Developed RAG Mastery Project and Flask App

• Day: 2025-01-23
• Time: 13:30 to 15:30
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: RAG, Flask, RAPTOR, Langchain, Development

Description

Session Goal

The session focused on developing a Retrieval-Augmented Generation (RAG) application, integrating the RAPTOR model, and setting up a minimal Flask application.

Key Activities

• Implemented a structured approach for mastering and implementing RAG systems, focusing on cost-effective strategies and customizable private app development.
• Developed a project roadmap for the RAG Mastery project, outlining short-term, mid-term, and long-term objectives.
• Conducted a rapid prototyping sprint for a minimum viable RAG application using Flask and FastAPI.
• Addressed common Flask errors such as 404, NameError, and TemplateNotFound.
• Outlined a project tree structure for a lightweight RAG application.
• Prioritized tasks for RAG pipeline development and integrated RAPTOR features.
• Explored modularization of the RAPTOR pipeline and LangChain architecture.

Achievements

• Completed the setup of a minimal Flask application with endpoints for file uploads and queries.
• Resolved common errors in Flask applications, ensuring a stable development environment.
• Established a comprehensive roadmap for the RAG Mastery project, integrating RAPTOR principles.

Pending Tasks

• Further refinement and scaling of the RAG system, focusing on optimization and modularization.
• Implementation of unit tests for the modularized RAPTOR pipeline.

Evidence

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• event_ids: []