📅 2025-04-19 — Session: Refactored PromptFlow for Lightweight AI Development
🕒 00:10–01:05
🏷️ Labels: Promptflow, Ai Development, Architecture, Python, Flowpower
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance the PromptFlow framework for lightweight AI development, focusing on leveraging existing infrastructure and minimizing complexity.
Key Activities
- Refactoring PromptFlow Runner: Developed strategies for utilizing PromptFlow’s capabilities, emphasizing delegation over replication.
- Enhanced Observability and Orchestration: Planned the use of PromptFlow’s infrastructure for run tracking and modular AI functions.
- Core Architecture Components: Drafted core components in Python, including decorators and a YAML-to-PromptFlow compiler.
- Integrating Contracts: Explored the use of contracts to enhance the strategic layer of a lightweight architecture.
- Bi-Directional Authoring: Implemented bi-directional authoring using Python functions and YAML flows.
- FlowExecutor Utilization: Detailed effective use of FlowExecutor for orchestration and AI workflows.
Achievements
- Successfully outlined a comprehensive strategy for adopting PromptFlow.
- Developed a draft of core architecture components for the FlowPower framework.
- Defined a new authoring paradigm in prompt engineering, drawing parallels to React’s impact on UI development.
Pending Tasks
- Further exploration of bi-directional authoring and its integration with existing systems.
- Finalization of the FlowPower stack layers and their documentation.