Developed Modular Python AI Agent Framework

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📅 2025-05-02 — Session: Developed Modular Python AI Agent Framework

🕒 20:15–21:40
🏷️ Labels: Ai Agents, Python, Modular Design, Deployment, Promptflow
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to explore and establish best practices for developing a modular Python framework for AI agents, focusing on scalable architecture, deployment strategies, and integration with existing tools.

Key Activities

  • Reviewed project structures and best practices for organizing AI agents, emphasizing modularity and scalability.
  • Identified core areas for mastering platform architecture, including modular design, metadata handling, and deployment automation.
  • Discussed principles of modular Python application design, focusing on callable functions and dynamic module loading.
  • Explored structured metadata and configuration handling using pydantic and dataclasses.
  • Outlined deployment strategies using Gradio and Streamlit on Hugging Face Spaces, and discussed CI/CD automation options.
  • Considered scaling strategies for Hugging Face Spaces and integrating existing tools like AIOS and PromptFlow.
  • Reflected on advanced @dataclass usage and architectural insights from PromptFlow.

Achievements

  • Established a comprehensive understanding of modular design principles and deployment strategies for AI agents.
  • Developed insights into integrating PromptFlow’s tracing and configuration capabilities into AIOS.
  • Identified advanced patterns for using dataclasses in orchestration systems.

Pending Tasks

  • Implement the discussed modular design and deployment strategies in a real-world AI agent framework.
  • Explore further integration of Cerebrum SDK capabilities with existing AI systems.

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