Extending the JoyAgent-JDGenie functionality requires the following development specifications:
- directory structure: New tools should be placed in the tools/ directory, it is recommended to have separate python files for each tool.
- interface standard: must be realized
execute()method as an entry point to receive input in JSON format and return structured data - Dependency management: Synchronize the requirements.txt file with new dependencies.
- Configuration Registration: Add the tool path and name mapping in config.yaml
Example of a specific development process:
- Create custom_module.py in the tools directory
- Implements the core processing class, inheriting from the BaseTool class and overriding key methods.
- After the test passes, add a new entry in the tools node of config.yaml
- (of a computer) run
python3 -m simulated_web_agent.main --persona example.jsonVerify the effectiveness of the integration
The project documentation recommends writing unit tests using pytest to ensure module compatibility. Advanced users can also develop multi-intelligent body collaboration strategies and implement custom task assignment logic by modifying agent_router.py.
This answer comes from the articleJoyAgent-JDGenie: an open source multi-intelligence framework to support automated processing of complex tasksThe
May not be reproduced without permission:AI productivity tools " How to add custom function modules to JoyAgent-JDGenie? What development specifications do I need to follow?
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