Autogen: Agents Building Agents - Surprising Results of 2 Use Cases

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AI Summary

• Overview of Autogen’s New Feature
  • Autogen can now automatically create agents based on user input.
  • Two examples demonstrated: content creation and code development.
• Installation Process
  • Create an Anaconda environment.
  • Clone the repository and open in Visual Studio Code.
  • Update files and add API keys by renaming oi_config_list.sample to oi_config_list.json.
  • Select the desired model and update API keys.
  • Copy a simple file and run the script.
• Content Creation Use Case
  • Request: Generate seven LinkedIn posts for a copywriter about copywriting.
  • Autogen created agents: Content Strategist, Copywriter, Social Media Manager, Graphic Designer, and SEO Specialist.
  • Agents generated posts on various copywriting topics.
  • Graphic Designer admitted inability to create visual content.
  • SEO Specialist suggested ideas for graphical content.
• Code Development Use Case
  • Request: Create a simple snake game.
  • Autogen created agents: Game Designer and Software Developer.
  • Software Developer outlined a comprehensive plan for the snake game in Python.
  • Provided Python code did not work, and subsequent advice did not resolve the issue.
• Conclusion
  • The feature shows promise in deploying agents for tasks.
  • Results were not satisfactory, with content creation using five agents and game development using two.
  • Comparison with other frameworks like SE task weaver and GPT-4 suggested.
  • Open to suggestions for script improvement.
  • Offer to assist with setup in the comments.
  • Encouragement to like, subscribe, and stay tuned for future updates.