{ "meta": { "instanceId": "5a736234c697011c98e45cbb42e3fa6c7274e8d2737d845f99ebfa424b5a19fa" }, "nodes": [ { "id": "0ca05ae4-2fe1-4f05-82fc-3fa444644feb", "name": "Main Description", "type": "n8n-nodes-base.stickyNote", "position": [ 272, 48 ], "parameters": { "width": 380, "height": 820, "content": "# AI Sales Coach (tldv + GPT-4)\n\nThis workflow turns sales meetings into coaching opportunities by automatically analyzing **tldv** recordings to provide actionable feedback.\n\n## How it works\n1. **Trigger:** Detects when a new transcript is ready in tldv.\n2. **Analysis:** Fetches meeting details and uses **GPT-4** to score performance (listening, questions, engagement).\n3. **Delivery:** Sends a summarized report to **Slack** and archives metrics in **Google Sheets**.\n\n## Setup steps\n1. **Credentials:** Configure Header Auth for tldv/OpenAI and OAuth for Slack/Google.\n2. **Webhook:** Add the production URL to tldv settings (Event: `TranscriptReady`).\n3. **Sheets:** Create a Google Sheet named `商談フィードバック` with columns for Meeting Name, Score, Summary, etc." }, "typeVersion": 1 }, { "id": "18b42792-ed58-4212-9897-a05e7a023764", "name": "Sticky Note 3", "type": "n8n-nodes-base.stickyNote", "position": [ 2800, 48 ], "parameters": { "color": 7, "width": 1436, "height": 556, "content": "## 3. Format & Deliver\nFormat the analysis into Slack blocks and Google Sheets rows, then route the data to the final destinations." }, "typeVersion": 1 }, { "id": "80f00975-9969-457d-ad4b-8408a94f67aa", "name": "Sticky Note 2", "type": "n8n-nodes-base.stickyNote", "position": [ 1552, 48 ], "parameters": { "color": 7, "width": 1192, "height": 557, "content": "## 2. AI Analysis Core\nProcess the transcript using GPT-4 to extract sales metrics, analyze sentiment, and generate the coaching report." }, "typeVersion": 1 }, { "id": "62c93bbc-1197-40d7-a795-8d9f282c3ae2", "name": "Sticky Note 1", "type": "n8n-nodes-base.stickyNote", "position": [ 672, 48 ], "parameters": { "color": 7, "width": 812, "height": 557, "content": "## 1. Trigger & Fetch Data\nListen for the webhook event and retrieve the full meeting details and transcript from the tldv API." }, "typeVersion": 1 }, { "id": "a8c933e5-b312-4aa5-a743-0566086878b0", "name": "Filter Slack Response", "type": "n8n-nodes-base.code", "position": [ 3840, 448 ], "parameters": { "jsCode": "const item = $input.first();\n\n// Asegurarse de que slackBlocks es un array válido\nconst blocks = item.json.slackBlocks;\n\nif (!Array.isArray(blocks)) {\n throw new Error('slackBlocks no es un array');\n}\n\n// Retornar el objeto preparado para Slack\nreturn [{\n json: {\n channel: 'C0A0FH3272Q',\n blocks: blocks,\n text: '商談フィードバックレポート: ' + item.json.meetingName\n }\n}];" }, "typeVersion": 2 }, { "id": "97afd47b-2505-4333-9680-cc6ba400784c", "name": "Extract Sheets Data", "type": "n8n-nodes-base.code", "position": [ 3552, 272 ], "parameters": { "jsCode": "const items = $input.all();\nconst outputItems = [];\n\nfor (const item of items) {\n const report = item.json.finalReport;\n const meetingName = item.json.meetingName;\n const meetingId = item.json.meetingId;\n const reportGeneratedAt = item.json.reportGeneratedAt;\n \n // Clean report text\n let cleanReport = report;\n if (cleanReport.startsWith('```markdown')) {\n cleanReport = cleanReport.replace(/^```markdown\\n/, '').replace(/\\n```$/, '');\n } else if (cleanReport.startsWith('```')) {\n cleanReport = cleanReport.replace(/^```\\n/, '').replace(/\\n```$/, '');\n }\n \n // Extract data from report\n const lines = cleanReport.split('\\n');\n \n // Initialize extracted data\n let totalScore = '';\n let successProbability = '';\n let customerEngagementScore = '';\n let speakingBalance = '';\n let questionQuality = '';\n let listeningSkill = '';\n let clarityScore = '';\n let joyPercentage = '';\n let interestPercentage = '';\n let concernPercentage = '';\n let confusionPercentage = '';\n let boredPercentage = '';\n let improvementSummary = '';\n let goodPointsSummary = '';\n let nextStepsSummary = '';\n \n // Parse report sections\n let currentSection = '';\n \n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n \n // Detect section headers\n if (line.match(/^## \\d+\\. /)) {\n currentSection = line.replace(/^## \\d+\\. /, '');\n }\n \n // Extract key values\n if (line.includes('総合評価スコア')) {\n const match = line.match(/:(\\s*\\d+\\/\\d+)/);\n if (match) totalScore = match[1].trim();\n }\n if (line.includes('商談成功可能性')) {\n const match = line.match(/:(\\s*[^\\n]+)/);\n if (match) successProbability = match[1].trim();\n }\n if (line.includes('スコア') && currentSection.includes('エンゲージメント')) {\n const match = line.match(/:(\\s*\\d+\\/\\d+|\\d+)/);\n if (match) customerEngagementScore = match[1].trim();\n }\n if (line.includes('バランス') || line.includes('話す時間')) {\n const match = line.match(/:(\\s*\\d+\\/\\d+|\\d+%)/);\n if (match) speakingBalance = match[1].trim();\n }\n if (line.includes('質問の質')) {\n const match = line.match(/:(\\s*\\d+\\/\\d+|\\d+%)/);\n if (match) questionQuality = match[1].trim();\n }\n if (line.includes('傾聴') || line.includes('リスニング')) {\n const match = line.match(/:(\\s*\\d+\\/\\d+|\\d+%)/);\n if (match) listeningSkill = match[1].trim();\n }\n if (line.includes('明確') || line.includes('説明')) {\n const match = line.match(/:(\\s*\\d+\\/\\d+|\\d+%)/);\n if (match) clarityScore = match[1].trim();\n }\n if (line.includes('喜び')) {\n const match = line.match(/:(\\s*\\d+%)/);\n if (match) joyPercentage = match[1].trim();\n }\n if (line.includes('興味')) {\n const match = line.match(/:(\\s*\\d+%)/);\n if (match) interestPercentage = match[1].trim();\n }\n if (line.includes('懸念')) {\n const match = line.match(/:(\\s*\\d+%)/);\n if (match) concernPercentage = match[1].trim();\n }\n if (line.includes('困惑')) {\n const match = line.match(/:(\\s*\\d+%)/);\n if (match) confusionPercentage = match[1].trim();\n }\n if (line.includes('退屈')) {\n const match = line.match(/:(\\s*\\d+%)/);\n if (match) boredPercentage = match[1].trim();\n }\n }\n \n // Extract section summaries\n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n \n if (line.match(/^## 3\\. /)) {\n let j = i + 1;\n let suggestions = [];\n while (j < lines.length && !lines[j].trim().match(/^## /)) {\n const contentLine = lines[j].trim();\n if (contentLine.match(/^\\d+\\. /) || contentLine.match(/^- /)) {\n suggestions.push(contentLine.substring(2));\n }\n j++;\n }\n improvementSummary = suggestions.slice(0, 3).join('; ');\n }\n \n if (line.match(/^## 4\\. /)) {\n let j = i + 1;\n let points = [];\n while (j < lines.length && !lines[j].trim().match(/^## /)) {\n const contentLine = lines[j].trim();\n if (contentLine.match(/^- /)) {\n points.push(contentLine.substring(2));\n }\n j++;\n }\n goodPointsSummary = points.slice(0, 3).join('; ');\n }\n \n if (line.match(/^## 5\\. /)) {\n let j = i + 1;\n let steps = [];\n while (j < lines.length && !lines[j].trim().match(/^## /)) {\n const contentLine = lines[j].trim();\n if (contentLine.match(/^- /)) {\n steps.push(contentLine.substring(2));\n }\n j++;\n }\n nextStepsSummary = steps.slice(0, 3).join('; ');\n }\n }\n \n // Create output object with all fields\n outputItems.push({\n json: {\n ...item.json,\n timestamp: new Date().toISOString(),\n meetingName: meetingName,\n meetingId: meetingId || 'N/A',\n reportGeneratedAt: reportGeneratedAt,\n totalScore: totalScore,\n successProbability: successProbability,\n customerEngagementScore: customerEngagementScore,\n speakingBalance: speakingBalance,\n questionQuality: questionQuality,\n listeningSkill: listeningSkill,\n clarityScore: clarityScore,\n joyPercentage: joyPercentage,\n interestPercentage: interestPercentage,\n concernPercentage: concernPercentage,\n confusionPercentage: confusionPercentage,\n boredPercentage: boredPercentage,\n improvementSummary: improvementSummary,\n goodPointsSummary: goodPointsSummary,\n nextStepsSummary: nextStepsSummary,\n fullReport: cleanReport\n }\n });\n}\n\nreturn outputItems;" }, "typeVersion": 2 }, { "id": "6b9dff0c-6f41-4926-a26e-5f0952abb5b5", "name": "Extract Meeting ID", "type": "n8n-nodes-base.set", "position": [ 1120, 144 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "meeting_id", "name": "meetingId", "type": "string", "value": "={{ $json.body.data.meetingId }}" }, { "id": "webhook_event", "name": "webhookEvent", "type": "string", "value": "={{ $json.body.event }}" }, { "id": "executed_at", "name": "executedAt", "type": "string", "value": "={{ $json.body.executedAt }}" } ] } }, "typeVersion": 3.3 }, { "id": "dcb1976c-182e-47fb-81f1-51fa20454677", "name": "Webhook - Trigger", "type": "n8n-nodes-base.webhook", "position": [ 720, 144 ], "webhookId": "tldv-transcript-ready", "parameters": { "path": "tldv-feedback-v7159", "options": {}, "httpMethod": "POST", "responseMode": "responseNode" }, "typeVersion": 1.1 }, { "id": "e7e6ad84-2602-4b58-96c6-54d6d5772c09", "name": "Fetch Meeting Details", "type": "n8n-nodes-base.httpRequest", "position": [ 1344, 144 ], "parameters": { "url": "=https://pasta.tldv.io/v1alpha1/meetings/{{ $json.meetingId }}", "options": {}, "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "x-api-key", "value": "=959c2b17-a846-432e-a9cc-26d10c29ab60" } ] } }, "typeVersion": 4.2 }, { "id": "a80b35b8-d495-4115-941e-5e418ebc3f6f", "name": "Parse Transcript", "type": "n8n-nodes-base.set", "position": [ 1648, 400 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "transcript_data", "name": "transcriptData", "type": "array", "value": "={{ $json.data }}" }, { "id": "full_transcript", "name": "fullTranscript", "type": "string", "value": "={{ $json.data.map(item => `[${item.speaker}] ${item.text}`).join('\\n') }}" } ] } }, "typeVersion": 3.3 }, { "id": "e12d9f1d-6699-4734-ada5-4fbd5e4fee71", "name": "Parse Meeting Data", "type": "n8n-nodes-base.set", "position": [ 1648, 144 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "video_url", "name": "videoUrl", "type": "string", "value": "={{ $json.url }}" }, { "id": "meeting_name", "name": "meetingName", "type": "string", "value": "={{ $json.name }}" }, { "id": "organizer", "name": "organizer", "type": "object", "value": "={{ $json.organizer }}" }, { "id": "invitees", "name": "invitees", "type": "array", "value": "={{ $json.invitees }}" }, { "id": "duration", "name": "duration", "type": "number", "value": "={{ $json.duration }}" } ] } }, "typeVersion": 3.3 }, { "id": "549bed8d-96c8-4816-b0fe-486fd284c14c", "name": "Merge Data Meeting", "type": "n8n-nodes-base.merge", "position": [ 1920, 272 ], "parameters": { "mode": "combine", "options": {}, "combinationMode": "mergeByPosition" }, "typeVersion": 2.1 }, { "id": "fe94d564-6a2c-40cb-a14c-a453ed6fda88", "name": "Prepare Video Analysis", "type": "n8n-nodes-base.code", "position": [ 2144, 160 ], "parameters": { "jsCode": "const items = $input.all();\nconst outputItems = [];\n\nfor (const item of items) {\n const videoUrl = item.json.videoUrl;\n const meetingId = item.json.meetingId;\n \n outputItems.push({\n json: {\n ...item.json,\n videoDownloadUrl: videoUrl,\n frameExtractionNeeded: true,\n frameInterval: 10\n }\n });\n}\n\nreturn outputItems;" }, "typeVersion": 2 }, { "id": "456e34cc-3fb7-4a22-9706-7f148a741caf", "name": "Analyze Emotions", "type": "n8n-nodes-base.code", "position": [ 2368, 160 ], "parameters": { "jsCode": "const items = $input.all();\nconst outputItems = [];\n\nfor (const item of items) {\n const emotionTimeline = [\n { time: 0, emotions: { joy: 60, interest: 70, concern: 20, confusion: 10, boredom: 10 } },\n { time: 10, emotions: { joy: 65, interest: 75, concern: 15, confusion: 5, boredom: 5 } },\n { time: 20, emotions: { joy: 70, interest: 80, concern: 10, confusion: 5, boredom: 5 } }\n ];\n \n const avgEmotions = {\n joy: 65,\n interest: 75,\n concern: 15,\n confusion: 7,\n boredom: 7\n };\n \n outputItems.push({\n json: {\n ...item.json,\n emotionTimeline: emotionTimeline,\n averageEmotions: avgEmotions,\n emotionAnalysisNote: \"注: 実際の実装では動画フレームからGPT-4 Visionで表情を分析します\"\n }\n });\n}\n\nreturn outputItems;" }, "typeVersion": 2 }, { "id": "b752a4d9-a038-4a4f-a447-f2903bc4fef2", "name": "Send Slack", "type": "n8n-nodes-base.slack", "position": [ 4032, 448 ], "webhookId": "9c0a4066-68a6-4668-a7cf-e246c349fbf7", "parameters": { "text": "={{ \"商談フィードバックレポート: \" + $json.meetingName }}", "select": "channel", "blocksUi": "={{ $json }}", "channelId": { "__rl": true, "mode": "list", "value": "C0A0FH3272Q", "cachedResultName": "n8nテスト" }, "messageType": "block", "otherOptions": {} }, "typeVersion": 2.1 }, { "id": "52248b5e-95b4-468b-8330-63694225db53", "name": "Send Webhook Response", "type": "n8n-nodes-base.respondToWebhook", "position": [ 928, 144 ], "parameters": { "options": {}, "respondWith": "json", "responseBody": "={{ { \"status\": \"received\", \"message\": \"Processing started\" } }}" }, "typeVersion": 1 }, { "id": "a769260d-03ea-4805-b8a1-e06e22210d74", "name": "Fetch Transcript", "type": "n8n-nodes-base.httpRequest", "position": [ 1344, 400 ], "parameters": { "url": "=https://pasta.tldv.io/v1alpha1/meetings/{{ $json.meetingId }}/transcript", "options": {}, "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "x-api-key", "value": "=959c2b17-a846-432e-a9cc-26d10c29ab60" } ] } }, "typeVersion": 4.2 }, { "id": "b8d21657-5611-4fc5-b4df-d6b2e296c220", "name": "Analyze Transcript GPT", "type": "n8n-nodes-base.httpRequest", "position": [ 2144, 400 ], "parameters": { "url": "https://api.openai.com/v1/chat/completions", "method": "POST", "options": {}, "sendBody": true, "authentication": "predefinedCredentialType", "bodyParameters": { "parameters": [ { "name": "model", "value": "gpt-4o" }, { "name": "temperature", "value": "={{ 0.3 }}" }, { "name": "messages", "value": "={{ [{\"role\": \"system\", \"content\": \"あなたは経験豊富な営業コーチングの専門家です。商談会議の文字起こしを客観的に分析し、具体的で実行可能なフィードバックを提供します。分析は必ずJSON形式で返してください。\"}, {\"role\": \"user\", \"content\": \"以下の商談会議の文字起こしを詳細に分析してください。\\n\\n【会議情報】\\n会議名: \" + $json.meetingName + \"\\n時間: \" + $json.duration + \"秒\\n\\n【文字起こし】\\n\" + $json.fullTranscript + \"\\n\\n【分析指示】\\n以下の各項目を0-100点で評価し、評価理由も必ず含めてください。\\n\\n1. 発言時間の配分\\n2. 質問の質と頻度\\n3. 傾聴力\\n4. 顧客エンゲージメント\\n5. 説明の明確さ\\n\\n【重要】必ずJSON形式で返してください。\\n\\n例:\\n{\\n \\\"speakingTimeBalance\\\": {\\\"score\\\": 85, \\\"salesRatio\\\": 40, \\\"customerRatio\\\": 60, \\\"feedback\\\": \\\"評価理由\\\"},\\n \\\"questionQuality\\\": {\\\"score\\\": 75, \\\"openQuestions\\\": 2, \\\"totalQuestions\\\": 3, \\\"feedback\\\": \\\"評価理由\\\"},\\n \\\"listeningSkills\\\": {\\\"score\\\": 80, \\\"feedback\\\": \\\"評価理由\\\"},\\n \\\"customerEngagement\\\": {\\\"score\\\": 90, \\\"customerQuestions\\\": 2, \\\"feedback\\\": \\\"評価理由\\\"},\\n \\\"explanationClarity\\\": {\\\"score\\\": 85, \\\"feedback\\\": \\\"評価理由\\\"},\\n \\\"keyTopics\\\": [\\\"トピック1\\\", \\\"トピック2\\\"],\\n \\\"customerConcerns\\\": [\\\"懸念1\\\"],\\n \\\"positiveSignals\\\": [\\\"シグナル1\\\"],\\n \\\"overallScore\\\": 83,\\n \\\"successProbability\\\": \\\"高\\\",\\n \\\"nextSteps\\\": [\\\"ステップ1\\\", \\\"ステップ2\\\"]\\n}\"}] }}" }, { "name": "response_format", "value": "={{ {\"type\": \"json_object\"} }}" } ] }, "nodeCredentialType": "openAiApi" }, "typeVersion": 4.2 }, { "id": "07d02d1a-92cf-494c-ba97-286c1f477e12", "name": "Parse GPT Analysis", "type": "n8n-nodes-base.set", "position": [ 2368, 400 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "analysis_parsed", "name": "analysisResult", "type": "object", "value": "={{ JSON.parse($json.choices[0].message.content) }}" }, { "id": "keep_meeting_data", "name": "meetingId", "type": "string", "value": "={{ $('Merge Data Meeting').item.json.meetingId }}" }, { "id": "keep_meeting_name", "name": "meetingName", "type": "string", "value": "={{ $('Merge Data Meeting').item.json.meetingName }}" }, { "id": "keep_duration", "name": "duration", "type": "number", "value": "={{ $('Merge Data Meeting').item.json.duration }}" } ] } }, "typeVersion": 3.3 }, { "id": "557efe7c-1e62-4c8a-8194-ca043ad26441", "name": "Merge All Analyses", "type": "n8n-nodes-base.merge", "position": [ 2592, 272 ], "parameters": { "mode": "combine", "options": {}, "combinationMode": "mergeByPosition" }, "typeVersion": 2.1 }, { "id": "51c5ba05-d5f3-4d19-adbf-69037d411a54", "name": "Generate Final Report", "type": "n8n-nodes-base.httpRequest", "position": [ 2880, 272 ], "parameters": { "url": "https://api.openai.com/v1/chat/completions", "method": "POST", "options": {}, "sendBody": true, "authentication": "predefinedCredentialType", "bodyParameters": { "parameters": [ { "name": "model", "value": "gpt-4o" }, { "name": "temperature", "value": "={{ 0.5 }}" }, { "name": "messages", "value": "={{ [{\"role\": \"system\", \"content\": \"あなたは営業コーチングの専門家です。会話分析と表情分析の結果を統合し、総合的なフィードバックレポートを作成します。\"}, {\"role\": \"user\", \"content\": \"以下のデータを基に、商談の総合フィードバックレポートを作成してください。\\n\\n【会議情報】\\n会議名: \" + $json.meetingName + \"\\n時間: \" + Math.floor($json.duration / 60) + \"分\\n\\n【会話分析結果】\\n\" + JSON.stringify($json.analysisResult, null, 2) + \"\\n\\n【表情・感情分析結果】\\n平均感情スコア:\\n- 喜び: \" + $json.averageEmotions.joy + \"%\\n- 興味: \" + $json.averageEmotions.interest + \"%\\n- 懸念: \" + $json.averageEmotions.concern + \"%\\n- 困惑: \" + $json.averageEmotions.confusion + \"%\\n- 退屈: \" + $json.averageEmotions.boredom + \"%\\n\\n【レポート構成】\\n1. エグゼクティブサマリー\\n - 総合評価スコア (0-100)\\n - 商談成功可能性 (高/中/低)\\n - 最重要アクションアイテム (3つ)\\n\\n2. 詳細分析\\n - 顧客エンゲージメント分析\\n - 会話品質の評価\\n - 表情・感情の傾向\\n\\n3. 改善提案 (優先度順に5つ)\\n\\n4. 良かった点 (3-5つ)\\n\\n5. 次のステップ\\n - フォローアップの推奨タイミング\\n - 送付すべき資料の提案\\n - 懸念事項への対応策\\n\\nMarkdown形式で、読みやすく構造化されたレポートを作成してください。\"}] }}" } ] }, "nodeCredentialType": "openAiApi" }, "typeVersion": 4.2 }, { "id": "298da6cb-c109-41f2-a597-cd4acad0d258", "name": "Extract Final Report", "type": "n8n-nodes-base.set", "position": [ 3104, 272 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "final_report", "name": "finalReport", "type": "string", "value": "={{ $json.choices[0].message.content }}" }, { "id": "report_time", "name": "reportGeneratedAt", "type": "string", "value": "={{ new Date().toISOString() }}" }, { "id": "meeting_id_final", "name": "meetingId", "type": "string", "value": "={{ $('Merge Data Meeting').item.json.meetingId }}" }, { "id": "meeting_name_final", "name": "meetingName", "type": "string", "value": "={{ $('Merge Data Meeting').item.json.meetingName }}" } ] } }, "typeVersion": 3.3 }, { "id": "84950dd7-5cc9-4b8e-9991-d27181eae6a1", "name": "Build Slack Blocks", "type": "n8n-nodes-base.code", "position": [ 3328, 272 ], "parameters": { "jsCode": "const items = $input.all();\nconst outputItems = [];\n\nfor (const item of items) {\n const report = item.json.finalReport;\n const meetingName = item.json.meetingName;\n const meetingId = item.json.meetingId;\n \n // Remove markdown code block markers if present\n let cleanReport = report;\n if (cleanReport.startsWith('```markdown')) {\n cleanReport = cleanReport.replace(/^```markdown\\n/, '').replace(/\\n```$/, '');\n } else if (cleanReport.startsWith('```')) {\n cleanReport = cleanReport.replace(/^```\\n/, '').replace(/\\n```$/, '');\n }\n \n // Create blocks array\n const blocks = [\n {\n type: \"header\",\n text: {\n type: \"plain_text\",\n text: \"📋 商談フィードバックレポート\",\n emoji: true\n }\n },\n {\n type: \"section\",\n fields: [\n {\n type: \"mrkdwn\",\n text: `*📅 会議名*\\n${meetingName}`\n },\n {\n type: \"mrkdwn\",\n text: `*🆔 Meeting ID*\\n${meetingId || 'N/A'}`\n }\n ]\n },\n {\n type: \"divider\"\n }\n ];\n \n // Parse report and create rich sections\n const lines = cleanReport.split('\\n');\n let i = 0;\n \n while (i < lines.length) {\n const line = lines[i].trim();\n \n // Main section header (## 1. など)\n if (line.match(/^## \\d+\\. /)) {\n const sectionNum = line.match(/^## (\\d+)\\. /)[1];\n const sectionTitle = line.replace(/^## \\d+\\. /, '');\n \n // Section emoji mapping\n const sectionEmojis = {\n '1': '🎯', // エグゼクティブサマリー\n '2': '📊', // 詳細分析\n '3': '💡', // 改善提案\n '4': '⭐', // 良かった点\n '5': '🚀' // 次のステップ\n };\n \n const emoji = sectionEmojis[sectionNum] || '📌';\n \n // Add section header with emoji\n blocks.push({\n type: \"section\",\n text: {\n type: \"mrkdwn\",\n text: `*${emoji} ${sectionTitle}*`\n }\n });\n \n blocks.push({\n type: \"divider\"\n });\n \n i++;\n \n // Collect section content\n const sectionContent = [];\n \n while (i < lines.length && !lines[i].trim().match(/^## \\d+\\. /)) {\n const contentLine = lines[i].trim();\n \n // Skip empty lines but keep track of them for formatting\n if (contentLine === '') {\n if (sectionContent.length > 0 && sectionContent[sectionContent.length - 1] !== '') {\n sectionContent.push('');\n }\n } else if (contentLine.match(/^### /)) {\n // Sub-section header - add as bold text\n const subTitle = contentLine.replace(/^### /, '');\n sectionContent.push(`\\n*${subTitle}*`);\n } else {\n // Regular content line\n sectionContent.push(contentLine);\n }\n \n i++;\n }\n \n // Add final content block\n if (sectionContent.length > 0) {\n // Filter out trailing empty lines\n while (sectionContent.length > 0 && sectionContent[sectionContent.length - 1] === '') {\n sectionContent.pop();\n }\n \n if (sectionContent.length > 0) {\n const content = sectionContent.join('\\n');\n blocks.push({\n type: \"section\",\n text: {\n type: \"mrkdwn\",\n text: content\n }\n });\n }\n }\n \n // Add spacing between sections\n blocks.push({\n type: \"divider\"\n });\n } else {\n i++;\n }\n }\n \n // Add footer\n blocks.push({\n type: \"context\",\n elements: [\n {\n type: \"mrkdwn\",\n text: \"_Automated with n8n workflow_\"\n }\n ]\n });\n \n outputItems.push({\n json: {\n ...item.json,\n slackBlocks: blocks\n }\n });\n}\n\nreturn outputItems;" }, "typeVersion": 2 }, { "id": "6c372496-120d-4cd5-8bad-75497e755f80", "name": "Append to Google Sheets", "type": "n8n-nodes-base.googleSheets", "position": [ 4032, 64 ], "parameters": { "columns": { "value": {}, "schema": [ { "id": "日時", "type": "string", "display": true, "removed": false, "required": false, "displayName": "日時", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "会議名", "type": "string", "display": true, "removed": false, "required": false, "displayName": "会議名", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Meeting ID", "type": "string", "display": true, "removed": false, "required": false, "displayName": "Meeting ID", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "総合評価スコア", "type": "string", "display": true, "removed": false, "required": false, "displayName": "総合評価スコア", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "商談成功可能性", "type": "string", "display": true, "removed": false, "required": false, "displayName": "商談成功可能性", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "顧客エンゲージメントスコア", "type": "string", "display": true, "removed": false, "required": false, "displayName": "顧客エンゲージメントスコア", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "発言バランス", "type": "string", "display": true, "removed": false, "required": false, "displayName": "発言バランス", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "質問の質", "type": "string", "display": true, "removed": false, "required": false, "displayName": "質問の質", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "傾聴スキル", "type": "string", "display": true, "removed": false, "required": false, "displayName": "傾聴スキル", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "説明の明確さ", "type": "string", "display": true, "removed": false, "required": false, "displayName": "説明の明確さ", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "感情-喜び(%)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "感情-喜び(%)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "感情-興味(%)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "感情-興味(%)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "感情-懸念(%)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "感情-懸念(%)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "感情-困惑(%)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "感情-困惑(%)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "感情-退屈(%)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "感情-退屈(%)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "改善提案(要約)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "改善提案(要約)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "良かった点(要約)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "良かった点(要約)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "次のステップ(要約)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "次のステップ(要約)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "レポート生成日時", "type": "string", "display": true, "removed": false, "required": false, "displayName": "レポート生成日時", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "最終レポート(全文)", "type": "string", "display": true, "removed": false, "required": false, "displayName": "最終レポート(全文)", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "autoMapInputData", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "name", "value": "商談フィードバック" }, "documentId": { "__rl": true, "mode": "id", "value": "1mrr_KweC9JThYdghm67ySyDjNZwG16sTlUvzLRnv4Zw" } }, "typeVersion": 4.4 }, { "id": "a9424348-8b30-4185-a993-39d141e21fa6", "name": "Format Sheets Data", "type": "n8n-nodes-base.set", "position": [ 3824, 64 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "timestamp", "name": "日時", "type": "string", "value": "={{ $json.timestamp }}" }, { "id": "meeting_name", "name": "会議名", "type": "string", "value": "={{ $json.meetingName }}" }, { "id": "meeting_id", "name": "Meeting ID", "type": "string", "value": "={{ $json.meetingId }}" }, { "id": "total_score", "name": "総合評価スコア", "type": "string", "value": "={{ $json.totalScore }}" }, { "id": "success_prob", "name": "商談成功可能性", "type": "string", "value": "={{ $json.successProbability }}" }, { "id": "engagement", "name": "顧客エンゲージメントスコア", "type": "string", "value": "={{ $json.customerEngagementScore }}" }, { "id": "speaking", "name": "発言バランス", "type": "string", "value": "={{ $json.speakingBalance }}" }, { "id": "question", "name": "質問の質", "type": "string", "value": "={{ $json.questionQuality }}" }, { "id": "listening", "name": "傾聴スキル", "type": "string", "value": "={{ $json.listeningSkill }}" }, { "id": "clarity", "name": "説明の明確さ", "type": "string", "value": "={{ $json.clarityScore }}" }, { "id": "joy", "name": "感情-喜び(%)", "type": "string", "value": "={{ $json.joyPercentage }}" }, { "id": "interest", "name": "感情-興味(%)", "type": "string", "value": "={{ $json.interestPercentage }}" }, { "id": "concern", "name": "感情-懸念(%)", "type": "string", "value": "={{ $json.concernPercentage }}" }, { "id": "confusion", "name": "感情-困惑(%)", "type": "string", "value": "={{ $json.confusionPercentage }}" }, { "id": "bored", "name": "感情-退屈(%)", "type": "string", "value": "={{ $json.boredPercentage }}" }, { "id": "improvement", "name": "改善提案(要約)", "type": "string", "value": "={{ $json.improvementSummary }}" }, { "id": "good_points", "name": "良かった点(要約)", "type": "string", "value": "={{ $json.goodPointsSummary }}" }, { "id": "next_steps", "name": "次のステップ(要約)", "type": "string", "value": "={{ $json.nextStepsSummary }}" }, { "id": "gen_at", "name": "レポート生成日時", "type": "string", "value": "={{ $json.reportGeneratedAt }}" }, { "id": "full_report", "name": "最終レポート(全文)", "type": "string", "value": "={{ $json.fullReport }}" } ] } }, "typeVersion": 3.3 } ], "pinData": {}, "connections": { "Analyze Emotions": { "main": [ [ { "node": "Merge All Analyses", "type": "main", "index": 0 } ] ] }, "Fetch Transcript": { "main": [ [ { "node": "Parse Transcript", "type": "main", "index": 0 } ] ] }, "Parse Transcript": { "main": [ [ { "node": "Merge Data Meeting", "type": "main", "index": 1 } ] ] }, "Webhook - Trigger": { "main": [ [ { "node": "Send Webhook Response", "type": "main", "index": 0 } ] ] }, "Build Slack Blocks": { "main": [ [ { "node": "Extract Sheets Data", "type": "main", "index": 0 } ] ] }, "Extract Meeting ID": { "main": [ [ { "node": "Fetch Transcript", "type": "main", "index": 0 }, { "node": "Fetch Meeting Details", "type": "main", "index": 0 } ] ] }, "Format Sheets Data": { "main": [ [ { "node": "Append to Google Sheets", "type": "main", "index": 0 } ] ] }, "Merge All Analyses": { "main": [ [ { "node": "Generate Final Report", "type": "main", "index": 0 } ] ] }, "Merge Data Meeting": { "main": [ [ { "node": "Prepare Video Analysis", "type": "main", "index": 0 }, { "node": "Analyze Transcript GPT", "type": "main", "index": 0 } ] ] }, "Parse GPT Analysis": { "main": [ [ { "node": "Merge All Analyses", "type": "main", "index": 1 } ] ] }, "Parse Meeting Data": { "main": [ [ { "node": "Merge Data Meeting", "type": "main", "index": 0 } ] ] }, "Extract Sheets Data": { "main": [ [ { "node": "Format Sheets Data", "type": "main", "index": 0 }, { "node": "Filter Slack Response", "type": "main", "index": 0 } ] ] }, "Extract Final Report": { "main": [ [ { "node": "Build Slack Blocks", "type": "main", "index": 0 } ] ] }, "Fetch Meeting Details": { "main": [ [ { "node": "Parse Meeting Data", "type": "main", "index": 0 } ] ] }, "Filter Slack Response": { "main": [ [ { "node": "Send Slack", "type": "main", "index": 0 } ] ] }, "Generate Final Report": { "main": [ [ { "node": "Extract Final Report", "type": "main", "index": 0 } ] ] }, "Analyze Transcript GPT": { "main": [ [ { "node": "Parse GPT Analysis", "type": "main", "index": 0 } ] ] }, "Prepare Video Analysis": { "main": [ [ { "node": "Analyze Emotions", "type": "main", "index": 0 } ] ] }, "Send Webhook Response": { "main": [ [ { "node": "Extract Meeting ID", "type": "main", "index": 0 } ] ] } } }