Langchain mongodb nodejs github. View the GitHub repo for the implementation code.
Langchain mongodb nodejs github This component stores each entity as a document with relationship fields that reference other documents in your collection. It contains the following packages. It includes integrations between MongoDB, Atlas, LangChain, and LangGraph. 0, last published: 9 months ago. . LangChain. 1. js file. langchain-mongodb ; langgraph-checkpoint-mongodb ; Note: This repository replaces all MongoDB integrations currently present in the langchain-community package Sample integration for LangChain. There are 9 other projects in the npm registry using @langchain/mongodb. View the GitHub repo for the implementation code. Latest version: 0. Start using @langchain/mongodb in your project by running `npm i @langchain/mongodb`. js. Add the following code to the asynchronous function that you defined in your get-started. js supports MongoDB Atlas as a vector store, and supports both standard similarity search and maximal marginal relevance search, which takes a combination of documents are most similar to To enable vector search queries on your vector store, create an Atlas Vector Search index on the langchain_db. Jun 6, 2024 ยท I showed you how to connect your MongoDB database to LangChain and LlamaIndex separately, load the data, create embeddings, store them back to the MongoDB collection, and then execute a semantic search using MongoDB Atlas vector search capabilities. RAG implementation with LangChain (node. test collection. This is a Monorepo containing partner packages of MongoDB and LangChainAI. js) and MongoDB - davidhou17/langchain-mongodb MongoDBGraphStore is a component in the LangChain MongoDB integration that allows you to implement GraphRAG by storing entities (nodes) and their relationships (edges) in a MongoDB collection. pqunijphbloylnvnpbfwajycyajktxwtwdfluewjbbdhresldthgr