mirror of
https://github.com/BerriAI/litellm.git
synced 2026-11-13 08:52:02 +00:00
chore(caching)!: remove the disk cache backend
Drop the disk cache type and its diskcache dependency, along with the caching install extra that existed only to pull it in. diskcache has not had a release since August 2023 Cache now raises a ValueError listing the supported types when it gets a type it does not know. Before, an unknown type built a Cache with no backend, which only failed on first use BREAKING CHANGE: cache_params type "disk" and the litellm[caching] extra are gone. A proxy configured with type disk now refuses to start. Use local or redis instead
This commit is contained in:
Yuneng Jiang
parent
f3d53a9b50
commit
041ed94e95
14 changed files with 23 additions and 290 deletions
8
.github/workflows/test-unit.yml
vendored
8
.github/workflows/test-unit.yml
vendored
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@ -996,9 +996,9 @@ jobs:
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run: |
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diff -u model_prices_and_context_window.json litellm/model_prices_and_context_window_backup.json
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if [ -z "$RUST_BRIDGE_ARTIFACT" ]; then
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra caching --extra extra_proxy --extra proxy-runtime --extra utils
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra extra_proxy --extra proxy-runtime --extra utils
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else
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra caching --extra extra_proxy --extra proxy-runtime --extra utils --no-install-project
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra extra_proxy --extra proxy-runtime --extra utils --no-install-project
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uv pip install --no-deps --python .venv/bin/python rust-bridge-dist/*.whl
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cp rust-bridge-dist/litellm/rust_bridge/_native.abi3.so litellm/rust_bridge/_native.abi3.so
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uv run --no-sync python -c "import importlib.metadata; import litellm.rust_bridge._native; print(importlib.metadata.version('litellm'))"
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@ -1434,9 +1434,9 @@ jobs:
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RUST_BRIDGE_ARTIFACT: ${{ needs.rust-bridge.outputs.artifact }}
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run: |
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if [ -z "$RUST_BRIDGE_ARTIFACT" ]; then
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra caching --extra extra_proxy --extra proxy-runtime --extra utils
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra extra_proxy --extra proxy-runtime --extra utils
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else
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra caching --extra extra_proxy --extra proxy-runtime --extra utils --no-install-project
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.github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml --extra extra_proxy --extra proxy-runtime --extra utils --no-install-project
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uv pip install --no-deps --python .venv/bin/python rust-bridge-dist/*.whl
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cp rust-bridge-dist/litellm/rust_bridge/_native.abi3.so litellm/rust_bridge/_native.abi3.so
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fi
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File diff suppressed because one or more lines are too long
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@ -8,10 +8,9 @@ The following caching mechanisms are supported:
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2. **RedisSemanticCache**
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3. **QdrantSemanticCache**
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4. **InMemoryCache**
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5. **DiskCache**
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6. **S3Cache**
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7. **AzureBlobCache**
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8. **DualCache** (updates both Redis and an in-memory cache simultaneously)
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5. **S3Cache**
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6. **AzureBlobCache**
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7. **DualCache** (updates both Redis and an in-memory cache simultaneously)
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## Folder Structure
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@ -20,7 +19,6 @@ litellm/caching/
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├── base_cache.py
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├── caching.py
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├── caching_handler.py
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├── disk_cache.py
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├── dual_cache.py
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├── in_memory_cache.py
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├── qdrant_semantic_cache.py
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@ -1,6 +1,5 @@
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from .azure_blob_cache import AzureBlobCache
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from .caching import Cache, LiteLLMCacheType
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from .disk_cache import DiskCache
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from .dual_cache import DualCache
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from .gcs_cache import GCSCache
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from .in_memory_cache import InMemoryCache
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@ -31,7 +31,6 @@ from litellm.types.utils import EmbeddingResponse, is_litellm_owned_kwarg
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from .azure_blob_cache import AzureBlobCache
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from .base_cache import BaseCache
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from .disk_cache import DiskCache
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from .dual_cache import DualCache # noqa: F401 # re-exported, callers import DualCache from litellm.caching.caching
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from .gcs_cache import GCSCache
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from .in_memory_cache import InMemoryCache
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@ -132,7 +131,6 @@ class Cache:
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valkey_semantic_cache_index_name: str | None = None,
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redis_flush_size: int | None = None,
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redis_startup_nodes: list | None = None,
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disk_cache_dir: str | None = None,
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qdrant_api_base: str | None = None,
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qdrant_api_key: str | None = None,
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qdrant_collection_name: str | None = None,
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@ -153,7 +151,7 @@ class Cache:
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Initializes the cache based on the given type.
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Args:
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type (str, optional): The type of cache to initialize. Can be "local", "redis", "redis-semantic", "qdrant-semantic", "s3" or "disk". Defaults to "local".
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type (str, optional): The type of cache to initialize. Can be "local", "redis", "redis-semantic", "qdrant-semantic" or "s3". Defaults to "local".
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# Redis Cache Args
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host (str, optional): The host address for the Redis cache. Required if type is "redis".
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@ -174,9 +172,6 @@ class Cache:
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semantic_cache_scope (str, optional): "key" isolates semantic-cache buckets per key/team/org. "end_user" additionally isolates per end user (falls back to the key scope when the request carries no end-user id). Defaults to "key".
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max_messages (int, optional): Requests with more `messages` (or Responses API `input` items) than this are neither looked up nor stored, so long agent conversations never serve or create a cache entry. None disables the limit. Defaults to 4.
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# Disk Cache Args
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disk_cache_dir (str, optional): The directory for the disk cache. Defaults to None.
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# S3 Cache Args
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s3_bucket_name (str, optional): The bucket name for the s3 cache. Defaults to None.
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s3_region_name (str, optional): The region name for the s3 cache. Defaults to None.
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@ -306,8 +301,9 @@ class Cache:
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account_url=azure_account_url,
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container=azure_blob_container,
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)
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elif type == LiteLLMCacheType.DISK:
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self.cache = DiskCache(disk_cache_dir=disk_cache_dir)
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else:
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supported_types: Final = ", ".join(member.value for member in LiteLLMCacheType)
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raise ValueError(f"Unsupported cache type {type!r}. Supported types: {supported_types}")
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if "cache" not in litellm.input_callback:
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litellm.input_callback.append("cache")
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if "cache" not in litellm.success_callback:
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@ -1028,7 +1024,7 @@ def enable_cache(
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Enable cache with the specified configuration.
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Args:
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type (Optional[Literal["local", "redis", "s3", "disk"]]): The type of cache to enable. Defaults to "local".
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type (Optional[Literal["local", "redis", "s3"]]): The type of cache to enable. Defaults to "local".
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host (Optional[str]): The host address of the cache server. Defaults to None.
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port (Optional[str]): The port number of the cache server. Defaults to None.
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password (Optional[str]): The password for the cache server. Defaults to None.
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@ -1075,7 +1071,7 @@ def update_cache(
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Update the cache for LiteLLM.
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Args:
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type (Optional[Literal["local", "redis", "s3", "disk"]]): The type of cache. Defaults to "local".
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type (Optional[Literal["local", "redis", "s3"]]): The type of cache. Defaults to "local".
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host (Optional[str]): The host of the cache. Defaults to None.
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port (Optional[str]): The port of the cache. Defaults to None.
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password (Optional[str]): The password for the cache. Defaults to None.
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@ -9,7 +9,7 @@ This file is a wrapper around caching.py
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This class is used to handle caching logic specific for LLM API requests (completion / embedding / text_completion / transcription etc)
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It utilizes the (RedisCache, s3Cache, RedisSemanticCache, QdrantSemanticCache, InMemoryCache, DiskCache) based on what the user has setup
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It utilizes the (RedisCache, s3Cache, RedisSemanticCache, QdrantSemanticCache, InMemoryCache) based on what the user has setup
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In each method it will call the appropriate method from caching.py
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"""
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@ -1,88 +0,0 @@
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import json
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from typing import TYPE_CHECKING, Any, Final
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from .base_cache import BaseCache
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if TYPE_CHECKING:
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from opentelemetry.trace import Span as _Span
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Span = _Span | Any
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else:
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Span = Any
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class DiskCache(BaseCache):
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def __init__(self, disk_cache_dir: str | None = None):
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try:
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import diskcache as dc
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except ModuleNotFoundError as e:
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raise ModuleNotFoundError("Please install litellm with `litellm[caching]` to use disk caching.") from e
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# if users don't provider one, use the default litellm cache
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if disk_cache_dir is None:
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self.disk_cache = dc.Cache(".litellm_cache")
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else:
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self.disk_cache = dc.Cache(disk_cache_dir)
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def set_cache(self, key, value, **kwargs):
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if "ttl" in kwargs:
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self.disk_cache.set(key, value, expire=kwargs["ttl"])
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else:
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self.disk_cache.set(key, value)
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async def async_set_cache(self, key, value, **kwargs):
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self.set_cache(key=key, value=value, **kwargs)
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async def async_set_cache_pipeline(self, cache_list, **kwargs):
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for cache_key, cache_value in cache_list:
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if "ttl" in kwargs:
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self.set_cache(key=cache_key, value=cache_value, ttl=kwargs["ttl"])
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else:
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self.set_cache(key=cache_key, value=cache_value)
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def get_cache(self, key, **kwargs):
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original_cached_response: Final = self.disk_cache.get(key)
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if original_cached_response:
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try:
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cached_response = json.loads(original_cached_response)
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except Exception:
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cached_response = original_cached_response
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return cached_response
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return None
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def batch_get_cache(self, keys: list, **kwargs):
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return_val: Final = []
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for k in keys:
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val = self.get_cache(key=k, **kwargs)
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return_val.append(val)
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return return_val
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def increment_cache(self, key, value: int, **kwargs) -> int:
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with self.disk_cache.transact():
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cached_value: Final = self.get_cache(key=key)
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init_value: Final = cached_value if isinstance(cached_value, int) else 0
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new_value: Final = init_value + value
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self.set_cache(key, new_value, **kwargs)
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return new_value
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async def async_get_cache(self, key, **kwargs):
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return self.get_cache(key=key, **kwargs)
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async def async_batch_get_cache(self, keys: list, **kwargs):
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return_val: Final = []
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for k in keys:
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val = self.get_cache(key=k, **kwargs)
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return_val.append(val)
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return return_val
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async def async_increment(self, key, value: int, **kwargs) -> int:
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return self.increment_cache(key=key, value=value, **kwargs)
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def flush_cache(self):
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self.disk_cache.clear()
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async def disconnect(self):
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pass
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def delete_cache(self, key):
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self.disk_cache.pop(key)
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@ -1343,7 +1343,7 @@ class Router:
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self.deployment_names: list = [] # names of models under litellm_params. ex. azure/chatgpt-v-2
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self.deployment_latency_map = {}
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### CACHING ###
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cache_type: Literal["local", "redis", "redis-semantic", "s3", "disk"] = "local" # default to an in-memory cache
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cache_type: Literal["local", "redis", "redis-semantic", "s3"] = "local" # default to an in-memory cache
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redis_cache = None
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cache_config: Final[dict[str, Any]] = {}
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@ -13,7 +13,6 @@ class LiteLLMCacheType(str, Enum):
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REDIS_SEMANTIC = "redis-semantic"
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VALKEY_SEMANTIC = "valkey-semantic"
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S3 = "s3"
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DISK = "disk"
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QDRANT_SEMANTIC = "qdrant-semantic"
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AZURE_BLOB = "azure-blob"
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GCS = "gcs"
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@ -1,8 +1,3 @@
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[[IgnoredVulns]]
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id = "GHSA-w8v5-vhqr-4h9v"
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ignoreUntil = 2026-11-01
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reason = "diskcache has no fixed release published; remove this entry once one exists"
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[[IgnoredVulns]]
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id = "GHSA-vfj7-8cjw-p6xm"
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ignoreUntil = 2026-11-03
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@ -125,7 +125,6 @@ utils = [
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# Not in Docker or PyPI proxy extra.
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"numpydoc>=1.8.0,<2.0",
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]
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caching = ["diskcache>=5.6.3,<6.0"]
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mcp = ["mcp>=2.3.0,<3", "httpx2>=2.10.0,<3", "pydantic>=2.12.0,<3"]
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# Driver for the MongoDB Atlas vector store; Atlas Vector Search has no HTTP query API.
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# The floor is 4.9 because that is the release AsyncMongoClient landed in.
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@ -250,6 +250,13 @@ def test_semantic_cache_key_reads_tenant_identity_from_litellm_metadata():
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assert key_a == key_a_in_litellm_params
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@pytest.mark.parametrize("cache_type", ["disk", "not-a-cache"])
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def test_cache_rejects_unsupported_type(cache_type: str) -> None:
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cache_params: Final = {"type": cache_type}
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with pytest.raises(ValueError, match=f"Unsupported cache type '{cache_type}'. Supported types: local, redis,"):
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Cache(**cache_params)
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def test_semantic_cache_scope_rejects_unknown_value():
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with pytest.raises(ValueError, match="'team' is not a valid SemanticCacheScope"):
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_semantic_cache(semantic_cache_scope="team")
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@ -1,158 +0,0 @@
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import threading
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import time
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from concurrent.futures import ThreadPoolExecutor
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import pytest
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pytest.importorskip("diskcache")
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from litellm.caching.disk_cache import DiskCache
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from tests._wait_helpers import await_until
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class _SlowInt(int):
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def __add__(self, value: int) -> "_SlowInt":
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time.sleep(0.05)
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return _SlowInt(int(self) + value)
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@pytest.fixture
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def cache(tmp_path):
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return DiskCache(disk_cache_dir=str(tmp_path))
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def test_increment_cache_starts_from_zero_when_key_missing(cache):
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assert cache.increment_cache("counter", 3) == 3
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assert cache.get_cache("counter") == 3
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def test_increment_cache_adds_to_existing_int(cache):
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cache.set_cache("counter", 7)
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assert cache.increment_cache("counter", 5) == 12
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assert cache.get_cache("counter") == 12
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def test_increment_cache_treats_non_int_cached_value_as_zero(cache):
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cache.set_cache("counter", "not-a-number")
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assert cache.increment_cache("counter", 4) == 4
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assert cache.get_cache("counter") == 4
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def test_increment_cache_is_atomic_under_thread_concurrency(cache):
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seed = 1000
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cache.set_cache("counter", _SlowInt(seed))
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thread_count = 8
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barrier = threading.Barrier(thread_count)
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def increment(_: int) -> int:
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barrier.wait()
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return cache.increment_cache("counter", 1)
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with ThreadPoolExecutor(max_workers=thread_count) as executor:
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tuple(executor.map(increment, range(thread_count)))
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assert cache.get_cache("counter") == seed + thread_count
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async def test_async_increment_starts_from_zero_when_key_missing(cache):
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assert await cache.async_increment("counter", 2) == 2
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async def test_async_increment_adds_to_existing_int(cache):
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await cache.async_set_cache("counter", 10)
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assert await cache.async_increment("counter", 5) == 15
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async def test_async_increment_treats_non_int_cached_value_as_zero(cache):
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await cache.async_set_cache("counter", "corrupt")
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assert await cache.async_increment("counter", 9) == 9
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@pytest.fixture
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def disk_cache(tmp_path):
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import litellm
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from litellm.caching import Cache
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litellm.cache = Cache(type="disk", disk_cache_dir=str(tmp_path))
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yield litellm.cache
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litellm.cache = None
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COMPLETION_MESSAGES = [{"role": "user", "content": "write a one sentence poem about: disk-cache-unit-key"}]
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def test_completion_is_served_from_disk_cache_until_params_change(disk_cache):
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import litellm
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first = litellm.completion(
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"gpt-3.5-turbo", messages=COMPLETION_MESSAGES, caching=True, max_tokens=20, mock_response="first"
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)
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repeat = litellm.completion(
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"gpt-3.5-turbo", messages=COMPLETION_MESSAGES, caching=True, max_tokens=20, mock_response="second"
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)
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changed = litellm.completion(
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"gpt-3.5-turbo", messages=COMPLETION_MESSAGES, caching=True, temperature=0.5, mock_response="third"
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)
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assert (repeat.choices[0].message.content, repeat.id, repeat.created) == (
|
||||
first.choices[0].message.content,
|
||||
first.id,
|
||||
first.created,
|
||||
)
|
||||
assert changed.choices[0].message.content == "third"
|
||||
|
||||
|
||||
async def test_async_completion_is_served_from_disk_cache_until_params_change(disk_cache):
|
||||
import litellm
|
||||
|
||||
first = await litellm.acompletion(
|
||||
"gpt-3.5-turbo", messages=COMPLETION_MESSAGES, caching=True, max_tokens=20, mock_response="first"
|
||||
)
|
||||
await await_until(lambda: len(disk_cache.cache.disk_cache) == 1, message="the first completion is cached")
|
||||
repeat = await litellm.acompletion(
|
||||
"gpt-3.5-turbo", messages=COMPLETION_MESSAGES, caching=True, max_tokens=20, mock_response="second"
|
||||
)
|
||||
changed = await litellm.acompletion(
|
||||
"gpt-3.5-turbo", messages=COMPLETION_MESSAGES, caching=True, temperature=0.5, mock_response="third"
|
||||
)
|
||||
|
||||
assert (repeat.choices[0].message.content, repeat.id, repeat.created) == (
|
||||
first.choices[0].message.content,
|
||||
first.id,
|
||||
first.created,
|
||||
)
|
||||
assert changed.choices[0].message.content == "third"
|
||||
|
||||
|
||||
async def test_embedding_is_served_from_disk_cache_until_params_change(disk_cache, respx_mock, monkeypatch):
|
||||
import httpx
|
||||
|
||||
import litellm
|
||||
|
||||
monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
|
||||
input_text = ["hello disk-embedding-unit-key"]
|
||||
embeddings_route = respx_mock.post("https://api.openai.com/v1/embeddings").mock(
|
||||
return_value=httpx.Response(
|
||||
200,
|
||||
json={
|
||||
"object": "list",
|
||||
"data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}],
|
||||
"model": "text-embedding-ada-002",
|
||||
"usage": {"prompt_tokens": 2, "total_tokens": 2},
|
||||
},
|
||||
)
|
||||
)
|
||||
|
||||
await litellm.aembedding("openai/text-embedding-ada-002", input=input_text, caching=True, api_key="sk-unit")
|
||||
await await_until(lambda: len(disk_cache.cache.disk_cache) == 1, message="the first embedding is cached")
|
||||
cached = await litellm.aembedding(
|
||||
"openai/text-embedding-ada-002", input=input_text, caching=True, api_key="sk-unit"
|
||||
)
|
||||
assert cached._hidden_params["cache_hit"] is True
|
||||
assert cached.data[0]["embedding"] == [0.1, 0.2, 0.3]
|
||||
assert embeddings_route.call_count == 1
|
||||
|
||||
await litellm.aembedding(
|
||||
"openai/text-embedding-ada-002", input=input_text, caching=True, user="charlie", api_key="sk-unit"
|
||||
)
|
||||
assert embeddings_route.call_count == 2
|
||||
15
uv.lock
generated
15
uv.lock
generated
|
|
@ -1858,15 +1858,6 @@ wheels = [
|
|||
{ url = "https://files.pythonhosted.org/packages/1e/77/dc8c558f7593132cf8fefec57c4f60c83b16941c574ac5f619abb3ae7933/dill-0.4.1-py3-none-any.whl", hash = "sha256:1e1ce33e978ae97fcfcff5638477032b801c46c7c65cf717f95fbc2248f79a9d", size = 120019, upload-time = "2026-01-19T02:36:55.663Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "diskcache"
|
||||
version = "5.6.3"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/3f/21/1c1ffc1a039ddcc459db43cc108658f32c57d271d7289a2794e401d0fdb6/diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc", size = 67916, upload-time = "2023-08-31T06:12:00.316Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/3f/27/4570e78fc0bf5ea0ca45eb1de3818a23787af9b390c0b0a0033a1b8236f9/diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19", size = 45550, upload-time = "2023-08-31T06:11:58.822Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "distro"
|
||||
version = "1.9.0"
|
||||
|
|
@ -4667,9 +4658,6 @@ dependencies = [
|
|||
bedrock-realtime = [
|
||||
{ name = "aws-sdk-bedrock-runtime", extra = ["awscrt"], marker = "python_full_version >= '3.12'" },
|
||||
]
|
||||
caching = [
|
||||
{ name = "diskcache" },
|
||||
]
|
||||
cli = [
|
||||
{ name = "inquirerpy" },
|
||||
{ name = "keyring" },
|
||||
|
|
@ -4919,7 +4907,6 @@ requires-dist = [
|
|||
{ name = "cryptography", marker = "extra == 'proxy'", specifier = ">=49.0.0,<51.0" },
|
||||
{ name = "ddtrace", marker = "extra == 'proxy-runtime'", specifier = ">=4.8.2,<5.0" },
|
||||
{ name = "detect-secrets", marker = "extra == 'proxy-runtime'", specifier = ">=1.5.0,<2.0" },
|
||||
{ name = "diskcache", marker = "extra == 'caching'", specifier = ">=5.6.3,<6.0" },
|
||||
{ name = "expression", marker = "extra == 'proxy'", specifier = ">=5.6.0,<6.0" },
|
||||
{ name = "fastapi", marker = "extra == 'proxy'", specifier = ">=0.136.3,<1.0" },
|
||||
{ name = "fastapi-sso", marker = "extra == 'proxy'", specifier = ">=0.19.0,<1.0" },
|
||||
|
|
@ -5007,7 +4994,7 @@ requires-dist = [
|
|||
{ name = "uvloop", marker = "sys_platform != 'win32' and extra == 'proxy'", specifier = ">=0.22.1,<1.0" },
|
||||
{ name = "websockets", marker = "extra == 'proxy'", specifier = ">=15.0.1,<16.0" },
|
||||
]
|
||||
provides-extras = ["proxy", "cli", "extra-proxy", "utils", "caching", "mcp", "saml", "semantic-router", "mlflow", "grpc", "stt-vertex-chirp", "stt-nvidia-riva", "google", "bedrock-realtime", "proxy-runtime"]
|
||||
provides-extras = ["proxy", "cli", "extra-proxy", "utils", "mcp", "saml", "semantic-router", "mlflow", "grpc", "stt-vertex-chirp", "stt-nvidia-riva", "google", "bedrock-realtime", "proxy-runtime"]
|
||||
|
||||
[package.metadata.requires-dev]
|
||||
admin-mcp = [{ name = "litellm-admin-mcp", marker = "python_full_version >= '3.12'", url = "https://github.com/BerriAI/liteadmin-mcp/archive/d35ec9c19c117d4c50cc1eccf6ce1296aac25a1a.tar.gz" }]
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue