mirror of
https://github.com/hwchase17/langchain
synced 2024-11-11 19:11:02 +00:00
98 lines
2.9 KiB
Python
98 lines
2.9 KiB
Python
from __future__ import annotations
|
|
|
|
from typing import TYPE_CHECKING, Dict, List, Optional
|
|
|
|
from langchain.callbacks.manager import (
|
|
AsyncCallbackManagerForRetrieverRun,
|
|
CallbackManagerForRetrieverRun,
|
|
)
|
|
from langchain.schema import BaseRetriever, Document
|
|
|
|
if TYPE_CHECKING:
|
|
from zep_python import MemorySearchResult
|
|
|
|
|
|
class ZepRetriever(BaseRetriever):
|
|
"""A Retriever implementation for the Zep long-term memory store. 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/
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
session_id: str,
|
|
url: str,
|
|
api_key: Optional[str] = None,
|
|
top_k: Optional[int] = None,
|
|
):
|
|
try:
|
|
from zep_python import ZepClient
|
|
except ImportError:
|
|
raise ValueError(
|
|
"Could not import zep-python package. "
|
|
"Please install it with `pip install zep-python`."
|
|
)
|
|
|
|
self.zep_client = ZepClient(base_url=url, api_key=api_key)
|
|
self.session_id = session_id
|
|
self.top_k = top_k
|
|
|
|
def _search_result_to_doc(
|
|
self, results: List[MemorySearchResult]
|
|
) -> List[Document]:
|
|
return [
|
|
Document(
|
|
page_content=r.message.pop("content"),
|
|
metadata={"score": r.dist, **r.message},
|
|
)
|
|
for r in results
|
|
if r.message
|
|
]
|
|
|
|
def _get_relevant_documents(
|
|
self,
|
|
query: str,
|
|
*,
|
|
run_manager: CallbackManagerForRetrieverRun,
|
|
metadata: Optional[Dict] = None,
|
|
) -> List[Document]:
|
|
from zep_python import MemorySearchPayload
|
|
|
|
payload: MemorySearchPayload = MemorySearchPayload(
|
|
text=query, metadata=metadata
|
|
)
|
|
|
|
results: List[MemorySearchResult] = self.zep_client.search_memory(
|
|
self.session_id, payload, limit=self.top_k
|
|
)
|
|
|
|
return self._search_result_to_doc(results)
|
|
|
|
async def _aget_relevant_documents(
|
|
self,
|
|
query: str,
|
|
*,
|
|
run_manager: AsyncCallbackManagerForRetrieverRun,
|
|
metadata: Optional[Dict] = None,
|
|
) -> List[Document]:
|
|
from zep_python import MemorySearchPayload
|
|
|
|
payload: MemorySearchPayload = MemorySearchPayload(
|
|
text=query, metadata=metadata
|
|
)
|
|
|
|
results: List[MemorySearchResult] = await self.zep_client.asearch_memory(
|
|
self.session_id, payload, limit=self.top_k
|
|
)
|
|
|
|
return self._search_result_to_doc(results)
|