📅 2025-04-14 — Session: Refactored AI Service Architecture and Modular Orchestration
🕒 13:55–16:06
🏷️ Labels: Ai Architecture, Modularity, YAML, Vertex Ai, Promptflow
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to refactor the AI service architecture for improved modularity, reusability, and testability, and to design a modular AI orchestration system.
Key Activities
- Refactoring AI Service Architecture: Focused on decoupling components, separating prompt semantics, LLM communication, and execution logic to enhance maintainability.
- Modular AI Orchestration System Design: Developed a vision for a modular, extensible AI orchestration system using a Prompt Flow OS, detailing core abstractions and integration strategies.
- YAML-based AI Prompt Engine for Vertex Compatibility: Created a YAML-based AI prompt engine aligning with Vertex AI pipelines, emphasizing structured metadata and modularity.
- Codebase Runner Analysis: Analyzed script runners within the codebase, providing recommendations for future action.
- Debugging and Code Optimization: Addressed various Python import errors and debugging issues in PromptFlow, ensuring proper functionality and execution.
Achievements
- Successfully refactored the AI service architecture and designed a modular orchestration system.
- Implemented a YAML-based AI prompt engine compatible with Vertex AI.
- Resolved multiple debugging issues, enhancing the robustness of the AI pipeline.
Pending Tasks
- Further enhancements in logging, caching, and UI improvements for the prompt-chain execution.
- Continued refinement of the modular orchestration system to support additional AI frameworks.