Agente de IA inteligente: conversar con archivos en el almacenamiento de Supabase
Avanzado
Este es unEngineering, DevOps, Product, AI, IT Opsflujo de automatización del dominio deautomatización que contiene 33 nodos.Utiliza principalmente nodos como If, Merge, Switch, Supabase, Aggregate, combinando tecnología de inteligencia artificial para lograr automatización inteligente. 与Supabase存储中文件对话deAIinteligente体
Requisitos previos
- •URL y Clave de API de Supabase
- •Pueden requerirse credenciales de autenticación para la API de destino
- •Clave de API de OpenAI
Nodos utilizados (33)
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
{
"meta": {
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"parameters": {
"url": "=https://yqtvdcvjboenlblgcivl.supabase.co/storage/v1/object/list/private",
"method": "POST",
"options": {},
"jsonBody": "={\n \"prefix\": \"\",\n \"limit\": 100,\n \"offset\": 0,\n \"sortBy\": {\n \"column\": \"name\",\n \"order\": \"asc\"\n }\n}",
"sendBody": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "supabaseApi"
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"position": [
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"parameters": {
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"name": "=file_id",
"value": "={{ $json.id }}"
}
]
}
},
"jsonData": "={{ $('Merge').item.json.data ?? $('Merge').item.json.text }}",
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},
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"content": "### ... or watch set up video [10 min]\n[](https://www.youtube.com/watch?v=glWUkdZe_3w)\n"
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"content": "\n## AI Agent To Chat With Files In Supabase Storage\n**Made by [Mark Shcherbakov](https://www.linkedin.com/in/marklowcoding/) from community [5minAI](https://www.skool.com/5minai-2861)**\n\nManually retrieving and analyzing specific information from large document repositories is time-consuming and inefficient. This workflow automates the process by vectorizing documents and enabling AI-powered interactions, making it easy to query and retrieve context-based information from uploaded files.\n\nThe workflow integrates Supabase with an AI-powered chatbot to process, store, and query text and PDF files. The steps include:\n- Fetching and comparing files to avoid duplicate processing.\n- Handling file downloads and extracting content based on the file type.\n- Converting documents into vectorized data for contextual information retrieval.\n- Storing and querying vectorized data from a Supabase vector store.\n\n"
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"parameters": {
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"content": "### Set up steps\n\n1. **Fetch File List from Supabase**:\n - Use Supabase to retrieve the stored file list from a specified bucket.\n - Add logic to manage empty folder placeholders returned by Supabase, avoiding incorrect processing.\n\n2. **Compare and Filter Files**:\n - Aggregate the files retrieved from storage and compare them to the existing list in the Supabase `files` table.\n - Exclude duplicates and skip placeholder files to ensure only unprocessed files are handled.\n\n3. **Handle File Downloads**:\n - Download new files using detailed storage configurations for public/private access.\n - Adjust the storage settings and GET requests to match your Supabase setup.\n\n4. **File Type Processing**:\n - Use a Switch node to target specific file types (e.g., PDFs or text files).\n - Employ relevant tools to process the content:\n - For PDFs, extract embedded content.\n - For text files, directly process the text data.\n\n5. **Content Chunking**:\n - Break large text data into smaller chunks using the Text Splitter node.\n - Define chunk size (default: 500 tokens) and overlap to retain necessary context across chunks.\n\n6. **Vector Embedding Creation**:\n - Generate vectorized embeddings for the processed content using OpenAI's embedding tools.\n - Ensure metadata, such as file ID, is included for easy data retrieval.\n\n7. **Store Vectorized Data**:\n - Save the vectorized information into a dedicated Supabase vector store.\n - Use the default schema and table provided by Supabase for seamless setup.\n\n8. **AI Chatbot Integration**:\n - Add a chatbot node to handle user input and retrieve relevant document chunks.\n - Use metadata like file ID for targeted queries, especially when multiple documents are involved."
},
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"parameters": {
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"content": "## Scenario 2 - AI agent"
},
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"parameters": {
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"content": "## Scenario 1 - Flow for adding new files from Supabase storage"
},
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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 - Ingeniería, DevOps, Producto, 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.
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Información del flujo de trabajo
Nivel de dificultad
Avanzado
Número de nodos33
Categoría5
Tipos de nodos18
Descripción de la dificultad
Autor
Mark Shcherbakov
@lowcodingdevI am a business analyst with a development background, dedicated to helping small businesses and entrepreneurs leverage cloud services for increased efficiency. My expertise lies in automating manual workflows, integrating data from multiple cloud service providers, creating insightful dashboards, and building custom CRM systems.
Enlaces externos
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