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 = if claims.is_staff {
175 state
176 .config
177 .anthropic_staff_api_key
178 .as_ref()
179 .context("no Anthropic AI staff API key configured on the server")?
180 } else {
181 state
182 .config
183 .anthropic_api_key
184 .as_ref()
185 .context("no Anthropic AI API key configured on the server")?
186 };
187
188 let mut request: anthropic::Request =
189 serde_json::from_str(¶ms.provider_request.get())?;
190
191 // Parse the model, throw away the version that was included, and then set a specific
192 // version that we control on the server.
193 // Right now, we use the version that's defined in `model.id()`, but we will likely
194 // want to change this code once a new version of an Anthropic model is released,
195 // so that users can use the new version, without having to update Zed.
196 request.model = match anthropic::Model::from_id(&request.model) {
197 Ok(model) => model.id().to_string(),
198 Err(_) => request.model,
199 };
200
201 let chunks = anthropic::stream_completion(
202 &state.http_client,
203 anthropic::ANTHROPIC_API_URL,
204 api_key,
205 request,
206 None,
207 )
208 .await
209 .map_err(|err| match err {
210 anthropic::AnthropicError::ApiError(ref api_error) => {
211 if api_error.code() == Some(anthropic::ApiErrorCode::RateLimitError) {
212 return Error::http(
213 StatusCode::TOO_MANY_REQUESTS,
214 "Upstream Anthropic rate limit exceeded.".to_string(),
215 );
216 }
217
218 Error::Internal(anyhow!(err))
219 }
220 anthropic::AnthropicError::Other(err) => Error::Internal(err),
221 })?;
222
223 chunks
224 .map(move |event| {
225 let chunk = event?;
226 let (input_tokens, output_tokens) = match &chunk {
227 anthropic::Event::MessageStart {
228 message: anthropic::Response { usage, .. },
229 }
230 | anthropic::Event::MessageDelta { usage, .. } => (
231 usage.input_tokens.unwrap_or(0) as usize,
232 usage.output_tokens.unwrap_or(0) as usize,
233 ),
234 _ => (0, 0),
235 };
236
237 anyhow::Ok((
238 serde_json::to_vec(&chunk).unwrap(),
239 input_tokens,
240 output_tokens,
241 ))
242 })
243 .boxed()
244 }
245 LanguageModelProvider::OpenAi => {
246 let api_key = state
247 .config
248 .openai_api_key
249 .as_ref()
250 .context("no OpenAI API key configured on the server")?;
251 let chunks = open_ai::stream_completion(
252 &state.http_client,
253 open_ai::OPEN_AI_API_URL,
254 api_key,
255 serde_json::from_str(¶ms.provider_request.get())?,
256 None,
257 )
258 .await?;
259
260 chunks
261 .map(|event| {
262 event.map(|chunk| {
263 let input_tokens =
264 chunk.usage.as_ref().map_or(0, |u| u.prompt_tokens) as usize;
265 let output_tokens =
266 chunk.usage.as_ref().map_or(0, |u| u.completion_tokens) as usize;
267 (
268 serde_json::to_vec(&chunk).unwrap(),
269 input_tokens,
270 output_tokens,
271 )
272 })
273 })
274 .boxed()
275 }
276 LanguageModelProvider::Google => {
277 let api_key = state
278 .config
279 .google_ai_api_key
280 .as_ref()
281 .context("no Google AI API key configured on the server")?;
282 let chunks = google_ai::stream_generate_content(
283 &state.http_client,
284 google_ai::API_URL,
285 api_key,
286 serde_json::from_str(¶ms.provider_request.get())?,
287 )
288 .await?;
289
290 chunks
291 .map(|event| {
292 event.map(|chunk| {
293 // TODO - implement token counting for Google AI
294 let input_tokens = 0;
295 let output_tokens = 0;
296 (
297 serde_json::to_vec(&chunk).unwrap(),
298 input_tokens,
299 output_tokens,
300 )
301 })
302 })
303 .boxed()
304 }
305 LanguageModelProvider::Zed => {
306 let api_key = state
307 .config
308 .qwen2_7b_api_key
309 .as_ref()
310 .context("no Qwen2-7B API key configured on the server")?;
311 let api_url = state
312 .config
313 .qwen2_7b_api_url
314 .as_ref()
315 .context("no Qwen2-7B URL configured on the server")?;
316 let chunks = open_ai::stream_completion(
317 &state.http_client,
318 &api_url,
319 api_key,
320 serde_json::from_str(¶ms.provider_request.get())?,
321 None,
322 )
323 .await?;
324
325 chunks
326 .map(|event| {
327 event.map(|chunk| {
328 let input_tokens =
329 chunk.usage.as_ref().map_or(0, |u| u.prompt_tokens) as usize;
330 let output_tokens =
331 chunk.usage.as_ref().map_or(0, |u| u.completion_tokens) as usize;
332 (
333 serde_json::to_vec(&chunk).unwrap(),
334 input_tokens,
335 output_tokens,
336 )
337 })
338 })
339 .boxed()
340 }
341 };
342
343 Ok(Response::new(Body::wrap_stream(TokenCountingStream {
344 state,
345 claims,
346 provider: params.provider,
347 model,
348 input_tokens: 0,
349 output_tokens: 0,
350 inner_stream: stream,
351 })))
352}
353
354fn normalize_model_name(provider: LanguageModelProvider, name: String) -> String {
355 let prefixes: &[_] = match provider {
356 LanguageModelProvider::Anthropic => &[
357 "claude-3-5-sonnet",
358 "claude-3-haiku",
359 "claude-3-opus",
360 "claude-3-sonnet",
361 ],
362 LanguageModelProvider::OpenAi => &[
363 "gpt-3.5-turbo",
364 "gpt-4-turbo-preview",
365 "gpt-4o-mini",
366 "gpt-4o",
367 "gpt-4",
368 ],
369 LanguageModelProvider::Google => &[],
370 LanguageModelProvider::Zed => &[],
371 };
372
373 if let Some(prefix) = prefixes
374 .iter()
375 .filter(|&&prefix| name.starts_with(prefix))
376 .max_by_key(|&&prefix| prefix.len())
377 {
378 prefix.to_string()
379 } else {
380 name
381 }
382}
383
384async fn check_usage_limit(
385 state: &Arc<LlmState>,
386 provider: LanguageModelProvider,
387 model_name: &str,
388 claims: &LlmTokenClaims,
389) -> Result<()> {
390 let model = state.db.model(provider, model_name)?;
391 let usage = state
392 .db
393 .get_usage(claims.user_id as i32, provider, model_name, Utc::now())
394 .await?;
395
396 let active_users = state.get_active_user_count().await?;
397
398 let per_user_max_requests_per_minute =
399 model.max_requests_per_minute as usize / active_users.users_in_recent_minutes.max(1);
400 let per_user_max_tokens_per_minute =
401 model.max_tokens_per_minute as usize / active_users.users_in_recent_minutes.max(1);
402 let per_user_max_tokens_per_day =
403 model.max_tokens_per_day as usize / active_users.users_in_recent_days.max(1);
404
405 let checks = [
406 (
407 usage.requests_this_minute,
408 per_user_max_requests_per_minute,
409 "requests per minute",
410 ),
411 (
412 usage.tokens_this_minute,
413 per_user_max_tokens_per_minute,
414 "tokens per minute",
415 ),
416 (
417 usage.tokens_this_day,
418 per_user_max_tokens_per_day,
419 "tokens per day",
420 ),
421 ];
422
423 for (usage, limit, resource) in checks {
424 // Temporarily bypass rate-limiting for staff members.
425 if claims.is_staff {
426 continue;
427 }
428
429 if usage > limit {
430 return Err(Error::http(
431 StatusCode::TOO_MANY_REQUESTS,
432 format!("Rate limit exceeded. Maximum {} reached.", resource),
433 ));
434 }
435 }
436
437 Ok(())
438}
439
440struct TokenCountingStream<S> {
441 state: Arc<LlmState>,
442 claims: LlmTokenClaims,
443 provider: LanguageModelProvider,
444 model: String,
445 input_tokens: usize,
446 output_tokens: usize,
447 inner_stream: S,
448}
449
450impl<S> Stream for TokenCountingStream<S>
451where
452 S: Stream<Item = Result<(Vec<u8>, usize, usize), anyhow::Error>> + Unpin,
453{
454 type Item = Result<Vec<u8>, anyhow::Error>;
455
456 fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<Option<Self::Item>> {
457 match Pin::new(&mut self.inner_stream).poll_next(cx) {
458 Poll::Ready(Some(Ok((mut bytes, input_tokens, output_tokens)))) => {
459 bytes.push(b'\n');
460 self.input_tokens += input_tokens;
461 self.output_tokens += output_tokens;
462 Poll::Ready(Some(Ok(bytes)))
463 }
464 Poll::Ready(Some(Err(e))) => Poll::Ready(Some(Err(e))),
465 Poll::Ready(None) => Poll::Ready(None),
466 Poll::Pending => Poll::Pending,
467 }
468 }
469}
470
471impl<S> Drop for TokenCountingStream<S> {
472 fn drop(&mut self) {
473 let state = self.state.clone();
474 let claims = self.claims.clone();
475 let provider = self.provider;
476 let model = std::mem::take(&mut self.model);
477 let input_token_count = self.input_tokens;
478 let output_token_count = self.output_tokens;
479 self.state.executor.spawn_detached(async move {
480 let usage = state
481 .db
482 .record_usage(
483 claims.user_id as i32,
484 claims.is_staff,
485 provider,
486 &model,
487 input_token_count,
488 output_token_count,
489 Utc::now(),
490 )
491 .await
492 .log_err();
493
494 if let Some((clickhouse_client, usage)) = state.clickhouse_client.as_ref().zip(usage) {
495 report_llm_usage(
496 clickhouse_client,
497 LlmUsageEventRow {
498 time: Utc::now().timestamp_millis(),
499 user_id: claims.user_id as i32,
500 is_staff: claims.is_staff,
501 plan: match claims.plan {
502 Plan::Free => "free".to_string(),
503 Plan::ZedPro => "zed_pro".to_string(),
504 },
505 model,
506 provider: provider.to_string(),
507 input_token_count: input_token_count as u64,
508 output_token_count: output_token_count as u64,
509 requests_this_minute: usage.requests_this_minute as u64,
510 tokens_this_minute: usage.tokens_this_minute as u64,
511 tokens_this_day: usage.tokens_this_day as u64,
512 input_tokens_this_month: usage.input_tokens_this_month as u64,
513 output_tokens_this_month: usage.output_tokens_this_month as u64,
514 spending_this_month: usage.spending_this_month as u64,
515 },
516 )
517 .await
518 .log_err();
519 }
520 })
521 }
522}