Developed AI Agent and Modular Orchestration Strategies

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📅 2025-04-24 — Session: Developed AI Agent and Modular Orchestration Strategies

🕒 16:50–18:10
🏷️ Labels: Ai Agent, Orchestration, Aios Architecture, Python Visualization, Yaml Workflows
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to explore and develop strategies for AI agent design and modular orchestration within the AIOS architecture, focusing on creating a self-reflective digital civilization.

Key Activities

  • Graph Visualization: Explored tools for automatic graph generation of Python classes and functions, including Pyreverse and custom AST parsing solutions.
  • Module Tree Generation: Generated visual module trees for project management, ensuring a clean output by excluding unnecessary files.
  • Class Diagrams: Used Pyreverse and Graphviz to generate UML class and package diagrams for the ‘aios’ project.
  • AIOS Architecture Analysis: Conducted a detailed analysis of the AIOS architecture, focusing on its orchestration unit, memory layer, and design patterns.
  • AI Agent Development: Outlined steps to build an AI agent using Retrieval-Augmented Generation (RAG) over a documentation corpus.
  • Orchestration Plane Design: Planned the transition to a comprehensive orchestration plane with ‘Cities of Intelligence’ model, detailing the structure and components.
  • Ecosystem Design: Designed interconnected ecosystems for personal and professional development, emphasizing dual-mind structures and champion agents.
  • YAML DAG Workflows: Developed strategies for modular orchestration of YAML DAG workflows, focusing on meta-agent creation and management.

Achievements

  • Established a framework for generating and visualizing Python code structures.
  • Clarified the AIOS architecture and identified potential improvements.
  • Developed a foundational design for AI agent development and orchestration.

Pending Tasks

  • Implement the orchestration plane and ‘Cities of Intelligence’ model.
  • Further develop and test the AI agent using RAG.
  • Finalize the YAML DAG workflow strategies and test their effectiveness.

Graph View

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