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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) # type: ignore[call-arg]
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
]
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