|
|
}
|
|
assert_eq!(stop_count, 1, "should emit exactly one Stop event");
|
|
assert!(saw_tool_use_stop, "Stop reason should be ToolUse");
|
|
}
|
|
|
|
#[test]
|
|
fn responses_stream_failed_maps_http_response_error() {
|
|
let events = vec![responses::StreamEvent::Failed {
|
|
response: responses::Response {
|
|
error: Some(responses::ResponseError {
|
|
code: "429".into(),
|
|
message: "too many requests".into(),
|
|
}),
|
|
..Default::default()
|
|
},
|
|
}];
|
|
|
|
let mapped_results = futures::executor::block_on(async {
|
|
CopilotResponsesEventMapper::new()
|
|
.map_stream(Box::pin(futures::stream::iter(events.into_iter().map(Ok))))
|
|
.collect::<Vec<_>>()
|
|
.await
|
|
});
|
|
|
|
assert_eq!(mapped_results.len(), 1);
|
|
match &mapped_results[0] {
|
|
Err(LanguageModelCompletionError::HttpResponseError {
|
|
status_code,
|
|
message,
|
|
..
|
|
}) => {
|
|
assert_eq!(*status_code, http_client::StatusCode::TOO_MANY_REQUESTS);
|
|
assert_eq!(message, "too many requests");
|
|
}
|
|
other => panic!("expected HttpResponseError, got {:?}", other),
|
|
}
|
|
}
|
|
}
|
|
struct ConfigurationView {
|
|
copilot_status: Option<copilot::Status>,
|
|
state: Entity<State>,
|
|
_subscription: Option<Subscription>,
|
|
}
|
|
|
|
impl ConfigurationView {
|
|
pub fn new(state: Entity<State>, cx: &mut Context<Self>) -> Self {
|
|
let copilot = Copilot::global(cx);
|
|
|
|
Self {
|
|
copilot_status: copilot.as_ref().map(|copilot| copilot.read(cx).status()),
|
|
state,
|
|
_subscription: copilot.as_ref().map(|copilot| {
|
|
cx.observe(copilot, |this, model, cx| {
|
|
this.copilot_status = Some(model.read(cx).status());
|
|
cx.notify();
|
|
})
|
|
}),
|
|
}
|
|
}
|
|
}
|
|
|
|
impl Render for ConfigurationView {
|
|
fn render(&mut self, _window: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
|
|
if self.state.read(cx).is_authenticated(cx) {
|
|
ConfiguredApiCard::new("Authorized")
|
|
.button_label("Sign Out")
|
|
.on_click(|_, window, cx| {
|
|
window.dispatch_action(copilot::SignOut.boxed_clone(), cx);
|
|
})
|
|
.into_any_element()
|
|
} else {
|
|
let loading_icon = Icon::new(IconName::ArrowCircle).with_rotate_animation(4);
|
|
|
|
const ERROR_LABEL: &str = "Copilot Chat requires an active GitHub Copilot subscription. Please ensure Copilot is configured and try again, or use a different Assistant provider.";
|
|
|
|
match &self.copilot_status {
|
|
Some(status) => match status {
|
|
Status::Starting { task: _ } => h_flex()
|
|
.gap_2()
|
|
.child(loading_icon)
|
|
.child(Label::new("Starting Copilot…"))
|
|
.into_any_element(),
|
|
Status::SigningIn { prompt: _ }
|
|
| Status::SignedOut {
|
|
awaiting_signing_in: true,
|
|
} => h_flex()
|
|
.gap_2()
|
|
.child(loading_icon)
|
|
.child(Label::new("Signing into Copilot…"))
|
|
.into_any_element(),
|
|
Status::Error(_) => {
|
|
const LABEL: &str = "Copilot had issues starting. Please try restarting it. If the issue persists, try reinstalling Copilot.";
|
|
v_flex()
|
|
.gap_6()
|
|
.child(Label::new(LABEL))
|
|
.child(svg().size_8().path(IconName::CopilotError.path()))
|
|
.into_any_element()
|
|
}
|
|
_ => {
|
|
const LABEL: &str = "To use Zed's agent with GitHub Copilot, you need to be logged in to GitHub. Note that your GitHub account must have an active Copilot Chat subscription.";
|
|
|
|
v_flex()
|
|
.gap_2()
|
|
.child(Label::new(LABEL))
|
|
.child(
|
|
Button::new("sign_in", "Sign in to use GitHub Copilot")
|
|
.full_width()
|
|
.style(ButtonStyle::Outlined)
|
|
.icon_color(Color::Muted)
|
|
.icon(IconName::Github)
|
|
.icon_position(IconPosition::Start)
|
|
.icon_size(IconSize::Small)
|
|
.on_click(|_, window, cx| {
|
|
copilot::initiate_sign_in(window, cx)
|
|
}),
|
|
)
|
|
.into_any_element()
|
|
}
|
|
},
|
|
None => v_flex()
|
|
.gap_6()
|
|
.child(Label::new(ERROR_LABEL))
|
|
.into_any_element(),
|
|
}
|
|
}
|
|
}
|
|
}
|