Langchain mongodb npm download. @langchain/openai, @langchain/anthropic, etc.
Langchain mongodb npm download langchain-mongodb ; langgraph-checkpoint-mongodb ; Note: This repository replaces all MongoDB integrations currently present in the langchain-community package Defines a LangChain prompt template to instruct the LLM to use these documents as context for your query. connection_string (str) – A valid MongoDB connection URI. This notebook covers how to MongoDB Atlas vector search in LangChain, using the langchain-mongodb package. Partner packages (e. io 0. Parameters. MongoDB Atlas is a fully-managed cloud database available in AWS, Azure, and GCP. ) in other applications and understand and utilize recent information. There are 411 other projects in the npm registry using langchain. It supports native Vector Search, full text search (BM25), and hybrid search on your MongoDB document data. 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 LangGraph. This will download the MongoDB Node. embedding – The text embedding model to use for the vector store. Installation npm install @langchain/mongodb Copy. Latest version: 0. . It enables applications that: It enables applications that: Are context-aware : connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response in, etc. It provided a clear, step-by-step approach to setting up a RAG application, including database creation, collection and index configuration, and utilizing LangChain to construct a RAG chain and application. 3 package - Last release 0. Typescript bindings for langchain. ) LangChain. Constructs a chain that uses OpenAI's chat model to generate context-aware responses based on your prompt. If you are using this package with other LangChain packages, you should make sure that all of the packages depend on the same LangChain is a framework for developing applications powered by language models. The Loader requires the following parameters: MongoDB connection string; MongoDB database name; MongoDB collection name To install MongoDB in Windows using npm, execute `npm install mongodb --save` in your root directory. Start using langchain in your project by running `npm i langchain`. Chat models and prompts: Build a simple LLM application with prompt templates and chat models. This package, along with the main LangChain package, depends on @langchain/core. kwargs (Any) – Returns Sep 18, 2024 · Learn how to build a powerful AI agent using LangGraph. There are 9 other projects in the npm registry using @langchain/mongodb. 12, last published: a day ago. It contains the following packages. Este tutorial demonstra como começar a usar o Atlas Vector Search com o LangChain para realizar pesquisas semânticas em seus dados e criar uma implementação de RAG. Start using @langchain/langgraph-checkpoint-mongodb in your project by running `npm i @langchain/langgraph-checkpoint-mongodb`. Familiarize yourself with LangChain's open-source components by building simple applications. Installing integration packages . 0, last published: 9 months ago. npm. js and MongoDB. json file. g. This step-by-step guide will show you how to create AI-driven applications capable of remembering conversations, accessing databases, and delivering smart responses. MongoDB. @langchain/openai, @langchain/anthropic, etc. 1. @langchain/community: Third party integrations. Check @langchain/mongodb 0. Dec 9, 2024 · Construct a MongoDB Atlas Vector Search vector store from a MongoDB connection URI. 6, last published: 4 months ago. MongoDB is a NoSQL , document-oriented database that supports JSON-like documents with a dynamic schema. You can integrate Atlas Vector Search with LangChain to build LLM applications and implement retrieval-augmented generation (RAG). ): Some integrations have been further split into their own lightweight packages that only depend on @langchain/core. Você pode integrar o Atlas Vector Search com o LangChain para construir aplicativos LLM e implementar a geração aumentada de recuperação (RAG). js. There are 4 other projects in the npm registry using @langchain/langgraph-checkpoint-mongodb. Sample integration for LangChain. 2. It includes integrations between MongoDB, Atlas, LangChain, and LangGraph. 3 • Published 27 days ago Sep 18, 2024 · This guide has simplified the process of incorporating memory into RAG applications through MongoDB and LangChain. LangChain actually helps facilitate the integration of various LLMs (ChatGPT-3, Hugging Face, etc. namespace (str) – A valid MongoDB namespace (database and collection). js integrations for MongoDB through their SDK. LangChain passes these documents to the {context} input variable and your query to the {question} variable. MongoDB Atlas. LangChain supports packages that contain module integrations with individual third-party providers. Start using @langchain/mongodb in your project by running `npm i @langchain/mongodb`. Perfect for JavaScript developers looking to integrate AI into their web apps. js driver and add a dependency entry in your package. langchain: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. This tutorial demonstrates how to start using Atlas Vector Search with LangChain to perform semantic search on your data and build a RAG implementation. This is a Monorepo containing partner packages of MongoDB and LangChainAI. Dec 8, 2023 · LangChain is a versatile Python library that enables developers to build applications that are powered by large language models (LLMs). 0. If you're looking to get started with chat models, vector stores, or other LangChain components from a specific provider, check out our supported integrations. 3 with MIT licence at our NPM packages aggregator and search engine. Overview The MongoDB Document Loader returns a list of Langchain Documents from a MongoDB database. This package contains the LangChain. They can be as specific as @langchain/anthropic, which contains integrations just for Anthropic models, or as broad as @langchain/community, which contains broader variety of community contributed integrations. irzclociwplktvwpfemimjgsextdhgvvxpvnecwtbfzkkrsapocu