📅 2025-04-11 — Session: Developed Modular AI Workflow Architecture
🕒 13:55–15:10
🏷️ Labels: AI, MVP, Modular Design, Fastapi, Python
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to design and execute a modular AI workflow architecture for a Minimum Viable Product (MVP) using FastAPI and Next.js, focusing on creating reusable components and ensuring future-proof integration.
Key Activities
- Modular App Architecture Design: Explored strategies for building a flexible AI framework with reusable components.
- API Layer Understanding: Detailed the components of the
/api/layer, including routes and adapters. - MVP Execution Checklist: Developed a checklist for executing MVP #1, covering folder setup, prompt schema, flow logic, and more.
- Directory Tree Setup: Provided instructions for scaffolding an MVP directory structure using Python and FastAPI.
- Phased Development Strategy: Implemented a phased strategy to maintain momentum and clarity in project execution.
- Role Definition in AI Workflow: Defined roles of
runner.pyandadapters/local.pyin the modular architecture. - Code Review Automation: Created initial boilerplate code for automating code review processes.
- Python Import Collision Resolution: Addressed and resolved a Python import name collision issue.
- Function Fix in local.py: Fixed a missing function error in
local.py. - Strategic Merge Plan: Outlined a plan for transitioning from a prototype to a clean MVP.
- API Setup Migration Plan: Detailed steps for migrating an API setup into the new MVP.
Achievements
- Successfully designed a modular architecture strategy and executed initial steps for MVP development.
- Resolved technical issues such as import collisions and missing functions.
- Established a clear roadmap and checklist for future development phases.
Pending Tasks
- Complete the implementation of the API setup migration.
- Finalize the strategic merge of components from the prototype to the MVP.