LangGraph

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Category:AI Agent Development Frameworks

Overview

An open-source AI framework for building stateful, multi-actor applications with large language models (LLMs).

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AI researchers software developers machine learning engineers automation engineers

LangGraph is an open-source library designed to facilitate the development of stateful, multi-actor applications utilizing large language models (LLMs). It enables the creation of complex agent and multi-agent workflows, supporting features such as cycles, controllability, and persistence. LangGraph allows developers to define flows involving cycles, essential for most agentic architectures, and provides fine-grained control over both the flow and state of applications. Additionally, it includes built-in persistence, enabling advanced human-in-the-loop and memory features, making it suitable for creating reliable, fault-tolerant agent-based systems.

Autonomy level

85%

Reasoning: LangGraph enables high autonomy through cyclic workflows and stateful execution that allow agents to dynamically adapt to evolving conditions without predefined linear paths. Its support for multi-agent collaboration, dynamic decision-making (conditional branching), and persistent context management permits agents to iteratively process tasks, eval...

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Some of the use cases of LangGraph:

Developing complex AI agents with stateful workflows.
Implementing multi-agent systems with controllable interactions.
Creating applications requiring iterative decision-making processes.
Enhancing AI agents with persistence and human-in-the-loop capabilities.

Pricing model:

free

Code access:

open-source

Popularity level: 82%