Build a PDF search system with Mistral OCR and Weaviate DB

Build a PDF to Vector RAG System: Mistral OCR, Weaviate Database and MCP Server

A comprehensive RAG (Retrieval-Augmented Generation) workflow that transforms PDF documents into searchable vector embeddings using advanced AI technologies.

🚀 Features

- PDF Document Processing: Upload and extract text from PDF files using Mistral's OCR capabilities - Vector Database Storage: Store document embeddings in Weaviate vector database for efficient retrieval - AI-Powered Search: Search through documents using semantic similarity with Cohere embeddings - MCP Server Integration: Expose the knowledge base as an AI tool through MCP (Model Context Protocol) - Document Metadata: Basic document metadata including filename, content, source, and upload timestamp - Text Chunking: Automatic text splitting for optimal vector storage and retrieval

🛠️ Technologies Used

- Mistral AI: OCR and text extraction from PDF documents - Weaviate: Vector database for storing and retrieving document embeddings - Cohere: Multilingual embeddings and reranking for improved search accuracy - MCP (Model Context Protocol): AI tool integration for external AI workflows - n8n: Workflow automation and orchestration

📋 Prerequisites

Before using this template, you'll need to set up the following credentials: