mirror of
https://github.com/hwchase17/langchain
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b1f22bf76c
"community: added a feature to filter documents in Mongoloader"
- **Description:** added a feature to filter documents in Mongoloader
- **Feature:** the feature #18251
- **Dependencies:** No
- **Twitter handle:** https://twitter.com/im_Kushagra
95 lines
3.1 KiB
Python
95 lines
3.1 KiB
Python
import asyncio
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import logging
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from typing import Dict, List, Optional, Sequence
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseLoader
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logger = logging.getLogger(__name__)
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class MongodbLoader(BaseLoader):
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"""Load MongoDB documents."""
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def __init__(
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self,
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connection_string: str,
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db_name: str,
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collection_name: str,
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*,
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filter_criteria: Optional[Dict] = None,
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field_names: Optional[Sequence[str]] = None,
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) -> None:
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try:
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from motor.motor_asyncio import AsyncIOMotorClient
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except ImportError as e:
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raise ImportError(
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"Cannot import from motor, please install with `pip install motor`."
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) from e
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if not connection_string:
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raise ValueError("connection_string must be provided.")
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if not db_name:
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raise ValueError("db_name must be provided.")
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if not collection_name:
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raise ValueError("collection_name must be provided.")
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self.client = AsyncIOMotorClient(connection_string)
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self.db_name = db_name
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self.collection_name = collection_name
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self.field_names = field_names
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self.filter_criteria = filter_criteria or {}
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self.db = self.client.get_database(db_name)
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self.collection = self.db.get_collection(collection_name)
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def load(self) -> List[Document]:
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"""Load data into Document objects.
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Attention:
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This implementation starts an asyncio event loop which
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will only work if running in a sync env. In an async env, it should
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fail since there is already an event loop running.
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This code should be updated to kick off the event loop from a separate
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thread if running within an async context.
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"""
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return asyncio.run(self.aload())
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async def aload(self) -> List[Document]:
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"""Load data into Document objects."""
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result = []
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total_docs = await self.collection.count_documents(self.filter_criteria)
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# Construct the projection dictionary if field_names are specified
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projection = (
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{field: 1 for field in self.field_names} if self.field_names else None
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)
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async for doc in self.collection.find(self.filter_criteria, projection):
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metadata = {
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"database": self.db_name,
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"collection": self.collection_name,
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}
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# Extract text content from filtered fields or use the entire document
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if self.field_names is not None:
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fields = {name: doc[name] for name in self.field_names}
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texts = [str(value) for value in fields.values()]
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text = " ".join(texts)
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else:
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text = str(doc)
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result.append(Document(page_content=text, metadata=metadata))
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if len(result) != total_docs:
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logger.warning(
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f"Only partial collection of documents returned. "
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f"Loaded {len(result)} docs, expected {total_docs}."
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)
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return result
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