Clasificar y extraer datos de planos usando Mistral AI OCR y JigsawStack

Avanzado

Este es unMiscellaneous, AI Summarization, Multimodal AIflujo de automatización del dominio deautomatización que contiene 24 nodos.Utiliza principalmente nodos como If, Code, Switch, Webhook, HttpRequest. Clasificar y extraer datos de planos usando OCR de Mistral AI y JigsawStack

Requisitos previos
  • Punto final de HTTP Webhook (n8n generará automáticamente)
  • Pueden requerirse credenciales de autenticación para la API de destino
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": {
    "instanceId": "834bc6c387a1c56d0622a24b912577f9e6d66c5873f4e6426166054eb488d8fc",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "120c98f6-17fd-46e7-b449-539cf0e6eccd",
      "name": "Nota: Endpoint de baja calidad",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        4500,
        -300
      ],
      "parameters": {
        "width": 400,
        "height": 440,
        "content": "## 🚫 Low Quality / Drop\n\n**When:** Confidence < 0.4 or unclear image\n\n**Response:**\n- Tell user file isn't a floorplan\n- Suggest uploading blueprint/CAD\n- List acceptable formats (JPG, PNG, PDF)\n\n**User sees:** \"Unable to Process Your Floorplan\""
      },
      "typeVersion": 1
    },
    {
      "id": "fa9dc8cf-6eaa-4a65-b6d0-27d8da7b1a59",
      "name": "Nota: Revisión manual",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        4820,
        520
      ],
      "parameters": {
        "color": 3,
        "width": 400,
        "height": 480,
        "content": "## ⚠️ Manual Review Needed\n\n**When:** Confidence 0.4-0.85 (uncertain)\n\n**Response:**\n- File needs human check\n- Promise 2-hour turnaround\n- Set expectation for email follow-up\n\n**User sees:** \"Manual Review Required\""
      },
      "typeVersion": 1
    },
    {
      "id": "65ded5cd-8648-4eaa-a230-b5eb562df429",
      "name": "Nota: Continuar a JIG",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        5140,
        20
      ],
      "parameters": {
        "color": 4,
        "width": 380,
        "height": 460,
        "content": "## ✅ Continue to Step 2\n\n**When:** Confidence ≥ 0.85 (from text analysis)\n\n**Response:**\n- Confirm successful validation\n- Explain next steps (OCR/measurement)\n- Set 30-60 second expectation\n\n**User sees:** \"Floorplan Accepted!\"\n\n*Continues to Jigsaw OCR*"
      },
      "typeVersion": 1
    },
    {
      "id": "0016e3f6-0552-4cee-b59a-445129a3236a",
      "name": "Nota: Clasificación exitosa",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        3280,
        -520
      ],
      "parameters": {
        "color": 5,
        "width": 580,
        "height": 540,
        "content": "## Image Classification\n\n**When:** Image files with high AI confidence\n\n**Response:**\n- Premium quality detected\n- Instant processing message\n- List what's being calculated\n\n**User sees:** \"Perfect Quality Floorplan\"\n\n*Fast track to measurements*"
      },
      "typeVersion": 1
    },
    {
      "id": "c96745c9-5646-423a-98e9-239df792662e",
      "name": "Nota: Resumen del flujo",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2340,
        -340
      ],
      "parameters": {
        "color": 6,
        "width": 400,
        "height": 360,
        "content": "## 📊 Flow Summary\n\n**PDF Path:**\nExtract text → Score confidence → Route by threshold\n\n**Image Path:**\nDirect to AI classification → Route by result\n\n**Thresholds:**\n- < 40%: Not a floorplan\n- 40-85%: Manual review\n- ≥ 85%: Auto-process\n\n**Goal:** Filter bad uploads early, save API costs"
      },
      "typeVersion": 1
    },
    {
      "id": "e0bcf1b8-ee8e-4a88-afe8-23b9a7b7c4ac",
      "name": "Nota: Límite de archivos",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        3700,
        480
      ],
      "parameters": {
        "color": 2,
        "width": 440,
        "height": 460,
        "content": "## 📏 File Size/Pages Limit\n\n**When:**\n- File > 10MB\n- PDF > 20 pages\n\n**Response:**\n- Explain size limits\n- Ask to split multi‑floor plans\n- Suggest extracting relevant pages\n\n**User sees:** \"File Too Large\""
      },
      "typeVersion": 1
    },
    {
      "id": "67704d28-dbab-4e48-b0b6-1643e0dadc7e",
      "name": "📘 Documentación del flujo de trabajo",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1620,
        -340
      ],
      "parameters": {
        "width": 600,
        "height": 1560,
        "content": "# 🏠 Floorplan Classifier & Measurement Extractor  \n\n## ✅ What This Workflow Does  \n\nAutomatically validates uploaded files (**PDFs or images**) to check if they are genuine floorplans. It rejects non‑floorplans early, and prepares valid files for **room measurement & analysis**.  \n\nThe workflow has **two phases**:  \n1. **Classification (Step 1):** Smart filters & classifiers decide if the upload is usable.  \n2. **Calculation (Step 2):** OCR + AI extract structured room measurements (area + wall surfaces) and compile results.  \n\n---\n\n### Supported File Types  \n- **PDFs** → text is extracted for keyword/measurement checks, then passed to AI.  \n- **Images (JPG, PNG, etc.)** → sent directly to the classifier (can’t extract metadata text).  \n\n---\n\n### Quality Filtering (Step 1)  \n1. **Heuristic checks** → detects floorplan indicators:  \n   - Room names (living room, keuken, slaapkamer, etc.)  \n   - Measurements (m², mm)  \n   - Technical symbols (e.g., WCD, TH, WP).  \n2. **AI classification (JigsawStack)** → robustly decides floorplan vs. not.  \n\n---\n\n### Confidence Routing (Step 1)  \n- **< 40% confidence** → ❌ Rejected (not a floorplan).  \n- **40–85% confidence** → ⚠️ Unclear → ask for better upload/manual review.  \n- **> 85% confidence** → ✅ Accepted floorplan → sent to **Measurement Extraction (Step 2)**.  \n\n---\n\n### Measurement Extraction (Paid version ONLY)  \n---\n\n## ⚒ Requirements  \n- **JigsawStack API key** → File storage + classification  \n- **Mistral Cloud API key** → OCR measurement extraction  \n- **n8n instance** → Self‑hosted or Cloud  \n- **Webhook endpoint** → for uploads & responses  \n\n---\n\n## 🔧 Customization  \n- Adjust **heuristic rules** (keywords/symbols) to match your market.  \n- Change **confidence thresholds** (strict vs. lenient filtering).  \n- Set **wall height** or fallback ratio for wall area calculations.  \n- Choose your OCR/AI provider (Mistral, AWS Textract, Azure Vision, etc.).  \n- Extend workflows to **save results to DB, Notion, Slack, CRM**.  \n\n---\n\n## ⚠️ Notes  \n- Never hardcode API keys → use **n8n credential manager**.  \n- All nodes are **renamed by purpose** (easy to follow).  \n- Sticky Notes document both phases clearly.  \n- Designed as **plug‑and‑play end‑to‑end pipeline** for fast onboarding.  \n"
      },
      "typeVersion": 1
    },
    {
      "id": "30aee9c1-02f8-40b4-b431-8bc122bb08d6",
      "name": "Verificar – Consentimiento GDPR",
      "type": "n8n-nodes-base.if",
      "position": [
        2560,
        80
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "loose"
          },
          "combinator": "or",
          "conditions": [
            {
              "id": "1e3d1d01-1b9e-45b5-9616-93335d2bc270",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{ $json.body.GDPR_check || $json.body.GDPR_check2}}",
              "rightValue": ""
            }
          ]
        },
        "looseTypeValidation": true
      },
      "typeVersion": 2.2
    },
    {
      "id": "2e9797b2-9ce9-4628-b049-95b28bd43e4e",
      "name": "Webhook – Recibir carga",
      "type": "n8n-nodes-base.webhook",
      "position": [
        2320,
        80
      ],
      "webhookId": "fb607944-5e45-4dab-b805-7d0701e5eaa9",
      "parameters": {
        "path": "fp-mvp",
        "options": {
          "ignoreBots": true,
          "allowedOrigins": "*"
        },
        "httpMethod": "POST",
        "responseMode": "responseNode",
        "authentication": "basicAuth"
      },
      "credentials": {
        "httpBasicAuth": {
          "id": "cBS3tiMMVMINcjbT",
          "name": "stucstunter.nl"
        }
      },
      "typeVersion": 2
    },
    {
      "id": "c2de825d-fd9b-4e42-a43c-ff570ea90068",
      "name": "Responder – Consentimiento requerido",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [
        2860,
        300
      ],
      "parameters": {
        "options": {},
        "respondWith": "json",
        "responseBody": "={\n  \"thankYouMessage\": \"<div style='text-align:center; padding:40px 20px; font-family:system-ui;'><h2 style='color:#FF5252;'>⚠️ Consent Required</h2><p>We need your permission to process your floorplan. Please check the privacy consent box and try again.</p><p style='font-size:12px; color:#999; margin-top:20px;'>Your data is deleted within 10 minutes • GDPR compliant</p></div>\"\n}"
      },
      "typeVersion": 1.1
    },
    {
      "id": "d48a571b-0dac-48b2-b60e-d8485ad9f980",
      "name": "Procesar – Cargas múltiples de archivos",
      "type": "n8n-nodes-base.code",
      "position": [
        2820,
        60
      ],
      "parameters": {
        "jsCode": "const results = [];\n\nfor (const item of items) {\n  if (!item.binary) continue;\n\n  for (const [key, value] of Object.entries(item.binary)) {\n    results.push({\n      json: {\n        fileKey: key,\n        fileName: value.fileName,\n        mimeType: value.mimeType,\n        fileExtension: value.fileExtension,\n        fileSize: value.fileSize\n      },\n      binary: {\n        [key]: value   // behoud originele binary key naam!\n      }\n    });\n  }\n}\n\nreturn results;"
      },
      "typeVersion": 2
    },
    {
      "id": "cb575124-245b-4d34-aa23-1d04fddfeea3",
      "name": "Verificar – Tipo de archivo (PDF/Imagen)",
      "type": "n8n-nodes-base.if",
      "position": [
        3040,
        60
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "or",
          "conditions": [
            {
              "id": "837a00af-0c9d-4dde-a184-4d4c2d918005",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{ [\"png\",\"jpg\",\"jpeg\",\"bmp\",\"tiff\",\"webp\",\"gif\"]\n   .includes($json.fileExtension.toLowerCase()) }}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "28353d44-0328-4407-b942-0a87b44c244f",
      "name": "Extraer – Metadatos/Texto de PDF",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        3300,
        80
      ],
      "parameters": {
        "options": {
          "keepSource": "both"
        },
        "operation": "pdf",
        "binaryPropertyName": "={{ $json.fileKey }}"
      },
      "typeVersion": 1
    },
    {
      "id": "4023d030-c089-413a-864d-7a467ce63232",
      "name": "Verificar – Tamaño y páginas del archivo",
      "type": "n8n-nodes-base.if",
      "position": [
        3500,
        80
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "d94826b9-a2fe-4af2-9c76-0d76fdb0c0d8",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{ \n  (() => {\n    const raw = $json.fileSize || \"\";\n    const val = parseFloat(raw);\n    if (raw.toLowerCase().includes(\"mb\")) return val < 10;\n    if (raw.toLowerCase().includes(\"kb\")) return val < 10000; // 10 MB = 10,000 KB\n    if (raw.toLowerCase().includes(\"bytes\")) return val < 10485760; // 10 MB in bytes\n    return false; // if unknown format\n  })()\n}}",
              "rightValue": ""
            },
            {
              "id": "b58f8207-18c9-4e0a-a52d-6a3151f6ee57",
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              },
              "leftValue": "={{$json.fileExtension.toLowerCase() !== \"pdf\"\n  ? true \n  : ($json.numpages && $json.numpages < 10)}}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "25d2a512-494a-4552-a6c6-e68714fd522d",
      "name": "Analizar – Puntuación de confianza (Heurística)",
      "type": "n8n-nodes-base.code",
      "position": [
        3740,
        60
      ],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "// --- SAFER INPUT HANDLING ---\nconst text = ($json.text || \"\").toLowerCase();\nconst numpages = $json.numpages || 1;\n\nlet score = 0;\nlet reasons = []; \n\n// --- KEYWORD LISTS ---\nconst nlSpaces = [\"woonkamer\", \"keuken\", \"slaapkamer\", \"badkamer\", \"overloop\", \"entree\", \"hal\", \"toilet\", \"berging\", \"techniek\", \"meterkast\", \"mk\"];\nconst enSpaces = [\"living room\", \"kitchen\", \"bedroom\", \"bathroom\", \"landing\", \"entrance\", \"hall\", \"toilet\", \"storage\", \"utility room\"];\nconst floorWords = [\"verdieping\", \"begane grond\", \"zolder\", \"kelder\", \"vliering\", \"doorsnede\", \"gevel\", \"plattegrond\"];\nconst enFloorWords = [\"floor\", \"ground floor\", \"attic\", \"basement\", \"cross-section\", \"facade\", \"floor plan\"];\nconst symbols = [\"wcd\", \"th\", \"wp\", \"v.v.\", \"wm\", \"wd\", \"wtw\", \"pv\", \"rad.\", \"rm\", \"gr\"];\nconst projectWords = [\"bouwnummer\", \"opdrachtgever\", \"project\", \"schaal\", \"datum\", \"bladnummer\", \"formaat\"];\n\n// --- CHECKS ---\n// 1. Spaces\nconst foundNlSpaces = nlSpaces.filter(w => text.includes(w));\nconst foundEnSpaces = enSpaces.filter(w => text.includes(w));\nif ((foundNlSpaces.length + foundEnSpaces.length) >= 3) {\n  score += 0.35;\n  reasons.push(`Found ${foundNlSpaces.length + foundEnSpaces.length} room names`);\n}\n\n// 2. m² matches\nconst m2Matches = text.match(/\\d+(?:[.,]\\d+)?\\s*m(?:²|2)/g) || [];\nif (m2Matches.length >= 3) {\n  score += 0.25;\n  reasons.push(`Found ${m2Matches.length} m² measurements`);\n}\n\n// 3. mm matches (dimensions)\nconst mmMatches = text.match(/\\d{3,}\\s*mm/g) || [];\nif (mmMatches.length >= 3) {\n  score += 0.15;\n  reasons.push(`Found ${mmMatches.length} mm measurements`);\n}\n\n// 4. Symbols\nconst foundSymbols = symbols.filter(s => text.includes(s.toLowerCase()));\nif (foundSymbols.length >= 3) {\n  score += 0.15;\n  reasons.push(`Found ${foundSymbols.length} technical symbols`);\n}\n\n// 5. Floor/plan words\nconst foundFloors = [...floorWords, ...enFloorWords].filter(w => text.includes(w));\nif (foundFloors.length >= 2) {\n  score += 0.10;\n  reasons.push(`Found ${foundFloors.length} floor/drawing parts`);\n}\n\n// 6. Project words\nconst foundProjectWords = projectWords.filter(w => text.includes(w));\nif (foundProjectWords.length >= 3) {\n  score += 0.10;\n  reasons.push(`Found ${foundProjectWords.length} project info words`);\n}\n\n// --- NORMALIZE SCORE ---\nif (score > 1) score = 1;\n\n// ✅ Return one item with JSON + preserve binary\nreturn {\n  json: {\n    ...$json,\n    confidence: parseFloat(score.toFixed(2)),\n    analysis: {\n      reasons,\n      foundNlSpaces,\n      foundEnSpaces,\n      m2Matches,\n      mmMatches,\n      foundSymbols,\n      foundFloors,\n      foundProjectWords,\n      pages: numpages\n    }\n  },\n   binary: item.binary // pass binary unchanged\n};"
      },
      "typeVersion": 2
    },
    {
      "id": "87868e3c-e4eb-47ff-acf0-bb4072d38bbc",
      "name": "Enrutar – Niveles de confianza",
      "type": "n8n-nodes-base.switch",
      "position": [
        4020,
        0
      ],
      "parameters": {
        "rules": {
          "values": [
            {
              "outputKey": "very_likely_not_floorplan",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "operator": {
                      "type": "number",
                      "operation": "lt"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.2
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "likely_not_floorplan",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "operator": {
                      "type": "number",
                      "operation": "lt"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.4
                  },
                  {
                    "operator": {
                      "type": "number",
                      "operation": "gte"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.2
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "uncertain_low_confidence",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "operator": {
                      "type": "number",
                      "operation": "lt"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.6
                  },
                  {
                    "operator": {
                      "type": "number",
                      "operation": "gte"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.4
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "=uncertain_high_confidence",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "operator": {
                      "type": "number",
                      "operation": "lt"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.85
                  },
                  {
                    "operator": {
                      "type": "number",
                      "operation": "gte"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.6
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "very_likely_floorplan",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "operator": {
                      "type": "number",
                      "operation": "gte"
                    },
                    "leftValue": "={{ $json.confidence }}",
                    "rightValue": 0.85
                  }
                ]
              },
              "renameOutput": true
            }
          ]
        },
        "options": {
          "fallbackOutput": "extra",
          "allMatchingOutputs": true,
          "renameFallbackOutput": "needs_review"
        }
      },
      "typeVersion": 3.2
    },
    {
      "id": "0a0bf7f3-0eb5-457a-b445-48111e7ac7d3",
      "name": "Responder – Baja calidad/Descartar",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [
        4640,
        -20
      ],
      "parameters": {
        "options": {},
        "respondWith": "json",
        "responseBody": "={{\n  {\n    \"thankYouMessage\":\n      $json.confidence && $json.confidence[0] < 0.4\n        ? \"🚫 Unable to Process Your Floorplan. The image quality is too low or unclear. Please upload an architectural blueprint or CAD drawing instead. Accepted formats: JPG, PNG, PDF.\"\n        : (\n            $json.predictions[0] === \"floorplan\"\n              ? \"SUCCESS: Floorplan detected! Processing your measurements now. This will take 15-30 seconds.\"\n              : \"ERROR: Not a floorplan detected. Please upload an architectural blueprint or technical floor layout instead.\"\n          )\n  }\n}}"
      },
      "typeVersion": 1.1
    },
    {
      "id": "cee2d67e-f07c-49b8-9018-e0753ff16d76",
      "name": "Clasificar – Archivos de imagen",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        3560,
        -200
      ],
      "parameters": {
        "url": "https://api.jigsawstack.com/v1/classification",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"dataset\": [\n    {\n      \"type\": \"image\",\n      \"value\": \"{{ $json.temp_public_url }}\"\n    }\n  ],\n  \"labels\": [\n    {\n      \"type\": \"text\",\n      \"value\": \"floorplan\"\n    },\n    {\n      \"type\": \"text\",\n      \"value\": \"not floorplan\"\n    }\n  ]\n}",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "headerParameters": {
          "parameters": [
            {}
          ]
        }
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "A2GUIb1l3Nybba3k",
          "name": "jigsaw"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "14201ed6-6613-4bfc-b8bd-d7434507036c",
      "name": "Clasificar – Texto PDF",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        4880,
        820
      ],
      "parameters": {
        "url": "https://api.jigsawstack.com/v1/classification",
        "method": "POST",
        "options": {},
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        "responseBody": "={{ {\n  \"thankYouMessage\": \"📏 File Too Large. The uploaded file exceeds our limits (max 10MB or PDFs with more than 20 pages). Please split multi‑floor plans into separate files or extract only the relevant pages, then try again.\"\n} }}"
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      "onError": "continueErrorOutput",
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        "url": "https://api.jigsawstack.com/v1/store/file",
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        "contentType": "binaryData",
        "sendHeaders": true,
        "authentication": "genericCredentialType",
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            {
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              "value": "={{ $json.fileName }}"
            },
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              "value": "true"
            },
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              "name": "temp_public_url",
              "value": "true"
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              "name": "Content-Type",
              "value": "={{ $json.mimeType }}"
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        "inputDataFieldName": "={{ $json.fileKey }}"
      },
      "credentials": {
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      "retryOnFail": true,
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      "waitBetweenTries": 3000
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      "name": "Sin operación, no hacer nada",
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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 - Varios, Resumen de IA, IA Multimodal

¿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 nodos24
Categoría3
Tipos de nodos9
Descripción de la dificultad

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

Autor
Stephan Koning

Stephan Koning

@reklaim

Account Executive by day , Noco builder for fun at night and always a proud dad of Togo the Samoyed.

Enlaces externos
Ver en n8n.io

Compartir este flujo de trabajo

Categorías

Categorías: 34