Un RAG completo basado en OCR de Mistral, empezando desde PDF

Avanzado

Este es unAI, IT Opsflujo de automatización del dominio deautomatización que contiene 34 nodos.Utiliza principalmente nodos como Set, Code, Wait, GoogleDrive, HttpRequest, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Construye un sistema RAG para documentos PDF usando OCR de Mistral, Qdrant y IA de Gemini

Requisitos previos
  • Credenciales de API de Google Drive
  • Pueden requerirse credenciales de autenticación para la API de destino
  • Clave de API de OpenAI
  • Información de conexión del servidor Qdrant
  • Clave de API de Google Gemini
Vista previa del flujo de trabajo
Visualización de las conexiones entre nodos, con soporte para zoom y panorámica
Exportar flujo de trabajo
Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo
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  "name": "Complete RAG from PDF with Mistral OCR",
  "tags": [],
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        "url": "https://api.mistral.ai/v1/files",
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        "contentType": "multipart-form-data",
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
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              "name": "purpose",
              "value": "ocr"
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              "parameterType": "formBinaryData",
              "inputDataFieldName": "data"
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        "nodeCredentialType": "mistralCloudApi"
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        "url": "=https://api.mistral.ai/v1/files/{{ $json.id }}/url",
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        "queryParameters": {
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      "parameters": {
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        "content": "# STEP 1\n\n## Create Qdrant Collection\nChange:\n- QDRANTURL\n- COLLECTION"
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        "content": "# STEP 2\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n## Documents vectorization with Qdrant and Google Drive\nChange:\n- QDRANTURL\n- COLLECTION"
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              "prompt": "Write a concise summary of the following (in italiano):\n\n\n\"{text}\"\n\n\nCONCISE SUMMARY:",
              "combineMapPrompt": "Write a concise summary of the following (in italiano):\n\n\n\"{text}\"\n\n\nCONCISE SUMMARY:"
            }
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        "content": "## STEP 3\nIf you want a \"light\" and faster rag with the main contents replace the \"Set page\" node with \"Summarization Chain\""
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        "width": 500,
        "height": 120,
        "content": "## STEP 4\nTest the RAG"
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        "content": "## Complete RAG system from PDF Documents with Mistral OCR, Qdrant and Gemini AI\n\nThis workflow is designed to process PDF documents using Mistral's OCR capabilities, store the extracted text in a Qdrant vector database, and enable Retrieval-Augmented Generation (RAG) for answering questions. "
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Preguntas frecuentes

¿Cómo usar este flujo de trabajo?

Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.

¿En qué escenarios es adecuado este flujo de trabajo?

Avanzado - Inteligencia Artificial, Operaciones de TI

¿Es de pago?

Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.

Información del flujo de trabajo
Nivel de dificultad
Avanzado
Número de nodos34
Categoría2
Tipos de nodos19
Descripción de la dificultad

Adecuado para usuarios avanzados, flujos de trabajo complejos con 16+ nodos

Autor

Full-stack Web Developer based in Italy specialising in Marketing & AI-powered automations. For business enquiries, send me an email at info@n3w.it or add me on Linkedin.com/in/davideboizza

Enlaces externos
Ver en n8n.io

Compartir este flujo de trabajo

Categorías

Categorías: 34