o gp%@sdZddlmZddlmZmZddlmZddlm Z m Z ddl m Z ddl mZee ZGdd d eZGd d d eZd S) a< .. warning:: Beta Feature! **Cache** provides an optional caching layer for LLMs. Cache is useful for two reasons: - It can save you money by reducing the number of API calls you make to the LLM provider if you're often requesting the same completion multiple times. - It can speed up your application by reducing the number of API calls you make to the LLM provider. Cache directly competes with Memory. See documentation for Pros and Cons. **Class hierarchy:** .. code-block:: BaseCache --> Cache # Examples: InMemoryCache, RedisCache, GPTCache ) annotations)ABCabstractmethod)Sequence)AnyOptional) Generation)run_in_executorc@sXeZdZdZedddZedd d ZedddZdddZdddZ dddZ dS) BaseCacheaFInterface for a caching layer for LLMs and Chat models. The cache interface consists of the following methods: - lookup: Look up a value based on a prompt and llm_string. - update: Update the cache based on a prompt and llm_string. - clear: Clear the cache. In addition, the cache interface provides an async version of each method. The default implementation of the async methods is to run the synchronous method in an executor. It's recommended to override the async methods and provide async implementations to avoid unnecessary overhead. promptstr llm_stringreturnOptional[RETURN_VAL_TYPE]cCdS)aLook up based on prompt and llm_string. A cache implementation is expected to generate a key from the 2-tuple of prompt and llm_string (e.g., by concatenating them with a delimiter). Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. This is used to capture the invocation parameters of the LLM (e.g., model name, temperature, stop tokens, max tokens, etc.). These invocation parameters are serialized into a string representation. Returns: On a cache miss, return None. On a cache hit, return the cached value. The cached value is a list of Generations (or subclasses). Nselfr r rrQ/var/www/html/chatdoc2/venv/lib/python3.10/site-packages/langchain_core/caches.pylookup3zBaseCache.lookup return_valRETURN_VAL_TYPENonecCr)aVUpdate cache based on prompt and llm_string. The prompt and llm_string are used to generate a key for the cache. The key should match that of the lookup method. Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. This is used to capture the invocation parameters of the LLM (e.g., model name, temperature, stop tokens, max tokens, etc.). These invocation parameters are serialized into a string representation. return_val: The value to be cached. The value is a list of Generations (or subclasses). Nrrr r rrrrupdateIrzBaseCache.updatekwargsrcKr)z7Clear cache that can take additional keyword arguments.Nrrrrrrclear]rzBaseCache.clearcstd|j||IdHS)aAsync look up based on prompt and llm_string. A cache implementation is expected to generate a key from the 2-tuple of prompt and llm_string (e.g., by concatenating them with a delimiter). Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. This is used to capture the invocation parameters of the LLM (e.g., model name, temperature, stop tokens, max tokens, etc.). These invocation parameters are serialized into a string representation. Returns: On a cache miss, return None. On a cache hit, return the cached value. The cached value is a list of Generations (or subclasses). N)r rrrrralookupaszBaseCache.alookupcstd|j|||IdHS)a]Async update cache based on prompt and llm_string. The prompt and llm_string are used to generate a key for the cache. The key should match that of the look up method. Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. This is used to capture the invocation parameters of the LLM (e.g., model name, temperature, stop tokens, max tokens, etc.). These invocation parameters are serialized into a string representation. return_val: The value to be cached. The value is a list of Generations (or subclasses). N)r rrrrraupdatewszBaseCache.aupdatecstd|jfi|IdHS)z=Async clear cache that can take additional keyword arguments.N)r rrrrraclearszBaseCache.aclearNr r r r rrr r r r rrrrrrrr) __name__ __module__ __qualname____doc__rrrrrr r!rrrrr #s     r c@s\eZdZdZddddd ZdddZd ddZd!ddZdddZd ddZ d!ddZ dS)" InMemoryCachez#Cache that stores things in memory.N)maxsizer* Optional[int]rrcCs,i|_|dur|dkrd}t|||_dS)azInitialize with empty cache. Args: maxsize: The maximum number of items to store in the cache. If None, the cache has no maximum size. If the cache exceeds the maximum size, the oldest items are removed. Default is None. Raises: ValueError: If maxsize is less than or equal to 0. Nrzmaxsize must be greater than 0)_cache ValueError_maxsize)rr*msgrrr__init__s   zInMemoryCache.__init__r r r rcCs|j||fdS)aLook up based on prompt and llm_string. Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. Returns: On a cache miss, return None. On a cache hit, return the cached value. N)r,getrrrrrs zInMemoryCache.lookuprrcCs>|jdurt|j|jkr|jtt|j=||j||f<dS)aUpdate cache based on prompt and llm_string. Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. return_val: The value to be cached. The value is a list of Generations (or subclasses). N)r.lenr,nextiterrrrrrs zInMemoryCache.updaterrcKs i|_dS)z Clear cache.N)r,rrrrrs zInMemoryCache.clearcs|||S)aAsync look up based on prompt and llm_string. Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. Returns: On a cache miss, return None. On a cache hit, return the cached value. )rrrrrrs zInMemoryCache.alookupcs||||dS)aAsync update cache based on prompt and llm_string. Args: prompt: a string representation of the prompt. In the case of a Chat model, the prompt is a non-trivial serialization of the prompt into the language model. llm_string: A string representation of the LLM configuration. return_val: The value to be cached. The value is a list of Generations (or subclasses). N)rrrrrr s zInMemoryCache.aupdatecs|dS)zAsync clear cache.N)rrrrrr!s zInMemoryCache.aclear)r*r+rrr"r#r$) r%r&r'r(r0rrrrr r!rrrrr)s     r)N)r( __future__rabcrrcollections.abcrtypingrrlangchain_core.outputsrlangchain_core.runnablesr rr r)rrrrs    o