Introduction to AgentBuilder | Automate your Agents with AutoGen

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AI Summary

• Introduction to Agent Builder
  • Agent Builder automates the creation of agents for specific tasks.
  • It generates agents and selects the best ones for execution.
• Process Overview
  • Configuration setup includes config list and llm config.
  • Agents are generated and saved in a JSON file.
  • An AgentBuilder class is instantiated and used to build agents from a library.
  • The task is executed by selecting the best agents.
• Setting Up the Project
  • Use PyCharm Community Edition to create a new project named “agent_builder”.
  • Install necessary libraries with pip install.
• Coding the Utility File
  • Create a utility file with tasks, system prompts, and a list of agent names.
  • Autogen will use this information to create system messages for each agent.
• Main Python File
  • Import necessary modules and set up variables.
  • Create a configuration file with the model and API key.
  • Define a function to generate agents using the build manager.
  • Dump generated agents into a JSON file.
  • Instantiate the AgentBuilder class.
  • Execute the build_from_library function to select agents.
  • Start the task with the selected agents.
  • Clear agents from the cache after execution.
• Running the Project
  • Insert the OpenAI API key.
  • Run the main Python file.
  • If Docker is not running, set AUTOGEN_DOCKER to false before execution.
  • Review the generated agents.json file and the saved configuration file.
• Conclusion
  • Agent Builder allows AI to select suitable agents for task execution.
  • The system still requires fine-tuning but demonstrates a promising concept.
  • Future improvements are expected to enhance agent selection and task performance.