LangGraphUpdated
Visualize and orchestrate AI workflows elegantly with its graph-based interface.
A working map of the platforms teams reach for to build, orchestrate, and operate AI agents — from graph-based orchestration and multi-agent crews to retrieval, observability, and guardrails.
Building an AI agent rarely means writing one program end to end. Most teams reach for a graph or chain framework to define the workflow, a multi-agent layer to split work across specialised roles, a retrieval layer to ground answers in real data, and an observability tool to see what the agent actually did in production. This directory groups 14 frameworks and platforms by the job they do in that stack.
Visualize and orchestrate AI workflows elegantly with its graph-based interface.
Team up multiple AI agents to perform collaborative problem-solving.
Straightforward library for building agentic applications where a model can use additional context and tools, hand off to other specialised agents, stream partial results, and keep a full trace.
Automate generation of agents tailored to diverse tasks.
Managing autonomous agents at scale with full lifecycle management and observability — enabling teams to deploy, monitor, and improve agents in production.
Bring together search, reasoning, and AI to provide intelligent agent capabilities.
Connecting LLMs with structured and unstructured data sources for intelligent data retrieval — the go-to framework for building knowledge-augmented AI applications.
Lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into C#, Python, or Java codebases — efficient middleware for enterprise-grade solutions.
Popular for chaining AI components, enabling complex agent workflows.
Lightweight, versatile, and designed for easy integration. Perfect to start your AI agent journey.
Simplify deployment and management of AI agents at scale.
Build, test, and refine AI agents with a comprehensive toolset.
A studio environment for rapid prototyping of AI agent applications.
Leverage large language models to create agents that manage real-world projects.
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