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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
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49
libs/community/langchain_community/retrievers/breebs.py
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49
libs/community/langchain_community/retrievers/breebs.py
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from typing import List
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import requests
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from langchain_core.callbacks.manager import CallbackManagerForRetrieverRun
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from langchain_core.documents.base import Document
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from langchain_core.retrievers import BaseRetriever
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class BreebsRetriever(BaseRetriever):
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"""A retriever class for `Breebs`.
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See https://www.breebs.com/ for more info.
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Args:
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breeb_key: The key to trigger the breeb
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(specialized knowledge pill on a specific topic).
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To retrieve the list of all available Breebs : you can call https://breebs.promptbreeders.com/web/listbreebs
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"""
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breeb_key: str
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url = "https://breebs.promptbreeders.com/knowledge"
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def __init__(self, breeb_key: str):
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super().__init__(breeb_key=breeb_key)
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self.breeb_key = breeb_key
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def _get_relevant_documents(
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self, query: str, *, run_manager: CallbackManagerForRetrieverRun
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) -> List[Document]:
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"""Retrieve context for given query.
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Note that for time being there is no score."""
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r = requests.post(
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self.url,
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json={
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"breeb_key": self.breeb_key,
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"query": query,
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},
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)
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if r.status_code != 200:
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return []
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else:
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chunks = r.json()
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return [
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Document(
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page_content=chunk["content"],
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metadata={"source": chunk["source_url"], "score": 1},
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)
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for chunk in chunks
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]
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