Example for running a multi-agent autogen workflow.
Autocomplete code snippets in Python
Generate code from a description
Explore Tailwind CSS with a customizable playground
Generate code with instructions
Submit code models for evaluation on benchmarks
Generate code snippets from a prompt
Answer programming questions with GenXAI
Obfuscate code
Complete code snippets with automated suggestions
Generate C++ code instructions
Execute any code snippet provided as an environment variable
AutoGen MultiAgent Example is a demonstration of a multi-agent workflow for auto-generating approved code and its associated help documentation. It serves as an example implementation for running such workflows, showcasing how multiple AI agents can collaborate to produce high-quality code and documentation efficiently.
• Multi-Agent Architecture: Utilizes multiple AI agents to handle different aspects of code generation and documentation.
• Code Generation: Automatically produces approved code based on specified requirements.
• Help Documentation: Generates comprehensive documentation to explain the generated code.
• Workflow Integration: Seamlessly integrates multiple agents to work together in a coordinated workflow.
• Customizable: Allows users to define specific tasks and output requirements for each agent.
• Open-Source Example: Provided as an open-source example for educational and development purposes.
pip install autogen
What is the purpose of the multi-agent architecture?
The multi-agent architecture allows for efficient and specialized handling of different tasks, such as code generation and documentation writing, by assigning them to different AI agents.
How do I customize the workflow for my needs?
You can customize the workflow by defining specific tasks and output requirements for each agent before running the workflow.
Where can I find more examples or documentation?
Additional examples and documentation can be found in the official repository or through the installed package's documentation.