--- name: caching-architecture description: LiteLLM-RS response caching architecture. Covers the two-tier deterministic cache (L1 in-memory + optional L2 Redis) behind LLMCache and DualCache, SHA-256 cache key generation with schema versioning, TTL and eviction policy, request-path wiring for chat completions and embeddings, cache statistics, and admin endpoints. Use when adding or tuning gateway response caching — cache keys, tiers, TTLs or eviction, cache metrics, or invalidation. --- # Caching Architecture Guide ## Overview LiteLLM-RS ships exactly one wired caching subsystem: an **exact-match response cache** for non-streaming chat completions and embeddings. It is a two-tier read-through cache, not a three-tier stack — the former unwired semantic (vector) module has been removed from unreleased source. ``` Request (non-streaming /v1/chat/completions, /v1/embeddings) │ lookup_chat / lookup_embedding (src/server/routes/ai/response_cache.rs) ▼ ┌────────────────────────────────────────────────────────────┐ │ LLMCache (src/core/cache/llm_cache.rs) │ │ chat_cache: DualCache │ │ embedding_cache: DualCache │ └────────────────────────────────────────────────────────────┘ │ per-key get / set ▼ ┌────────────────────────────────────────────────────────────┐ │ DualCache (src/core/cache/dual.rs) │ │ L1 InMemoryCache — DashMap, TTL, sampled eviction │ │ L2 RedisCache — optional, backed by RedisPool │ │ Read: L1 miss → L2 hit → repopulate L1 │ │ Write: both tiers; L2 failure logs a warning, not fatal │ └────────────────────────────────────────────────────────────┘ │ miss ▼ LLM Provider → response stored back into both tiers ``` ### What Is Wired vs Not | Capability | Status | |---|---| | Exact-match response cache (chat + embeddings) | Wired: `AppState.response_cache`, built by `build_response_cache` (src/server/state.rs:143) | | Semantic similarity cache | Removed: `core::semantic_cache`, `cache.semantic_cache`, and `cache.similarity_threshold` no longer exist in unreleased source; remove those config keys, including false/default values | | Vector DB backends | Storage-only: `QdrantStore` implemented; weaviate/pinecone declared but return "not implemented yet" (src/storage/vector/backend.rs:29). Nothing connects them to caching at runtime | | Cloud object-storage caches | `core::cache::cloud` (`CloudCache` trait; S3/GCS/Azure under feature `s3`) — not part of the request path | --- ## Configuration ```yaml cache: enabled: true # default false; requires ttl > 0 ttl: 3600 # seconds; applied to chat AND embedding entries max_size: 1000 # max entries per in-memory layer ``` These are the only three fields (`src/config/models/cache.rs:9`, `deny_unknown_fields`). There is no `l1`/`l2`/`l3` block, `redis_url`, `prefix`, `exclude_models`, or `skip_streaming` key. - Redis is not configured here: the cache reuses the gateway's Redis pool. Without a pool it runs memory-only (`CacheMode::MemoryOnly`). - `enabled: true` with `ttl: 0` logs an error and leaves the cache off (src/server/state.rs:148). - Validation rejects `enabled: true, ttl: 0` outright (src/config/validation/cache_validators.rs:12). --- ## Request Flow 1. `POST /v1/chat/completions` calls `lookup_chat` before routing (src/server/routes/ai/chat.rs:112). A hit passes `ensure_chat_cache_pricing_gate` and returns immediately. 2. On a miss, the provider executes and `store_chat` writes the response (chat.rs:261). Embeddings do the same via `lookup_embedding` / `store_embedding` (src/server/routes/ai/embeddings.rs:98,283). 3. Chat lookups and stores are skipped when the request carries a per-key budget, sets `store: true`, or was marked bypassed by an upstream handler (`should_bypass_chat_cache`, src/server/routes/ai/response_cache.rs:25). Embeddings have no such bypass conditions. 4. Chat entries are scoped per caller: identity is `api_key:{id}` or `user:{id}`, optionally suffixed `:max_tokens_per_request:{limit}` (`cache_identity`, response_cache.rs:46). The key does not hash the separate client-supplied `ChatCompletionRequest.user`, so two requests from the same caller that differ only in that provider-facing field collide. Embedding entries are currently shared across callers: the route copies the identity into `EmbeddingRequest.user`, but `LLMCache` calls `generate_embedding_key` with no `user_id`, and that key does not hash `request.user`. Identical model/input embeddings therefore reuse one entry. Streaming chat requests are never cached (`LLMCache::get_chat_response_with_user`, src/core/cache/llm_cache.rs:280). 5. Cache lookup errors are logged and treated as misses. Gateway startup constructs only `Dual` or `MemoryOnly` caches, and `Dual` suppresses Redis L2 write failures. A programmatically installed `RedisOnly` `LLMCache` differs: Redis store errors propagate through `store_chat` / `store_embedding`, so the route returns an error after the provider call succeeded. --- ## Best Practices ### 1. Cache Key Determinism Keys come from free functions, not a generator struct. They hash a canonical-JSON payload (sorted keys, transport fields stripped) with SHA-256 under schema version `v4`: ```rust use litellm_rs::core::cache::{generate_chat_key, generate_chat_key_with_user}; let key = generate_chat_key(&request); // chat:gpt-4:v4:<64-hex> let key = generate_chat_key_with_user(&request, Some(user)); // user-scoped variant ``` Do not add non-deterministic fields (`request_id`, `stream`, timestamps) — `canonical_json_string` already strips the known ones at the top level and inside `extra_body`. Details: [reference/cache-key-generation.md](reference/cache-key-generation.md). ### 2. TTL Strategy ```rust // LLMCacheConfig::default() (src/core/cache/llm_cache.rs:55) chat_ttl: Duration::from_secs(3600), // 1 hour embedding_ttl: Duration::from_secs(86400), // 24 hours — embeddings are deterministic ``` At startup `build_response_cache` overrides both from `cache.ttl`, so per-tier TTL tuning requires code changes, not YAML. ### 3. Skip Caching — the Real Rules The deterministic path already enforces its own skips; do not re-implement them: ```rust // src/core/cache/llm_cache.rs:280 — streaming requests are never cached if request.stream.unwrap_or(false) { return Ok(None); } // src/server/routes/ai/response_cache.rs:25 — chat-only bypasses fn should_bypass_chat_cache(request: &ChatCompletionRequest, context: &RequestContext) -> bool { context.metadata.get(BYPASS_CHAT_RESPONSE_CACHE_KEY).and_then(|v| v.as_bool()).unwrap_or(false) || context.api_key_budget_id().is_some() || request.store == Some(true) } ``` The removed semantic-cache filters are not part of the current request path. --- ## References - [reference/response-cache.md](reference/response-cache.md) — LLMCache + DualCache composition, startup wiring, read/write paths, admin endpoints. - [reference/cache-key-generation.md](reference/cache-key-generation.md) — Key functions, `v4` key format, canonicalization policy, `CacheKeyBuilder`. - [reference/in-memory-cache.md](reference/in-memory-cache.md) — L1 `InMemoryCache`: DashMap storage, TTL, sampled eviction, cleanup task. - [reference/redis-cache.md](reference/redis-cache.md) — L2 `RedisCache`: RedisPool usage, key prefix, serializable entry envelope. - [reference/semantic-cache.md](reference/semantic-cache.md) — Semantic-cache removal and supported replacement boundary. - [reference/cache-metrics.md](reference/cache-metrics.md) — `AtomicCacheStats` / `CacheStatsSnapshot` / `CombinedCacheStats`, admin status endpoint, collector hooks.