📅 2025-04-18 — Session: Defined architecture for PromptFlow AI workflows
🕒 17:55–18:35
🏷️ Labels: Promptflow, Ai Workflows, Architecture, Modular Design, Script Analysis
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to define and outline the architecture of the PromptFlow Engine, a modular orchestration framework for AI workflows, utilizing YAML-defined flows and reusable building blocks.
Key Activities
- Reviewed the architecture of the PromptFlow Engine, focusing on its modular design and the use of YAML for defining workflows.
- Outlined the open-source architecture of PromptFlow, detailing its components, responsibilities, and developer interfaces.
- Discussed the seven core architectural pillars of PromptFlow, emphasizing modularity, composability, scalability, and developer intuitiveness.
- Analyzed and decomposed scripts into executable snippets, tagging them according to the PromptFlow pillars and suggesting refactoring directions.
- Mapped AI workflow scripts to the architectural pillars, highlighting the purpose and functionality of each code segment.
- Outlined the mapping of a blog clustering and deduplication script to the PromptFlow pillars, detailing the script’s execution and organization.
- Implemented a structured PromptFlow pipeline for extracting structured metadata from blog post ideas.
- Organized Python blocks for use within an AI flow engine, categorizing them by functional roles.
Achievements
- Successfully defined the architecture of the PromptFlow Engine, emphasizing its modular and scalable design.
- Clarified the mapping of AI workflow scripts to the architectural pillars of PromptFlow.
- Enhanced the organization and usability of Python blocks within the AI flow engine.
Pending Tasks
- Further refinement of script decomposition and refactoring directions.
- Additional testing and validation of the PromptFlow pipeline for AI extraction.
- Continued development of developer interfaces and documentation.