πŸ“… 2025-04-27 β€” Session: Enhanced Daemon Liveness and MVP Planning

πŸ•’ 00:30–01:00
🏷️ Labels: Python, Daemon, MVP, Testing, Automation, Architecture
πŸ“‚ Project: Dev
⭐ Priority: MEDIUM

Session Goal:

The session aimed to enhance the robustness of the alive.py daemon, test its functionalities without disrupting production, and plan an MVP for a Gmail autocomplete feature.

Key Activities:

  • Improved Liveness Loop: Enhanced the alive.py script with better signal handling, logging, and error management to ensure robustness and graceful shutdowns.
  • Testing Strategies: Developed three strategies for testing alive.py safely, including isolated agent calls and test mode launches.
  • Dynamic Script Loading: Implemented a solution for dynamically loading Python scripts using sys.path manipulation.
  • Import Error Fixes: Addressed Python import issues by configuring sys.path correctly and provided best practices.
  • Agent Architecture: Outlined a system architecture for organizing agents, distinguishing between agent classes and workflow functions.
  • MVP Development Plan: Created a structured plan for developing a Gmail autocomplete Chrome extension, detailing components and timeline.

Achievements:

  • Successfully improved the alive.py daemon’s liveness loop.
  • Established a clear plan to test alive.py without affecting production.
  • Resolved common Python import issues, enhancing development efficiency.
  • Developed a comprehensive MVP plan for a Gmail autocomplete extension.

Pending Tasks:

  • Implement the proposed agent architecture and integrate it with the alive.py scheduler.