Description:
To enhance repository security and maintain code authenticity, implement an AI-driven system that checks whether a Pull Request (PR) was generated using AI. The system should leverage AI agents and an LLM of your choice to analyze PR content, comments, and commit messages.
Tasks:
Select an LLM and set up an AI agent to evaluate PRs.
Define criteria for detecting AI-generated code (e.g., syntax patterns, comment structures, repetition).
Integrate the AI agent with GitHub Actions or another CI/CD pipeline for automated checks.
Provide a report or confidence score indicating AI-generated content probability.
Name the notebook ai_generated_pr_checker.ipynb.
Update the README with implementation details and references.
Description:
To enhance repository security and maintain code authenticity, implement an AI-driven system that checks whether a Pull Request (PR) was generated using AI. The system should leverage AI agents and an LLM of your choice to analyze PR content, comments, and commit messages.
Tasks:
Select an LLM and set up an AI agent to evaluate PRs.
Define criteria for detecting AI-generated code (e.g., syntax patterns, comment structures, repetition).
Integrate the AI agent with GitHub Actions or another CI/CD pipeline for automated checks.
Provide a report or confidence score indicating AI-generated content probability.
Name the notebook ai_generated_pr_checker.ipynb.
Update the README with implementation details and references.