1mod authorization;
2pub mod db;
3mod telemetry;
4mod token;
5
6use crate::{
7 api::CloudflareIpCountryHeader, build_clickhouse_client, executor::Executor, Config, Error,
8 Result,
9};
10use anyhow::{anyhow, Context as _};
11use authorization::authorize_access_to_language_model;
12use axum::{
13 body::Body,
14 http::{self, HeaderName, HeaderValue, Request, StatusCode},
15 middleware::{self, Next},
16 response::{IntoResponse, Response},
17 routing::post,
18 Extension, Json, Router, TypedHeader,
19};
20use chrono::{DateTime, Duration, Utc};
21use db::{ActiveUserCount, LlmDatabase};
22use futures::{Stream, StreamExt as _};
23use http_client::IsahcHttpClient;
24use rpc::{
25 proto::Plan, LanguageModelProvider, PerformCompletionParams, EXPIRED_LLM_TOKEN_HEADER_NAME,
26};
27use std::{
28 pin::Pin,
29 sync::Arc,
30 task::{Context, Poll},
31};
32use telemetry::{report_llm_usage, LlmUsageEventRow};
33use tokio::sync::RwLock;
34use util::ResultExt;
35
36pub use token::*;
37
38pub struct LlmState {
39 pub config: Config,
40 pub executor: Executor,
41 pub db: Arc<LlmDatabase>,
42 pub http_client: IsahcHttpClient,
43 pub clickhouse_client: Option<clickhouse::Client>,
44 active_user_count: RwLock<Option<(DateTime<Utc>, ActiveUserCount)>>,
45}
46
47const ACTIVE_USER_COUNT_CACHE_DURATION: Duration = Duration::seconds(30);
48
49impl LlmState {
50 pub async fn new(config: Config, executor: Executor) -> Result<Arc<Self>> {
51 let database_url = config
52 .llm_database_url
53 .as_ref()
54 .ok_or_else(|| anyhow!("missing LLM_DATABASE_URL"))?;
55 let max_connections = config
56 .llm_database_max_connections
57 .ok_or_else(|| anyhow!("missing LLM_DATABASE_MAX_CONNECTIONS"))?;
58
59 let mut db_options = db::ConnectOptions::new(database_url);
60 db_options.max_connections(max_connections);
61 let mut db = LlmDatabase::new(db_options, executor.clone()).await?;
62 db.initialize().await?;
63
64 let db = Arc::new(db);
65
66 let user_agent = format!("Zed Server/{}", env!("CARGO_PKG_VERSION"));
67 let http_client = IsahcHttpClient::builder()
68 .default_header("User-Agent", user_agent)
69 .build()
70 .context("failed to construct http client")?;
71
72 let initial_active_user_count =
73 Some((Utc::now(), db.get_active_user_count(Utc::now()).await?));
74
75 let this = Self {
76 executor,
77 db,
78 http_client,
79 clickhouse_client: config
80 .clickhouse_url
81 .as_ref()
82 .and_then(|_| build_clickhouse_client(&config).log_err()),
83 active_user_count: RwLock::new(initial_active_user_count),
84 config,
85 };
86
87 Ok(Arc::new(this))
88 }
89
90 pub async fn get_active_user_count(&self) -> Result<ActiveUserCount> {
91 let now = Utc::now();
92
93 if let Some((last_updated, count)) = self.active_user_count.read().await.as_ref() {
94 if now - *last_updated < ACTIVE_USER_COUNT_CACHE_DURATION {
95 return Ok(*count);
96 }
97 }
98
99 let mut cache = self.active_user_count.write().await;
100 let new_count = self.db.get_active_user_count(now).await?;
101 *cache = Some((now, new_count));
102 Ok(new_count)
103 }
104}
105
106pub fn routes() -> Router<(), Body> {
107 Router::new()
108 .route("/completion", post(perform_completion))
109 .layer(middleware::from_fn(validate_api_token))
110}
111
112async fn validate_api_token<B>(mut req: Request<B>, next: Next<B>) -> impl IntoResponse {
113 let token = req
114 .headers()
115 .get(http::header::AUTHORIZATION)
116 .and_then(|header| header.to_str().ok())
117 .ok_or_else(|| {
118 Error::http(
119 StatusCode::BAD_REQUEST,
120 "missing authorization header".to_string(),
121 )
122 })?
123 .strip_prefix("Bearer ")
124 .ok_or_else(|| {
125 Error::http(
126 StatusCode::BAD_REQUEST,
127 "invalid authorization header".to_string(),
128 )
129 })?;
130
131 let state = req.extensions().get::<Arc<LlmState>>().unwrap();
132 match LlmTokenClaims::validate(&token, &state.config) {
133 Ok(claims) => {
134 req.extensions_mut().insert(claims);
135 Ok::<_, Error>(next.run(req).await.into_response())
136 }
137 Err(ValidateLlmTokenError::Expired) => Err(Error::Http(
138 StatusCode::UNAUTHORIZED,
139 "unauthorized".to_string(),
140 [(
141 HeaderName::from_static(EXPIRED_LLM_TOKEN_HEADER_NAME),
142 HeaderValue::from_static("true"),
143 )]
144 .into_iter()
145 .collect(),
146 )),
147 Err(_err) => Err(Error::http(
148 StatusCode::UNAUTHORIZED,
149 "unauthorized".to_string(),
150 )),
151 }
152}
153
154async fn perform_completion(
155 Extension(state): Extension<Arc<LlmState>>,
156 Extension(claims): Extension<LlmTokenClaims>,
157 country_code_header: Option<TypedHeader<CloudflareIpCountryHeader>>,
158 Json(params): Json<PerformCompletionParams>,
159) -> Result<impl IntoResponse> {
160 let model = normalize_model_name(params.provider, params.model);
161
162 authorize_access_to_language_model(
163 &state.config,
164 &claims,
165 country_code_header.map(|header| header.to_string()),
166 params.provider,
167 &model,
168 )?;
169
170 check_usage_limit(&state, params.provider, &model, &claims).await?;
171
172 let stream = match params.provider {
173 LanguageModelProvider::Anthropic => {
174 let api_key = state
175 .config
176 .anthropic_api_key
177 .as_ref()
178 .context("no Anthropic AI API key configured on the server")?;
179
180 let mut request: anthropic::Request =
181 serde_json::from_str(¶ms.provider_request.get())?;
182
183 // Parse the model, throw away the version that was included, and then set a specific
184 // version that we control on the server.
185 // Right now, we use the version that's defined in `model.id()`, but we will likely
186 // want to change this code once a new version of an Anthropic model is released,
187 // so that users can use the new version, without having to update Zed.
188 request.model = match anthropic::Model::from_id(&request.model) {
189 Ok(model) => model.id().to_string(),
190 Err(_) => request.model,
191 };
192
193 let chunks = anthropic::stream_completion(
194 &state.http_client,
195 anthropic::ANTHROPIC_API_URL,
196 api_key,
197 request,
198 None,
199 )
200 .await
201 .map_err(|err| match err {
202 anthropic::AnthropicError::ApiError(ref api_error) => {
203 if api_error.code() == Some(anthropic::ApiErrorCode::RateLimitError) {
204 return Error::http(
205 StatusCode::TOO_MANY_REQUESTS,
206 "Upstream Anthropic rate limit exceeded.".to_string(),
207 );
208 }
209
210 Error::Internal(anyhow!(err))
211 }
212 anthropic::AnthropicError::Other(err) => Error::Internal(err),
213 })?;
214
215 chunks
216 .map(move |event| {
217 let chunk = event?;
218 let (input_tokens, output_tokens) = match &chunk {
219 anthropic::Event::MessageStart {
220 message: anthropic::Response { usage, .. },
221 }
222 | anthropic::Event::MessageDelta { usage, .. } => (
223 usage.input_tokens.unwrap_or(0) as usize,
224 usage.output_tokens.unwrap_or(0) as usize,
225 ),
226 _ => (0, 0),
227 };
228
229 anyhow::Ok((
230 serde_json::to_vec(&chunk).unwrap(),
231 input_tokens,
232 output_tokens,
233 ))
234 })
235 .boxed()
236 }
237 LanguageModelProvider::OpenAi => {
238 let api_key = state
239 .config
240 .openai_api_key
241 .as_ref()
242 .context("no OpenAI API key configured on the server")?;
243 let chunks = open_ai::stream_completion(
244 &state.http_client,
245 open_ai::OPEN_AI_API_URL,
246 api_key,
247 serde_json::from_str(¶ms.provider_request.get())?,
248 None,
249 )
250 .await?;
251
252 chunks
253 .map(|event| {
254 event.map(|chunk| {
255 let input_tokens =
256 chunk.usage.as_ref().map_or(0, |u| u.prompt_tokens) as usize;
257 let output_tokens =
258 chunk.usage.as_ref().map_or(0, |u| u.completion_tokens) as usize;
259 (
260 serde_json::to_vec(&chunk).unwrap(),
261 input_tokens,
262 output_tokens,
263 )
264 })
265 })
266 .boxed()
267 }
268 LanguageModelProvider::Google => {
269 let api_key = state
270 .config
271 .google_ai_api_key
272 .as_ref()
273 .context("no Google AI API key configured on the server")?;
274 let chunks = google_ai::stream_generate_content(
275 &state.http_client,
276 google_ai::API_URL,
277 api_key,
278 serde_json::from_str(¶ms.provider_request.get())?,
279 )
280 .await?;
281
282 chunks
283 .map(|event| {
284 event.map(|chunk| {
285 // TODO - implement token counting for Google AI
286 let input_tokens = 0;
287 let output_tokens = 0;
288 (
289 serde_json::to_vec(&chunk).unwrap(),
290 input_tokens,
291 output_tokens,
292 )
293 })
294 })
295 .boxed()
296 }
297 LanguageModelProvider::Zed => {
298 let api_key = state
299 .config
300 .qwen2_7b_api_key
301 .as_ref()
302 .context("no Qwen2-7B API key configured on the server")?;
303 let api_url = state
304 .config
305 .qwen2_7b_api_url
306 .as_ref()
307 .context("no Qwen2-7B URL configured on the server")?;
308 let chunks = open_ai::stream_completion(
309 &state.http_client,
310 &api_url,
311 api_key,
312 serde_json::from_str(¶ms.provider_request.get())?,
313 None,
314 )
315 .await?;
316
317 chunks
318 .map(|event| {
319 event.map(|chunk| {
320 let input_tokens =
321 chunk.usage.as_ref().map_or(0, |u| u.prompt_tokens) as usize;
322 let output_tokens =
323 chunk.usage.as_ref().map_or(0, |u| u.completion_tokens) as usize;
324 (
325 serde_json::to_vec(&chunk).unwrap(),
326 input_tokens,
327 output_tokens,
328 )
329 })
330 })
331 .boxed()
332 }
333 };
334
335 Ok(Response::new(Body::wrap_stream(TokenCountingStream {
336 state,
337 claims,
338 provider: params.provider,
339 model,
340 input_tokens: 0,
341 output_tokens: 0,
342 inner_stream: stream,
343 })))
344}
345
346fn normalize_model_name(provider: LanguageModelProvider, name: String) -> String {
347 let prefixes: &[_] = match provider {
348 LanguageModelProvider::Anthropic => &[
349 "claude-3-5-sonnet",
350 "claude-3-haiku",
351 "claude-3-opus",
352 "claude-3-sonnet",
353 ],
354 LanguageModelProvider::OpenAi => &[
355 "gpt-3.5-turbo",
356 "gpt-4-turbo-preview",
357 "gpt-4o-mini",
358 "gpt-4o",
359 "gpt-4",
360 ],
361 LanguageModelProvider::Google => &[],
362 LanguageModelProvider::Zed => &[],
363 };
364
365 if let Some(prefix) = prefixes
366 .iter()
367 .filter(|&&prefix| name.starts_with(prefix))
368 .max_by_key(|&&prefix| prefix.len())
369 {
370 prefix.to_string()
371 } else {
372 name
373 }
374}
375
376async fn check_usage_limit(
377 state: &Arc<LlmState>,
378 provider: LanguageModelProvider,
379 model_name: &str,
380 claims: &LlmTokenClaims,
381) -> Result<()> {
382 let model = state.db.model(provider, model_name)?;
383 let usage = state
384 .db
385 .get_usage(claims.user_id as i32, provider, model_name, Utc::now())
386 .await?;
387
388 let active_users = state.get_active_user_count().await?;
389
390 let per_user_max_requests_per_minute =
391 model.max_requests_per_minute as usize / active_users.users_in_recent_minutes.max(1);
392 let per_user_max_tokens_per_minute =
393 model.max_tokens_per_minute as usize / active_users.users_in_recent_minutes.max(1);
394 let per_user_max_tokens_per_day =
395 model.max_tokens_per_day as usize / active_users.users_in_recent_days.max(1);
396
397 let checks = [
398 (
399 usage.requests_this_minute,
400 per_user_max_requests_per_minute,
401 "requests per minute",
402 ),
403 (
404 usage.tokens_this_minute,
405 per_user_max_tokens_per_minute,
406 "tokens per minute",
407 ),
408 (
409 usage.tokens_this_day,
410 per_user_max_tokens_per_day,
411 "tokens per day",
412 ),
413 ];
414
415 for (usage, limit, resource) in checks {
416 // Temporarily bypass rate-limiting for staff members.
417 if claims.is_staff {
418 continue;
419 }
420
421 if usage > limit {
422 return Err(Error::http(
423 StatusCode::TOO_MANY_REQUESTS,
424 format!("Rate limit exceeded. Maximum {} reached.", resource),
425 ));
426 }
427 }
428
429 Ok(())
430}
431
432struct TokenCountingStream<S> {
433 state: Arc<LlmState>,
434 claims: LlmTokenClaims,
435 provider: LanguageModelProvider,
436 model: String,
437 input_tokens: usize,
438 output_tokens: usize,
439 inner_stream: S,
440}
441
442impl<S> Stream for TokenCountingStream<S>
443where
444 S: Stream<Item = Result<(Vec<u8>, usize, usize), anyhow::Error>> + Unpin,
445{
446 type Item = Result<Vec<u8>, anyhow::Error>;
447
448 fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<Option<Self::Item>> {
449 match Pin::new(&mut self.inner_stream).poll_next(cx) {
450 Poll::Ready(Some(Ok((mut bytes, input_tokens, output_tokens)))) => {
451 bytes.push(b'\n');
452 self.input_tokens += input_tokens;
453 self.output_tokens += output_tokens;
454 Poll::Ready(Some(Ok(bytes)))
455 }
456 Poll::Ready(Some(Err(e))) => Poll::Ready(Some(Err(e))),
457 Poll::Ready(None) => Poll::Ready(None),
458 Poll::Pending => Poll::Pending,
459 }
460 }
461}
462
463impl<S> Drop for TokenCountingStream<S> {
464 fn drop(&mut self) {
465 let state = self.state.clone();
466 let claims = self.claims.clone();
467 let provider = self.provider;
468 let model = std::mem::take(&mut self.model);
469 let input_token_count = self.input_tokens;
470 let output_token_count = self.output_tokens;
471 self.state.executor.spawn_detached(async move {
472 let usage = state
473 .db
474 .record_usage(
475 claims.user_id as i32,
476 provider,
477 &model,
478 input_token_count,
479 output_token_count,
480 Utc::now(),
481 )
482 .await
483 .log_err();
484
485 if let Some((clickhouse_client, usage)) = state.clickhouse_client.as_ref().zip(usage) {
486 report_llm_usage(
487 clickhouse_client,
488 LlmUsageEventRow {
489 time: Utc::now().timestamp_millis(),
490 user_id: claims.user_id as i32,
491 is_staff: claims.is_staff,
492 plan: match claims.plan {
493 Plan::Free => "free".to_string(),
494 Plan::ZedPro => "zed_pro".to_string(),
495 },
496 model,
497 provider: provider.to_string(),
498 input_token_count: input_token_count as u64,
499 output_token_count: output_token_count as u64,
500 requests_this_minute: usage.requests_this_minute as u64,
501 tokens_this_minute: usage.tokens_this_minute as u64,
502 tokens_this_day: usage.tokens_this_day as u64,
503 input_tokens_this_month: usage.input_tokens_this_month as u64,
504 output_tokens_this_month: usage.output_tokens_this_month as u64,
505 spending_this_month: usage.spending_this_month as u64,
506 },
507 )
508 .await
509 .log_err();
510 }
511 })
512 }
513}