📅 2025-04-27 — Session: AI Architecture and Agent Development

🕒 02:35–03:55
🏷️ Labels: Ai Architecture, Llmadapter, Jinja2, Email Processing, Automation
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to explore and develop AI architecture components and enhance existing agents with modular and scalable solutions.

Key Activities

  • Reviewed AI OS-level architecture components, focusing on Router Strategies, LLMAdapter, and BaseScheduler.
  • Integrated alive.py with LLMAdapter, discussing compatibility and integration strategies.
  • Designed a router dictionary for automated email processing using an Email Triager Agent.
  • Implemented TaskProcessorAgent and EventProcessorAgent for enriching email data and integrating with calendar systems.
  • Developed Jinja2 templates for dynamic prompt rendering in LLM calls, enhancing the TaskProcessorAgent and JobPostingProcessorAgent.

Achievements

  • Established a framework for scalable AI architecture components.
  • Enhanced email processing agents with modular event processing functions.
  • Upgraded agents with Jinja2 templates for improved prompt engineering.

Pending Tasks

  • Further testing and validation of the integrated systems and templates.
  • Explore additional use cases for the Jinja2 templates in other AI agents.