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rag43,023MIT

langgraph

Build resilient agents.

Updated Oct 10, 2026
Website GitHub Docs
Platforms
Pricing
free-open-source
Status
active
License
MIT

What it does

Core capabilities at a glance

  • Agents
  • AI Agents
  • Chatgpt
  • Deepagents
  • Enterprise
  • Framework
  • Gemini
  • Generative AI

Deep dive

The full breakdown - performance, comparisons, and setup

langgraph

langgraph is a RAG toolkit - Build resilient agents.

Overview

Low-level orchestration framework for building stateful agents.

Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.

For an equivalent JS/TS library, check out LangGraph.js and the JS docs.

  • Durable execution — Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off. - Human-in-the-loop — Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution. - Comprehensive memory — Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions. - Debugging with LangSmith — Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics. - Production-ready deployment — Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.

While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents.

langgraph is open-source, written primarily in Python, with 43,023 GitHub stars under the MIT license. The latest release is cli==0.4.33 (2026-10-07).

Key capabilities

From the project's documentation:

  • LangGraph Quickstart – Get started building with LangGraph
  • Chat LangChain – Chat with the LangChain documentation and get answers to your questions

Install

A quick way to get started (always check the official docs for the latest):

pip install -U langgraph

How it fits a local-AI stack

langgraph runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related RAG toolkits in the directory:

Sources

Stats from GitHub, 2026-10-10.

Frequently asked

Quick answers to common questions

What is langgraph?

langgraph is a rag tool for local AI workloads. Build resilient agents.

Is langgraph free and open source?

Yes, langgraph has 43,023 GitHub stars and is licensed under MIT. You can self-host it for free on .

What hardware do I need for langgraph?

The hardware requirements depend on which models you run. Check our hardware directory for compatible GPUs and systems. langgraph has 43,023 GitHub stars and an active community.

Does langgraph support GPU acceleration?

langgraph's GPU support depends on your specific setup. Check the documentation for details. For the best performance, pair it with an NVIDIA RTX 4090 or 5090.

What are the best alternatives to langgraph?

Popular alternatives include other rag tools in our directory. Browse our full collection at /tool for comparisons, community reviews, and benchmark data to find the right fit for your workflow.

How much does langgraph cost?

langgraph is free-open-source. It is completely free and open source to self-host.

Pairs well with

Complementary tools, models, and hardware