Build PDF Search RAG System: Mistral OCR + Weaviate DB - n8n Workflow | Neura Market

    Build PDF Search RAG System: Mistral OCR + Weaviate DB

    Transforms PDFs into searchable vector embeddings using Mistral OCR for text extraction, Weaviate for storage, Cohere for semantic search, and MCP for AI integration.

    This n8n workflow creates a complete Retrieval-Augmented Generation (RAG) system for PDF documents. It starts by processing uploaded PDFs with Mistral AI's OCR to accurately extract text, even from scanned or image-based files. The extracted text is then automatically chunked into optimal sizes for vectorization, preserving context for better retrieval. Embeddings are generated using Cohere's multilingual models and stored in a Weaviate vector database under a 'KnowledgeDocuments' collection. T
    Platform
    n8n
    Category
    AI & Machine Learning
    Price
    $24.99
    Creator
    Fred Garcia
    • RAG
    • PDF OCR
    • Mistral AI
    • Weaviate
    • Cohere Embeddings
    • Vector Database
    • Semantic Search
    • Document Processing
    • AI Automation
    • MCP Server
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    How to import this workflow into n8n

    1. 1Purchase or download the workflow to get the n8n workflow JSON file.
    2. 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
    3. 3Open each node marked with a credential warning and connect your own accounts and API keys.
    4. 4Run the workflow once manually to verify the data flow, then toggle it to Active.

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