{"workflow":{"id":14314,"name":"Classify documents with easybits Extractor via web form","views":1,"recentViews":0,"totalViews":1,"createdAt":"2026-03-25T13:05:36.844Z","description":"## What This Workflow Does\nUpload a document (PDF, PNG, or JPEG) via a hosted web form and let **easybits Extractor** classify it into one of your defined categories. This workflow handles the upload, file conversion, and API call – you just define the categories.\n\n## How It Works\n1. **Form Upload** – A user uploads a file through the n8n web form\n2. **Base64 Conversion** – The binary file is extracted and converted to a base64 string\n3. **Build Data URI** – The correct MIME type is read from the original upload and prepended to create a proper data URI\n4. **Classification via easybits** – The data URI is POSTed to the easybits Extractor API, which analyzes the document and returns a `document_class` label (e.g. `medical_invoice`, `hotel_invoice`, or `null` if uncertain)\n\nFrom here, you can extend the workflow however you like – route files to Google Drive folders, send Slack alerts for unrecognized documents, log results to a spreadsheet, etc.\n\n---\n\n## Setup Guide\n\n### 1. Create Your easybits Extractor Pipeline\n1. Go to **https://extractor.easybits.tech/** and create a new pipeline\n2. Add a single field to the mapping called **`document_class`**\n3. In that field's description, paste a classification prompt that tells the model which categories exist and how to identify each one.\n4. The prompt should instruct the model to return **exactly one category label** – or `null` if the document doesn't match any category. No explanations, no extra text.\n5. Adjust the categories to fit your use case. The example uses `medical_invoice`, `restaurant_invoice`, and `hotel_invoice` – but you can define whatever classes you need.\n6. Copy your **Pipeline ID** and **API Key**\n\n### 2. Connect the Nodes in n8n\n1. In the **easybits Extractor (Classification)** HTTP node, replace the pipeline URL with your own: `https://extractor.easybits.tech/api/pipelines/YOUR_PIPELINE_ID`\n2. Create a **Bearer Auth** credential using your easybits API Key and assign it to that node\n\n### 3. Activate & Test\n1. Click **Active** in the top-right corner of n8n\n2. Open the form URL and upload a test document\n3. Check the execution output – you should see your `document_class` label in the response","workflow":{"meta":{"instanceId":"","templateCredsSetupCompleted":false},"name":"easybits' Extractor Classification Workflow","tags":[{"name":"AI Classification"},{"name":"AI"},{"name":"Document Processing"},{"name":"easybits"}],"nodes":[{"id":"3d2cbf06-949a-451d-adca-51f53dfe22b5","name":"Extract from File","type":"n8n-nodes-base.extractFromFile","position":[224,16],"parameters":{"options":{},"operation":"binaryToPropery","binaryPropertyName":"image"},"typeVersion":1.1},{"id":"bcc48497-e7c3-417a-a5f6-af8dd4e783a4","name":"On form submission","type":"n8n-nodes-base.formTrigger","position":[-64,16],"webhookId":"84421bc8-bdd1-4dc5-be28-f53fd5b474c7","parameters":{"options":{},"formTitle":"Image Upload","formFields":{"values":[{"fieldType":"file","fieldLabel":"image"}]}},"typeVersion":2.5},{"id":"3cf93bc1-f3d5-4ccc-946c-d22f4df05ef3","name":"Edit Fields","type":"n8n-nodes-base.set","position":[512,16],"parameters":{"options":{},"assignments":{"assignments":[{"id":"540141e7-42d3-4011-b681-8335d9105044","name":"data","type":"string","value":"=data:{{ $('On form submission').first().binary.image.mimeType }};base64,{{ $json.data }}"}]}},"typeVersion":3.4},{"id":"2b527430-c39d-41cc-9491-4fd6b2609af1","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-144,-160],"parameters":{"color":7,"width":256,"height":368,"content":"## 📋 Form Upload\nAccepts a file upload via a **web form**. Supports **PDF, PNG, and JPEG**."},"typeVersion":1},{"id":"820b5a61-15bb-4263-b19a-f36070473e6a","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[144,-160],"parameters":{"color":7,"width":256,"height":368,"content":"## 📄 Extract to Base64\nConverts the uploaded **binary file** into a base64-encoded string stored in `data`."},"typeVersion":1},{"id":"f400bb96-a3cd-4529-8aef-f3462b232e8b","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[432,-160],"parameters":{"color":7,"width":256,"height":368,"content":"## 🔗 Build Data URI\nDynamically reads the **MIME type** from the uploaded file and prepends it as a base64 data URI."},"typeVersion":1},{"id":"a20f3462-32a1-40db-a288-8c08518e4549","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[-832,-496],"parameters":{"width":656,"height":1088,"content":"# 📄 easybits' Document Classification\n\n## What This Workflow Does\nUpload a document (PDF, PNG, or JPEG) via a hosted web form and let **easybits Extractor** classify it into one of your defined categories. This workflow handles the upload, file conversion, and API call – you just define the categories.\n\n## How It Works\n1. **Form Upload** – A user uploads a file through the n8n web form\n2. **Base64 Conversion** – The binary file is extracted and converted to a base64 string\n3. **Build Data URI** – The correct MIME type is read from the original upload and prepended to create a proper data URI\n4. **Classification via easybits** – The data URI is POSTed to the easybits Extractor API, which analyzes the document and returns a `document_class` label (e.g. `medical_invoice`, `hotel_invoice`, or `null` if uncertain)\n\nFrom here, you can extend the workflow however you like – route files to Google Drive folders, send Slack alerts for unrecognized documents, log results to a spreadsheet, etc.\n\n---\n\n## Setup Guide\n\n### 1. Create Your easybits Extractor Pipeline\n1. Go to **extractor.easybits.tech** and create a new pipeline\n2. Add a single field to the mapping called **`document_class`**\n3. In that field's description, paste a classification prompt that tells the model which categories exist and how to identify each one (see the \"📊 Document Classification\" sticky note in this workflow for a full example prompt you can copy and adapt)\n4. The prompt should instruct the model to return **exactly one category label** – or `null` if the document doesn't match any category. No explanations, no extra text.\n5. Adjust the categories to fit your use case. The example uses `medical_invoice`, `restaurant_invoice`, and `hotel_invoice` – but you can define whatever classes you need.\n6. Copy your **Pipeline ID** and **API Key**\n\n### 2. Connect the Nodes in n8n\n1. In the **easybits Extractor (Classification)** HTTP node, replace the pipeline URL with your own: `https://extractor.easybits.tech/api/pipelines/YOUR_PIPELINE_ID`\n2. Create a **Bearer Auth** credential using your easybits API Key and assign it to that node\n\n### 3. Activate & Test\n1. Click **Active** in the top-right corner of n8n\n2. Open the form URL and upload a test document\n3. Check the execution output – you should see your `document_class` label in the response"},"typeVersion":1},{"id":"36fde793-1174-4c35-9b54-659691be5cd4","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[720,-160],"parameters":{"color":7,"width":256,"height":368,"content":"## 🚀 Send to easybits\nPOSTs the data URI to the **easybits Extractor API** for classifcation."},"typeVersion":1},{"id":"e8ff79f8-6a47-4d66-b321-1be874e8694d","name":"easybits Extractor for Classification","type":"n8n-nodes-base.httpRequest","position":[800,16],"parameters":{"url":"https://extractor.easybits.tech/api/pipelines/YOUR_PIPELINE_ID","method":"POST","options":{},"jsonBody":"={\n  \"files\": [\n    \"{{ $json.data }}\"\n  ]\n} ","sendBody":true,"specifyBody":"json","authentication":"predefinedCredentialType","nodeCredentialType":"httpBearerAuth"},"typeVersion":4.3}],"active":false,"pinData":{},"settings":{"callerPolicy":"workflowsFromSameOwner","timeSavedMode":"fixed","availableInMCP":false,"executionOrder":"v1"},"connections":{"Edit Fields":{"main":[[{"node":"easybits Extractor for Classification","type":"main","index":0}]]},"Extract from File":{"main":[[{"node":"Edit Fields","type":"main","index":0}]]},"On form submission":{"main":[[{"node":"Extract from File","type":"main","index":0}]]},"easybits Extractor for Classification":{"main":[[]]}}},"lastUpdatedBy":1,"workflowInfo":{"nodeCount":9,"nodeTypes":{"n8n-nodes-base.set":{"count":1},"n8n-nodes-base.stickyNote":{"count":5},"n8n-nodes-base.formTrigger":{"count":1},"n8n-nodes-base.httpRequest":{"count":1},"n8n-nodes-base.extractFromFile":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"Felix","username":"easybits","bio":"Marketing Lead with a passion for automation and AI. 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