1mod authorization;
2pub mod db;
3mod token;
4
5use crate::api::events::SnowflakeRow;
6use crate::api::CloudflareIpCountryHeader;
7use crate::build_kinesis_client;
8use crate::{db::UserId, executor::Executor, Cents, Config, Error, Result};
9use anyhow::{anyhow, Context as _};
10use authorization::authorize_access_to_language_model;
11use axum::routing::get;
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 collections::HashMap;
22use db::TokenUsage;
23use db::{usage_measure::UsageMeasure, ActiveUserCount, LlmDatabase};
24use futures::{Stream, StreamExt as _};
25use reqwest_client::ReqwestClient;
26use rpc::{
27 proto::Plan, LanguageModelProvider, PerformCompletionParams, EXPIRED_LLM_TOKEN_HEADER_NAME,
28};
29use rpc::{
30 ListModelsResponse, PredictEditsParams, PredictEditsResponse,
31 MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME,
32};
33use serde_json::json;
34use std::{
35 pin::Pin,
36 sync::Arc,
37 task::{Context, Poll},
38};
39use strum::IntoEnumIterator;
40use tokio::sync::RwLock;
41use util::ResultExt;
42
43pub use token::*;
44
45pub struct LlmState {
46 pub config: Config,
47 pub executor: Executor,
48 pub db: Arc<LlmDatabase>,
49 pub http_client: ReqwestClient,
50 pub kinesis_client: Option<aws_sdk_kinesis::Client>,
51 active_user_count_by_model:
52 RwLock<HashMap<(LanguageModelProvider, String), (DateTime<Utc>, ActiveUserCount)>>,
53}
54
55const ACTIVE_USER_COUNT_CACHE_DURATION: Duration = Duration::seconds(30);
56
57impl LlmState {
58 pub async fn new(config: Config, executor: Executor) -> Result<Arc<Self>> {
59 let database_url = config
60 .llm_database_url
61 .as_ref()
62 .ok_or_else(|| anyhow!("missing LLM_DATABASE_URL"))?;
63 let max_connections = config
64 .llm_database_max_connections
65 .ok_or_else(|| anyhow!("missing LLM_DATABASE_MAX_CONNECTIONS"))?;
66
67 let mut db_options = db::ConnectOptions::new(database_url);
68 db_options.max_connections(max_connections);
69 let mut db = LlmDatabase::new(db_options, executor.clone()).await?;
70 db.initialize().await?;
71
72 let db = Arc::new(db);
73
74 let user_agent = format!("Zed Server/{}", env!("CARGO_PKG_VERSION"));
75 let http_client =
76 ReqwestClient::user_agent(&user_agent).context("failed to construct http client")?;
77
78 let this = Self {
79 executor,
80 db,
81 http_client,
82 kinesis_client: if config.kinesis_access_key.is_some() {
83 build_kinesis_client(&config).await.log_err()
84 } else {
85 None
86 },
87 active_user_count_by_model: RwLock::new(HashMap::default()),
88 config,
89 };
90
91 Ok(Arc::new(this))
92 }
93
94 pub async fn get_active_user_count(
95 &self,
96 provider: LanguageModelProvider,
97 model: &str,
98 ) -> Result<ActiveUserCount> {
99 let now = Utc::now();
100
101 {
102 let active_user_count_by_model = self.active_user_count_by_model.read().await;
103 if let Some((last_updated, count)) =
104 active_user_count_by_model.get(&(provider, model.to_string()))
105 {
106 if now - *last_updated < ACTIVE_USER_COUNT_CACHE_DURATION {
107 return Ok(*count);
108 }
109 }
110 }
111
112 let mut cache = self.active_user_count_by_model.write().await;
113 let new_count = self.db.get_active_user_count(provider, model, now).await?;
114 cache.insert((provider, model.to_string()), (now, new_count));
115 Ok(new_count)
116 }
117}
118
119pub fn routes() -> Router<(), Body> {
120 Router::new()
121 .route("/models", get(list_models))
122 .route("/completion", post(perform_completion))
123 .route("/predict_edits", post(predict_edits))
124 .layer(middleware::from_fn(validate_api_token))
125}
126
127async fn validate_api_token<B>(mut req: Request<B>, next: Next<B>) -> impl IntoResponse {
128 let token = req
129 .headers()
130 .get(http::header::AUTHORIZATION)
131 .and_then(|header| header.to_str().ok())
132 .ok_or_else(|| {
133 Error::http(
134 StatusCode::BAD_REQUEST,
135 "missing authorization header".to_string(),
136 )
137 })?
138 .strip_prefix("Bearer ")
139 .ok_or_else(|| {
140 Error::http(
141 StatusCode::BAD_REQUEST,
142 "invalid authorization header".to_string(),
143 )
144 })?;
145
146 let state = req.extensions().get::<Arc<LlmState>>().unwrap();
147 match LlmTokenClaims::validate(token, &state.config) {
148 Ok(claims) => {
149 if state.db.is_access_token_revoked(&claims.jti).await? {
150 return Err(Error::http(
151 StatusCode::UNAUTHORIZED,
152 "unauthorized".to_string(),
153 ));
154 }
155
156 tracing::Span::current()
157 .record("user_id", claims.user_id)
158 .record("login", claims.github_user_login.clone())
159 .record("authn.jti", &claims.jti)
160 .record("is_staff", claims.is_staff);
161
162 req.extensions_mut().insert(claims);
163 Ok::<_, Error>(next.run(req).await.into_response())
164 }
165 Err(ValidateLlmTokenError::Expired) => Err(Error::Http(
166 StatusCode::UNAUTHORIZED,
167 "unauthorized".to_string(),
168 [(
169 HeaderName::from_static(EXPIRED_LLM_TOKEN_HEADER_NAME),
170 HeaderValue::from_static("true"),
171 )]
172 .into_iter()
173 .collect(),
174 )),
175 Err(_err) => Err(Error::http(
176 StatusCode::UNAUTHORIZED,
177 "unauthorized".to_string(),
178 )),
179 }
180}
181
182async fn list_models(
183 Extension(state): Extension<Arc<LlmState>>,
184 Extension(claims): Extension<LlmTokenClaims>,
185 country_code_header: Option<TypedHeader<CloudflareIpCountryHeader>>,
186) -> Result<Json<ListModelsResponse>> {
187 let country_code = country_code_header.map(|header| header.to_string());
188
189 let mut accessible_models = Vec::new();
190
191 for (provider, model) in state.db.all_models() {
192 let authorize_result = authorize_access_to_language_model(
193 &state.config,
194 &claims,
195 country_code.as_deref(),
196 provider,
197 &model.name,
198 );
199
200 if authorize_result.is_ok() {
201 accessible_models.push(rpc::LanguageModel {
202 provider,
203 name: model.name,
204 });
205 }
206 }
207
208 Ok(Json(ListModelsResponse {
209 models: accessible_models,
210 }))
211}
212
213async fn perform_completion(
214 Extension(state): Extension<Arc<LlmState>>,
215 Extension(claims): Extension<LlmTokenClaims>,
216 country_code_header: Option<TypedHeader<CloudflareIpCountryHeader>>,
217 Json(params): Json<PerformCompletionParams>,
218) -> Result<impl IntoResponse> {
219 let model = normalize_model_name(
220 state.db.model_names_for_provider(params.provider),
221 params.model,
222 );
223
224 authorize_access_to_language_model(
225 &state.config,
226 &claims,
227 country_code_header
228 .map(|header| header.to_string())
229 .as_deref(),
230 params.provider,
231 &model,
232 )?;
233
234 check_usage_limit(&state, params.provider, &model, &claims).await?;
235
236 let stream = match params.provider {
237 LanguageModelProvider::Anthropic => {
238 let api_key = if claims.is_staff {
239 state
240 .config
241 .anthropic_staff_api_key
242 .as_ref()
243 .context("no Anthropic AI staff API key configured on the server")?
244 } else {
245 state
246 .config
247 .anthropic_api_key
248 .as_ref()
249 .context("no Anthropic AI API key configured on the server")?
250 };
251
252 let mut request: anthropic::Request =
253 serde_json::from_str(params.provider_request.get())?;
254
255 // Override the model on the request with the latest version of the model that is
256 // known to the server.
257 //
258 // Right now, we use the version that's defined in `model.id()`, but we will likely
259 // want to change this code once a new version of an Anthropic model is released,
260 // so that users can use the new version, without having to update Zed.
261 request.model = match model.as_str() {
262 "claude-3-5-sonnet" => anthropic::Model::Claude3_5Sonnet.id().to_string(),
263 "claude-3-opus" => anthropic::Model::Claude3Opus.id().to_string(),
264 "claude-3-haiku" => anthropic::Model::Claude3Haiku.id().to_string(),
265 "claude-3-sonnet" => anthropic::Model::Claude3Sonnet.id().to_string(),
266 _ => request.model,
267 };
268
269 let (chunks, rate_limit_info) = anthropic::stream_completion_with_rate_limit_info(
270 &state.http_client,
271 anthropic::ANTHROPIC_API_URL,
272 api_key,
273 request,
274 )
275 .await
276 .map_err(|err| match err {
277 anthropic::AnthropicError::ApiError(ref api_error) => match api_error.code() {
278 Some(anthropic::ApiErrorCode::RateLimitError) => {
279 tracing::info!(
280 target: "upstream rate limit exceeded",
281 user_id = claims.user_id,
282 login = claims.github_user_login,
283 authn.jti = claims.jti,
284 is_staff = claims.is_staff,
285 provider = params.provider.to_string(),
286 model = model
287 );
288
289 Error::http(
290 StatusCode::TOO_MANY_REQUESTS,
291 "Upstream Anthropic rate limit exceeded.".to_string(),
292 )
293 }
294 Some(anthropic::ApiErrorCode::InvalidRequestError) => {
295 Error::http(StatusCode::BAD_REQUEST, api_error.message.clone())
296 }
297 Some(anthropic::ApiErrorCode::OverloadedError) => {
298 Error::http(StatusCode::SERVICE_UNAVAILABLE, api_error.message.clone())
299 }
300 Some(_) => {
301 Error::http(StatusCode::INTERNAL_SERVER_ERROR, api_error.message.clone())
302 }
303 None => Error::Internal(anyhow!(err)),
304 },
305 anthropic::AnthropicError::Other(err) => Error::Internal(err),
306 })?;
307
308 if let Some(rate_limit_info) = rate_limit_info {
309 tracing::info!(
310 target: "upstream rate limit",
311 is_staff = claims.is_staff,
312 provider = params.provider.to_string(),
313 model = model,
314 tokens_remaining = rate_limit_info.tokens_remaining,
315 requests_remaining = rate_limit_info.requests_remaining,
316 requests_reset = ?rate_limit_info.requests_reset,
317 tokens_reset = ?rate_limit_info.tokens_reset,
318 );
319 }
320
321 chunks
322 .map(move |event| {
323 let chunk = event?;
324 let (
325 input_tokens,
326 output_tokens,
327 cache_creation_input_tokens,
328 cache_read_input_tokens,
329 ) = match &chunk {
330 anthropic::Event::MessageStart {
331 message: anthropic::Response { usage, .. },
332 }
333 | anthropic::Event::MessageDelta { usage, .. } => (
334 usage.input_tokens.unwrap_or(0) as usize,
335 usage.output_tokens.unwrap_or(0) as usize,
336 usage.cache_creation_input_tokens.unwrap_or(0) as usize,
337 usage.cache_read_input_tokens.unwrap_or(0) as usize,
338 ),
339 _ => (0, 0, 0, 0),
340 };
341
342 anyhow::Ok(CompletionChunk {
343 bytes: serde_json::to_vec(&chunk).unwrap(),
344 input_tokens,
345 output_tokens,
346 cache_creation_input_tokens,
347 cache_read_input_tokens,
348 })
349 })
350 .boxed()
351 }
352 LanguageModelProvider::OpenAi => {
353 let api_key = state
354 .config
355 .openai_api_key
356 .as_ref()
357 .context("no OpenAI API key configured on the server")?;
358 let chunks = open_ai::stream_completion(
359 &state.http_client,
360 open_ai::OPEN_AI_API_URL,
361 api_key,
362 serde_json::from_str(params.provider_request.get())?,
363 )
364 .await?;
365
366 chunks
367 .map(|event| {
368 event.map(|chunk| {
369 let input_tokens =
370 chunk.usage.as_ref().map_or(0, |u| u.prompt_tokens) as usize;
371 let output_tokens =
372 chunk.usage.as_ref().map_or(0, |u| u.completion_tokens) as usize;
373 CompletionChunk {
374 bytes: serde_json::to_vec(&chunk).unwrap(),
375 input_tokens,
376 output_tokens,
377 cache_creation_input_tokens: 0,
378 cache_read_input_tokens: 0,
379 }
380 })
381 })
382 .boxed()
383 }
384 LanguageModelProvider::Google => {
385 let api_key = state
386 .config
387 .google_ai_api_key
388 .as_ref()
389 .context("no Google AI API key configured on the server")?;
390 let chunks = google_ai::stream_generate_content(
391 &state.http_client,
392 google_ai::API_URL,
393 api_key,
394 serde_json::from_str(params.provider_request.get())?,
395 )
396 .await?;
397
398 chunks
399 .map(|event| {
400 event.map(|chunk| {
401 // TODO - implement token counting for Google AI
402 CompletionChunk {
403 bytes: serde_json::to_vec(&chunk).unwrap(),
404 input_tokens: 0,
405 output_tokens: 0,
406 cache_creation_input_tokens: 0,
407 cache_read_input_tokens: 0,
408 }
409 })
410 })
411 .boxed()
412 }
413 };
414
415 Ok(Response::new(Body::wrap_stream(TokenCountingStream {
416 state,
417 claims,
418 provider: params.provider,
419 model,
420 tokens: TokenUsage::default(),
421 inner_stream: stream,
422 })))
423}
424
425fn normalize_model_name(known_models: Vec<String>, name: String) -> String {
426 if let Some(known_model_name) = known_models
427 .iter()
428 .filter(|known_model_name| name.starts_with(known_model_name.as_str()))
429 .max_by_key(|known_model_name| known_model_name.len())
430 {
431 known_model_name.to_string()
432 } else {
433 name
434 }
435}
436
437async fn predict_edits(
438 Extension(state): Extension<Arc<LlmState>>,
439 Extension(claims): Extension<LlmTokenClaims>,
440 _country_code_header: Option<TypedHeader<CloudflareIpCountryHeader>>,
441 Json(params): Json<PredictEditsParams>,
442) -> Result<impl IntoResponse> {
443 if !claims.is_staff && !claims.has_predict_edits_feature_flag {
444 return Err(Error::http(
445 StatusCode::FORBIDDEN,
446 "no access to Zed's edit prediction feature".to_string(),
447 ));
448 }
449
450 let api_url = state
451 .config
452 .prediction_api_url
453 .as_ref()
454 .context("no PREDICTION_API_URL configured on the server")?;
455 let api_key = state
456 .config
457 .prediction_api_key
458 .as_ref()
459 .context("no PREDICTION_API_KEY configured on the server")?;
460 let model = state
461 .config
462 .prediction_model
463 .as_ref()
464 .context("no PREDICTION_MODEL configured on the server")?;
465
466 let outline_prefix = params
467 .outline
468 .as_ref()
469 .map(|outline| format!("### Outline for current file:\n{}\n", outline))
470 .unwrap_or_default();
471
472 let prompt = include_str!("./llm/prediction_prompt.md")
473 .replace("<outline>", &outline_prefix)
474 .replace("<events>", ¶ms.input_events)
475 .replace("<excerpt>", ¶ms.input_excerpt);
476
477 let request_start = std::time::Instant::now();
478 let mut response = fireworks::complete(
479 &state.http_client,
480 api_url,
481 api_key,
482 fireworks::CompletionRequest {
483 model: model.to_string(),
484 prompt: prompt.clone(),
485 max_tokens: 2048,
486 temperature: 0.,
487 prediction: Some(fireworks::Prediction::Content {
488 content: params.input_excerpt,
489 }),
490 rewrite_speculation: Some(true),
491 },
492 )
493 .await?;
494 let duration = request_start.elapsed();
495
496 let choice = response
497 .completion
498 .choices
499 .pop()
500 .context("no output from completion response")?;
501
502 state.executor.spawn_detached({
503 let kinesis_client = state.kinesis_client.clone();
504 let kinesis_stream = state.config.kinesis_stream.clone();
505 let model = model.clone();
506 async move {
507 SnowflakeRow::new(
508 "Fireworks Completion Requested",
509 claims.metrics_id,
510 claims.is_staff,
511 claims.system_id.clone(),
512 json!({
513 "model": model.to_string(),
514 "headers": response.headers,
515 "usage": response.completion.usage,
516 "duration": duration.as_secs_f64(),
517 }),
518 )
519 .write(&kinesis_client, &kinesis_stream)
520 .await
521 .log_err();
522 }
523 });
524
525 Ok(Json(PredictEditsResponse {
526 output_excerpt: choice.text,
527 }))
528}
529
530/// The maximum monthly spending an individual user can reach on the free tier
531/// before they have to pay.
532pub const FREE_TIER_MONTHLY_SPENDING_LIMIT: Cents = Cents::from_dollars(10);
533
534/// The default value to use for maximum spend per month if the user did not
535/// explicitly set a maximum spend.
536///
537/// Used to prevent surprise bills.
538pub const DEFAULT_MAX_MONTHLY_SPEND: Cents = Cents::from_dollars(10);
539
540async fn check_usage_limit(
541 state: &Arc<LlmState>,
542 provider: LanguageModelProvider,
543 model_name: &str,
544 claims: &LlmTokenClaims,
545) -> Result<()> {
546 if claims.is_staff {
547 return Ok(());
548 }
549
550 let model = state.db.model(provider, model_name)?;
551 let usage = state
552 .db
553 .get_usage(
554 UserId::from_proto(claims.user_id),
555 provider,
556 model_name,
557 Utc::now(),
558 )
559 .await?;
560 let free_tier = claims.free_tier_monthly_spending_limit();
561
562 if usage.spending_this_month >= free_tier {
563 if !claims.has_llm_subscription {
564 return Err(Error::http(
565 StatusCode::PAYMENT_REQUIRED,
566 "Maximum spending limit reached for this month.".to_string(),
567 ));
568 }
569
570 if (usage.spending_this_month - free_tier) >= Cents(claims.max_monthly_spend_in_cents) {
571 return Err(Error::Http(
572 StatusCode::FORBIDDEN,
573 "Maximum spending limit reached for this month.".to_string(),
574 [(
575 HeaderName::from_static(MAX_LLM_MONTHLY_SPEND_REACHED_HEADER_NAME),
576 HeaderValue::from_static("true"),
577 )]
578 .into_iter()
579 .collect(),
580 ));
581 }
582 }
583
584 let active_users = state.get_active_user_count(provider, model_name).await?;
585
586 let users_in_recent_minutes = active_users.users_in_recent_minutes.max(1);
587 let users_in_recent_days = active_users.users_in_recent_days.max(1);
588
589 let per_user_max_requests_per_minute =
590 model.max_requests_per_minute as usize / users_in_recent_minutes;
591 let per_user_max_tokens_per_minute =
592 model.max_tokens_per_minute as usize / users_in_recent_minutes;
593 let per_user_max_tokens_per_day = model.max_tokens_per_day as usize / users_in_recent_days;
594
595 let checks = [
596 (
597 usage.requests_this_minute,
598 per_user_max_requests_per_minute,
599 UsageMeasure::RequestsPerMinute,
600 ),
601 (
602 usage.tokens_this_minute,
603 per_user_max_tokens_per_minute,
604 UsageMeasure::TokensPerMinute,
605 ),
606 (
607 usage.tokens_this_day,
608 per_user_max_tokens_per_day,
609 UsageMeasure::TokensPerDay,
610 ),
611 ];
612
613 for (used, limit, usage_measure) in checks {
614 if used > limit {
615 let resource = match usage_measure {
616 UsageMeasure::RequestsPerMinute => "requests_per_minute",
617 UsageMeasure::TokensPerMinute => "tokens_per_minute",
618 UsageMeasure::TokensPerDay => "tokens_per_day",
619 };
620
621 tracing::info!(
622 target: "user rate limit",
623 user_id = claims.user_id,
624 login = claims.github_user_login,
625 authn.jti = claims.jti,
626 is_staff = claims.is_staff,
627 provider = provider.to_string(),
628 model = model.name,
629 requests_this_minute = usage.requests_this_minute,
630 tokens_this_minute = usage.tokens_this_minute,
631 tokens_this_day = usage.tokens_this_day,
632 users_in_recent_minutes = users_in_recent_minutes,
633 users_in_recent_days = users_in_recent_days,
634 max_requests_per_minute = per_user_max_requests_per_minute,
635 max_tokens_per_minute = per_user_max_tokens_per_minute,
636 max_tokens_per_day = per_user_max_tokens_per_day,
637 );
638
639 SnowflakeRow::new(
640 "Language Model Rate Limited",
641 claims.metrics_id,
642 claims.is_staff,
643 claims.system_id.clone(),
644 json!({
645 "usage": usage,
646 "users_in_recent_minutes": users_in_recent_minutes,
647 "users_in_recent_days": users_in_recent_days,
648 "max_requests_per_minute": per_user_max_requests_per_minute,
649 "max_tokens_per_minute": per_user_max_tokens_per_minute,
650 "max_tokens_per_day": per_user_max_tokens_per_day,
651 "plan": match claims.plan {
652 Plan::Free => "free".to_string(),
653 Plan::ZedPro => "zed_pro".to_string(),
654 },
655 "model": model.name.clone(),
656 "provider": provider.to_string(),
657 "usage_measure": resource.to_string(),
658 }),
659 )
660 .write(&state.kinesis_client, &state.config.kinesis_stream)
661 .await
662 .log_err();
663
664 return Err(Error::http(
665 StatusCode::TOO_MANY_REQUESTS,
666 format!("Rate limit exceeded. Maximum {} reached.", resource),
667 ));
668 }
669 }
670
671 Ok(())
672}
673
674struct CompletionChunk {
675 bytes: Vec<u8>,
676 input_tokens: usize,
677 output_tokens: usize,
678 cache_creation_input_tokens: usize,
679 cache_read_input_tokens: usize,
680}
681
682struct TokenCountingStream<S> {
683 state: Arc<LlmState>,
684 claims: LlmTokenClaims,
685 provider: LanguageModelProvider,
686 model: String,
687 tokens: TokenUsage,
688 inner_stream: S,
689}
690
691impl<S> Stream for TokenCountingStream<S>
692where
693 S: Stream<Item = Result<CompletionChunk, anyhow::Error>> + Unpin,
694{
695 type Item = Result<Vec<u8>, anyhow::Error>;
696
697 fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<Option<Self::Item>> {
698 match Pin::new(&mut self.inner_stream).poll_next(cx) {
699 Poll::Ready(Some(Ok(mut chunk))) => {
700 chunk.bytes.push(b'\n');
701 self.tokens.input += chunk.input_tokens;
702 self.tokens.output += chunk.output_tokens;
703 self.tokens.input_cache_creation += chunk.cache_creation_input_tokens;
704 self.tokens.input_cache_read += chunk.cache_read_input_tokens;
705 Poll::Ready(Some(Ok(chunk.bytes)))
706 }
707 Poll::Ready(Some(Err(e))) => Poll::Ready(Some(Err(e))),
708 Poll::Ready(None) => Poll::Ready(None),
709 Poll::Pending => Poll::Pending,
710 }
711 }
712}
713
714impl<S> Drop for TokenCountingStream<S> {
715 fn drop(&mut self) {
716 let state = self.state.clone();
717 let claims = self.claims.clone();
718 let provider = self.provider;
719 let model = std::mem::take(&mut self.model);
720 let tokens = self.tokens;
721 self.state.executor.spawn_detached(async move {
722 let usage = state
723 .db
724 .record_usage(
725 UserId::from_proto(claims.user_id),
726 claims.is_staff,
727 provider,
728 &model,
729 tokens,
730 claims.has_llm_subscription,
731 Cents(claims.max_monthly_spend_in_cents),
732 claims.free_tier_monthly_spending_limit(),
733 Utc::now(),
734 )
735 .await
736 .log_err();
737
738 if let Some(usage) = usage {
739 tracing::info!(
740 target: "user usage",
741 user_id = claims.user_id,
742 login = claims.github_user_login,
743 authn.jti = claims.jti,
744 is_staff = claims.is_staff,
745 requests_this_minute = usage.requests_this_minute,
746 tokens_this_minute = usage.tokens_this_minute,
747 );
748
749 let properties = json!({
750 "has_llm_subscription": claims.has_llm_subscription,
751 "max_monthly_spend_in_cents": claims.max_monthly_spend_in_cents,
752 "plan": match claims.plan {
753 Plan::Free => "free".to_string(),
754 Plan::ZedPro => "zed_pro".to_string(),
755 },
756 "model": model,
757 "provider": provider,
758 "usage": usage,
759 "tokens": tokens
760 });
761 SnowflakeRow::new(
762 "Language Model Used",
763 claims.metrics_id,
764 claims.is_staff,
765 claims.system_id.clone(),
766 properties,
767 )
768 .write(&state.kinesis_client, &state.config.kinesis_stream)
769 .await
770 .log_err();
771 }
772 })
773 }
774}
775
776pub fn log_usage_periodically(state: Arc<LlmState>) {
777 state.executor.clone().spawn_detached(async move {
778 loop {
779 state
780 .executor
781 .sleep(std::time::Duration::from_secs(30))
782 .await;
783
784 for provider in LanguageModelProvider::iter() {
785 for model in state.db.model_names_for_provider(provider) {
786 if let Some(active_user_count) = state
787 .get_active_user_count(provider, &model)
788 .await
789 .log_err()
790 {
791 tracing::info!(
792 target: "active user counts",
793 provider = provider.to_string(),
794 model = model,
795 users_in_recent_minutes = active_user_count.users_in_recent_minutes,
796 users_in_recent_days = active_user_count.users_in_recent_days,
797 );
798 }
799 }
800 }
801
802 if let Some(usages) = state
803 .db
804 .get_application_wide_usages_by_model(Utc::now())
805 .await
806 .log_err()
807 {
808 for usage in usages {
809 tracing::info!(
810 target: "computed usage",
811 provider = usage.provider.to_string(),
812 model = usage.model,
813 requests_this_minute = usage.requests_this_minute,
814 tokens_this_minute = usage.tokens_this_minute,
815 );
816 }
817 }
818 }
819 })
820}