Now that you have learned the basics of AutoGen, you can start to build your own agents. Here are some ideas to get you started without going to the advanced topics:

  1. Chat with LLMs: In Human in the Loop we covered the basic human-in-the-loop usage. You can try to hook up different LLMs using local model servers like Ollama and LM Studio, and chat with them using the human-in-the-loop component of your human proxy agent.
  2. Prompt Engineering: In Code Executors we covered the simple two agent scenario using GPT-4 and Python code executor. To make this scenario work for different LLMs and programming languages, you probably need to tune the system message of the code writer agent. Same with other scenarios that we have covered in this tutorial, you can also try to tune system messages for different LLMs.
  3. Complex Tasks: In ConversationPatterns we covered the basic conversation patterns. You can try to find other tasks that can be decomposed into these patterns, and leverage the code executors and tools to make the agents more powerful.

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Dig Deeper

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Get Help

If you have any questions, you can ask in our Discord Server.

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Get Involved

  • Check out Roadmap Issues to see what we are working on.
  • Contribute your work to our gallery
  • Follow our contribution guide to make a pull request to AutoGen
  • You can also share your work with the community on the Discord server.
Conversation PatternsMulti-agent Conversation Framework