{ "name": "Class Transcript Ingest v1.1", "nodes": [ { "parameters": { "httpMethod": "POST", "path": "class/ingest", "responseMode": "responseNode", "options": {} }, "id": "a1b2c3d4-0001-0001-0001-000000000001", "name": "Class Ingest Webhook", "type": "n8n-nodes-base.webhook", "typeVersion": 2, "position": [ 0, 0 ], "webhookId": "class-ingest-rocinante-v1" }, { "parameters": { "respondWith": "json", "responseBody": "={ \"status\": \"accepted\" }", "options": {} }, "id": "a1b2c3d4-0001-0001-0001-000000000002", "name": "Respond Accepted", "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1, "position": [ 224, -200 ] }, { "parameters": { "jsCode": "const body = $input.first().json.body || $input.first().json;\n\nconst className = body.class_name || 'unclassified';\nconst lectureTitle = body.lecture_title || 'Untitled Lecture';\nconst fullText = body.transcript || '';\nconst timestampedText = body.timestamped_transcript || fullText;\nconst durationMinutes = Math.round((body.duration_seconds || 0) / 60);\nconst classSlug = className.toLowerCase().replace(/[^a-z0-9]+/g, '-').replace(/^-|-$/g, '');\n\nreturn [{\n json: {\n className,\n classSlug,\n lectureTitle,\n fullText,\n timestampedText,\n durationMinutes\n }\n}];" }, "id": "a1b2c3d4-0001-0001-0001-000000000003", "name": "Extract Class Info", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 224, 0 ] }, { "parameters": { "method": "POST", "url": "http://10.5.30.6:4000/v1/chat/completions", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" }, { "name": "Authorization", "value": "={{'Bearer ' + $env.LITELLM_API_KEY}}" } ] }, "sendBody": true, "specifyBody": "json", "jsonBody": "={\n \"model\": \"medium\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an academic note-taking assistant. Given a class lecture transcription, provide:\\n1. A concise summary (3-5 sentences)\\n2. Key concepts covered (as a list)\\n3. Important definitions or formulas\\n4. Any assignments or deadlines mentioned\\n\\nRespond in JSON with keys: summary, key_concepts (array), definitions (array of {term, definition}), assignments (array)\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Class: {{ $json.className }}\\nLecture: {{ $json.lectureTitle }}\\n\\nTranscription (first 4000 chars):\\n{{ $json.fullText.substring(0, 4000) }}\"\n }\n ],\n \"max_tokens\": 600,\n \"temperature\": 0.2,\n \"response_format\": { \"type\": \"json_object\" }\n}", "options": {} }, "id": "a1b2c3d4-0001-0001-0001-000000000004", "name": "AI Extract Notes", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 448, 0 ] }, { "parameters": { "jsCode": "const llmResponse = $input.first().json;\nconst classInfo = $('Extract Class Info').first().json;\n\nlet notes;\ntry {\n notes = JSON.parse(llmResponse.choices?.[0]?.message?.content || '{}');\n} catch(e) {\n notes = { summary: 'Could not parse notes', key_concepts: [], definitions: [], assignments: [] };\n}\n\nconst ragText = [\n `Class: ${classInfo.className}`,\n `Lecture: ${classInfo.lectureTitle}`,\n `Duration: ${classInfo.durationMinutes} minutes`,\n `Summary: ${notes.summary}`,\n `Key Concepts: ${(notes.key_concepts || []).join(', ')}`,\n '',\n 'Full Transcript:',\n classInfo.fullText\n].join('\\n');\n\nreturn [{\n json: {\n className: classInfo.className,\n classSlug: classInfo.classSlug,\n lectureTitle: classInfo.lectureTitle,\n durationMinutes: classInfo.durationMinutes,\n fullText: classInfo.fullText,\n notes,\n ragText,\n source: `class-${classInfo.classSlug}-${Date.now()}`,\n metadata: {\n class_name: classInfo.className,\n class_slug: classInfo.classSlug,\n lecture_title: classInfo.lectureTitle,\n duration_minutes: classInfo.durationMinutes,\n type: 'class_recording',\n recorded_at: new Date().toISOString()\n }\n }\n}];" }, "id": "a1b2c3d4-0001-0001-0001-000000000005", "name": "Prepare for RAG", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 672, 0 ] }, { "parameters": { "jsCode": "const input = $input.first().json;\nconst text = input.ragText || '';\nconst source = input.source;\nconst metadata = input.metadata;\n\nconst CHUNK_SIZE = 400;\nconst MAX_CHUNK = 600;\nconst OVERLAP = 50;\n\nconst chunks = [];\nconst sentences = text.split(/(?<=[.!?])\\s+/);\nlet current = '';\n\nfor (const sentence of sentences) {\n // If a single sentence exceeds MAX_CHUNK, split it by words first\n const parts = [];\n if (sentence.length > MAX_CHUNK) {\n const words = sentence.split(' ');\n let part = '';\n for (const word of words) {\n if ((part + ' ' + word).length > CHUNK_SIZE && part.length > 0) {\n parts.push(part.trim());\n part = word;\n } else {\n part = part ? part + ' ' + word : word;\n }\n }\n if (part.trim()) parts.push(part.trim());\n } else {\n parts.push(sentence);\n }\n\n for (const part of parts) {\n if ((current + ' ' + part).length > CHUNK_SIZE && current.length > 0) {\n chunks.push(current.trim());\n const words = current.split(' ');\n current = words.slice(-OVERLAP).join(' ') + ' ' + part;\n } else {\n current = current ? current + ' ' + part : part;\n }\n }\n}\nif (current.trim()) chunks.push(current.trim());\n\nreturn chunks.map((chunk, i) => ({\n json: { chunk, chunkIndex: i, totalChunks: chunks.length, source, metadata }\n}));" }, "id": "a1b2c3d4-0001-0001-0001-000000000006", "name": "Chunk Text", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 896, 0 ] }, { "parameters": { "method": "POST", "url": "http://10.5.30.6:11434/v1/embeddings", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" } ] }, "sendBody": true, "specifyBody": "json", "jsonBody": "={\n \"model\": \"nomic-embed-text\",\n \"input\": {{ JSON.stringify($json.chunk) }}\n}", "options": { "batching": { "batch": { "batchSize": 5, "batchInterval": 500 } } } }, "id": "a1b2c3d4-0001-0001-0001-000000000007", "name": "Get Embedding", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 1120, 0 ] }, { "parameters": { "jsCode": "const embeddingResponse = $input.first().json;\nconst chunkData = $('Chunk Text').item;\nconst embedding = embeddingResponse.data?.[0]?.embedding || [];\n\nconst pointId = 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, c => {\n const r = Math.random() * 16 | 0;\n return (c === 'x' ? r : (r & 0x3 | 0x8)).toString(16);\n});\n\nreturn [{\n json: {\n id: pointId,\n vector: embedding,\n payload: {\n text: chunkData.json.chunk,\n source: chunkData.json.source,\n chunkIndex: chunkData.json.chunkIndex,\n totalChunks: chunkData.json.totalChunks,\n metadata: chunkData.json.metadata,\n ingested_at: new Date().toISOString()\n }\n }\n}];" }, "id": "a1b2c3d4-0001-0001-0001-000000000008", "name": "Prepare Qdrant Point", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1344, 0 ] }, { "parameters": { "method": "PUT", "url": "http://10.5.30.6:6333/collections/knowledge_base/points", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" } ] }, "sendBody": true, "specifyBody": "json", "jsonBody": "={\n \"points\": [\n {\n \"id\": \"{{ $json.id }}\",\n \"vector\": {{ JSON.stringify($json.vector) }},\n \"payload\": {{ JSON.stringify($json.payload) }}\n }\n ]\n}", "options": {} }, "id": "a1b2c3d4-0001-0001-0001-000000000009", "name": "Upsert to Qdrant", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 1568, 0 ] }, { "parameters": { "jsCode": "const rag = $('Prepare for RAG').first().json;\nreturn [{\n json: {\n title: `\ud83c\udf93 ${rag.className} Lecture Processed`,\n message: `${rag.lectureTitle} (${rag.durationMinutes}min)\\nSummary: ${rag.notes.summary}\\nKey concepts: ${(rag.notes.key_concepts || []).slice(0, 5).join(', ')}`,\n priority: 5\n }\n}];" }, "id": "a1b2c3d4-0001-0001-0001-000000000010", "name": "Format Gotify Message", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1552, -200 ] }, { "parameters": { "message": "={{ $json.message }}", "additionalFields": { "priority": "={{ $json.priority }}", "title": "={{ $json.title }}" }, "options": { "contentType": "text/plain" } }, "id": "a1b2c3d4-0001-0001-0001-000000000011", "name": "Notify via Gotify", "type": "n8n-nodes-base.gotify", "typeVersion": 1, "position": [ 1776, -200 ], "credentials": { "gotifyApi": { "id": "SETUP_REQUIRED", "name": "Class Recordings" } } }, { "parameters": { "jsCode": "const rag = $('Prepare for RAG').first().json;\nconst notes = rag.notes || {};\nconst concepts = (notes.key_concepts || []).map((c,i) => `${i+1}. ${c}`).join('\\n');\nconst defList = notes.definitions || [];\nconst defs = Array.isArray(defList)\n ? defList.map(d => `${d.term}: ${d.definition}`).join('\\n')\n : Object.entries(defList).map(([k,v]) => `${k}: ${v}`).join('\\n');\nconst assignments = (notes.assignments || []).map((a,i) => `${i+1}. ${a}`).join('\\n');\n\nconst content = [\n `Lecture Notes: ${rag.lectureTitle}`,\n `Class: ${rag.className}`,\n `Duration: ${rag.durationMinutes} minutes`,\n `Date: ${new Date().toISOString()}`, '',\n `Summary`, `=======`, notes.summary || '', '',\n `Key Concepts`, `=============`, concepts,\n ...(defs ? ['', `Definitions`, `===========`, defs] : []),\n ...(assignments ? ['', `Assignments`, `===========`, assignments] : []),\n '', `Full Transcript`, `================`, rag.fullText || '',\n].join('\\n');\n\nconst title = `${rag.className} \u2014 ${rag.lectureTitle}`;\nreturn [{\n binary: {\n document: {\n data: Buffer.from(content, 'utf-8').toString('base64'),\n mimeType: 'text/plain',\n fileName: `${title}.txt`\n }\n },\n json: { title, className: rag.className }\n}];" }, "id": "a1b2c3d4-0001-0001-0001-000000000012", "name": "Prepare Notes Doc", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1776, 200 ] }, { "parameters": { "method": "POST", "url": "https://paperless.paccoco.com/api/documents/post_document/", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Authorization", "value": "=Token {{ $env.PAPERLESS_API_TOKEN }}" } ] }, "sendBody": true, "contentType": "multipart-form-data", "bodyParameters": { "parameters": [ { "parameterType": "formBinaryData", "name": "document", "inputDataFieldName": "document" }, { "name": "title", "value": "={{ $json.title }}" }, { "name": "tags[]", "value": "={{ $env.PAPERLESS_TAG_LECTURE_NOTES }}" } ] }, "options": { "response": { "response": { "responseFormat": "text" } } } }, "id": "a1b2c3d4-0001-0001-0001-000000000013", "name": "Save Notes to Paperless", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 2000, 200 ], "continueOnFail": true } ], "connections": { "Class Ingest Webhook": { "main": [ [ { "node": "Extract Class Info", "type": "main", "index": 0 }, { "node": "Respond Accepted", "type": "main", "index": 0 } ] ] }, "Extract Class Info": { "main": [ [ { "node": "AI Extract Notes", "type": "main", "index": 0 } ] ] }, "AI Extract Notes": { "main": [ [ { "node": "Prepare for RAG", "type": "main", "index": 0 } ] ] }, "Prepare for RAG": { "main": [ [ { "node": "Chunk Text", "type": "main", "index": 0 } ] ] }, "Chunk Text": { "main": [ [ { "node": "Get Embedding", "type": "main", "index": 0 } ] ] }, "Get Embedding": { "main": [ [ { "node": "Prepare Qdrant Point", "type": "main", "index": 0 } ] ] }, "Prepare Qdrant Point": { "main": [ [ { "node": "Upsert to Qdrant", "type": "main", "index": 0 } ] ] }, "Upsert to Qdrant": { "main": [ [ { "node": "Format Gotify Message", "type": "main", "index": 0 }, { "node": "Prepare Notes Doc", "type": "main", "index": 0 } ] ] }, "Format Gotify Message": { "main": [ [ { "node": "Notify via Gotify", "type": "main", "index": 0 } ] ] }, "Prepare Notes Doc": { "main": [ [ { "node": "Save Notes to Paperless", "type": "main", "index": 0 } ] ] } }, "settings": { "executionOrder": "v1", "binaryMode": "separate" }, "staticData": null, "meta": null, "pinData": {}, "tags": [ { "name": "school" }, { "name": "rag" }, { "name": "ai" } ] }