langchain/libs/community/langchain_community/retrievers/breebs.py
Alex Boury 334b6ebdf3
community[minor]: Breebs docs retriever (#16578)
- **Description:** Implementation of breeb retriever with integration
tests ->
libs/community/tests/integration_tests/retrievers/test_breebs.py and
documentation (notebook) ->
docs/docs/integrations/retrievers/breebs.ipynb.
  - **Dependencies:** None
2024-02-05 15:51:08 -08:00

50 lines
1.5 KiB
Python

from typing import List
import requests
from langchain_core.callbacks.manager import CallbackManagerForRetrieverRun
from langchain_core.documents.base import Document
from langchain_core.retrievers import BaseRetriever
class BreebsRetriever(BaseRetriever):
"""A retriever class for `Breebs`.
See https://www.breebs.com/ for more info.
Args:
breeb_key: The key to trigger the breeb
(specialized knowledge pill on a specific topic).
To retrieve the list of all available Breebs : you can call https://breebs.promptbreeders.com/web/listbreebs
"""
breeb_key: str
url = "https://breebs.promptbreeders.com/knowledge"
def __init__(self, breeb_key: str):
super().__init__(breeb_key=breeb_key)
self.breeb_key = breeb_key
def _get_relevant_documents(
self, query: str, *, run_manager: CallbackManagerForRetrieverRun
) -> List[Document]:
"""Retrieve context for given query.
Note that for time being there is no score."""
r = requests.post(
self.url,
json={
"breeb_key": self.breeb_key,
"query": query,
},
)
if r.status_code != 200:
return []
else:
chunks = r.json()
return [
Document(
page_content=chunk["content"],
metadata={"source": chunk["source_url"], "score": 1},
)
for chunk in chunks
]