The current Agent class lacks detailed logging of each step, tool usage, and memory consumption. This makes it difficult for users to debug and analyze the agent's behavior, especially when dealing with complex tasks.
Solution
We've implemented comprehensive logging for the Agent class, capturing detailed information about each step, tool usage, and memory consumption. The logging system now supports both string and JSON output formats, allowing users to choose the most suitable format for their needs.
Key changes include:
Enhanced step logging in the log_step_metadata method
Detailed tool usage tracking
Memory usage monitoring for both short-term and long-term memory
Option to switch between string and JSON output formats
Updated documentation to reflect new logging capabilities
New unit tests and integration tests to ensure logging functionality
Impact
These changes significantly improve the transparency and debuggability of the Agent class. Users can now:
Analyze each step of the agent's decision-making process
Track tool usage and effectiveness
Monitor memory consumption to optimize performance
Choose between human-readable string output or machine-parseable JSON format
Final Results
With these changes, users can now:
Get detailed logs of each step in the agent's process
Track tool usage and performance
Monitor memory consumption
Choose between string and JSON output formats
Easily debug and analyze agent behavior
The enhanced logging system provides valuable insights into the agent's decision-making process, making it easier for developers to optimize and troubleshoot their AI applications.
Problem
The current Agent class lacks detailed logging of each step, tool usage, and memory consumption. This makes it difficult for users to debug and analyze the agent's behavior, especially when dealing with complex tasks.
Solution
We've implemented comprehensive logging for the Agent class, capturing detailed information about each step, tool usage, and memory consumption. The logging system now supports both string and JSON output formats, allowing users to choose the most suitable format for their needs.
Key changes include:
log_step_metadatamethodImpact
These changes significantly improve the transparency and debuggability of the Agent class. Users can now:
Final Results
With these changes, users can now:
The enhanced logging system provides valuable insights into the agent's decision-making process, making it easier for developers to optimize and troubleshoot their AI applications.
Videos And Screenshots
You can find the video of the code explaination , walkthrough , demos , unittests etc here : https://drive.google.com/file/d/1IsL288KWy5IyZ6bKJiEKpWyDAbNomFvH/view?usp=sharing
A small glimpse of all testcases successfully passing including the integration test is as follows :
The first 5 here are indications of successful unittests and the 6th is the successful integration test .
Additional Notes
📚 Documentation preview 📚: https://swarms--615.org.readthedocs.build/en/615/