langchain-mongodb

from libs.community.tests.unit_tests.chains.test_pebblo_retrieval import retriever

langchain-mongodb

Installation

pip install -U langchain-mongodb

Usage

• Integrate Atlas Vector Search with LangChain for a walkthrough on using your first LangChain implementation with MongoDB Atlas.

Using MongoDBAtlasVectorSearch

import os
from langchain_mongodb import MongoDBAtlasVectorSearch
from langchain_openai import OpenAIEmbeddings

# Pull MongoDB Atlas URI from environment variables
MONGODB_ATLAS_CONNECTION_STRING = os.environ["MONGODB_CONNECTION_STRING"]
DB_NAME = "langchain_db"
COLLECTION_NAME = "test"
VECTOR_SEARCH_INDEX_NAME = "index_name"

MODEL_NAME = "text-embedding-3-large"
OPENAI_API_KEY =  os.environ["OPENAI_API_KEY"]


vectorstore = MongoDBAtlasVectorSearch.from_connection_string(
    connection_string=MONGODB_ATLAS_CONNECTION_STRING,
    namespace=DB_NAME + "." + COLLECTION_NAME,
    embedding=OpenAIEmbeddings(model=MODEL_NAME),
    index_name=VECTOR_SEARCH_INDEX_NAME,
)

retrieved_docs = vectorstore.similarity_search(
    "How do I deploy MongoDBAtlasVectorSearch in our production environment?")