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::{Context as _, Result};
 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}
104
105#[derive(Debug, Clone, Copy)]
106pub struct RequestUsage {
107    pub limit: UsageLimit,
108    pub amount: i32,
109}
110
111impl RequestUsage {
112    pub fn from_headers(headers: &HeaderMap<HeaderValue>) -> Result<Self> {
113        let limit = headers
114            .get(MODEL_REQUESTS_USAGE_LIMIT_HEADER_NAME)
115            .with_context(|| {
116                format!("missing {MODEL_REQUESTS_USAGE_LIMIT_HEADER_NAME:?} header")
117            })?;
118        let limit = UsageLimit::from_str(limit.to_str()?)?;
119
120        let amount = headers
121            .get(MODEL_REQUESTS_USAGE_AMOUNT_HEADER_NAME)
122            .with_context(|| {
123                format!("missing {MODEL_REQUESTS_USAGE_AMOUNT_HEADER_NAME:?} header")
124            })?;
125        let amount = amount.to_str()?.parse::<i32>()?;
126
127        Ok(Self { limit, amount })
128    }
129}
130
131#[derive(Debug, PartialEq, Clone, Copy, Serialize, Deserialize, Default)]
132pub struct TokenUsage {
133    #[serde(default, skip_serializing_if = "is_default")]
134    pub input_tokens: u32,
135    #[serde(default, skip_serializing_if = "is_default")]
136    pub output_tokens: u32,
137    #[serde(default, skip_serializing_if = "is_default")]
138    pub cache_creation_input_tokens: u32,
139    #[serde(default, skip_serializing_if = "is_default")]
140    pub cache_read_input_tokens: u32,
141}
142
143impl TokenUsage {
144    pub fn total_tokens(&self) -> u32 {
145        self.input_tokens
146            + self.output_tokens
147            + self.cache_read_input_tokens
148            + self.cache_creation_input_tokens
149    }
150}
151
152impl Add<TokenUsage> for TokenUsage {
153    type Output = Self;
154
155    fn add(self, other: Self) -> Self {
156        Self {
157            input_tokens: self.input_tokens + other.input_tokens,
158            output_tokens: self.output_tokens + other.output_tokens,
159            cache_creation_input_tokens: self.cache_creation_input_tokens
160                + other.cache_creation_input_tokens,
161            cache_read_input_tokens: self.cache_read_input_tokens + other.cache_read_input_tokens,
162        }
163    }
164}
165
166impl Sub<TokenUsage> for TokenUsage {
167    type Output = Self;
168
169    fn sub(self, other: Self) -> Self {
170        Self {
171            input_tokens: self.input_tokens - other.input_tokens,
172            output_tokens: self.output_tokens - other.output_tokens,
173            cache_creation_input_tokens: self.cache_creation_input_tokens
174                - other.cache_creation_input_tokens,
175            cache_read_input_tokens: self.cache_read_input_tokens - other.cache_read_input_tokens,
176        }
177    }
178}
179
180#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
181pub struct LanguageModelToolUseId(Arc<str>);
182
183impl fmt::Display for LanguageModelToolUseId {
184    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
185        write!(f, "{}", self.0)
186    }
187}
188
189impl<T> From<T> for LanguageModelToolUseId
190where
191    T: Into<Arc<str>>,
192{
193    fn from(value: T) -> Self {
194        Self(value.into())
195    }
196}
197
198#[derive(Debug, PartialEq, Eq, Hash, Clone, Serialize, Deserialize)]
199pub struct LanguageModelToolUse {
200    pub id: LanguageModelToolUseId,
201    pub name: Arc<str>,
202    pub raw_input: String,
203    pub input: serde_json::Value,
204    pub is_input_complete: bool,
205}
206
207pub struct LanguageModelTextStream {
208    pub message_id: Option<String>,
209    pub stream: BoxStream<'static, Result<String, LanguageModelCompletionError>>,
210    // Has complete token usage after the stream has finished
211    pub last_token_usage: Arc<Mutex<TokenUsage>>,
212}
213
214impl Default for LanguageModelTextStream {
215    fn default() -> Self {
216        Self {
217            message_id: None,
218            stream: Box::pin(futures::stream::empty()),
219            last_token_usage: Arc::new(Mutex::new(TokenUsage::default())),
220        }
221    }
222}
223
224pub trait LanguageModel: Send + Sync {
225    fn id(&self) -> LanguageModelId;
226    fn name(&self) -> LanguageModelName;
227    fn provider_id(&self) -> LanguageModelProviderId;
228    fn provider_name(&self) -> LanguageModelProviderName;
229    fn telemetry_id(&self) -> String;
230
231    fn api_key(&self, _cx: &App) -> Option<String> {
232        None
233    }
234
235    /// Whether this model supports images
236    fn supports_images(&self) -> bool;
237
238    /// Whether this model supports tools.
239    fn supports_tools(&self) -> bool;
240
241    /// Whether this model supports choosing which tool to use.
242    fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool;
243
244    /// Returns whether this model supports "max mode";
245    fn supports_max_mode(&self) -> bool {
246        if self.provider_id().0 != ZED_CLOUD_PROVIDER_ID {
247            return false;
248        }
249
250        const MAX_MODE_CAPABLE_MODELS: &[CloudModel] = &[
251            CloudModel::Anthropic(anthropic::Model::ClaudeOpus4),
252            CloudModel::Anthropic(anthropic::Model::ClaudeOpus4Thinking),
253            CloudModel::Anthropic(anthropic::Model::ClaudeSonnet4),
254            CloudModel::Anthropic(anthropic::Model::ClaudeSonnet4Thinking),
255            CloudModel::Anthropic(anthropic::Model::Claude3_7Sonnet),
256            CloudModel::Anthropic(anthropic::Model::Claude3_7SonnetThinking),
257        ];
258
259        for model in MAX_MODE_CAPABLE_MODELS {
260            if self.id().0 == model.id() {
261                return true;
262            }
263        }
264
265        false
266    }
267
268    fn tool_input_format(&self) -> LanguageModelToolSchemaFormat {
269        LanguageModelToolSchemaFormat::JsonSchema
270    }
271
272    fn max_token_count(&self) -> usize;
273    fn max_output_tokens(&self) -> Option<u32> {
274        None
275    }
276
277    fn count_tokens(
278        &self,
279        request: LanguageModelRequest,
280        cx: &App,
281    ) -> BoxFuture<'static, Result<usize>>;
282
283    fn stream_completion(
284        &self,
285        request: LanguageModelRequest,
286        cx: &AsyncApp,
287    ) -> BoxFuture<
288        'static,
289        Result<
290            BoxStream<'static, Result<LanguageModelCompletionEvent, LanguageModelCompletionError>>,
291        >,
292    >;
293
294    fn stream_completion_text(
295        &self,
296        request: LanguageModelRequest,
297        cx: &AsyncApp,
298    ) -> BoxFuture<'static, Result<LanguageModelTextStream>> {
299        let future = self.stream_completion(request, cx);
300
301        async move {
302            let events = future.await?;
303            let mut events = events.fuse();
304            let mut message_id = None;
305            let mut first_item_text = None;
306            let last_token_usage = Arc::new(Mutex::new(TokenUsage::default()));
307
308            if let Some(first_event) = events.next().await {
309                match first_event {
310                    Ok(LanguageModelCompletionEvent::StartMessage { message_id: id }) => {
311                        message_id = Some(id.clone());
312                    }
313                    Ok(LanguageModelCompletionEvent::Text(text)) => {
314                        first_item_text = Some(text);
315                    }
316                    _ => (),
317                }
318            }
319
320            let stream = futures::stream::iter(first_item_text.map(Ok))
321                .chain(events.filter_map({
322                    let last_token_usage = last_token_usage.clone();
323                    move |result| {
324                        let last_token_usage = last_token_usage.clone();
325                        async move {
326                            match result {
327                                Ok(LanguageModelCompletionEvent::StatusUpdate { .. }) => None,
328                                Ok(LanguageModelCompletionEvent::StartMessage { .. }) => None,
329                                Ok(LanguageModelCompletionEvent::Text(text)) => Some(Ok(text)),
330                                Ok(LanguageModelCompletionEvent::Thinking { .. }) => None,
331                                Ok(LanguageModelCompletionEvent::Stop(_)) => None,
332                                Ok(LanguageModelCompletionEvent::ToolUse(_)) => None,
333                                Ok(LanguageModelCompletionEvent::UsageUpdate(token_usage)) => {
334                                    *last_token_usage.lock() = token_usage;
335                                    None
336                                }
337                                Err(err) => Some(Err(err)),
338                            }
339                        }
340                    }
341                }))
342                .boxed();
343
344            Ok(LanguageModelTextStream {
345                message_id,
346                stream,
347                last_token_usage,
348            })
349        }
350        .boxed()
351    }
352
353    fn cache_configuration(&self) -> Option<LanguageModelCacheConfiguration> {
354        None
355    }
356
357    #[cfg(any(test, feature = "test-support"))]
358    fn as_fake(&self) -> &fake_provider::FakeLanguageModel {
359        unimplemented!()
360    }
361}
362
363#[derive(Debug, Error)]
364pub enum LanguageModelKnownError {
365    #[error("Context window limit exceeded ({tokens})")]
366    ContextWindowLimitExceeded { tokens: usize },
367}
368
369pub trait LanguageModelTool: 'static + DeserializeOwned + JsonSchema {
370    fn name() -> String;
371    fn description() -> String;
372}
373
374/// An error that occurred when trying to authenticate the language model provider.
375#[derive(Debug, Error)]
376pub enum AuthenticateError {
377    #[error("credentials not found")]
378    CredentialsNotFound,
379    #[error(transparent)]
380    Other(#[from] anyhow::Error),
381}
382
383pub trait LanguageModelProvider: 'static {
384    fn id(&self) -> LanguageModelProviderId;
385    fn name(&self) -> LanguageModelProviderName;
386    fn icon(&self) -> IconName {
387        IconName::ZedAssistant
388    }
389    fn default_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>>;
390    fn default_fast_model(&self, cx: &App) -> Option<Arc<dyn LanguageModel>>;
391    fn provided_models(&self, cx: &App) -> Vec<Arc<dyn LanguageModel>>;
392    fn recommended_models(&self, _cx: &App) -> Vec<Arc<dyn LanguageModel>> {
393        Vec::new()
394    }
395    fn load_model(&self, _model: Arc<dyn LanguageModel>, _cx: &App) {}
396    fn is_authenticated(&self, cx: &App) -> bool;
397    fn authenticate(&self, cx: &mut App) -> Task<Result<(), AuthenticateError>>;
398    fn configuration_view(&self, window: &mut Window, cx: &mut App) -> AnyView;
399    fn must_accept_terms(&self, _cx: &App) -> bool {
400        false
401    }
402    fn render_accept_terms(
403        &self,
404        _view: LanguageModelProviderTosView,
405        _cx: &mut App,
406    ) -> Option<AnyElement> {
407        None
408    }
409    fn reset_credentials(&self, cx: &mut App) -> Task<Result<()>>;
410}
411
412#[derive(PartialEq, Eq)]
413pub enum LanguageModelProviderTosView {
414    /// When there are some past interactions in the Agent Panel.
415    ThreadtEmptyState,
416    /// When there are no past interactions in the Agent Panel.
417    ThreadFreshStart,
418    PromptEditorPopup,
419    Configuration,
420}
421
422pub trait LanguageModelProviderState: 'static {
423    type ObservableEntity;
424
425    fn observable_entity(&self) -> Option<gpui::Entity<Self::ObservableEntity>>;
426
427    fn subscribe<T: 'static>(
428        &self,
429        cx: &mut gpui::Context<T>,
430        callback: impl Fn(&mut T, &mut gpui::Context<T>) + 'static,
431    ) -> Option<gpui::Subscription> {
432        let entity = self.observable_entity()?;
433        Some(cx.observe(&entity, move |this, _, cx| {
434            callback(this, cx);
435        }))
436    }
437}
438
439#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd, Serialize, Deserialize)]
440pub struct LanguageModelId(pub SharedString);
441
442#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
443pub struct LanguageModelName(pub SharedString);
444
445#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
446pub struct LanguageModelProviderId(pub SharedString);
447
448#[derive(Clone, Eq, PartialEq, Hash, Debug, Ord, PartialOrd)]
449pub struct LanguageModelProviderName(pub SharedString);
450
451impl fmt::Display for LanguageModelProviderId {
452    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
453        write!(f, "{}", self.0)
454    }
455}
456
457impl From<String> for LanguageModelId {
458    fn from(value: String) -> Self {
459        Self(SharedString::from(value))
460    }
461}
462
463impl From<String> for LanguageModelName {
464    fn from(value: String) -> Self {
465        Self(SharedString::from(value))
466    }
467}
468
469impl From<String> for LanguageModelProviderId {
470    fn from(value: String) -> Self {
471        Self(SharedString::from(value))
472    }
473}
474
475impl From<String> for LanguageModelProviderName {
476    fn from(value: String) -> Self {
477        Self(SharedString::from(value))
478    }
479}