Repository History
6 repositories tagged with multi-agent
AgentBridge: Local Bridge for Claude Code and Codex Collaboration
AgentBridge is an innovative local tool designed to facilitate real-time, bidirectional collaboration between Claude Code and Codex AI agents. It enables seamless cross-review, task splitting, and quota relay, allowing these powerful models to work together efficiently within a single session without manual intervention. Notably, the tool itself was largely built by Claude Code and Codex collaborating through AgentBridge.
nanobot: An Ultra-Lightweight, Self-Hosted Personal AI Agent Framework
nanobot is an ultra-lightweight, open-source, self-hosted personal AI agent framework built in Python. It offers a WebUI, tools, memory, multi-agent workflows, and automation capabilities, making it a versatile solution for personal AI tasks. Users can deploy it across various platforms, including chat apps, for seamless integration.
AgentTeams: Collaborative Multi-Agent OS for Human-in-the-Loop Task Coordination
AgentTeams is an innovative open-source Collaborative Multi-Agent Operating System designed for transparent, human-in-the-loop task coordination. It leverages Matrix rooms to facilitate seamless interaction between human users and AI agents. This platform empowers teams to manage complex tasks efficiently, ensuring full visibility and control over agent activities.
Deliberation: Multi-Agent LLM Consensus for Code and Plan Review
Deliberation is an innovative GitHub repository that enables Claude Code to leverage multiple LLMs like GPT, Gemini, Grok, and 400+ OpenRouter models for expert second opinions and arbiter-mediated consensus. It provides specialized AI agents for tasks such as code review, security analysis, and architectural design, ensuring comprehensive and reliable feedback. This project helps developers get diverse perspectives and achieve higher quality in their work.
AutoGen: A Programming Framework for Agentic AI
AutoGen is a versatile programming framework from Microsoft designed for building multi-agent AI applications. It empowers AI agents to operate autonomously or collaborate seamlessly with human users, streamlining the execution of complex tasks. The framework offers a layered, extensible design, providing both high-level APIs for rapid prototyping and low-level components for fine-grained control.
DeerFlow: A Deep Research Framework Powered by LLMs and Multi-Agent Systems
DeerFlow is a community-driven Deep Research framework developed by ByteDance, designed to combine language models with powerful tools for web search, crawling, and Python execution. It enables comprehensive research processes, from intelligent clarification to report generation and even podcast creation, all while giving back to the open-source community.