Langchain agents documentation github. An agent is a custom 2 days ago · LangChain is a powerful framework that simplifies the development of applications powered by large language models (LLMs). A Python library for creating hierarchical multi-agent systems using LangGraph. These agents enable Large Language Models (LLMs) to perform complex tasks by integrating with external APIs, generating personalized images, and more, providing a comprehensive approach to bridging AI with real-world data. The retrieval chat bot manages a chat history and The core idea of agents is to use a language model to choose a sequence of actions to take. , runs the tool), and receives an observation. note This is a starter project to help you get started with developing a retrieval agent using LangGraph in LangGraph Studio. The tool is a wrapper for the PyGitHub library. Follow their code on GitHub. I used the GitHub search to find a similar question and LangGraph — used by Replit, Uber, LinkedIn, GitLab and more — is a low-level orchestration framework for building controllable agents. Azure OpenAI GPT-4 for intelligent language understanding and generation of SQL queries in PostgreSQL. LangChain provides a standard interface for agents, along with LangGraph. New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications. Structured Learning Path: Start from the basics and progress to advanced topics. This repository contains an 'agent' which can take in a URL, and generate a Twitter & LinkedIn post based on the content of the URL. Classes Overview and tutorial of the LangChain Library. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support Architecture LangChain is a framework that consists of a number of packages. agents. A Python library for creating swarm-style multi-agent systems using LangGraph. 1. For details, refer to the LangGraph documentation as well as guides for 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. In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. LangGraph offers a more flexible and full-featured framework for building agents, including support for tool-calling, persistence of state, and human-in-the-loop workflows. It provides essential building blocks like chains, agents, and memory components that enable developers to create sophisticated AI workflows beyond simple prompt-response interactions. 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 To use the Agent Inbox, you'll have to use the interrupt function, instead of raising a NodeInterrupt exception in your codebase. Copy the . For more details, please refer to the Langchain documentation. LangSmith documentation is hosted on a separate site. Additionally, it integrates with Introduction LangChain is a framework for developing applications powered by large language models (LLMs). The agent returns the observation to the LLM, which can then be used to generate the next action. Open Agent Platform provides a modern, web-based interface for creating, managing, and interacting with LangGraph agents. LangChain Python API Reference langchain-community: 0. Build resilient language agents as graphs. agent. 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). 3. The interfaces for core components like chat models, vector stores, tools and more are defined here. 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. The agent executes the action (e. While langchain provides integrations and composable components to streamline LLM application development, the LangGraph library enables agent orchestration — offering customizable architectures, long-term memory, and human-in-the-loop to reliably handle 🌟 Features Dynamic AI Agent Creation: Build agents with custom prompts and logic. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. It is easy to write custom tools, and you can easily pass these to the model. This is a simple way to let an agent persist important information to reuse later. 🌐 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. This will clone a frontend chat application (Next. LangChain 🔌 MCP. Complete LangChain Guide: Covers all key concepts, including chains, agents, and document loaders. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support. I used the GitHub search to find a similar question and In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. LangGraph ReAct Agent Template This template showcases a ReAct agent implemented using LangGraph, designed for LangGraph Studio. js, a library for building stateful, multi-actor applications with LLMs. tools_renderer (Callable[[list[BaseTool]], str]) – This controls how the tools are LangChain is a framework for developing applications powered by large language models (LLMs). 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. 3 days ago · Learn how to use the LangChain ecosystem to build, test, deploy, monitor, and visualize complex agentic workflows. This project aims to simplify data manipulation tasks by providing a natural language interface for executing complex pandas operations. The library is not exhaustive of the entire Stripe API. tools (Sequence[BaseTool]) – Tools this agent has access to. Hierarchical systems are a type of multi-agent architecture where specialized agents are coordinated by a central supervisor agent. 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. 27 agents RAG Integration: Uses LangChain and FAISS to retrieve relevant documents from a knowledge base. Specifically, we enable this model to call tools by providing it a list of LangChain tools. js template - template LangChain. The dependencies are kept purposefully very lightweight You can just invoke it with an empty list (default) to index sample documents from LangChain and LangGraph documentation. ReAct agents are uncomplicated, prototypical agents that can be flexibly extended to many tools. Parameters: llm (BaseLanguageModel) – LLM to use as the agent. LangGraph ReAct Memory Agent This repo provides a simple example of a ReAct-style agent with a tool to save memories. By default, the Agent Chat UI is setup for local development, and connects to your LangGraph server directly from the client. I used the GitHub search to find a similar question and This project enables chatting with multiple CSV documents to extract insights. This repository contains implementations of AI email assistants built using LangGraph. 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 Sep 26, 2023 · I understand you're trying to use the LangChain CSV and pandas dataframe agents with open-source language models, specifically the LLama 2 models. What is Open Agent Platform? Open Agent Platform provides a modern, web-based interface for creating, managing, and interacting with LangGraph agents. Jul 15, 2024 · Checked other resources I added a very descriptive title to this question. Contribute to langchain-ai/langchain-mcp-adapters development by creating an account on GitHub. LangChain is a powerful framework for building applications with large language models (LLMs), and this tutorial 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. According to the official LangChain website, their code‑generation capabilities “accelerate software development by automating code writing, refactoring, and documentation for your team” 【46645545831789†L296-L299】. 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 What is Open Agent Platform? Open Agent Platform provides a modern, web-based interface for creating, managing, and interacting with LangGraph agents. When the agent reaches a stopping condition, it returns a final return value. I searched the LangChain documentation with the integrated search. We send a couple of emails per month about the articles, videos, projects, and 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. Python Code Examples: Practical and easy-to-follow code snippets for each topic. This project demonstrates how to 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. 4 days ago · Learn the key differences between LangChain, LangGraph, and LangSmith. AutoGen for coordinating AI agents in collaborative workflows. I'm happy to share the code with you! The Stripe Agent Toolkit enables popular agent frameworks including OpenAI's Agent SDK, LangChain, CrewAI, Vercel's AI SDK, and Model Context Protocol (MCP) to integrate with Stripe APIs through function calling. This will assume knowledge of LLMs and retrieval so if you haven't already explored those sections, it is recommended you do so. It provides tooling to extract important information from conversations, optimize agent behavior through prompt refinement, and maintain long-term memory. Contribute to lloydchang/langchain-ai-langgraph development by creating an account on GitHub. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. It provides a standard interface for chains, many integrations with other tools, and end-to-end chains for common applications. Build controllable agents with LangGraph, our low-level agent orchestration framework. langchain-core This package contains base abstractions for different components and ways to compose them together. I used the GitHub search to find a similar question and LangMem helps agents learn and adapt from their interactions over time. For detailed documentation of all GithubToolkit features and configurations head to the API reference. Feb 14, 2024 · I developed a multi-modal chatbot that leverages agents to address this issue. 5 to build an agent that can interact with pandas DataFrames. 0: LangChain agents will continue to be supported, but it is recommended for new use cases to be built with LangGraph. Contribute to VRSEN/langchain-agents-tutorial development by creating an account on GitHub. Subscribe to the newsletter to stay informed about the Awesome LangChain. You can peruse LangSmith how-to guides here, but we'll highlight a few sections that are particularly relevant to LangChain below: Evaluation langgraph-bigtool is a Python library for creating LangGraph agents that can access large numbers of tools. Agents involve an LLM making decisions about which Actions to take, taking that Action, seeing an Observation, and repeating that until done. FastAPI Endpoint: Provides a simple API to interact with the agent. Deploy and scale with LangGraph Platform, with APIs for state management, a visual studio for debugging, and multiple deployment options. LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Mar 6, 2024 · Checked other resources I added a very descriptive title to this question. The LangChain community in Seoul is excited to announce the LangChain OpenTutorial, a brand-new resource designed for everyone. ai Overview and tutorial of the LangChain Library. Contribute to Cdaprod/langchain-cookbook development by creating an account on GitHub. It’s designed with simplicity in mind, making it accessible to users without technical expertise, while still offering advanced capabilities for developers. It includes support for both This prebuilt graph is an agent that uses a reflection-style architecture to check and improve an initial agent's output. LangChain is an open source orchestration framework for application development using large language models (LLMs). Available in both Python- and Javascript-based libraries, LangChain’s tools and APIs simplify the process of building LLM-driven applications like chatbots and AI agents. Contribute to TheAILearner/Langchain-Agents development by creating an account on GitHub. LangChain provides the smoothest path to high quality agents. These section build from the basics of Apr 11, 2024 · Quickstart To best understand the agent framework, let's build an agent that has two tools: one to look things up online, and one to look up specific data that we've loaded into a index. A swarm is a type of multi-agent architecture where agents dynamically hand off control to one another based on their specializations. LangGraph Visualizations: Easily visualize the reasoning and workflow of your agents. It's designed with simplicity in mind, making it accessible to users without technical expertise, while still offering advanced capabilities for developers. The AWS Bedrock stack includes a conversational chain About langchain ReAct agent代码示例，展示了如何定义custom tools来让llm使用。 详情请参照langchain文档。 The Langchain ReAct Agent code example demonstrates how to define custom tools for LLM usage. These agents are designed to streamline and enhance various research tasks, leveraging advanced AI capabilities. Framework to build resilient language agents as graphs. It seamlessly integrates with LangChain and LangGraph, and you can use it to inspect and debug individual steps of your chains and agents as you build. LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source components and third-party integrations. Jan 17, 2025 · Hi everyone, I’ve partially updated the documentation to replace deprecated references to initialize_agent with langgraph. env Curated list of tools and projects using LangChain. I plan to work on pages 2 and 3 shortly to complete the updates. The example in this repository demonstrates how to expose those The agent executes the action (e. When you use all LangChain products, you'll build better, get to production quicker, and grow visibility -- all with less set up and friction. The agent operates by maintaining an internal state and iteratively performing actions based on the input and the results of previous actions. 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. Studio also integrates with LangSmith to enable tracing, evaluation, and prompt engineering. It demonstrates how to create, test, and add features like Human-in-the-Loop (HITL) and persistent memory to an AI agent. 💻 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. Chroma DB & Pinecone: Learn how to integrate Chroma DB and Pinecone with OpenAI embeddings for powerful data management. This lets your agents continuously Oct 1, 2023 · How to build a LangChain agents that can interact with data from a postgresql database of an Human Resources Systems. 🦜🎤 Voice ReAct Agent This is an implementation of a ReAct -style agent that uses OpenAI's new Realtime API. , a tool to run). It builds up to an "ambient" agent that can manage your email with connection to the Gmail API. Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. Specifically: I addressed the instances for page 1 of 3 in the search: repo:langchain-ai/langchain path:/^docs\// initialize_agent. Customizable System Prompt: Tailor the supervisor's behavior and instructions Deprecated since version 0. Docker Support: Containerized setup for easy deployment. To improve your LLM application development, pair LangChain with: LangSmith - Helpful for agent evals and observability. Contribute to langchain-ai/langgraph development by creating an account on GitHub. js + Next. LangChain + Next. prebuilt. LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. If you want to get started quickly check out mcp-use. The schemas for the agents themselves are defined in langchain. As per the requirements for a language model to be compatible with LangChain's CSV and pandas dataframe agents, the language model should be an instance of BaseLanguageModel or a subclass of it. Agent Framework: Leverages LangChain's agent framework with OpenAI's GPT-4o-mini for query processing. LangChain / LangGraph SQL Agent Demo This repository demonstrates the use of LangChain and LangGraph for SQL query generation, execution and validation. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. 2 days ago · LangChain is a powerful framework that simplifies the development of applications powered by large language models (LLMs). Jul 9, 2025 · The startup, which sources say is raising at a $1. No third-party integrations are defined here. Agent [source] # Bases: BaseSingleActionAgent Deprecated since version 0. Agents use language models to choose a sequence of actions to take. Setup At a high-level, we will: Install the pygithub library Create a Github app Set your environmental variables Pass the tools to A Python library for creating hierarchical multi-agent systems using LangGraph. As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization, chatbots, and code analysis. 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 Dynamic Agent Delegation: The supervisor can decide whether to handle a user query itself or delegate it to a configured specialist agent. The LangChain agents will be queried for use cases like employee password reque Agent # class langchain. This repository demonstrates how to build a multi-agent AI system using: LangChain for natural language to SQL translation. LangChain's products work seamlessly together to provide an integrated solution for every step of the application development journey. LangChain provides a standard interface for agents, a selection of agents to choose from, and examples of end to end agents. The repo is a guide to building agents from scratch. Additionally, I noticed a recurring pattern in Sep 26, 2024 · Checked other resources I added a very descriptive title to this question. mcp-agent is a simple, composable framework to build agents using Model Context Protocol with extended support for LangChain integrations. LangChain implements a standard interface for large language models and related technologies, such as embedding models and vector stores, and integrates with hundreds of providers. This tutorial delves into LangChain, starting from an overview then providing practical examples. Configurable Agents: Easily define and configure multiple child agents, selecting from the list of existing agents you have deployed and configured in Open Agent Platform (OAP). It offers both functional primitives you can use with any storage system and native integration with LangGraph's storage layer. It also includes a simple web interface for interacting with the agent. js for building custom agents. Jul 23, 2025 · LangChain is an open-source framework designed to simplify the creation of applications using large language models (LLMs). It's grouped into 4 sections, each with a notebook and accompanying code in the src/email_assistant directory. Essentially, langchain makes it easier to build chatbots for your own data and "personal assistant" bots that Jupyter Notebooks to help you get hands-on with Pinecone vector databases - pinecone-io/examples An LLM agent built using LangChain and OpenAI API, integrated with tools like DuckDuckGo, Wikipedia, and Arxiv for real-time web search, factual information, and academic research. py that implement a retrieval-based question answering system. You'll know that the indexing is complete when the indexer "delete"'s the content from its graph memory (since it's been persisted in your configured storage provider). Course Website: 📚 deeplearning. Agents select and use Tools and Toolkits for actions. 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. It leverages LangGraph's long-term memory store to allow an agent to search for and retrieve relevant tools for a given problem. A CLI tool to quickly set up a LangGraph agent chat application. LangGraph development by creating an account on GitHub. Contribute to antoinewg/langchain-agent-collection development by creating an account on GitHub. Discover how each tool fits into the LLM application stack and when to use them. Contribute to gkamradt/langchain-tutorials development by creating an account on GitHub. Agents make decisions about which Actions to take, then take that Action, observe the result, and repeat until the task is complete. LangChain has 208 repositories available. This tutorial builds upon the foundation of the existing tutorial available here: link written in Korean. LangChain Integration: Harness the power of LangChain for streamlined AI pipelines. This is driven by a LLMChain. output_parser (AgentOutputParser | None) – AgentOutputParser for parse the LLM output. Productionization LangGraph Studio is a specialized agent IDE that enables visualization, interaction, and debugging of agentic systems that implement the LangGraph Server API protocol. The system remembers which agent was last active, ensuring that on subsequent Langchain Agents. 0: Use new agent constructor methods like create_react_agent, create_json_agent, create_structured_chat_agent, etc. The Github toolkit contains tools that enable an LLM agent to interact with a github repository. js or Vite), along with up to 4 pre-built agents. 💡 Let developers easily connect any LLM to tools like web browsing, file operations, and more. 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 code demo's how you can connect to an SQL database using langchain SQL agent, query the data with natural language and send it to the LLM for generating a insightful response Github Toolkit The Github toolkit contains tools that enable an LLM agent to interact with a github repository. The application showcases a shipping company LangChain's products work seamlessly together to provide an integrated solution for every step of the application development journey. This is not possible if you want to go to production, because it requires every user to have their own LangSmith API key, and set the LangGraph configuration themselves. 🤖 Agents: Agents allow an LLM autonomy over how a task is accomplished. . Contribute to AI-App/LangChain-AI. Graph mode exposes the full feature-set 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. prompt (BasePromptTemplate) – The prompt to use. Agent that calls the language model and deciding the action. A basic agent works in the following manner: Given a prompt an agent uses an LLM to request an action to take (e. 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 theodo-group/langchain-agent development by creating an account on GitHub. create_react_agent. See Prompt section below for more. LangChain provides abstractions for building agents that use language models alongside arbitrary tools. It utilizes the LangChain library and various language models, such as ChatGroq and ChatOpenAI, to generate SQL queries and provide responses. g. Collection of Langchain agents. Azure Database for PostgreSQL for data storage and querying. It contains example graphs exported from src/retrieval_agent/graph. Setup: LangSmith By definition, agents take a self-determined, input-dependent This project is an AI-powered SQL query agent that can answer natural language questions by querying a SQLite database. Customizable and Scalable: Designed to adapt to various use cases, from Q&A to autonomous 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. The langchain_pandas_agent project integrates LangChain and OpenAI 3. 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. 1 billion valuation, helps developers at companies like Klarna and Rippling use off-the-shelf AI models to create new applications. com website to build and deploy agents with your favorite MCP servers Feb 5, 2024 · Checked other resources I added a very descriptive title to this question. hxeab ehjnbx hdpjflw bcwd zpv wekemy mtuzk tbaeb enegn mwuvsql