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Project description

Raggify Perception

Introduction

This document is an input reference for developing raggify-perception: the part of Raggify system.

Related Modules

Raggify App

  • Developed as a web application

Web Server (raggify-app client)

  • The client folder is the root of raggify-app client
  • Frontend of raggify-app
  • Uses React, TypeScript, etc.
  • Main feature is chat-style querying over documents ingested into the knowledge base
  • Chat UI aims for a NotebookLM-like experience
  • RAG pipeline settings UI aims for a Dify-like experience

App Server (raggify-app server)

  • The server folder is the root of raggify-app server
  • Backend of raggify-app
  • Python program
  • Manages user information and routes requests to raggify server
  • Sits between raggify-app client (front) and raggify server (back)
  • raggify server is treated as a driver abstraction
  • It has an agent implementation and uses the backend LLM server to generate answers

RAG Server (raggify server)

  • The RAG foundation library described above
  • Published as a PyPI library
  • Handles upstream RAG processing (local file/URL ingestion, embeddings, index generation, etc.)
  • Can selectively use local models and third-party APIs
  • Supports several usage modes; in this project it runs as a resident REST API server
  • This is where scaling should happen

Raggify Client

  • Client program used when raggify server is accessed as a REST API server
  • Published as a PyPI library
  • Supports several usage modes; in this project it provides an API for requests from raggify-app server to raggify server

LLM Server

  • Pure local LLM server.

Raggify Perception Library

  • The development target of this project
  • Provides REST API Client for OCR, ASR, and image, audio, and video captioning, used by the raggify server when ingesting documents and by the app server when generating queries

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