litellm/litellm-rust/crates/cache-response/README.md
devin-ai-integration[bot] 4677f1028e
refactor(rust): align the cache crates with Python and wire every native backend (#42530)
* refactor(rust): align the cache crates with Python and activate every backend

The cache port had drifted: lifecycle and Redis-only operations sat on
`BaseCache`, counters were pinned to `f64`, each semantic backend defined its
own embedder and prompt handling, and only the in-memory backend could be
selected natively.

- Split `disconnect` and `test_connection` out of `BaseCache` into optional
  capabilities, implemented only where the Python class defines them, and give
  every Redis-only operation its own capability trait.
- Decouple counters from the stored value type, so one backend can serve both
  responses and counters as Python's `RedisCache` does.
- Share one `Embedder` and prompt contract in `litellm_cache::semantic`, and
  make the Redis and Valkey semantic backends generic over their codec.
- Port the Python operations that were missing: `async_refresh_ttl`,
  `async_rpush_and_trim`, `async_set_cache_pipeline_with_ttls`, the DualCache
  pipeline, sadd, bulk delete and TTL reads, and the semantic-similarity
  write-back.
- Take the HTTP client from the host pool in the GCS, S3 and Azure backends.
- Activate all nine backends through the Rust catalog, whose rules all stay
  `PYTHON_ONLY`, and route the `Cache` facade's storage calls to the native
  runtime when one is selected.
- Give every crate the same layout, move all tests to `tests/` on rstest, and
  add the shared `litellm-cache-testing` contract suite.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* fix: freeze native cache request kwargs and batch entries for type discipline

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix: declare semantic lookup methods in the native stub

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(rust): align the cache crates with Python and activate every backend

The cache port had drifted: lifecycle and Redis-only operations sat on
`BaseCache`, counters were pinned to `f64`, each semantic backend defined its
own embedder and prompt handling, and only the in-memory backend could be
selected natively.

- Split `disconnect` and `test_connection` out of `BaseCache` into optional
  capabilities, implemented only where the Python class defines them, and give
  every Redis-only operation its own capability trait.
- Decouple counters from the stored value type, so one backend can serve both
  responses and counters as Python's `RedisCache` does.
- Share one `Embedder` and prompt contract in `litellm_cache::semantic`, and
  make the Redis and Valkey semantic backends generic over their codec.
- Port the Python operations that were missing: `async_refresh_ttl`,
  `async_rpush_and_trim`, `async_set_cache_pipeline_with_ttls`, the DualCache
  pipeline, sadd, bulk delete and TTL reads, and the semantic-similarity
  write-back.
- Take the HTTP client from the host pool in the GCS, S3 and Azure backends.
- Activate all nine backends through the Rust catalog, whose rules all stay
  `PYTHON_ONLY`, and route the `Cache` facade's storage calls to the native
  runtime when one is selected.
- Give every crate the same layout, move all tests to `tests/` on rstest, and
  add the shared `litellm-cache-testing` contract suite.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* fix: freeze native cache request kwargs and batch entries for type discipline

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix: declare semantic lookup methods in the native stub

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(rust): opt the native Messages and tokenizer suites into Rust explicitly

#42517 made the Messages, token counter and tokenizer routes Python-only, so
tests/test_litellm_rust silently exercised the Python path or failed outright.
Each suite now prepends a RUST_OPT_IN rule for its route, keeping native
coverage without changing the shipped default.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* fix(rust): pop one at a time in the Redis 6 lpop pipeline and drop explanatory comments

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: Yujong Lee <yujong@berri.ai>
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-09-22 13:13:02 -07:00

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Markdown

# Response cache
`ResponseCache<B>` adds request keys, independent read/write controls, response envelopes, and freshness checks to any `B: BaseCache<Value = CacheEntry>`
## Ownership
`litellm-cache` defines typed storage, codec, and capability traits. `BaseCache` is only get, set, TTL, and pipeline writes. Everything else is an optional capability a backend implements only where its Python class defines the method: `DisconnectCache`, `ConnectionCache` (`test_connection`), `PingCache`, `BatchCache`, `DeleteCache`, `FlushCache`, counters, queues, TTL, scan, and scripts. Memory, Redis, disk, S3, GCS, and Azure Blob implement those traits without depending on response policy, so other consumers can store their own value types in the same backends
Semantic backends (Redis, Valkey, Qdrant) are generic over their embedder and codec, and share one prompt and embedding contract from `litellm_cache::semantic`. They take a `SemanticCacheContext`, so `ResponseCache` drives them the same way it drives exact backends
`litellm-cache-response` owns response keys, controls, entries, the Python-compatible response codec, and `WriteBuffer`, the backend-neutral deferred-write policy. It has no runtime dependency on a specific cache backend or Python
`ExactResponseCache` is the object-safe view of a `ResponseCache` over an exact backend. `ConnectionProbe` is the object-safe `test_connection`, implemented only when the backend implements `ConnectionCache`, so a host holds one next to its `ExactResponseCache` and reports the operation as unsupported otherwise, as Python's `BaseCache` does. Lookup, store, batch, and flush never require it
## Native Rust use
```rust
use std::{sync::Arc, time::Duration};
use litellm_cache_memory::InMemoryCache;
use litellm_cache_response::{CacheKeyInput, ResponseCache, ResponseCacheRequest};
use serde_json::json;
let cache = ResponseCache::new(Arc::new(InMemoryCache::default()));
let request = ResponseCacheRequest::new(CacheKeyInput {
preset: Some("example:key".into()),
..Default::default()
});
let now = Duration::from_secs(100);
cache.store(&request, json!({"answer": 7}), now)?;
assert_eq!(cache.async_lookup(&request, now).await?, Some(json!({"answer": 7})));
```
For Redis, inject `RedisCache::new(url, ttl, ResponseCacheCodec)` instead. Namespaces are optional and existing namespace prefixes are preserved
Callers supply Unix time for response freshness. Backend TTL uses its own clock. A read can reject an entry through `max_age` even while the backend still retains it
## Python integration
The bridge activates backends through the Rust catalog in `litellm/rust_bridge/catalog.py`. Every cache rule ships as `PYTHON_ONLY`, so SDK, Router, and proxy calls stay on Python and construct no native cache resources until a rule is changed
When a rule selects a backend, the Python `Cache` facade builds the native runtime from its own configuration and routes its storage calls (sync and async lookup and store, and pipelined batch store) to it. Stream replay, embedding partial-hit merging, response reconstruction, and callbacks stay in Python on top of that native store. The Python backend object remains for its direct API
Object responses are written as they are, and every other response shape is written as a serialized string, which is the pair of shapes Python reads. A string on the wire is therefore always a serialized response, so string-valued responses round trip. Typed backends such as memory never pass through the codec
Native cache handles must be recreated after fork. Native errors propagate to the host, which owns the existing fail-open and logging policy
## Adding another backend
Implement `BaseCache` for the backend with its associated value type and the capability traits its Python class supports, and accept a `CacheCodec` when wire serialization is needed. `ResponseCache<B>` then works without another response implementation
Run the `litellm-cache-testing` contract checks the backend's capabilities allow, and run response fixtures with `ResponseCacheCodec`, including both Python envelope encodings, before adding a catalog rule