📅 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.