mirror of
https://github.com/hwchase17/langchain
synced 2024-11-04 06:00:26 +00:00
91 lines
3.0 KiB
Python
91 lines
3.0 KiB
Python
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from __future__ import annotations
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from typing import List, Optional
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import aiohttp
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import requests
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from langchain_core.callbacks import (
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AsyncCallbackManagerForRetrieverRun,
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CallbackManagerForRetrieverRun,
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)
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from langchain_core.documents import Document
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from langchain_core.retrievers import BaseRetriever
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class ChatGPTPluginRetriever(BaseRetriever):
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"""`ChatGPT plugin` retriever."""
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url: str
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"""URL of the ChatGPT plugin."""
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bearer_token: str
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"""Bearer token for the ChatGPT plugin."""
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top_k: int = 3
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"""Number of documents to return."""
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filter: Optional[dict] = None
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"""Filter to apply to the results."""
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aiosession: Optional[aiohttp.ClientSession] = None
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"""Aiohttp session to use for requests."""
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class Config:
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"""Configuration for this pydantic object."""
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arbitrary_types_allowed = True
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"""Allow arbitrary types."""
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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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url, json, headers = self._create_request(query)
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response = requests.post(url, json=json, headers=headers)
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results = response.json()["results"][0]["results"]
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docs = []
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for d in results:
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content = d.pop("text")
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metadata = d.pop("metadata", d)
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if metadata.get("source_id"):
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metadata["source"] = metadata.pop("source_id")
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docs.append(Document(page_content=content, metadata=metadata))
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return docs
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async def _aget_relevant_documents(
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self, query: str, *, run_manager: AsyncCallbackManagerForRetrieverRun
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) -> List[Document]:
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url, json, headers = self._create_request(query)
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if not self.aiosession:
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async with aiohttp.ClientSession() as session:
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async with session.post(url, headers=headers, json=json) as response:
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res = await response.json()
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else:
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async with self.aiosession.post(
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url, headers=headers, json=json
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) as response:
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res = await response.json()
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results = res["results"][0]["results"]
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docs = []
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for d in results:
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content = d.pop("text")
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metadata = d.pop("metadata", d)
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if metadata.get("source_id"):
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metadata["source"] = metadata.pop("source_id")
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docs.append(Document(page_content=content, metadata=metadata))
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return docs
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def _create_request(self, query: str) -> tuple[str, dict, dict]:
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url = f"{self.url}/query"
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json = {
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"queries": [
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{
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"query": query,
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"filter": self.filter,
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"top_k": self.top_k,
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}
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]
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}
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {self.bearer_token}",
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}
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return url, json, headers
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