Langchain agents github. There’s a lot of excitement around building agents .

Langchain agents github. LangGraph is an extension of LangChain specifically aimed at creating highly controllable and customizable agents. To address these issues and facilitate communication with external applications, we introduce the concept of an Agent as a processor. Open Agent Platform provides a modern, web-based interface for creating, managing, and interacting with LangGraph agents. py" script. This project demonstrates how to LangChain Agents are comprised of one or more tools that can be used by the agent to get to the final decision. Agents By themselves, language models can't take actions - they just output text. An agent is a custom The role of Agent in LangChain is to help solve feature problems, which include tasks such as numerical operations, web search, and terminal invocation that cannot be handled internally by the language model. Sep 27, 2023 · 🤖 Hello, To create a chain in LangChain that utilizes the create_csv_agent() function and memory, you would first need to import the necessary modules and classes. The flow of the agent can be visualized with With LangChain, we can create data-aware and agentic applications that can interact with their environment using language models. g. It builds up to an "ambient" agent that can manage your email with connection to the Gmail API. It is easy to write custom tools, and you can easily pass these to the model. Visit the mcp-use. js - langchain-ai/agent-inbox-langgraphjs-example This is an early experiment, agents do automatic things, here be dragons, run at your own risk. It leverages LangGraph's long-term memory store to allow an agent to search for and retrieve relevant tools for a given problem. I used the GitHub search to find a similar question and Unlimited Open-source Gemini Agents With Langchain - GitHub - ZeroXClem/Gemini-agent-example: Unlimited Open-source Gemini Agents With Langchain Build resilient language agents as graphs. This README provides detailed instructions on how to set up and use the Langchain Agents application. LangChain / LangGraph SQL Agent Demo This repository demonstrates the use of LangChain and LangGraph for SQL query generation, execution and validation. Azure Database for PostgreSQL for data storage and querying. Agent trajectory match evaluators are used to judge the trajectory of an agent's execution either against an expected trajectory or using an LLM. The system remembers which agent was last active, ensuring that on subsequent In simple terms, langchain is a framework and library of useful templates and tools that make it easier to build large language model applications that use custom data and external tools. Contribute to lalolv/AgentsChain development by creating an account on GitHub. Contribute to kkdai/langchain-jira-agent development by creating an account on GitHub. Enfuse agents with updated data so they make better informed decisions that scale with your analytics practice - tableau/tableau_ Contribute to VRSEN/langchain-agents-tutorial development by creating an account on GitHub. Each approach has distinct strengths LangChain Integration: Harness the power of LangChain for streamlined AI pipelines. AIBTC AI Agent Crew is a Python-based project that leverages AI agents to perform various tasks related to Bitcoin and the Stacks blockchain. The core logic, defined in src/react_agent/graph. To use the Agent Inbox, you'll have to use the interrupt function, instead of raising a NodeInterrupt exception in your codebase. Insert your OpenAI API key in the "ai-langchain-react-agent. These tools can be online search, or chains carrying out modular tasks in an application flow. These section build from the basics of Jun 17, 2025 · LangChain supports the creation of agents, or systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action. It contains example graphs exported from src/retrieval_agent/graph. This is a simple way to let an agent persist important information to reuse later. My objective is to develop an Agent using Langchain, that can take actions on inputs from LLM conversations, and execute various scripts or one-off s Example application for constructing and running an LLM-based LangChain SQL Agent based on GPT-4o mini that can dynamically query a database and invoke multiple visualization tools - EliasK93/LangC Build resilient language agents as graphs. AutoGen for coordinating AI agents in collaborative workflows. The repo is a guide to building agents from scratch, building from simple principles to self-improving and personalized agents that use LangChain, LangGraph, and LangSmith. The project leverages the IBM Watsonx Granite LLM and LangChain to set up and configure a Retrieval Augmented Langchain Agents. Ready to support ollama. There’s a lot of excitement around building agents 基于 LangChain 框架的开源多智能体 Agent 项目. This README provides step-by-step instructions to set up and run the project. This will clone a frontend chat application (Next. (Update when i a Build resilient language agents as graphs. A collection of generative UI agents written with LangGraph. The project provides detailed instructions for setting up the environment and loading travel data, aiming to empower developers to integrate similar agents into their Contribute to theodo-group/langchain-agent development by creating an account on GitHub. Welcome to "Awesome LagnChain Agents" repository! This repository is dedicated to showcasing the most amazing, innovative, and intriguing LangChain Agents from all over the world. This project aims to simplify data manipulation tasks by providing a natural language interface for executing complex pandas operations. LangChain + Next. py that implement a retrieval-based question answering system. It uses a human-in-the-loop (HITL) flow to handle authentication with different social media platforms, and to allow the user to make changes, or accept/reject the Aug 30, 2023 · Explores the implementation of a LangChain Agent using Azure Cosmos DB for MongoDB vCore to handle traveler inquiries and bookings. An Agentic RAG implementation using Langchain and a telegram client to send/receive messages from the chatbot - riolaf05/langchain-rag-agent-chatbot This project demonstrates how to use LangChain to create a question-and-answer (Q&A) agent based on a large language model (LLM) and retrieval augmented generation (RAG) technology. The agent operates by maintaining an internal state and iteratively performing actions based on the input and the results of previous actions. These evaluators expect you to format your agent's trajectory as a list of OpenAI format dicts or as a list of LangChain BaseMessage classes, and handle message formatting under the hood. . Setup At a high-level, we will: Install the pygithub library Create a Github app Set your environmental variables Pass the tools to Contribute to langchain-ai/agent-protocol development by creating an account on GitHub. Agents give decision-making powers to Large Language Models (LLMs) and decide which action (s) to take to get the best answer. This project provides a user-friendly interface for deploying ReAct agents that can access various data sources and APIs Build a Smart Jira Agent Using LangChain. I implement and compare three main architectures: Plan and Execute, Multi-Agent Supervisor Multi-Agent Collaborative. It utilizes the LangChain library and various language models, such as ChatGroq and ChatOpenAI, to generate SQL queries and provide responses. LangGraph ReAct Memory Agent This repo provides a simple example of a ReAct-style agent with a tool to save memories. Contribute to TheAILearner/Langchain-Agents development by creating an account on GitHub. LangGraph Visualizations: Easily visualize the reasoning and workflow of your agents. A financial agent, built entirely with LangChain! Contribute to virattt/financial-agent development by creating an account on GitHub. Course Website: 📚 deeplearning. Learn to build AI agents with LangChain and LangGraph. You can use this code to get started with a LangGraph application, or to test out the pre-built agents! Usage: create-agent-chat-app 🦜💬 Web app for interacting with any LangGraph agent (PY & TS) via a chat interface. LangChain is a framework for developing applications powered by large language models (LLMs). For detailed documentation of all GithubToolkit features and configurations head to the API reference. Run the agent: Execute the agent to review git commits. Mar 30, 2025 · LangChain-MCP-Adapters is a toolkit provided by LangChain AI that enables AI agents to interact with external tools and data sources through the Model Context Protocol (MCP). An example repository for getting started with the Agent Inbox and LangGraph. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. Contribute to antoinewg/langchain-agent-collection development by creating an account on GitHub. Specifically, we enable this model to call tools by providing it a list of LangChain tools. Langchain_CrewAI_Gemini-AI_Agents This GitHub repository houses a project where the Langchain platform, powered by Google's Gemini AI, collaborates with CREWAI to develop AI agents tailored for automating research activities. LangChain is a library that utilizes natural language processing and machine learning algorithms to create agents to answer questions from CSV data. 💻 Welcome to the "Functions, Tools and Agents with LangChain" course! Instructed by Harrison Chase, Co-Founder and CEO at LangChain, this course will keep you updated with the latest advancements in Large Language Models (LLMs) and the libraries supporting them. TheAILearner / Langchain-Agents Public Notifications You must be signed in to change notification settings Fork 19 Star 26 🦜🎤 Voice ReAct Agent This is an implementation of a ReAct -style agent that uses OpenAI's new Realtime API. That's all for this example of building a retrieval augmented conversational agent with OpenAI and Pinecone (the OP stack) and LangChain. ReAct agents are uncomplicated, prototypical agents that can be flexibly extended to many tools. Hierarchical systems are a type of multi-agent architecture where specialized agents are coordinated by a central supervisor agent. These agents have specific roles, such as CEO, CTO, and Assistant, and can provide responses based on predefined templates and tools. One type of LLM application you can build is an agent. In this case, we save all memories scoped to a configurable user_id, which lets the bot learn a user's preferences across conversational threads. This repository provides resources for building AI agents using Langchain and Langgraph. Agents are systems that take a high-level task and use an LLM as a reasoning engine to decide what actions to take and execute those actions. This template This is a starter project to help you get started with developing a retrieval agent using LangGraph in LangGraph Studio. AgentKit is a LangChain-based starter kit developed by BCG X to build Agent apps. To improve your LLM application development, pair LangChain with: LangSmith - Helpful for agent evals and observability. Amazon Bedrock Custom LangChain Agent Create a custom LangChain agent dubbed "Agent AWS" that queries the AWS Well-Architected Framework and deploys Lambda functions, all backed by Amazon Bedrock and housed in a Streamlit chatbot. It provides a Streamlit user interface for interacting with Sep 5, 2024 · Hello, @SAIL-Fang! To create a custom Agent that reviews git commits and checks their names using LangChain, you can follow these steps: Define the tools: Create a tool that can interact with the git repository to fetch commit names. Contribute to langchain-ai/agent-evals development by creating an account on GitHub. Contribute to langchain-ai/langchain-experimental development by creating an account on GitHub. js template - template LangChain. Azure OpenAI GPT-4 for intelligent language understanding and generation of SQL queries in PostgreSQL. For these applications, LangChain simplifies the entire application lifecycle: Open-source libraries: Build your applications using LangChain's open-source components and third-party integrations. A CUA is a type of agent which has the ability to interact with a computer to preform tasks. Contribute to langchain-ai/langgraph development by creating an account on GitHub. Here's a step-by-step Welcome to Adaptive RAG 101! In this session, we'll walk through a fun example setting up an Adaptive RAG agent in LangGraph. - langchain-ai/agent-chat-ui ReAct Agents Overview ReAct agents in LangChain are designed to handle natural language inputs, process them, and determine the appropriate actions to take using a set of integrated tools. This project is an AI-powered SQL query agent that can answer natural language questions by querying a SQLite database. At LangChain, we aim to make it easy to build LLM applications. It provides a unified interface to create agents based on different language models such as OpenAI. com website to know how to build and deploy MCP agents. The tool is a wrapper for the PyGitHub library. Please find the Multi-Agent Chatbot is a sophisticated chatbot application that leverages multiple agents to handle different types of queries. js in LangGraph Studio. This project demonstrates the integration of a Large Language Model (LLM) with the Google Search API via LangChain agents to automate data retrieval and provide summarized, real-time insights. 🌐 MCP-Use is the open source way to connect any LLM to any MCP server and build custom MCP agents that have tool access, without using closed source or application clients. Contribute to langchain-ai/langchain development by creating an account on GitHub. To read more about how the interrupt function works, see the LangGraph documentation: conceptual guide how-to guide (TypeScript docs coming soon, but the concepts & implementation are the same). py, demonstrates a flexible ReAct agent that iteratively This repository demonstrates how to build a multi-agent AI system using: LangChain for natural language to SQL translation. js project. Create autonomous workflows using memory, tools, and LLM orchestration. Contribute to n-mhatre/ReAct-Agent-Implementation-from-Scratch-with-LangChain development by creating an account on GitHub. Github Toolkit The Github toolkit contains tools that enable an LLM agent to interact with a github repository. Additionally, it integrates with LangChain offers SQL Chains and Agents to build and run SQL queries based on natural language prompts. , MySQL, PostgreSQL, Oracle SQL, Databricks, SQLite). GitHub Gist: instantly share code, notes, and snippets. 💡 Let developers easily connect any LLM to tools like web browsing, file operations, and more. js or Vite), along with up to 4 pre-built agents. mcp-agent is a simple, composable framework to build agents using Model Context Protocol with extended support for LangChain integrations. After that, you would call the create_csv_agent() function with the language model instance, the path to your CSV The langchain_pandas_agent project integrates LangChain and OpenAI 3. It focuses on creating intelligent systems with language models for tasks like chatbots, personal assistants Build resilient language agents as graphs. Key Enhancements: LangChain Integration: Native support for LangChain models and tools Multi-LLM Support: GigaChat, OpenAI, DeepSeek, Qwen, and more via LangChain Maintained Compatibility: Full backward compatibility with original MCP patterns Inspiration A Python library for creating swarm-style multi-agent systems using LangGraph. The Github toolkit contains tools that enable an LLM agent to interact with a github repository. Below is the process diagram for the app designed in this tutorial: For each user query, the agent uses the LLM to decide which tool to use. Developers can use AgentKit to Quickly experiment on your constrained agent architecture with a beautiful UI Build a full stack chat-based Agent app that can scale to production-grade MVP Key advantages of the AgentKit Build resilient language agents as graphs. Contribute to jayli/langchain-GLM_Agent development by creating an account on GitHub. LangChain’s ecosystem While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications. This repository contains sample code to demonstrate how to create a ReAct agent using Langchain. Evals for agents. Create the agent: Use the defined tools and a language model to create an agent. I searched the LangChain documentation with the integrated search. Jan 30, 2024 · Checked other resources I added a very descriptive title to this question. Welcome to the LangChain 101 repository! This project serves as an accessible entry point for beginners eager to explore the world of agentic AI, focusing on the crucial concept of tools. Looks great! We're also able to ask questions that refer to previous interactions in the conversation and the agent is able to refer to the conversation history to as a source of information. The retrieval chat bot manages a chat history and An examples code to make langchain agents without openai API key (Google Gemini), Completely free unlimited and open source, run it yourself on website. 本地知识库 + chatGLM6B + CustomAgent. Visit the mcp-use docs to get started with mcp Langchain Agents is a Streamlit web application that allows users to simulate conversations with virtual agents. It's designed to be simple yet informative, guiding you through the essentials of integrating custom tools with Langchain. js + Next. The repo is a guide to building agents from scratch. It's designed with simplicity in mind, making it accessible to users without technical expertise, while still offering advanced capabilities for developers. Build resilient language agents as graphs. By combining the historical data capabilities of the LLM with the live information from Google Search, we This template showcases a ReAct agent implemented using LangGraph, designed for LangGraph Studio. The AWS Bedrock stack includes a conversational chain A CLI tool to quickly set up a LangGraph agent chat application. Tableau tools for Agentic use cases with Langchain & Langgraph. This monorepo is a customizable template example of an AI chatbot agent that "ingests" PDF documents, stores embeddings in a vector database (Supabase), and then answers user queries using OpenAI (or another LLM provider) utilising LangChain and LangGraph as orchestration frameworks. Apr 2, 2024 · I am using MacOS, and installed Ollama locally. Lambda instruments the Financial Services agent logic as a LangChain Conversational Agent that can access customer-specific data stored on DynamoDB, curate opinionated responses using your documents and webpages indexed by Kendra, and provide general knowledge answers through the FM on Bedrock. A Python library for creating computer use agent (CUA) systems using LangGraph. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support This YouTube tutorial goes over the architecture and concepts used for easily spinning up agents with using LangChain using OpenAI's API - edrickdch/langchain-agents This project explores multiple multi-agent architectures using Langchain (LangGraph), focusing on agent collaboration to solve complex problems. 🦜🔗 Build context-aware reasoning applications. Then, you would create an instance of the BaseLanguageModel (or any other specific language model you are using). It also includes a simple web interface for interacting with the agent. An example repository for getting started with the Agent Inbox and LangGraph - langchain-ai/agent-inbox-langgraph-example This is a starter project to help you get started with developing a RAG research agent using LangGraph in LangGraph Studio. This repository contains an 'agent' which can take in a URL, and generate a Twitter & LinkedIn post based on the content of the URL. These are compatible with any SQL dialect supported by SQLAlchemy (e. If an empty list is provided (default), a list of sample documents from src/sample_docs. Contribute to lloydchang/langchain-ai-langgraph development by creating an account on GitHub. It's grouped into 4 sections, each with a notebook and accompanying code in the src/email_assistant directory. Currently the OpenAI stack includes a simple conversational Langchain agent running on AWS Lambda and using DynamoDB for memory that can be customized with tools and prompts. AI agents promise to transform how we work, but there's often a gap between hype and reality: to act on our behalf, agents need to learn and remember our preferences. json is indexed instead. LangChain is a powerful framework for building applications with large language models (LLMs), and this tutorial The ReAct agent: Takes a user query as input Reasons about the query and decides on an action Executes the chosen action using available tools Observes the result of the action Repeats steps 2-4 until it can provide a final answer By default, it's set up with a basic set of tools, but can be easily extended with custom tools to suit various use cases. js - langchain-ai/langgraphjs-gen-ui-examples 🦜🔗 Build context-aware reasoning applications. 5 to build an agent that can interact with pandas DataFrames. Feb 4, 2025 · To create a LangChain AI agent with a tool using any LLM available in LangChain's AzureOpenAI or AzureChatOpenAI class, follow these steps: Instantiate the LLM: Use the AzureChatOpenAI class to create an instance of the language model. langgraph-bigtool is a Python library for creating LangGraph agents that can access large numbers of tools. In this tutorial, we will be focusing on building a chatbot agent t This is a starter project to help you get started with developing a RAG research agent using LangGraph. Nov 14, 2023 · LangChain SQL - Agent Setup. It utilizes LangChain's CSV Agent and Pandas DataFrame Agent, alongside OpenAI and Gemini APIs, to facilitate natural language interactions with structured data, aiming to uncover hidden insights through conversational AI. ai The Agent-IA Project is an intelligent agent system leveraging Retrieval-Augmented Generation (RAG) and other components such as Wikipedia and ReadFile. It is designed to enhance information retrieval and interaction capabilities by integrating various APIs and tools. Essentially, langchain makes it easier to build chatbots for your own data and "personal assistant" bots that Looking for the TypeScript version? Check out the repo here. It integrates with LangChain, OpenAI, and various tools to deliver accurate and helpful responses. I want to contribute to the LangGraph. These agents are designed to streamline and enhance various research tasks, leveraging advanced AI capabilities. A swarm is a type of multi-agent architecture where agents dynamically hand off control to one another based on their specializations. js application Social media agent - agent for sourcing, curating, and scheduling social media posts with human-in-the-loop (TypeScript) Agent Protocol - Agent Protocol is our attempt at codifying the framework-agnostic APIs that are needed to serve LLM agents in production Build resilient language agents as graphs. Those sample documents are based on the conceptual guides for This project enables chatting with multiple CSV documents to extract insights. My goal is to support the LangChain community by giving these fantastic 🦜🔗 Build context-aware reasoning applications. Curated list of agents built on LangChain. The application showcases a shipping company A Python library for creating hierarchical multi-agent systems using LangGraph. Collection of Langchain agents.