Agency Swarm Can Now Create Your Agent Swarms for You

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AI Summary

Summary: Introduction of Genesys Swarm

• Introduction of Genesys Swarm
  • A step towards self-expanding AI.
  • Agency Swarm framework allows creation of agents without coding.
  • Agents contributed to GitHub enhance the collective library.
• Demonstration
  • Demo of creating a Bitcoin investing agency.
  • Utilizes Binance API and web browsing for news.
• Agency Swarm Framework
  • Orchestration of AI agents using OpenAI Assistance API.
  • Agents can be created, structured, and communicated with each other.
• Creation Process
  • CEO agent defines agency structure.
  • Agent Creator creates Market Analyzer using templates.
  • Browsing agent finds APIs, exports documentation for analysis.
  • OpenAPI creator generates schemas from documentation.
  • News Harvester agent gathers news.
  • Genesys CEO finalizes agency, adds imports, and formats files.
• Testing the Agency
  • API keys needed for real API interactions.
  • API keys added to agents via API headers or params.
  • Agency tested with python-agency.py command.
  • CEO compiles Bitcoin market analysis.
• Framework Updates
  • CI pipeline on GitHub for stability.
  • Agents can share files using message files parameter.
  • ToolFactory simplifies tool creation from schemas.
  • Genesis Agency includes CEO, Agent Creator, OpenAPI Creator, and Browsing Agent.
• Testing the Framework
  • Steps to clone the repo, set up the environment, and run Jupyter Notebook.
  • Contribution to GitHub encouraged with guidelines in [contributing.md].
• Conclusion
  • Open Source community’s potential to create AGI.
  • OpenAI’s models’ potential not fully realized.
  • Collective contribution could cover many jobs on earth.
  • Encouragement to subscribe and contribute to the project.