Discuter avec des fichiers PDF/MD/texte via GraphRAG (sans stockage vectoriel)
Avancé
Ceci est unSupport, AIworkflow d'automatisation du domainecontenant 20 nœuds.Utilise principalement des nœuds comme Set, Switch, GoogleDrive, HttpRequest, ManualTrigger, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Dialoguer avec des fichiers PDF/MD/texte en utilisant GraphRAG (sans stockage vectoriel)
Prérequis
- •Informations d'identification Google Drive API
- •Peut nécessiter les informations d'identification d'authentification de l'API cible
- •Clé API OpenAI
Nœuds utilisés (20)
Catégorie
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
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"meta": {
"instanceId": "2a26454b0172ffcb8d70ba77c235b1209f92cd71bf06c79ba609c7173b416d68",
"templateCredsSetupCompleted": true
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"name": "Chat with PDF / MD / Text Files using GraphRAG (no vector store needed)",
"tags": [
{
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"name": "Support",
"createdAt": "2025-05-21T17:06:32.355Z",
"updatedAt": "2025-05-21T17:06:32.355Z"
},
{
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"createdAt": "2025-05-21T19:44:19.136Z",
"updatedAt": "2025-05-21T19:44:19.136Z"
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{
"id": "sJk9cUvmMU8FkJXv",
"name": "AI",
"createdAt": "2025-05-20T13:16:15.636Z",
"updatedAt": "2025-05-20T13:16:15.636Z"
}
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"nodes": [
{
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"name": "Rechercher Google Drive",
"type": "n8n-nodes-base.googleDrive",
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"cachedResultUrl": "https://drive.google.com/drive/folders/13tqp0SaI_v4jG1CFLAZo96isx-UBno4v",
"cachedResultName": "GraphRAG"
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},
"options": {},
"resource": "fileFolder",
"returnAll": true,
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{
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"type": "n8n-nodes-base.googleDrive",
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"value": "={{ $json.id }}"
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{
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"parameters": {
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"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "application/pdf"
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"renameOutput": true
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{
"outputKey": "text",
"conditions": {
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"operator": {
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"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "text/plain"
}
]
},
"renameOutput": true
},
{
"outputKey": "md",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
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"operator": {
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"type": "string",
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},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "text/markdown"
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},
"renameOutput": true
},
{
"outputKey": "json",
"conditions": {
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"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "application/json"
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"renameOutput": true
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{
"outputKey": "docs",
"conditions": {
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{
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"conditions": {
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"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "csv"
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},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "fe133ad7-bd7a-43e2-91a7-4b3dd2652490",
"name": "Extraire depuis PDF",
"type": "n8n-nodes-base.extractFromFile",
"position": [
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],
"parameters": {
"options": {},
"operation": "pdf"
},
"typeVersion": 1
},
{
"id": "49f89141-a8ea-46c6-888d-cf9dafcc7c2a",
"name": "Extraire depuis un fichier texte",
"type": "n8n-nodes-base.extractFromFile",
"position": [
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],
"parameters": {
"options": {},
"operation": "text"
},
"typeVersion": 1
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{
"id": "a47d8f07-917e-44ed-a69e-5d6085981d36",
"name": "Extraire depuis Markdown",
"type": "n8n-nodes-base.extractFromFile",
"position": [
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"parameters": {
"options": {},
"operation": "text"
},
"typeVersion": 1
},
{
"id": "a2298650-5408-45f8-accf-292ac669002a",
"name": "InfraNodus Save to Graph",
"type": "n8n-nodes-base.httpRequest",
"position": [
1480,
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],
"parameters": {
"url": "https://infranodus.com/api/v1/graphAndStatements?doNotSave=false&includeGraph=false&includeGraphSummary=true&includeGraph=false",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "name",
"value": "graphrag_from_google_drive"
},
{
"name": "text",
"value": "={{ $json.data }}"
},
{
"name": "=categories",
"value": "=[filename: {{ $('Switch').item.json.name }}]"
},
{
"name": "contextSettings",
"value": "={{{ \"squareBracketsProcessing\":\"IGNORE_BRACKETS\"} }}"
}
]
},
"genericAuthType": "httpBearerAuth"
},
"credentials": {
"httpBearerAuth": {
"id": "FPDx6PA5CtzGEIQc",
"name": "InfraNodus DeeMeeTree API Key"
}
},
"typeVersion": 4.2
},
{
"id": "bb06d60a-01c7-4a1e-bc7a-901e1f7f175d",
"name": "Note adhésive4",
"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"color": 4,
"width": 2200,
"height": 980,
"content": "# Step 1: Upload Your PDF / MD / Text Files to InfraNodus GraphRAG\n\n## Copy your PDF files to a Google drive and then upload them to your InfraNodus knowledge graph\n\n### InfraNodus visualizes your text as a knowledge graph, showing the main topics and ideas inside. It also provides API access to the knowledge graph, so you can use it as a knowledge base instead of the complex vector store setup\n\n1. You need an [InfraNodus](https://infranodus.com) account to use this workflow. Get the API key at [https://infranodus.com/api-access](https://infranodus.com/api-access)\n2. Also, specify the **name of the graph** you want to save the files to in the InfraNodus HTTP node\n3. When the workflow finishes running, you can get a visualization of your knowledge base at [https://infranodus.com/your_user_name/your_graph_name/edit](https://infranodus.com/your_user_name/your_graph_name/edit)\n\n\n"
},
"typeVersion": 1
},
{
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"name": "Mapper PDF en texte",
"type": "n8n-nodes-base.set",
"position": [
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"parameters": {
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"assignments": {
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},
"typeVersion": 3.4
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{
"id": "49426e56-7d6c-4dc0-a279-348dea59cca2",
"name": "Convertir le fichier en PDF",
"type": "n8n-nodes-base.httpRequest",
"disabled": true,
"position": [
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"parameters": {
"url": "https://v2.convertapi.com/convert/pdf/to/txt",
"method": "POST",
"options": {
"response": {
"response": {
"responseFormat": "text"
}
}
},
"sendBody": true,
"contentType": "multipart-form-data",
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "file",
"parameterType": "formBinaryData",
"inputDataFieldName": "data"
}
]
},
"genericAuthType": "httpBearerAuth",
"headerParameters": {
"parameters": [
{
"name": "Accept",
"value": "application/octet-stream"
}
]
}
},
"credentials": {
"httpBearerAuth": {
"id": "mDxLoJUWSmuTJsAC",
"name": "ConvertAPI"
}
},
"notesInFlow": true,
"typeVersion": 4.2
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{
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"name": "Note adhésive5",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 2,
"width": 360,
"height": 840,
"content": "## Optional: Better PDF Conversion\n\n### Standard Map PDF to Text node will split your PDF files into very short chunks, which deteriorates retrieval. \n\nUse can use [ConvertAPI](https://convertapi.com?ref=4l54n) which is a high-quality convertor that will respect the layout of the original document and not cut the paragraphs into short chunks. \n\nHere is an HTTP node that makes a request to their API to convert the PDF into text. If you have a ConvertAPI account, you can replace the \"Map PDF to Text\" node in step 4 with this node. \n"
},
"typeVersion": 1
},
{
"id": "ceda9ea4-963b-4ffb-a741-6e7eb3fc7411",
"name": "À la réception d'un message de chat",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"disabled": true,
"position": [
-520,
840
],
"webhookId": "a2cfd3b0-aaa4-4003-940d-e520e64830c6",
"parameters": {
"public": true,
"options": {
"title": "Talk to PDFs"
},
"initialMessages": "=Ask any question about the PDFs or write `/question` to generate an interesting question to discuss."
},
"typeVersion": 1.1
},
{
"id": "d78cf21e-753b-44d3-a2b4-493f85aa5129",
"name": "Agent IA",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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],
"parameters": {
"options": {
"systemMessage": "You provide information about the topic of user's interest. Always use the knowledge base attached to get the final response. "
}
},
"typeVersion": 1.9
},
{
"id": "02497c8b-89d6-4440-bc4d-d3906b9c4872",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
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],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "07wFa8Wa4mMRCHAj",
"name": "OpenAi account 2"
}
},
"typeVersion": 1.2
},
{
"id": "6d77fb59-fb03-4d22-ac40-4cf9bde25909",
"name": "Mémoire simple",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
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],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "978c8309-380d-4fc8-b238-e0d0148b77b9",
"name": "Base de connaissances GraphRAG",
"type": "n8n-nodes-base.httpRequestTool",
"position": [
100,
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],
"parameters": {
"url": "https://infranodus.com/api/v1/graphAndAdvice?doNotSave=true&addStats=true&optimize=develop&includeStatements=true&includeGraphSummary=true&includeGraph=false",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "name",
"value": "graphrag_from_google_drive"
},
{
"name": "requestMode",
"value": "response"
},
{
"name": "prompt",
"value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters2_Value', `User query to send to the expert`, 'string') }}"
},
{
"name": "aiTopics",
"value": "true"
}
]
},
"genericAuthType": "httpBearerAuth",
"toolDescription": "You contain knowledge on the topic of user's interst"
},
"credentials": {
"httpBearerAuth": {
"id": "6lSuuSDajZrvI2GM",
"name": "InfraNodus API Key"
}
},
"typeVersion": 4.2
},
{
"id": "b005f83d-3d4a-42c8-b70a-63e267747fcd",
"name": "Note adhésive",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
540
],
"parameters": {
"width": 2200,
"height": 700,
"content": "# Step 2: Chat with your PDF / MD / Text Files using [InfraNodus](https://infranodus.com) Graph RAG Knowledge Base\n\n## InfraNodus is used instead of the vector store. It combines traditional RAG and GraphRAG, providing a better topical overview of your knowledge base and having a better understanding of relations between entities in your documents.\n\n1. Deactivate the trigger node in Step 1 and activate the trigger Chat node here\n2. Provide your API key at [https://infranodus.com/api-access](https://infranodus.com/api-access) to the HTTP agent tool\n3. Specify the same **name of the graph** as in the Step 1, so you query the graph where saved the files. \n4. If you connect several knowledge bases, make sure to describe them well, so the agent knows what to query. Get the description from the InfraNodus Graph > Project Notes > RAG enhancement"
},
"typeVersion": 1
},
{
"id": "6a6ad150-670d-45d5-a69e-0bafaf8f2ac4",
"name": "Cliquer sur 'Tester le workflow' pour ingérer les documents",
"type": "n8n-nodes-base.manualTrigger",
"position": [
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-120
],
"parameters": {},
"typeVersion": 1
},
{
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"name": "Note adhésive1",
"type": "n8n-nodes-base.stickyNote",
"position": [
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100
],
"parameters": {
"width": 680,
"height": 380,
"content": "## [InfraNodus](https://infranodus.com) Knowledege Graph Example\n\n"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "90ea1bad-6d21-4f20-81b4-0ba48cc7e7fa",
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"type": "ai_languageModel",
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}Foire aux questions
Comment utiliser ce workflow ?
Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.
Dans quelles scénarios ce workflow est-il adapté ?
Avancé - Support, Intelligence Artificielle
Est-ce payant ?
Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.
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Code
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Code
129 NœudsKumar Shivam
Support
Ingestion de fichiers Google Drive vers la base de connaissances Supabase
Base de connaissances interactive de type chat basée sur RAG Supabase et GPT-4o-mini
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Gmail
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Gmail
46 NœudsImmanuel
Support
Agent de Chatbot IA : Groupe d'experts utilisant les connaissances Graph RAG d'InfraNodus
Agent de chatbot IA en groupe d'experts utilisant la technologie de graphe de connaissances GraphRAG d'InfraNodus
Agent
Http Request Tool
Chat Trigger
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Agent
Http Request Tool
Chat Trigger
14 NœudsInfraNodus
Support
Traitement de documents RAG piloté par IA et chatbot - Google Drive, Supabase, OpenAI
Traitement de documents RAG piloté par IA et chatbot basé sur Google Drive, Supabase et OpenAI
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35 NœudsBilly Christi
Intelligence Artificielle
Informations sur le workflow
Niveau de difficulté
Avancé
Nombre de nœuds20
Catégorie2
Types de nœuds13
Description de la difficulté
Auteur
InfraNodus
@infranodusI'm Dmitry, the founder of InfraNodus — an AI text network analysis tool. I'm passionate about networks and data visualization and its ability to reveal what everyone else is missing and to highlight different perspectives. I'm sharing the n8n templates that make use of this unique capability of InfraNodus for multiple scenarios.
Liens externes
Voir sur n8n.io →
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