Developed Modular AI Workflow Framework and RAG Mastery Enhancements

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Developed Modular AI Workflow Framework and RAG Mastery Enhancements

  • Day: 2025-01-28
  • Time: 13:40 to 14:50
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Modular Systems, Ai Workflows, Rag Mastery, UI/UX, Flask, Debugging

Description

Session Goal: The session aimed to explore and develop frameworks for modular AI-driven systems and enhance the RAG Mastery prototype’s user interface.

Key Activities:

  • Outlined a comprehensive framework for modular knowledge workflows, detailing components for inputs, prompts, outputs, and UI/UX concepts.
  • Explored off-the-shelf solutions for building modular AI-driven systems, including workflow automation and prompt orchestration.
  • Proposed a unique product opportunity combining modular AI workflows with a drag-and-drop UI.
  • Planned enhancements for the RAG Mastery Prototype UI, focusing on UI improvements and backend enhancements.
  • Detailed steps for enhancing the UI and tech stack for the RAG Mastery prototype using React and FastAPI.
  • Outlined frontend architecture principles for ChatGPT-like applications using React, TypeScript, and Next.js.
  • Developed a ‘Box of Context’ system architecture for file uploads, including a Flask backend implementation and debugging strategies for file upload issues.

Achievements:

  • Established a clear framework for modular AI workflows and identified potential product opportunities.
  • Enhanced the RAG Mastery prototype’s UI and tech stack, improving user experience and system functionality.
  • Implemented a Flask backend for the ‘Box of Context’ system, addressing file management and debugging issues.

Pending Tasks:

  • Further refine the modular AI workflow framework and explore integration with existing platforms.
  • Continue UI enhancements for the RAG Mastery prototype, focusing on responsive design and accessibility improvements.

Evidence

  • source_file=2025-01-28.sessions.jsonl, line_number=1, event_count=0, session_id=3538214d9b018473a55a57b316bfed3b50c5b0e529cc0d96b4ea161e0021afd1
  • event_ids: []

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