## Closes #43887 ## Release Notes: ### Problem DeepSeek's reasoning mode API requires `reasoning_content` to be included in assistant messages that precede tool calls. Without it, the API returns a 400 error: ``` Missing `reasoning_content` field in the assistant message at message index 2 ``` ### Added/Fixed/Improved - Add `reasoning_content` field to `RequestMessage::Assistant` in `crates/deepseek/src/deepseek.rs` - Accumulate thinking content from `MessageContent::Thinking` and attach it to the next assistant/tool-call message - Wire reasoning content through the language model provider in `crates/language_models/src/provider/deepseek.rs` ### Testing - Verified with DeepSeek Reasoner model using tool calls - Confirmed reasoning content is properly included in API requests Fixes tool-call errors when using DeepSeek's reasoning mode. --------- Co-authored-by: Ben Brandt <benjamin.j.brandt@gmail.com>
661 lines
22 KiB
Rust
661 lines
22 KiB
Rust
use anyhow::{Result, anyhow};
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use collections::{BTreeMap, HashMap};
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use deepseek::DEEPSEEK_API_URL;
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use futures::Stream;
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use futures::{FutureExt, StreamExt, future, future::BoxFuture, stream::BoxStream};
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use gpui::{AnyView, App, AsyncApp, Context, Entity, SharedString, Task, Window};
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use http_client::HttpClient;
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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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LanguageModelToolChoice, LanguageModelToolResultContent, LanguageModelToolUse, MessageContent,
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RateLimiter, Role, StopReason, TokenUsage,
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};
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pub use settings::DeepseekAvailableModel as AvailableModel;
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use settings::{Settings, SettingsStore};
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use std::pin::Pin;
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use std::str::FromStr;
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use std::sync::{Arc, LazyLock};
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use ui::{List, prelude::*};
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use ui_input::InputField;
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use util::ResultExt;
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use zed_env_vars::{EnvVar, env_var};
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use crate::ui::ConfiguredApiCard;
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use crate::{api_key::ApiKeyState, ui::InstructionListItem};
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const PROVIDER_ID: LanguageModelProviderId = LanguageModelProviderId::new("deepseek");
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const PROVIDER_NAME: LanguageModelProviderName = LanguageModelProviderName::new("DeepSeek");
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const API_KEY_ENV_VAR_NAME: &str = "DEEPSEEK_API_KEY";
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static API_KEY_ENV_VAR: LazyLock<EnvVar> = env_var!(API_KEY_ENV_VAR_NAME);
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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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#[derive(Default, Clone, Debug, PartialEq)]
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pub struct DeepSeekSettings {
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pub api_url: String,
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pub available_models: Vec<AvailableModel>,
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}
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pub struct DeepSeekLanguageModelProvider {
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http_client: Arc<dyn HttpClient>,
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state: Entity<State>,
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}
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pub struct State {
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api_key_state: ApiKeyState,
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}
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impl State {
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fn is_authenticated(&self) -> bool {
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self.api_key_state.has_key()
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}
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fn set_api_key(&mut self, api_key: Option<String>, cx: &mut Context<Self>) -> Task<Result<()>> {
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let api_url = DeepSeekLanguageModelProvider::api_url(cx);
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self.api_key_state
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.store(api_url, api_key, |this| &mut this.api_key_state, cx)
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}
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fn authenticate(&mut self, cx: &mut Context<Self>) -> Task<Result<(), AuthenticateError>> {
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let api_url = DeepSeekLanguageModelProvider::api_url(cx);
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self.api_key_state.load_if_needed(
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api_url,
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&API_KEY_ENV_VAR,
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|this| &mut this.api_key_state,
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cx,
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)
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}
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}
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impl DeepSeekLanguageModelProvider {
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pub fn new(http_client: Arc<dyn HttpClient>, cx: &mut App) -> Self {
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let state = cx.new(|cx| {
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cx.observe_global::<SettingsStore>(|this: &mut State, cx| {
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let api_url = Self::api_url(cx);
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this.api_key_state.handle_url_change(
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api_url,
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&API_KEY_ENV_VAR,
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|this| &mut this.api_key_state,
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cx,
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);
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cx.notify();
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})
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.detach();
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State {
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api_key_state: ApiKeyState::new(Self::api_url(cx)),
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}
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});
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Self { http_client, state }
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}
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fn create_language_model(&self, model: deepseek::Model) -> Arc<dyn LanguageModel> {
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Arc::new(DeepSeekLanguageModel {
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id: LanguageModelId::from(model.id().to_string()),
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model,
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state: self.state.clone(),
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http_client: self.http_client.clone(),
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request_limiter: RateLimiter::new(4),
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})
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}
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fn settings(cx: &App) -> &DeepSeekSettings {
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&crate::AllLanguageModelSettings::get_global(cx).deepseek
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}
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fn api_url(cx: &App) -> SharedString {
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let api_url = &Self::settings(cx).api_url;
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if api_url.is_empty() {
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DEEPSEEK_API_URL.into()
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} else {
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SharedString::new(api_url.as_str())
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}
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}
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}
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impl LanguageModelProviderState for DeepSeekLanguageModelProvider {
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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 DeepSeekLanguageModelProvider {
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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::AiDeepSeek
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}
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fn default_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
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Some(self.create_language_model(deepseek::Model::default()))
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}
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fn default_fast_model(&self, _cx: &App) -> Option<Arc<dyn LanguageModel>> {
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Some(self.create_language_model(deepseek::Model::default_fast()))
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}
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fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>> {
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let mut models = BTreeMap::default();
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models.insert("deepseek-chat", deepseek::Model::Chat);
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models.insert("deepseek-reasoner", deepseek::Model::Reasoner);
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for available_model in &Self::settings(cx).available_models {
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models.insert(
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&available_model.name,
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deepseek::Model::Custom {
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name: available_model.name.clone(),
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display_name: available_model.display_name.clone(),
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max_tokens: available_model.max_tokens,
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max_output_tokens: available_model.max_output_tokens,
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},
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);
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}
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models
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.into_values()
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.map(|model| self.create_language_model(model))
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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()
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}
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fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>> {
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self.state.update(cx, |state, cx| state.authenticate(cx))
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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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window: &mut Window,
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cx: &mut App,
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) -> AnyView {
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cx.new(|cx| ConfigurationView::new(self.state.clone(), window, cx))
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.into()
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}
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fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>> {
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self.state
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.update(cx, |state, cx| state.set_api_key(None, cx))
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}
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}
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pub struct DeepSeekLanguageModel {
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id: LanguageModelId,
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model: deepseek::Model,
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state: Entity<State>,
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http_client: Arc<dyn HttpClient>,
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request_limiter: RateLimiter,
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}
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impl DeepSeekLanguageModel {
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fn stream_completion(
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&self,
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request: deepseek::Request,
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cx: &AsyncApp,
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) -> BoxFuture<'static, Result<BoxStream<'static, Result<deepseek::StreamResponse>>>> {
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let http_client = self.http_client.clone();
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let Ok((api_key, api_url)) = self.state.read_with(cx, |state, cx| {
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let api_url = DeepSeekLanguageModelProvider::api_url(cx);
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(state.api_key_state.key(&api_url), api_url)
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}) else {
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return future::ready(Err(anyhow!("App state dropped"))).boxed();
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};
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let future = self.request_limiter.stream(async move {
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let Some(api_key) = api_key else {
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return Err(LanguageModelCompletionError::NoApiKey {
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provider: PROVIDER_NAME,
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});
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};
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let request =
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deepseek::stream_completion(http_client.as_ref(), &api_url, &api_key, request);
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let response = request.await?;
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Ok(response)
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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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impl LanguageModel for DeepSeekLanguageModel {
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fn id(&self) -> LanguageModelId {
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self.id.clone()
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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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true
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}
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fn supports_tool_choice(&self, _choice: LanguageModelToolChoice) -> bool {
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true
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}
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fn supports_images(&self) -> bool {
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false
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}
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fn telemetry_id(&self) -> String {
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format!("deepseek/{}", 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 max_output_tokens(&self) -> Option<u64> {
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self.model.max_output_tokens()
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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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cx.background_spawn(async move {
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let messages = 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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tiktoken_rs::num_tokens_from_messages("gpt-4", &messages).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 request = into_deepseek(request, &self.model, self.max_output_tokens());
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let stream = self.stream_completion(request, cx);
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async move {
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let mapper = DeepSeekEventMapper::new();
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Ok(mapper.map_stream(stream.await?).boxed())
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}
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.boxed()
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}
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}
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pub fn into_deepseek(
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request: LanguageModelRequest,
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model: &deepseek::Model,
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max_output_tokens: Option<u64>,
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) -> deepseek::Request {
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let is_reasoner = model == &deepseek::Model::Reasoner;
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let mut messages = Vec::new();
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let mut current_reasoning: Option<String> = None;
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for message in request.messages {
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for content in message.content {
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match content {
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MessageContent::Text(text) => messages.push(match message.role {
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Role::User => deepseek::RequestMessage::User { content: text },
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Role::Assistant => deepseek::RequestMessage::Assistant {
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content: Some(text),
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tool_calls: Vec::new(),
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reasoning_content: current_reasoning.take(),
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},
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Role::System => deepseek::RequestMessage::System { content: text },
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}),
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MessageContent::Thinking { text, .. } => {
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// Accumulate reasoning content for next assistant message
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current_reasoning.get_or_insert_default().push_str(&text);
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}
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MessageContent::RedactedThinking(_) => {}
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MessageContent::Image(_) => {}
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MessageContent::ToolUse(tool_use) => {
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let tool_call = deepseek::ToolCall {
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id: tool_use.id.to_string(),
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content: deepseek::ToolCallContent::Function {
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function: deepseek::FunctionContent {
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name: tool_use.name.to_string(),
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arguments: serde_json::to_string(&tool_use.input)
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.unwrap_or_default(),
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},
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},
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};
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if let Some(deepseek::RequestMessage::Assistant { tool_calls, .. }) =
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messages.last_mut()
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{
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tool_calls.push(tool_call);
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} else {
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messages.push(deepseek::RequestMessage::Assistant {
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content: None,
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tool_calls: vec![tool_call],
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reasoning_content: current_reasoning.take(),
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});
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}
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}
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MessageContent::ToolResult(tool_result) => {
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match &tool_result.content {
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LanguageModelToolResultContent::Text(text) => {
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messages.push(deepseek::RequestMessage::Tool {
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content: text.to_string(),
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tool_call_id: tool_result.tool_use_id.to_string(),
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});
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}
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LanguageModelToolResultContent::Image(_) => {}
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};
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}
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}
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}
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}
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deepseek::Request {
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model: model.id().to_string(),
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messages,
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stream: true,
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max_tokens: max_output_tokens,
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temperature: if is_reasoner {
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None
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} else {
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request.temperature
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},
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response_format: None,
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tools: request
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.tools
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.into_iter()
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.map(|tool| deepseek::ToolDefinition::Function {
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function: deepseek::FunctionDefinition {
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name: tool.name,
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description: Some(tool.description),
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parameters: Some(tool.input_schema),
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},
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})
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.collect(),
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}
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}
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pub struct DeepSeekEventMapper {
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tool_calls_by_index: HashMap<usize, RawToolCall>,
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}
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impl DeepSeekEventMapper {
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pub fn new() -> Self {
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Self {
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tool_calls_by_index: HashMap::default(),
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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<deepseek::StreamResponse>>>>,
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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(error))],
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})
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})
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}
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pub fn map_event(
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&mut self,
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event: deepseek::StreamResponse,
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) -> Vec<Result<LanguageModelCompletionEvent, LanguageModelCompletionError>> {
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let Some(choice) = event.choices.first() else {
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return vec![Err(LanguageModelCompletionError::from(anyhow!(
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"Response contained no choices"
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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) = choice.delta.content.clone() {
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events.push(Ok(LanguageModelCompletionEvent::Text(content)));
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}
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if let Some(reasoning_content) = choice.delta.reasoning_content.clone() {
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events.push(Ok(LanguageModelCompletionEvent::Thinking {
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text: reasoning_content,
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signature: None,
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}));
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}
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|
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if let Some(tool_calls) = choice.delta.tool_calls.as_ref() {
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for tool_call in tool_calls {
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let entry = self.tool_calls_by_index.entry(tool_call.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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|
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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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|
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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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}
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|
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if let Some(usage) = event.usage {
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events.push(Ok(LanguageModelCompletionEvent::UsageUpdate(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(StopReason::EndTurn)));
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}
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Some("tool_calls") => {
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events.extend(self.tool_calls_by_index.drain().map(|(_, tool_call)| {
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match serde_json::Value::from_str(&tool_call.arguments) {
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Ok(input) => Ok(LanguageModelCompletionEvent::ToolUse(
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LanguageModelToolUse {
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id: tool_call.id.clone().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.clone(),
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thought_signature: None,
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},
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)),
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Err(error) => Ok(LanguageModelCompletionEvent::ToolUseJsonParseError {
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id: tool_call.id.clone().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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|
|
events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::ToolUse)));
|
|
}
|
|
Some(stop_reason) => {
|
|
log::error!("Unexpected DeepSeek stop_reason: {stop_reason:?}",);
|
|
events.push(Ok(LanguageModelCompletionEvent::Stop(StopReason::EndTurn)));
|
|
}
|
|
None => {}
|
|
}
|
|
|
|
events
|
|
}
|
|
}
|
|
|
|
struct ConfigurationView {
|
|
api_key_editor: Entity<InputField>,
|
|
state: Entity<State>,
|
|
load_credentials_task: Option<Task<()>>,
|
|
}
|
|
|
|
impl ConfigurationView {
|
|
fn new(state: Entity<State>, window: &mut Window, cx: &mut Context<Self>) -> Self {
|
|
let api_key_editor =
|
|
cx.new(|cx| InputField::new(window, cx, "sk-00000000000000000000000000000000"));
|
|
|
|
cx.observe(&state, |_, _, cx| {
|
|
cx.notify();
|
|
})
|
|
.detach();
|
|
|
|
let load_credentials_task = Some(cx.spawn({
|
|
let state = state.clone();
|
|
async move |this, cx| {
|
|
if let Some(task) = state
|
|
.update(cx, |state, cx| state.authenticate(cx))
|
|
.log_err()
|
|
{
|
|
let _ = task.await;
|
|
}
|
|
|
|
this.update(cx, |this, cx| {
|
|
this.load_credentials_task = None;
|
|
cx.notify();
|
|
})
|
|
.log_err();
|
|
}
|
|
}));
|
|
|
|
Self {
|
|
api_key_editor,
|
|
state,
|
|
load_credentials_task,
|
|
}
|
|
}
|
|
|
|
fn save_api_key(&mut self, _: &menu::Confirm, _window: &mut Window, cx: &mut Context<Self>) {
|
|
let api_key = self.api_key_editor.read(cx).text(cx).trim().to_string();
|
|
if api_key.is_empty() {
|
|
return;
|
|
}
|
|
|
|
let state = self.state.clone();
|
|
cx.spawn(async move |_, cx| {
|
|
state
|
|
.update(cx, |state, cx| state.set_api_key(Some(api_key), cx))?
|
|
.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
}
|
|
|
|
fn reset_api_key(&mut self, window: &mut Window, cx: &mut Context<Self>) {
|
|
self.api_key_editor
|
|
.update(cx, |editor, cx| editor.set_text("", window, cx));
|
|
|
|
let state = self.state.clone();
|
|
cx.spawn(async move |_, cx| {
|
|
state
|
|
.update(cx, |state, cx| state.set_api_key(None, cx))?
|
|
.await
|
|
})
|
|
.detach_and_log_err(cx);
|
|
}
|
|
|
|
fn should_render_editor(&self, cx: &mut Context<Self>) -> bool {
|
|
!self.state.read(cx).is_authenticated()
|
|
}
|
|
}
|
|
|
|
impl Render for ConfigurationView {
|
|
fn render(&mut self, _window: &mut Window, cx: &mut Context<Self>) -> impl IntoElement {
|
|
let env_var_set = self.state.read(cx).api_key_state.is_from_env_var();
|
|
let configured_card_label = if env_var_set {
|
|
format!("API key set in {API_KEY_ENV_VAR_NAME} environment variable")
|
|
} else {
|
|
let api_url = DeepSeekLanguageModelProvider::api_url(cx);
|
|
if api_url == DEEPSEEK_API_URL {
|
|
"API key configured".to_string()
|
|
} else {
|
|
format!("API key configured for {}", api_url)
|
|
}
|
|
};
|
|
|
|
if self.load_credentials_task.is_some() {
|
|
div()
|
|
.child(Label::new("Loading credentials..."))
|
|
.into_any_element()
|
|
} else if self.should_render_editor(cx) {
|
|
v_flex()
|
|
.size_full()
|
|
.on_action(cx.listener(Self::save_api_key))
|
|
.child(Label::new("To use DeepSeek in Zed, you need an API key:"))
|
|
.child(
|
|
List::new()
|
|
.child(InstructionListItem::new(
|
|
"Get your API key from the",
|
|
Some("DeepSeek console"),
|
|
Some("https://platform.deepseek.com/api_keys"),
|
|
))
|
|
.child(InstructionListItem::text_only(
|
|
"Paste your API key below and hit enter to start using the assistant",
|
|
)),
|
|
)
|
|
.child(self.api_key_editor.clone())
|
|
.child(
|
|
Label::new(format!(
|
|
"Or set the {API_KEY_ENV_VAR_NAME} environment variable."
|
|
))
|
|
.size(LabelSize::Small)
|
|
.color(Color::Muted),
|
|
)
|
|
.into_any_element()
|
|
} else {
|
|
ConfiguredApiCard::new(configured_card_label)
|
|
.disabled(env_var_set)
|
|
.on_click(cx.listener(|this, _, window, cx| this.reset_api_key(window, cx)))
|
|
.into_any_element()
|
|
}
|
|
}
|
|
}
|