What to compare

  • Does the framework fit your language and deployment runtime?
  • How will a failed run resume without repeating side effects?
  • Can you test the workflow with your own examples?

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Agency Swarm by VRSEN

Agent frameworks

Agency Swarm is a framework designed to automate AI agencies by creating a swarm of collaborative agents with customizable roles and functionalities, aiming to simplify the agent creation process and make automation more intuitive

Agent Reach

Agent frameworks

Agent Reach installs and checks internet access tools for AI agents, routing search and platform access through supported CLIs and services.

AgentOS

Agent frameworks

The Agent OS is an experimental platform for creating self-evolving, autonomous AI agents capable of writing and executing their own code, designed to be a long-term environment for such agents and supports various programming languages

Agents Squads

Agent frameworks

Agents Squads is a CLI for defining and running autonomous AI squads with persistent memory, shared goals, git-backed state, and verification across engineering, research, product, and operations.

AGiXT

Agent frameworks

AGiXT is an advanced AI Automation Platform designed to enhance AI instruction management and task execution across various providers, incorporating features like adaptive memory, smart instruct, and a versatile plugin system to push the boundaries of AI technology towards achieving Artificial General Intelligence (AGI)

AGX

AI agents

A local workspace for coordinating AI coding agents across tickets, repositories, and pull requests, with project tracking, retained context, and human approval gates.

AIOS

Agent frameworks

AIOS by AGI Research is an LLM Agent Operating System which enables an operating system 'with soul' -- an important step towards AGI

AIWG

Agent frameworks

AIWG deploys specialized agents, skills, context, rules, and governed workflows into native project paths across multiple AI coding platforms.

Arachne

AI agents

A DSPy-native runtime that turns natural-language goals into inspectable agent graphs, executes independent steps in parallel, evaluates results, and can repair failed runs.

AutoGen by Microsoft

Agent frameworks

AutoGen is a multi-agent conversation framework facilitating the development of next-gen LLM applications, highlighted by various accomplishments and offering enhanced LLM inferences, customizable agents, and comprehensive documentation

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