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langchain/libs/community/langchain_community/storage/mongodb.py

127 lines
4.3 KiB
Python

from typing import Iterator, List, Optional, Sequence, Tuple
from langchain_core.documents import Document
from langchain_core.stores import BaseStore
class MongoDBStore(BaseStore[str, Document]):
"""BaseStore implementation using MongoDB as the underlying store.
Examples:
Create a MongoDBStore instance and perform operations on it:
.. code-block:: python
# Instantiate the MongoDBStore with a MongoDB connection
from langchain.storage import MongoDBStore
mongo_conn_str = "mongodb://localhost:27017/"
mongodb_store = MongoDBStore(mongo_conn_str, db_name="test-db",
collection_name="test-collection")
# Set values for keys
doc1 = Document(...)
doc2 = Document(...)
mongodb_store.mset([("key1", doc1), ("key2", doc2)])
# Get values for keys
values = mongodb_store.mget(["key1", "key2"])
# [doc1, doc2]
# Iterate over keys
for key in mongodb_store.yield_keys():
print(key)
# Delete keys
mongodb_store.mdelete(["key1", "key2"])
"""
def __init__(
self,
connection_string: str,
db_name: str,
collection_name: str,
*,
client_kwargs: Optional[dict] = None,
) -> None:
"""Initialize the MongoDBStore with a MongoDB connection string.
Args:
connection_string (str): MongoDB connection string
db_name (str): name to use
collection_name (str): collection name to use
client_kwargs (dict): Keyword arguments to pass to the Mongo client
"""
try:
from pymongo import MongoClient
except ImportError as e:
raise ImportError(
"The MongoDBStore requires the pymongo library to be "
"installed. "
"pip install pymongo"
) from e
if not connection_string:
raise ValueError("connection_string must be provided.")
if not db_name:
raise ValueError("db_name must be provided.")
if not collection_name:
raise ValueError("collection_name must be provided.")
self.client = MongoClient(connection_string, **(client_kwargs or {}))
self.collection = self.client[db_name][collection_name]
def mget(self, keys: Sequence[str]) -> List[Optional[Document]]:
"""Get the list of documents associated with the given keys.
Args:
keys (list[str]): A list of keys representing Document IDs..
Returns:
list[Document]: A list of Documents corresponding to the provided
keys, where each Document is either retrieved successfully or
represented as None if not found.
"""
result = self.collection.find({"_id": {"$in": keys}})
result_dict = {doc["_id"]: Document(**doc["value"]) for doc in result}
return [result_dict.get(key) for key in keys]
def mset(self, key_value_pairs: Sequence[Tuple[str, Document]]) -> None:
"""Set the given key-value pairs.
Args:
key_value_pairs (list[tuple[str, Document]]): A list of id-document
pairs.
Returns:
None
"""
from pymongo import UpdateOne
updates = [{"_id": k, "value": v.__dict__} for k, v in key_value_pairs]
self.collection.bulk_write(
[UpdateOne({"_id": u["_id"]}, {"$set": u}, upsert=True) for u in updates]
)
def mdelete(self, keys: Sequence[str]) -> None:
"""Delete the given ids.
Args:
keys (list[str]): A list of keys representing Document IDs..
"""
self.collection.delete_many({"_id": {"$in": keys}})
def yield_keys(self, prefix: Optional[str] = None) -> Iterator[str]:
"""Yield keys in the store.
Args:
prefix (str): prefix of keys to retrieve.
"""
if prefix is None:
for doc in self.collection.find(projection=["_id"]):
yield doc["_id"]
else:
for doc in self.collection.find(
{"_id": {"$regex": f"^{prefix}"}}, projection=["_id"]
):
yield doc["_id"]