Automated PDF Document RAG System with Mistral, OCR, Qdrant, and Gemini AI

Overview

This workflow automates the creation of a Retrieval-Augmented Generation (RAG) system for PDF documents using Mistral, OCR, Qdrant, and Gemini AI. It streamlines the process of uploading, processing, and querying PDF content through chat interfaces.

Key Features

• Automated PDF Upload & OCR: Utilizes Mistral for secure PDF uploads and advanced OCR extraction.
• Data Processing: Splits and processes document text using tokenization and OpenAI embeddings for semantic search.
• Vector Storage: Integrates with Qdrant for efficient vector storage and retrieval.
• Chat Integration: Enables real-time querying of document content via chat triggers powered by Gemini AI.

Benefits

• Efficiency: Eliminates manual document processing, saving significant time and reducing errors.
• Scalability: Handles large volumes of documents and queries with ease.
• Enhanced Accessibility: Makes document data instantly searchable and accessible through conversational AI.

Use Cases

• Legal, HR, or compliance teams needing rapid access to document insights.
• Customer support agents retrieving information from manuals or contracts.
• Any business automating knowledge extraction from large PDF repositories.

Integrations & Automation

Key integrations include Mistral for OCR, OpenAI for embeddings, Qdrant for vector storage, and Gemini AI for chat-based retrieval, all orchestrated within n8n for seamless automation.