language_model.rs

  1mod model;
  2mod rate_limiter;
  3mod registry;
  4mod request;
  5mod role;
  6mod telemetry;
  7
  8#[cfg(any(test, feature = "test-support"))]
  9pub mod fake_provider;
 10
 11use anyhow::{Result, anyhow};
 12use client::Client;
 13use futures::FutureExt;
 14use futures::{StreamExt, future::BoxFuture, stream::BoxStream};
 15use gpui::{AnyElement, AnyView, App, AsyncApp, SharedString, Task, Window};
 16use http_client::http::{HeaderMap, HeaderValue};
 17use icons::IconName;
 18use parking_lot::Mutex;
 19use schemars::JsonSchema;
 20use serde::{Deserialize, Serialize, de::DeserializeOwned};
 21use std::fmt;
 22use std::ops::{Add, Sub};
 23use std::str::FromStr as _;
 24use std::sync::Arc;
 25use thiserror::Error;
 26use util::serde::is_default;
 27use zed_llm_client::{
 28    CompletionRequestStatus, MODEL_REQUESTS_USAGE_AMOUNT_HEADER_NAME,
 29    MODEL_REQUESTS_USAGE_LIMIT_HEADER_NAME, UsageLimit,
 30};
 31
 32pub use crate::model::*;
 33pub use crate::rate_limiter::*;
 34pub use crate::registry::*;
 35pub use crate::request::*;
 36pub use crate::role::*;
 37pub use crate::telemetry::*;
 38
 39pub const ZED_CLOUD_PROVIDER_ID: &str = "zed.dev";
 40
 41pub fn init(client: Arc<Client>, cx: &mut App) {
 42    init_settings(cx);
 43    RefreshLlmTokenListener::register(client.clone(), cx);
 44}
 45
 46pub fn init_settings(cx: &mut App) {
 47    registry::init(cx);
 48}
 49
 50/// Configuration for caching language model messages.
 51#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, JsonSchema)]
 52pub struct LanguageModelCacheConfiguration {
 53    pub max_cache_anchors: usize,
 54    pub should_speculate: bool,
 55    pub min_total_token: usize,
 56}
 57
 58/// A completion event from a language model.
 59#[derive(Debug, PartialEq, Clone, Serialize, Deserialize)]
 60pub enum LanguageModelCompletionEvent {
 61    StatusUpdate(CompletionRequestStatus),
 62    Stop(StopReason),
 63    Text(String),
 64    Thinking {
 65        text: String,
 66        signature: Option<String>,
 67    },
 68    ToolUse(LanguageModelToolUse),
 69    StartMessage {
 70        message_id: String,
 71    },
 72    UsageUpdate(TokenUsage),
 73}
 74
 75#[derive(Error, Debug)]
 76pub enum LanguageModelCompletionError {
 77    #[error("received bad input JSON")]
 78    BadInputJson {
 79        id: LanguageModelToolUseId,
 80        tool_name: Arc<str>,
 81        raw_input: Arc<str>,
 82        json_parse_error: String,
 83    },
 84    #[error(transparent)]
 85    Other(#[from] anyhow::Error),
 86}
 87
 88/// Indicates the format used to define the input schema for a language model tool.
 89#[derive(Debug, PartialEq, Eq, Clone, Copy, Hash)]
 90pub enum LanguageModelToolSchemaFormat {
 91    /// A JSON schema, see https://json-schema.org
 92    JsonSchema,
 93    /// A subset of an OpenAPI 3.0 schema object supported by Google AI, see https://ai.google.dev/api/caching#Schema
 94    JsonSchemaSubset,
 95}
 96
 97#[derive(Debug, PartialEq, Clone, Copy, Serialize, Deserialize)]
 98#[serde(rename_all = "snake_case")]
 99pub enum StopReason {
100    EndTurn,
101    MaxTokens,
102    ToolUse,
103    Refusal,
104}
105
106#[derive(Debug, Clone, Copy)]
107pub struct RequestUsage {
108    pub limit: UsageLimit,
109    pub amount: i32,
110}
111
112impl RequestUsage {
113    pub fn from_headers(headers: &HeaderMap<HeaderValue>) -> Result<Self> {
114        let limit = headers
115            .get(MODEL_REQUESTS_USAGE_LIMIT_HEADER_NAME)
116            .ok_or_else(|| anyhow!("missing {MODEL_REQUESTS_USAGE_LIMIT_HEADER_NAME:?} header"))?;
117        let limit = UsageLimit::from_str(limit.to_str()?)?;
118
119        let amount = headers
120            .get(MODEL_REQUESTS_USAGE_AMOUNT_HEADER_NAME)
121            .ok_or_else(|| anyhow!("missing {MODEL_REQUESTS_USAGE_AMOUNT_HEADER_NAME:?} header"))?;
122        let amount = amount.to_str()?.parse::<i32>()?;
123
124        Ok(Self { limit, amount })
125    }
126}
127
128#[derive(Debug, PartialEq, Clone, Copy, Serialize, Deserialize, Default)]
129pub struct TokenUsage {
130    #[serde(default, skip_serializing_if = "is_default")]
131    pub input_tokens: u32,
132    #[serde(default, skip_serializing_if = "is_default")]
133    pub output_tokens: u32,
134    #[serde(default, skip_serializing_if = "is_default")]
135    pub cache_creation_input_tokens: u32,
136    #[serde(default, skip_serializing_if = "is_default")]
137    pub cache_read_input_tokens: u32,
138}
139
140impl TokenUsage {
141    pub fn total_tokens(&self) -> u32 {
142        self.input_tokens
143            + self.output_tokens
144            + self.cache_read_input_tokens
145            + self.cache_creation_input_tokens
146    }
147}
148
149impl Add<TokenUsage> for TokenUsage {
150    type Output = Self;
151
152    fn add(self, other: Self) -> Self {
153        Self {
154            input_tokens: self.input_tokens + other.input_tokens,
155            output_tokens: self.output_tokens + other.output_tokens,
156            cache_creation_input_tokens: self.cache_creation_input_tokens
157                + other.cache_creation_input_tokens,
158            cache_read_input_tokens: self.cache_read_input_tokens + other.cache_read_input_tokens,
159        }
160    }
161}
162
163impl Sub<TokenUsage> for TokenUsage {
164    type Output = Self;
165
166    fn sub(self, other: Self) -> Self {
167        Self {
168            input_tokens: self.input_tokens - other.input_tokens,
169            output_tokens: self.output_tokens - other.output_tokens,
170            cache_creation_input_tokens: self.cache_creation_input_tokens
171                - other.cache_creation_input_tokens,
172            cache_read_input_tokens: self.cache_read_input_tokens - other.cache_read_input_tokens,
173        }
174    }
175}
176
177#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
178pub struct LanguageModelToolUseId(Arc<str>);
179
180impl fmt::Display for LanguageModelToolUseId {
181    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
182        write!(f, "{}", self.0)
183    }
184}
185
186impl<T> From<T> for LanguageModelToolUseId
187where
188    T: Into<Arc<str>>,
189{
190    fn from(value: T) -> Self {
191        Self(value.into())
192    }
193}
194
195#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
196pub struct LanguageModelToolUse {
197    pub id: LanguageModelToolUseId,
198    pub name: Arc<str>,
199    pub raw_input: String,
200    pub input: serde_json::Value,
201    pub is_input_complete: bool,
202}
203
204pub struct LanguageModelTextStream {
205    pub message_id: Option<String>,
206    pub stream: BoxStream<'static, Result<String, LanguageModelCompletionError>>,
207    // Has complete token usage after the stream has finished
208    pub last_token_usage: Arc<Mutex<TokenUsage>>,
209}
210
211impl Default for LanguageModelTextStream {
212    fn default() -> Self {
213        Self {
214            message_id: None,
215            stream: Box::pin(futures::stream::empty()),
216            last_token_usage: Arc::new(Mutex::new(TokenUsage::default())),
217        }
218    }
219}
220
221pub trait LanguageModel: Send + Sync {
222    fn id(&self) -> LanguageModelId;
223    fn name(&self) -> LanguageModelName;
224    fn provider_id(&self) -> LanguageModelProviderId;
225    fn provider_name(&self) -> LanguageModelProviderName;
226    fn telemetry_id(&self) -> String;
227
228    fn api_key(&self, _cx: &App) -> Option<String> {
229        None
230    }
231
232    /// Whether this model supports images
233    fn supports_images(&self) -> bool;
234
235    /// Whether this model supports tools.
236    fn supports_tools(&self) -> bool;
237
238    /// Whether this model supports choosing which tool to use.
239    fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool;
240
241    /// Returns whether this model supports "max mode";
242    fn supports_max_mode(&self) -> bool {
243        if self.provider_id().0 != ZED_CLOUD_PROVIDER_ID {
244            return false;
245        }
246
247        const MAX_MODE_CAPABLE_MODELS: &[CloudModel] = &[
248            CloudModel::Anthropic(anthropic::Model::ClaudeOpus4),
249            CloudModel::Anthropic(anthropic::Model::ClaudeOpus4Thinking),
250            CloudModel::Anthropic(anthropic::Model::ClaudeSonnet4),
251            CloudModel::Anthropic(anthropic::Model::ClaudeSonnet4Thinking),
252            CloudModel::Anthropic(anthropic::Model::Claude3_7Sonnet),
253            CloudModel::Anthropic(anthropic::Model::Claude3_7SonnetThinking),
254        ];
255
256        for model in MAX_MODE_CAPABLE_MODELS {
257            if self.id().0 == model.id() {
258                return true;
259            }
260        }
261
262        false
263    }
264
265    fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
266        LanguageModelToolSchemaFormat::JsonSchema
267    }
268
269    fn max_token_count(&self) -> usize;
270    fn max_output_tokens(&self) -> Option<u32> {
271        None
272    }
273
274    fn count_tokens(
275        &self,
276        request: LanguageModelRequest,
277        cx: &App,
278    ) -> BoxFuture<'static, Result<usize>>;
279
280    fn stream_completion(
281        &self,
282        request: LanguageModelRequest,
283        cx: &AsyncApp,
284    ) -> BoxFuture<
285        'static,
286        Result<
287            BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
288        >,
289    >;
290
291    fn stream_completion_text(
292        &self,
293        request: LanguageModelRequest,
294        cx: &AsyncApp,
295    ) -> BoxFuture<'static, Result<LanguageModelTextStream>> {
296        let future = self.stream_completion(request, cx);
297
298        async move {
299            let events = future.await?;
300            let mut events = events.fuse();
301            let mut message_id = None;
302            let mut first_item_text = None;
303            let last_token_usage = Arc::new(Mutex::new(TokenUsage::default()));
304
305            if let Some(first_event) = events.next().await {
306                match first_event {
307                    Ok(LanguageModelCompletionEvent::StartMessage { message_id: id }) => {
308                        message_id = Some(id.clone());
309                    }
310                    Ok(LanguageModelCompletionEvent::Text(text)) => {
311                        first_item_text = Some(text);
312                    }
313                    _ => (),
314                }
315            }
316
317            let stream = futures::stream::iter(first_item_text.map(Ok))
318                .chain(events.filter_map({
319                    let last_token_usage = last_token_usage.clone();
320                    move |result| {
321                        let last_token_usage = last_token_usage.clone();
322                        async move {
323                            match result {
324                                Ok(LanguageModelCompletionEvent::StatusUpdate { .. }) => None,
325                                Ok(LanguageModelCompletionEvent::StartMessage { .. }) => None,
326                                Ok(LanguageModelCompletionEvent::Text(text)) => Some(Ok(text)),
327                                Ok(LanguageModelCompletionEvent::Thinking { .. }) => None,
328                                Ok(LanguageModelCompletionEvent::Stop(_)) => None,
329                                Ok(LanguageModelCompletionEvent::ToolUse(_)) => None,
330                                Ok(LanguageModelCompletionEvent::UsageUpdate(token_usage)) => {
331                                    *last_token_usage.lock() = token_usage;
332                                    None
333                                }
334                                Err(err) => Some(Err(err)),
335                            }
336                        }
337                    }
338                }))
339                .boxed();
340
341            Ok(LanguageModelTextStream {
342                message_id,
343                stream,
344                last_token_usage,
345            })
346        }
347        .boxed()
348    }
349
350    fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
351        None
352    }
353
354    #[cfg(any(test, feature = "test-support"))]
355    fn as_fake(&self) -> &fake_provider::FakeLanguageModel {
356        unimplemented!()
357    }
358}
359
360#[derive(Debug, Error)]
361pub enum LanguageModelKnownError {
362    #[error("Context window limit exceeded ({tokens})")]
363    ContextWindowLimitExceeded { tokens: usize },
364}
365
366pub trait LanguageModelTool: 'static + DeserializeOwned + JsonSchema {
367    fn name() -> String;
368    fn description() -> String;
369}
370
371/// An error that occurred when trying to authenticate the language model provider.
372#[derive(Debug, Error)]
373pub enum AuthenticateError {
374    #[error("credentials not found")]
375    CredentialsNotFound,
376    #[error(transparent)]
377    Other(#[from] anyhow::Error),
378}
379
380pub trait LanguageModelProvider: 'static {
381    fn id(&self) -> LanguageModelProviderId;
382    fn name(&self) -> LanguageModelProviderName;
383    fn icon(&self) -> IconName {
384        IconName::ZedAssistant
385    }
386    fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>>;
387    fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>>;
388    fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>>;
389    fn recommended_models(&self, _cx: &App) -> Vec<Arc<dyn LanguageModel>> {
390        Vec::new()
391    }
392    fn load_model(&self, _model: Arc<dyn LanguageModel>, _cx: &App) {}
393    fn is_authenticated(&self, cx: &App) -> bool;
394    fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>>;
395    fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView;
396    fn must_accept_terms(&self, _cx: &App) -> bool {
397        false
398    }
399    fn render_accept_terms(
400        &self,
401        _view: LanguageModelProviderTosView,
402        _cx: &mut App,
403    ) -> Option<AnyElement> {
404        None
405    }
406    fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>>;
407}
408
409#[derive(PartialEq, Eq)]
410pub enum LanguageModelProviderTosView {
411    /// When there are some past interactions in the Agent Panel.
412    ThreadtEmptyState,
413    /// When there are no past interactions in the Agent Panel.
414    ThreadFreshStart,
415    PromptEditorPopup,
416    Configuration,
417}
418
419pub trait LanguageModelProviderState: 'static {
420    type ObservableEntity;
421
422    fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>>;
423
424    fn subscribe<T: 'static>(
425        &self,
426        cx: &mut gpui::Context<T>,
427        callback: impl Fn(&mut T, &mut gpui::Context<T>) + 'static,
428    ) -> Option<gpui::Subscription> {
429        let entity = self.observable_entity()?;
430        Some(cx.observe(&entity, move |this, _, cx| {
431            callback(this, cx);
432        }))
433    }
434}
435
436#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd, Serialize, Deserialize)]
437pub struct LanguageModelId(pub SharedString);
438
439#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
440pub struct LanguageModelName(pub SharedString);
441
442#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
443pub struct LanguageModelProviderId(pub SharedString);
444
445#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
446pub struct LanguageModelProviderName(pub SharedString);
447
448impl fmt::Display for LanguageModelProviderId {
449    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
450        write!(f, "{}", self.0)
451    }
452}
453
454impl From<String> for LanguageModelId {
455    fn from(value: String) -> Self {
456        Self(SharedString::from(value))
457    }
458}
459
460impl From<String> for LanguageModelName {
461    fn from(value: String) -> Self {
462        Self(SharedString::from(value))
463    }
464}
465
466impl From<String> for LanguageModelProviderId {
467    fn from(value: String) -> Self {
468        Self(SharedString::from(value))
469    }
470}
471
472impl From<String> for LanguageModelProviderName {
473    fn from(value: String) -> Self {
474        Self(SharedString::from(value))
475    }
476}