हम “langgraph tutorial” से मेल खाने वाली ओपन-सोर्स GitHub रिपॉजिटरी को क्यूरेट करते हैं। परिणाम आपकी क्वेरी के आधार पर रैंक किए गए हैं — सीमित करने के लिए नीचे दिए गए फ़िल्टर चुनें, या AI के साथ रिफाइन करें।
This project provides a collection of example implementations for building AI agents and workflows using the Spring AI Alibaba framework. It focuses on demonstrating how to create intelligent agents that iteratively reason and act to solve problems, coordinate multiple agents across services, and integrate human oversight into automated processes. The examples showcase key differentiators such as graph-based workflow automation with conditional routing, nested graphs, and parallel execution, as well as real-time streaming of agent responses to clients. The project also illustrates how to mana
This repository offers example code for building multi-agent workflows and graph-based orchestration, but it uses Spring AI Alibaba rather than LangGraph, so it is not a direct tutorial for the framework you are looking for.
GenAI_Agents is a development framework and orchestration engine designed for building autonomous, multi-agent systems. It provides the infrastructure to construct complex, state-managed workflows where specialized agents collaborate to execute multi-step tasks, manage long-term memory, and perform iterative reasoning. The platform distinguishes itself through its graph-based orchestration model, which allows developers to define intricate agentic processes with explicit state transitions. It supports advanced control mechanisms such as human-in-the-loop intervention for manual oversight and
This repository is a multi-agent orchestration framework built with LangGraph, which uses state graphs and multi-agent coordination, but its identity is a ready-to-use framework rather than a tutorial or example project focused on teaching LangGraph usage, so it serves more as a case study than the learning resource you are looking for.
AG2 is a multi-agent large language model orchestration framework, agentic workflow automation tool, and RAG-enabled agent platform. It functions as a communication protocol and framework for coordinating multiple AI agents to solve complex tasks through shared state and standardized messaging. The project distinguishes itself through flexible coordination strategies, including hierarchical agent organization, hub-and-spoke models, and dynamic routing that analyzes conversation context to distribute work. It implements multi-stage feedback loops for iterative refinement and uses schema-constr
AG2 is a multi-agent framework itself, not a tutorial on LangGraph, so it won't show you how to use LangGraph's state graph, conditional routing, or checkpointing features.
Agent Squad is a multi-agent system orchestrator and language model agent orchestration framework. It serves as an AI workflow automation engine and tool integration layer designed to coordinate teams of specialized agents to solve complex tasks through routing, parallel execution, and state management. The project is distinguished by its ability to dynamically compose purpose-specific agents on-demand and route requests based on intent, language, or domain expertise. It supports advanced coordination patterns, including parallel subtask distribution, sequential task pipelines, and the abilit
Agent Squad is a multi-agent orchestration framework built with AWS services and generic agent coordination, but it is not a tutorial or example project specifically demonstrating LangGraph usage, so it does not fit the search for LangGraph learning resources.
This project is a software development kit and framework for building AI agent orchestration, session management, and tool integration systems. It provides a backend infrastructure for hosting remote AI sessions and coordinating multi-agent workflows using large language models. The SDK enables the definition of specialized agents and the orchestration of complex tasks through parallel workstreams. It distinguishes itself by offering a multi-tenant backend capable of horizontal scaling and a headless server runtime that separates session execution from the client interface. The system covers
This is an SDK for building multi-agent orchestration systems, not a LangGraph tutorial or example project — it is a different tool rather than a demonstration of how to use LangGraph.
This project is an educational curriculum and architectural framework for building autonomous AI agents and multi-agent systems. It provides a structured learning path focused on the development of independent software components capable of planning, executing tasks, and utilizing external tools to achieve high-level goals. The framework emphasizes multi-agent system orchestration through distributed architectures where specialized agents collaborate using standardized communication protocols. It details specific design patterns such as dual-memory systems for maintaining short-term plans and
This repository is an educational curriculum and architectural framework for agentic AI and multi-agent systems, but it does not specifically demonstrate using LangGraph; it covers broad agent orchestration with tools like Dapr, Kafka, and LangMem, making it relevant but not a LangGraph tutorial.
Flowise is a low-code platform designed for building and deploying complex language model workflows through a visual, node-based interface. It functions as an orchestrator for autonomous multi-agent systems, allowing users to construct conversational pipelines by connecting language models, memory stores, and external tools on a drag-and-drop canvas. The platform distinguishes itself through its support for sophisticated agentic patterns, including supervisor-worker delegation and iterative reasoning strategies. Users can design directed acyclic graphs to manage conditional branching, state p
Flowise is a visual low-code platform for building LLM workflows, not a tutorial or example project specifically demonstrating how to use LangGraph; while it shares concepts like conditional branching and multi-agent orchestration, it does not serve as a learning resource for LangGraph itself.
UFO is a multi-device task orchestrator and LLM agent orchestration framework designed to decompose natural language requests into executable task graphs. It functions as a cross-platform UI automation tool capable of performing interactions on Windows and mobile devices while routing tasks to distributed agents based on their hardware and software capabilities. The system is distinguished by its RAG-enhanced agent architecture, which integrates external documentation and previous execution traces to improve decision-making. It employs a hybrid UI detection approach that combines computer vis
UFO is a multi-device task orchestrator and agent framework that uses its own graph-based design, but it is not a tutorial or example project demonstrating how to use LangGraph for building LLM applications.
The agent-framework is an LLM agent orchestration framework and multi-agent workflow engine designed for building autonomous AI agents. It provides a tool integration layer for binding external functions, APIs, and sandboxed code as executable tools for language models. The framework distinguishes itself through a graph-based system for designing sequential and parallel task flows, featuring state management and checkpointing for long-running processes. It implements comprehensive conversational state management and an observability suite that uses telemetry to trace execution flows and monit
This is the Microsoft agent framework, a general multi-agent orchestration tool with graph-based state management, but it is not a tutorial or example project for LangGraph itself, so it doesn't demonstrate how to use LangGraph specifically.
This project provides a comprehensive framework for building, deploying, and orchestrating autonomous agents within a decentralized network. It serves as a collection of patterns and examples for developing intelligent software entities capable of performing complex tasks, making decisions, and interacting with other agents to achieve shared goals. The framework distinguishes itself through its focus on multi-agent orchestration and decentralized communication. It enables the coordination of specialized agent teams that collaborate on workflows through structured messaging protocols, allowing
This repo provides examples for building multi-agent systems with the Fetch.ai agent framework, not LangGraph — so while it covers multi-agent orchestration, it does not demonstrate LangGraph's state graphs, conditional routing, or checkpointing as requested.
This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks. The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin
This is a structured educational resource for building AI agents, but it uses Microsoft's AutoGen and Semantic Kernel rather than LangGraph, so it does not directly demonstrate LangGraph-based stateful multi-agent applications.
The BeeAI Framework is an LLM agent framework and multi-agent orchestration engine used to build autonomous agents that coordinate reasoning, tool execution, and complex workflows. It functions as a structured AI output controller and RAG integration library, providing a unified interface to manage multiple language model providers. The framework is distinguished by its implementation of the Model Context Protocol, allowing agents, tools, and models to be shared between different AI platforms and hosted as agentic tooling servers. It enables the design of collaborative agent teams through dec
This is the BeeAI Framework, a standalone multi-agent orchestration engine, not a tutorial or example project for using LangGraph specifically, which is what this search targets.
This is an open-source Python SDK for building and orchestrating production-grade AI agents. It provides a unified framework for creating conversational agents that can use tools, maintain state, and coordinate across multiple language model providers including OpenAI, Anthropic, Google, Amazon Bedrock, and locally-hosted models. The SDK supports multi-agent orchestration through graphs, teams, and swarms, allowing several specialized agents to collaborate on complex tasks. Agents can be composed as callable tools that other agents invoke, and the framework includes policy handlers that inspe
This is a full-featured multi-agent SDK, not a tutorial or example project for LangGraph; it uses its own graph-based orchestration rather than demonstrating LangGraph's specific approach.
PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo
PraisonAI is a multi-agent orchestration platform rather than a tutorial or example project specifically demonstrating LangGraph usage — it does not serve as a learning resource for LangGraph, which is what this search targets.
Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level
Claude Code is a multi-agent orchestration framework rather than a tutorial or example project demonstrating LangGraph usage, and there is no mention of LangGraph in its description or tags, so it does not directly fulfill the intent to learn how to use LangGraph.
Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut
Mastra is a multi-agent orchestration framework of its own, not a tutorial or example project demonstrating LangGraph — it’s a different tool, not a learning resource for the framework you asked about.
DSPy is a declarative programming framework designed for building complex language model applications. It treats model interactions as modular, composable programs, allowing developers to define task logic through typed class schemas rather than relying on manually written prompts. By organizing workflows into hierarchical, reusable Python objects, the framework enables the construction of sophisticated AI systems that manage state and execution flow independently. The framework distinguishes itself through an automated optimization engine that iteratively refines prompt instructions and few-
DSPy is a framework for building complex LLM applications with its own declarative programming model, not a collection of tutorials or examples for LangGraph, so it doesn't fit the specific tool this search targets.