Langchain mongodb npm github. Reload to refresh your session.
Langchain mongodb npm github There are 4 other projects in the npm registry using @langchain/langgraph-checkpoint-mongodb. 6, last published: 4 months ago. It contains the following packages. Start using @langchain/langgraph-checkpoint-mongodb in your project by running `npm i @langchain/langgraph-checkpoint-mongodb`. I'm running langchain in a project that already contains a mongodb. There are 9 other projects in the npm registry using @langchain/mongodb. You switched accounts on another tab or window. This repository demonstrates how to use LangGraph with MongoDB for building and managing AI agents and conversational applications using an agentic approach. When I install langchain in this project, I'm getting depency conflicts: npm ERR! code ERESOLVE npm ERR! LangChain. 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 the inputs, then reranks and optimizes for diversity. Learn how semantic search and embeddings revolutionize data retrieval. , mongodb@^6. MongoDB is a NoSQL , document-oriented database that supports JSON-like documents with a dynamic schema. This is a Monorepo containing partner packages of MongoDB and LangChainAI. Upgrade the mongodb dependency in the @langchain/community package to align with the latest version required by other packages (i. js. The Loader requires the following parameters: MongoDB connection string; MongoDB database name; MongoDB collection name For longer-term persistence across chat sessions, you can swap out the default in-memory chatHistory that backs chat memory classes like BufferMemory for a MongoDB instance. You signed out in another tab or window. This starter template implements a Retrieval-Augmented Generation (RAG) chatbot using LangChain, MongoDB Atlas, and Render. Reload to refresh your session. This will resolve the dependency conflict and allow for smooth project setup. Chains are LangChain-specific components that can be combined for a variety of AI use cases, including RAG. langchain-mongodb ; langgraph-checkpoint-mongodb ; Note: This repository replaces all MongoDB integrations currently present in the langchain-community package Enabling semantic search on user-specific data is a multi-step process that includes loading, transforming, embedding and storing data before it can be queried. RAG Based Chat-bot using Langchain, MongoDB Atlas, and SingleStore Kai This project implements a Retrieval-Augmented Generation (RAG) chatbot using LangChain, MongoDB Atlas, and SingleStore Kai. Sep 18, 2024 · Discover the integration of MongoDB Atlas Vector Search with LangChain, in Python. To use MongoDB Atlas vector stores, you’ll need to configure a MongoDB Atlas cluster and install the @langchain/mongodb integration package. LangChain simplifies building the chatbot logic, while MongoDB Atlas' vector LangGraph. js, the Vercel AI SDK, OpenAI, LangChain, and MongoDB 💬 - nsoybean/chatbot-ui. 0. 2# Integrate your operational database and vector search in a single, unified, fully managed platform with full vector database capabilities on MongoDB Atlas. It combines AI language generation with knowledge retrieval for more informative responses. Overview The MongoDB Document Loader returns a list of Langchain Documents from a MongoDB database. 7. from_conn_string (MONGODB_URI, DB_NAME) as checkpointer: checkpoint = { "v": 1, "ts": "2024-07-31T20:14:19. 0). Initial Cluster Configuration To create a MongoDB Atlas cluster, navigate to the MongoDB Atlas website and create an account if you don’t already have one. e. 804150+00:00", You signed in with another tab or window. That graphic is from the team over at LangChain, whose goal is to provide a set of utilities to greatly simplify this process. It includes integrations between MongoDB, Atlas, LangChain, and LangGraph. Implementation of LangGraph CheckpointSaver that uses MongoDB. Start using @langchain/mongodb in your project by running `npm i @langchain/mongodb`. Sample integration for LangChain. read_config = {"configurable": {"thread_id": "1"}} MONGODB_URI = "mongodb://localhost:27017" DB_NAME = "checkpoint_example" with MongoDBSaver. It showcases the integration of language models, graph-based conversation management, and MongoDB for data persistence, enabling the creation Marketing Chatbot built with Next. 6. By integrating Atlas Vector Search with LangChain, you can use Atlas as a vector database and use Atlas Vector Search to implement RAG by retrieving semantically similar documents from langchain-mongodb: 0. 0, last published: 9 months ago. Store your operational data, metadata, and vector embeddings in oue VectorStore, MongoDBAtlasVectorSearch. Latest version: 0. Voyage AI joins MongoDB to power more accurate and trustworthy AI applications on Atlas. RAG combines AI language generation with knowledge retrieval for more informative responses. LangChain. 1. Saved searches Use saved searches to filter your results more quickly MongoDB. qtzwnswliwwbqhpczurbtdkkqjfwdylyqpzqevryznbprhppe