{ "updatedAt": "2026-04-04T20:52:16.458Z", "createdAt": "2026-01-09T23:20:53.320Z", "id": "F9OWClEBtwYHjHTv", "name": "Chat Question Suggestions With Persistence", "active": true, "isArchived": false, "nodes": [ { "parameters": { "httpMethod": "POST", "path": "chat_suggestions", "responseMode": "responseNode", "options": {} }, "type": "n8n-nodes-base.webhook", "typeVersion": 2.1, "position": [ -144, 256 ], "id": "150560c9-b6bf-40e8-9d3b-cf9427e30c52", "name": "Webhook" }, { "parameters": { "assignments": { "assignments": [ { "id": "7bdf57f2-c6ca-43ca-a584-60495cf70e2d", "name": "book_id", "value": "={{ $json.body.book_id }}", "type": "string" }, { "id": "316af802-b37f-4d88-89e5-69c167410869", "name": "locale", "value": "={{ $json.body.locale }}", "type": "string" } ] }, "options": {} }, "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ 80, 256 ], "id": "59a3061a-c67b-424a-b559-59f3cd5a533d", "name": "Edit Fields" }, { "parameters": { "promptType": "define", "text": "=book title: {{ $('Load Book').item.json.title}}\n\nsummary: {{$('Load Book').item.json.summary }}\n\n", "options": { "systemMessage": "=You are an executive thinking partner.\n You respond in the following language: {{$('Edit Fields').item.json.locale == 'de'? 'German' : 'English' }}\nYour only input is a book title and summary.\n\nBased solely on the implications, themes, and promises suggested by the title and summary, generate 2\u20133 sharp questions that a high-performing individual would naturally ask. \n\nAssume the reader is:\n- Experienced\n- Time-constrained\n- Focused on leverage, clarity, and outcomes\n\nYour questions must:\n- Be short, direct, and high-signal\n\n\nDo NOT:\n- Explain the questions\n- Add preamble or commentary\n\nOutput format:\nReturn ONLY a JSON array of strings.\n\nExample output:\n[\n \"What is meant by [key phrase in book title]?\",\n \"What are the key takeaways from this book?\",\n \"Where could I apply the principles to my business?\"\n]\n" } }, "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 3.1, "position": [ 976, 0 ], "id": "3bbc1ed2-9bd0-49ee-9578-d02002be98f1", "name": "AI Agent" }, { "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4.1-mini" }, "builtInTools": {}, "options": {} }, "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "typeVersion": 1.3, "position": [ 1056, 224 ], "id": "416b2a68-67d7-4e1b-bd47-907c669cfdeb", "name": "OpenAI", "credentials": { "openAiApi": { "name": "" } } }, { "parameters": { "options": {} }, "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.5, "position": [ 1328, 112 ], "id": "5c6debe8-fc0e-43e0-86bf-a17a4adfa74f", "name": "Respond to Webhook" }, { "parameters": { "operation": "get", "tableId": "books", "filters": { "conditions": [ { "keyName": "id", "keyValue": "={{ $json.book_id }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 304, 256 ], "id": "b9a79999-fe19-4aea-b6c3-3532b6575dbf", "name": "Load Book", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "operation": "getAll", "tableId": "chat_suggestions", "matchType": "allFilters", "filters": { "conditions": [ { "keyName": "book_id", "condition": "eq", "keyValue": "={{ $json.id }}" }, { "keyName": "locale", "condition": "eq", "keyValue": "={{ $('Edit Fields').item.json.locale }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 528, 256 ], "id": "2878f446-a007-447e-b45e-15e5a9325256", "name": "Load Suggestions", "alwaysOutputData": true, "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 3 }, "conditions": [ { "id": "76d6027e-ff87-47c2-b251-65d340567f19", "leftValue": "={{ $json.isEmpty() }}", "rightValue": "", "operator": { "type": "boolean", "operation": "true", "singleValue": true } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ 752, 256 ], "id": "f7195611-3650-44f9-80e4-38e57d353a9a", "name": "If Suggestions Empty" }, { "parameters": { "options": {} }, "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.5, "position": [ 1328, 400 ], "id": "32302a5e-8c37-4981-8d17-448f869e2b0f", "name": "Respond to Webhook1" }, { "parameters": { "tableId": "chat_suggestions", "fieldsUi": { "fieldValues": [ { "fieldId": "suggestion", "fieldValue": "={{ $json.question }}" }, { "fieldId": "book_id", "fieldValue": "={{ $('Load Book').item.json.id }}" }, { "fieldId": "locale", "fieldValue": "={{ $('Edit Fields').item.json.locale }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 1776, 112 ], "id": "ec1fe71b-f138-4d67-aff5-173f09fa5c65", "name": "Store Suggestions", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "jsCode": "const raw = items[0].json.output;\n\n// Parse the stringified JSON array\nlet parsed;\ntry {\n parsed = JSON.parse(raw);\n} catch (e) {\n throw new Error(\"Failed to parse output as JSON array\");\n}\n\n// Ensure it's an array\nif (!Array.isArray(parsed)) {\n throw new Error(\"Parsed output is not an array\");\n}\n\n// Return one item per entry\nreturn parsed.map(question => ({\n json: {\n question\n }\n}));\n" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1552, 112 ], "id": "b4914a54-4c60-4f82-a258-f4a39f6eb514", "name": "Parse Response" }, { "parameters": { "jsCode": "// Extract suggestion strings from all incoming items\nconst suggestions = items.map(item => item.json.suggestion);\n\n// Encode as a JSON string (array of strings)\nconst encoded = JSON.stringify(suggestions, null, 2);\n\n// Return a single item matching the required format\nreturn [\n {\n json: {\n output: encoded\n }\n }\n];\n" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1040, 400 ], "id": "20fcb9eb-e0a5-4e65-b07e-4131cce462a9", "name": "PreProcess Suggestions" }, { "parameters": { "content": "## \ud83d\uddc2\ufe0f Chat Question Suggestions (with persistence)\n\n### Purpose\nGenerate and cache 2\u20133 high-signal executive questions for a book, returning them instantly on repeat requests.\n\n### How it works\n- Accepts a `book_id` via webhook \n- Loads the book (title + summary) from Supabase \n- Checks for existing chat suggestions for that book \n - **If found** \u2192 returns them immediately \n - **If missing** \u2192 asks an AI agent to generate new questions \n- Parses the AI response into individual questions \n- Persists the questions to Supabase for future requests \n- Responds with a single `output` field containing a JSON-encoded array of strings (LLM-friendly format)\n\n### Why this exists\n- Keeps chat UIs fast and deterministic \n- Avoids regenerating suggestions on every page load \n- Ensures consistent, high-quality starter questions per book \n\n", "height": 512, "width": 768, "color": 4 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -208, -336 ], "id": "0407f240-b923-49fb-9f61-19dfcbd2564b", "name": "Sticky Note" }, { "parameters": { "content": "## Output\n```json\n{\n \"output\": \"[\\\"Question 1\\\", \\\"Question 2\\\", \\\"Question 3\\\"]\"\n}\n", "height": 352, "width": 672, "color": 6 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ 1296, -80 ], "id": "e1503ce7-18cf-4465-821e-303d99257812", "name": "Sticky Note1" }, { "parameters": { "content": "## Input\n```json\n{ \n \"book_id\": \"uuid\" \n}\n```", "height": 224, "width": 752, "color": 7 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -192, 496 ], "id": "6c9e65a4-9cb4-4e13-bbaa-7403c09cf370", "name": "Sticky Note2" } ], "connections": { "Webhook": { "main": [ [ { "node": "Edit Fields", "type": "main", "index": 0 } ] ] }, "Edit Fields": { "main": [ [ { "node": "Load Book", "type": "main", "index": 0 } ] ] }, "OpenAI": { "ai_languageModel": [ [ { "node": "AI Agent", "type": "ai_languageModel", "index": 0 } ] ] }, "AI Agent": { "main": [ [ { "node": "Respond to Webhook", "type": "main", "index": 0 } ] ] }, "Load Book": { "main": [ [ { "node": "Load Suggestions", "type": "main", "index": 0 } ] ] }, "Load Suggestions": { "main": [ [ { "node": "If Suggestions Empty", "type": "main", "index": 0 } ] ] }, "If Suggestions Empty": { "main": [ [ { "node": "AI Agent", "type": "main", "index": 0 } ], [ { "node": "PreProcess Suggestions", "type": "main", "index": 0 } ] ] }, "Respond to Webhook": { "main": [ [ { "node": "Parse Response", "type": "main", "index": 0 } ] ] }, "Parse Response": { "main": [ [ { "node": "Store Suggestions", "type": "main", "index": 0 } ] ] }, "PreProcess Suggestions": { "main": [ [ { "node": "Respond to Webhook1", "type": "main", "index": 0 } ] ] } }, "settings": { "executionOrder": "v1", "availableInMCP": false, "binaryMode": "separate" }, "staticData": null, "meta": { "templateCredsSetupCompleted": true }, "versionId": "9cd67fcc-c8bf-4f63-83b8-683e90caf6ef", "activeVersionId": "9cd67fcc-c8bf-4f63-83b8-683e90caf6ef", "triggerCount": 1, "shared": [ { "updatedAt": "2026-01-09T23:20:53.328Z", "createdAt": "2026-01-09T23:20:53.328Z", "role": "workflow:owner", "workflowId": "F9OWClEBtwYHjHTv", "projectId": "B7QJE85HA2Vij1it" } ], "activeVersion": { "updatedAt": "2026-04-04T20:52:29.000Z", "createdAt": "2026-04-04T20:52:16.460Z", "versionId": "9cd67fcc-c8bf-4f63-83b8-683e90caf6ef", "workflowId": "F9OWClEBtwYHjHTv", "nodes": [ { "parameters": { "httpMethod": "POST", "path": "chat_suggestions", "responseMode": "responseNode", "options": {} }, "type": "n8n-nodes-base.webhook", "typeVersion": 2.1, "position": [ -144, 256 ], "id": "150560c9-b6bf-40e8-9d3b-cf9427e30c52", "name": "Webhook", "webhookId": "5d2431c9-171b-40d3-ab9a-f043258399d7" }, { "parameters": { "assignments": { "assignments": [ { "id": "7bdf57f2-c6ca-43ca-a584-60495cf70e2d", "name": "book_id", "value": "={{ $json.body.book_id }}", "type": "string" }, { "id": "316af802-b37f-4d88-89e5-69c167410869", "name": "locale", "value": "={{ $json.body.locale }}", "type": "string" } ] }, "options": {} }, "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ 80, 256 ], "id": "59a3061a-c67b-424a-b559-59f3cd5a533d", "name": "Edit Fields" }, { "parameters": { "promptType": "define", "text": "=book title: {{ $('Load Book').item.json.title}}\n\nsummary: {{$('Load Book').item.json.summary }}\n\n", "options": { "systemMessage": "=You are an executive thinking partner.\n You respond in the following language: {{$('Edit Fields').item.json.locale == 'de'? 'German' : 'English' }}\nYour only input is a book title and summary.\n\nBased solely on the implications, themes, and promises suggested by the title and summary, generate 2\u20133 sharp questions that a high-performing individual would naturally ask. \n\nAssume the reader is:\n- Experienced\n- Time-constrained\n- Focused on leverage, clarity, and outcomes\n\nYour questions must:\n- Be short, direct, and high-signal\n\n\nDo NOT:\n- Explain the questions\n- Add preamble or commentary\n\nOutput format:\nReturn ONLY a JSON array of strings.\n\nExample output:\n[\n \"What is meant by [key phrase in book title]?\",\n \"What are the key takeaways from this book?\",\n \"Where could I apply the principles to my business?\"\n]\n" } }, "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 3.1, "position": [ 976, 0 ], "id": "3bbc1ed2-9bd0-49ee-9578-d02002be98f1", "name": "AI Agent" }, { "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4.1-mini" }, "builtInTools": {}, "options": {} }, "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "typeVersion": 1.3, "position": [ 1056, 224 ], "id": "416b2a68-67d7-4e1b-bd47-907c669cfdeb", "name": "OpenAI", "credentials": { "openAiApi": { "id": "BRRf66J5aSwt4UDP", "name": "OpenAi account" } } }, { "parameters": { "options": {} }, "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.5, "position": [ 1328, 112 ], "id": "5c6debe8-fc0e-43e0-86bf-a17a4adfa74f", "name": "Respond to Webhook" }, { "parameters": { "operation": "get", "tableId": "books", "filters": { "conditions": [ { "keyName": "id", "keyValue": "={{ $json.book_id }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 304, 256 ], "id": "b9a79999-fe19-4aea-b6c3-3532b6575dbf", "name": "Load Book", "credentials": { "supabaseApi": { "id": "fdzgJDGuPA2JozKn", "name": "Supabase account" } } }, { "parameters": { "operation": "getAll", "tableId": "chat_suggestions", "matchType": "allFilters", "filters": { "conditions": [ { "keyName": "book_id", "condition": "eq", "keyValue": "={{ $json.id }}" }, { "keyName": "locale", "condition": "eq", "keyValue": "={{ $('Edit Fields').item.json.locale }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 528, 256 ], "id": "2878f446-a007-447e-b45e-15e5a9325256", "name": "Load Suggestions", "alwaysOutputData": true, "credentials": { "supabaseApi": { "id": "fdzgJDGuPA2JozKn", "name": "Supabase account" } } }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 3 }, "conditions": [ { "id": "76d6027e-ff87-47c2-b251-65d340567f19", "leftValue": "={{ $json.isEmpty() }}", "rightValue": "", "operator": { "type": "boolean", "operation": "true", "singleValue": true } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ 752, 256 ], "id": "f7195611-3650-44f9-80e4-38e57d353a9a", "name": "If Suggestions Empty" }, { "parameters": { "options": {} }, "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.5, "position": [ 1328, 400 ], "id": "32302a5e-8c37-4981-8d17-448f869e2b0f", "name": "Respond to Webhook1" }, { "parameters": { "tableId": "chat_suggestions", "fieldsUi": { "fieldValues": [ { "fieldId": "suggestion", "fieldValue": "={{ $json.question }}" }, { "fieldId": "book_id", "fieldValue": "={{ $('Load Book').item.json.id }}" }, { "fieldId": "locale", "fieldValue": "={{ $('Edit Fields').item.json.locale }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 1776, 112 ], "id": "ec1fe71b-f138-4d67-aff5-173f09fa5c65", "name": "Store Suggestions", "credentials": { "supabaseApi": { "id": "fdzgJDGuPA2JozKn", "name": "Supabase account" } } }, { "parameters": { "jsCode": "const raw = items[0].json.output;\n\n// Parse the stringified JSON array\nlet parsed;\ntry {\n parsed = JSON.parse(raw);\n} catch (e) {\n throw new Error(\"Failed to parse output as JSON array\");\n}\n\n// Ensure it's an array\nif (!Array.isArray(parsed)) {\n throw new Error(\"Parsed output is not an array\");\n}\n\n// Return one item per entry\nreturn parsed.map(question => ({\n json: {\n question\n }\n}));\n" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1552, 112 ], "id": "b4914a54-4c60-4f82-a258-f4a39f6eb514", "name": "Parse Response" }, { "parameters": { "jsCode": "// Extract suggestion strings from all incoming items\nconst suggestions = items.map(item => item.json.suggestion);\n\n// Encode as a JSON string (array of strings)\nconst encoded = JSON.stringify(suggestions, null, 2);\n\n// Return a single item matching the required format\nreturn [\n {\n json: {\n output: encoded\n }\n }\n];\n" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1040, 400 ], "id": "20fcb9eb-e0a5-4e65-b07e-4131cce462a9", "name": "PreProcess Suggestions" }, { "parameters": { "content": "## \ud83d\uddc2\ufe0f Chat Question Suggestions (with persistence)\n\n### Purpose\nGenerate and cache 2\u20133 high-signal executive questions for a book, returning them instantly on repeat requests.\n\n### How it works\n- Accepts a `book_id` via webhook \n- Loads the book (title + summary) from Supabase \n- Checks for existing chat suggestions for that book \n - **If found** \u2192 returns them immediately \n - **If missing** \u2192 asks an AI agent to generate new questions \n- Parses the AI response into individual questions \n- Persists the questions to Supabase for future requests \n- Responds with a single `output` field containing a JSON-encoded array of strings (LLM-friendly format)\n\n### Why this exists\n- Keeps chat UIs fast and deterministic \n- Avoids regenerating suggestions on every page load \n- Ensures consistent, high-quality starter questions per book \n\n", "height": 512, "width": 768, "color": 4 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -208, -336 ], "id": "0407f240-b923-49fb-9f61-19dfcbd2564b", "name": "Sticky Note" }, { "parameters": { "content": "## Output\n```json\n{\n \"output\": \"[\\\"Question 1\\\", \\\"Question 2\\\", \\\"Question 3\\\"]\"\n}\n", "height": 352, "width": 672, "color": 6 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ 1296, -80 ], "id": "e1503ce7-18cf-4465-821e-303d99257812", "name": "Sticky Note1" }, { "parameters": { "content": "## Input\n```json\n{ \n \"book_id\": \"uuid\" \n}\n```", "height": 224, "width": 752, "color": 7 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -192, 496 ], "id": "6c9e65a4-9cb4-4e13-bbaa-7403c09cf370", "name": "Sticky Note2" } ], "connections": { "Webhook": { "main": [ [ { "node": "Edit Fields", "type": "main", "index": 0 } ] ] }, "Edit Fields": { "main": [ [ { "node": "Load Book", "type": "main", "index": 0 } ] ] }, "OpenAI": { "ai_languageModel": [ [ { "node": "AI Agent", "type": "ai_languageModel", "index": 0 } ] ] }, "AI Agent": { "main": [ [ { "node": "Respond to Webhook", "type": "main", "index": 0 } ] ] }, "Load Book": { "main": [ [ { "node": "Load Suggestions", "type": "main", "index": 0 } ] ] }, "Load Suggestions": { "main": [ [ { "node": "If Suggestions Empty", "type": "main", "index": 0 } ] ] }, "If Suggestions Empty": { "main": [ [ { "node": "AI Agent", "type": "main", "index": 0 } ], [ { "node": "PreProcess Suggestions", "type": "main", "index": 0 } ] ] }, "Respond to Webhook": { "main": [ [ { "node": "Parse Response", "type": "main", "index": 0 } ] ] }, "Parse Response": { "main": [ [ { "node": "Store Suggestions", "type": "main", "index": 0 } ] ] }, "PreProcess Suggestions": { "main": [ [ { "node": "Respond to Webhook1", "type": "main", "index": 0 } ] ] } }, "authors": "Gordan Kljajic", "name": "Version 9cd67fcc", "description": "", "autosaved": true }, "tags": [] }