langchain.retrievers.zep.ZepRetriever¶
class langchain.retrievers.zep.ZepRetriever[source]¶
Bases: BaseRetriever
Zep long-term memory store retriever.
Search your user’s long-term chat history with Zep.
Note: You will need to provide the user’s session_id to use this retriever.
More on Zep:
Zep provides long-term conversation storage for LLM apps. The server stores,
summarizes, embeds, indexes, and enriches conversational AI chat
histories, and exposes them via simple, low-latency APIs.
For server installation instructions, see:
https://docs.getzep.com/deployment/quickstart/
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the retriever. Defaults to None
This metadata will be associated with each call to this retriever,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a retriever with its
use case.
param session_id: str [Required]¶
Zep session ID.
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the retriever. Defaults to None
These tags will be associated with each call to this retriever,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a retriever with its
use case.
param top_k: Optional[int] = None¶
Number of documents to return.
param zep_client: Any = None¶
Zep client.