KI-gestützte automatische Analyse von Meeting-Effekten mit Slack-Feedback
Experte
Dies ist ein Content Creation, Multimodal AI-Bereich Automatisierungsworkflow mit 18 Nodes. Hauptsächlich werden If, Set, Code, Wait, Slack und andere Nodes verwendet. Automatische Analyse der Besprechungsleistung basierend auf KI und Feedback-Sende an Slack
Voraussetzungen
- •Slack Bot Token oder Webhook URL
- •Google Drive API-Anmeldedaten
- •OpenAI API Key
Verwendete Nodes (18)
Kategorie
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
"meta": {
"instanceId": "271ad271582e33e7052a1750142c4d1e028deb0c5d010978918984ab393ca4cf",
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "650def54-b86d-444f-9d0f-0b20aa6ec372",
"name": "KI-Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
448,
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],
"parameters": {
"options": {
"systemMessage": "=# Meeting Coach AI System Prompt\n\nYou are a Meeting Coach AI that analyzes meeting effectiveness and provides constructive feedback.\n\n## Role and Purpose\n\nAnalyze meeting minutes or transcripts to provide objective and specific feedback on meeting effectiveness, communication quality, and areas for improvement. Avoid being overly critical and ensure to include actionable improvement suggestions.\n\n## Steps\n\n1. If there is a Google Docs URL for the meeting minutes, use it to retrieve the minutes from Google Drive. If not, search Google Drive using the meeting title name to retrieve the relevant minutes.\n2. If the meeting minutes cannot be found, report this and conclude.\n3. Review the retrieved meeting minutes to understand the full text and content.\n4. Compile feedback with the following content:\n\n## Analysis Items and Output Format\n\n### 1. Meeting Effectiveness\n\n- **Effectiveness Score**: Rate from 0% to 100%\n- Analyze from the following perspectives:\n - **Meeting Purpose**: What was the goal of the meeting?\n - **Achievements**: What was accomplished toward the goal?\n - **Challenges**: What hindered the meeting's effectiveness (e.g., topic derailment, lack of focus)?\n - **Conclusions and Next Steps**: Were specific decisions and action items clearly defined?\n\n### 2. Speaking Time Distribution\n\n- Display each participant's speaking time as a percentage\n- Comments on speaking balance:\n - Was the balance appropriate?\n - Was it a one-sided conversation?\n - Suggestions for more effective dialogue\n\n### 3. Interruptions\n\n- Analyze whether there were significant interruptions and their impact on the meeting\n- Note if there were no interruptions\n\n### 4. Communication Quality\n\nRate each of the following items on a 5-star scale (★☆☆☆☆ to ★★★★★) and provide specific comments:\n\n- **Clarity**: Were the agenda and opinions communicated clearly?\n - ★☆☆☆☆: Very unclear\n - ★★☆☆☆: Unclear\n - ★★★☆☆: Average\n - ★★★★☆: Clear\n - ★★★★★: Very clear\n\n- **Friendliness**: Was the atmosphere cooperative and positive?\n - ★☆☆☆☆: Hostile\n - ★★☆☆☆: Somewhat cold\n - ★★★☆☆: Average\n - ★★★★☆: Friendly\n - ★★★★★: Very friendly\n\n- **Decisiveness**: Were decisions and next actions clearly defined?\n - ★☆☆☆☆: No decisions made\n - ★★☆☆☆: Ambiguous\n - ★★★☆☆: Some decisions\n - ★★★★☆: Clear decisions\n - ★★★★★: Very clear decisions and actions\n\n- **Listening**: Did participants listen to and try to understand each other's opinions?\n - ★☆☆☆☆: Not listening at all\n - ★★☆☆☆: Not listening much\n - ★★★☆☆: Average\n - ★★★★☆: Listening well\n - ★★★★★: Listening very well\n\nFor each item:\n- Quote specific examples of what went well from the conversation\n- Points that could be improved and specific suggestions\n\n### 5. Disagreements\n\n- List topics that became points of discussion\n- Briefly explain each participant's position\n- Note whether issues were resolved or remained unresolved\n- If there were no conflicts, note \"None in particular\"\n\n### 6. Meeting Info\n\n- Meeting title (extract from minutes, or \"Unknown\" if unavailable)\n- List of participants\n\n## Tone and Style\n\n- **Constructive**: Provide insights for growth, not criticism\n- **Specific**: Quote concrete examples from the conversation rather than abstract evaluations\n- **Balanced**: Point out both strengths and areas for improvement\n- **Practical**: Include improvement suggestions that can be implemented immediately\n\n## Output Format\n\n**Meeting Effectiveness** → **[Your evaluated score]%**\n* [Analysis of meeting purpose]\n* [What was achieved]\n* [Challenges]\n* [Evaluation of conclusions and next steps]\n\n**Speaking Time Distribution**\n* **[Participant name]**: [Your calculated percentage]%\n* **[Participant name]**: [Your calculated percentage]%\n* [Comments on speaking balance]\n* [Improvement suggestions]\n\n**Interruptions**\n* [Analysis of presence and impact of interruptions]\n\n**Communication Quality**\n* [Your evaluated number of ★s] **| Clarity**: [Evaluation comment]\n* [Your evaluated number of ★s] **| Friendliness**: [Evaluation comment]\n* [Your evaluated number of ★s] **| Decisiveness**: [Evaluation comment]\n* [Your evaluated number of ★s] **| Listening**: [Evaluation comment]\n* [Specific improvement suggestions and examples of positive points]\n\n**Disagreements**\n❌ [Topic name]:\n1. **[Participant name]**: [Explanation of position]\n2. **[Participant name]**: [Explanation of position]\n3. **Resolution status**: [Explanation of whether consensus was reached or issue remains unresolved]\n\n(If no conflicts: \"There were no significant disagreements.\")\n\n**Meeting Info**\n* **Meeting Title**: [Title]\n* **Participants**: [Participant list]\n\n---\n\nWhen meeting minutes or transcripts are provided, analyze and provide feedback following the above format. Evaluate each assessment item appropriately based on the actual meeting content."
}
},
"typeVersion": 2.2
},
{
"id": "199072fb-3fb9-440d-aa57-44dc6afb2bee",
"name": "OpenAI-Chat-Modell",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
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],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-5",
"cachedResultName": "gpt-5"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "azgro9Tx2nlIAQVv",
"name": "OpenAi(tobe)"
}
},
"typeVersion": 1.2
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{
"id": "0194fded-a382-47e8-8cec-0a6936df9faa",
"name": "SearchDoc",
"type": "n8n-nodes-base.googleDriveTool",
"position": [
576,
416
],
"parameters": {
"limit": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Limit', ``, 'number') }}",
"filter": {
"whatToSearch": "files"
},
"options": {},
"resource": "fileFolder",
"queryString": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Search_Query', ``, 'string') }}"
},
"credentials": {
"googleDriveOAuth2Api": {
"id": "hOG09SnmNsGXlS9o",
"name": "GoogleDrive(j.tobe)"
}
},
"typeVersion": 3
},
{
"id": "4a61eb43-d664-493b-887e-c412d6652dfc",
"name": "GetDoc",
"type": "n8n-nodes-base.googleDocsTool",
"position": [
672,
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],
"parameters": {
"operation": "get",
"documentURL": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Doc_ID_or_URL', ``, 'string') }}"
},
"credentials": {
"googleDocsOAuth2Api": {
"id": "gIuEB1RhXjXKNGUs",
"name": "GoogldDocs(j.tobe)"
}
},
"typeVersion": 2
},
{
"id": "9d1fa3ac-5030-416e-8020-b2eec0c1f1b4",
"name": "Nachricht senden",
"type": "n8n-nodes-base.slack",
"position": [
1040,
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],
"webhookId": "ae52c4f6-573f-4388-93d9-a8af0142d929",
"parameters": {
"text": "=テスト",
"user": {
"__rl": true,
"mode": "id",
"value": "U03H0J4KU7R"
},
"select": "user",
"blocksUi": "={{ $json.slackPayload }}",
"messageType": "block",
"otherOptions": {
"mrkdwn": true
},
"authentication": "oAuth2"
},
"credentials": {
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}
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{
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"name": "Simple Speicher",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
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],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "22b64ef2-5672-43c7-9a8c-e761447eedc1",
"name": "Google Kalender Trigger",
"type": "n8n-nodes-base.googleCalendarTrigger",
"position": [
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],
"parameters": {
"options": {},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "eventEnded",
"calendarId": {
"__rl": true,
"mode": "id",
"value": "=[your-id]"
}
},
"credentials": {
"googleCalendarOAuth2Api": {
"id": "t5AgzbZYZniiNqS3",
"name": "Google Calendar (j.tobe)"
}
},
"typeVersion": 1
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{
"id": "c70fd6b4-5428-44ab-8080-f4a10a35de58",
"name": "Felder bearbeiten",
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"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "82a8a73d-5c24-4c67-aed4-8d3f26ccf8f8",
"name": "chatInput",
"type": "string",
"value": "={{ $json.summary }} というタイトルの会議を行い {{ $json.attachment[0].fileUrl }} という URL の Google Docs に気議事録を保存しました\n\nGoogle Docs の fileId は {{ $json.attachment[0].fileId }} です"
},
{
"id": "3f8f99b5-9cf2-4005-b1fc-cc89fa79183a",
"name": "=sessionId",
"type": "string",
"value": "=a {{ $json.id }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "e468e662-b2fa-4f8a-b01d-e0213cdb4d40",
"name": "Warten",
"type": "n8n-nodes-base.wait",
"position": [
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],
"webhookId": "04af6fbe-7a07-494a-ad4b-ac3b2d46414b",
"parameters": {
"unit": "minutes"
},
"typeVersion": 1.1
},
{
"id": "8cbf5fe5-879c-456a-9b4d-66d1f04f0b26",
"name": "Event abrufen",
"type": "n8n-nodes-base.googleCalendar",
"position": [
-336,
240
],
"parameters": {
"eventId": "={{ $json.id }}",
"options": {},
"calendar": {
"__rl": true,
"mode": "id",
"value": "=[your-id]"
},
"operation": "get"
},
"credentials": {
"googleCalendarOAuth2Api": {
"id": "t5AgzbZYZniiNqS3",
"name": "Google Calendar (j.tobe)"
}
},
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{
"id": "ed8ecac5-c3c2-464b-8cfe-540a76525187",
"name": "Test Trigger",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
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],
"webhookId": "14967cec-2211-4d1c-9570-8e7d85ced11e",
"parameters": {
"options": {
"responseMode": "lastNode"
}
},
"typeVersion": 1.3
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{
"id": "398412f8-29fa-49eb-ac55-cfef96469809",
"name": "Code",
"type": "n8n-nodes-base.code",
"position": [
896,
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],
"parameters": {
"jsCode": "/**\n * n8n Code node (JavaScript)\n * 入力: $input.first().json.output に Markdown風の長文(実改行 or リテラル \"\\n\")\n * 出力: 最初のアイテムに以下を格納\n * - json.blocks: Array<Block>(Block Kit の配列)\n * - json.slackPayload: { blocks: Array<Block> } // ← UI Builder と同じトップレベル\n * - json.text_fallback: Slack text 用フォールバック\n *\n * 次ノード(Slack 送信例):\n * - Body JSON に {{$json.slackPayload}} をそのまま使う\n * - もしくは blocks: {{$json.blocks}}, text: {{$json.text_fallback}}\n */\n\n// ===== Utils =====\nfunction toActualNewlines(s) {\n if (typeof s !== 'string') return '';\n return s.replace(/\\r\\n?/g, '\\n').replace(/\\\\n/g, '\\n');\n}\n\n// インライン: *bold* / **bold**, _italic_, `code`, [text](url)\nfunction tokenizeInline(text) {\n const tokens = [];\n let i = 0;\n\n const pushPlain = (t) => { if (t) tokens.push({ type: 'text', text: t }); };\n\n const patterns = [\n { // code\n re: /`([^`]+)`/g,\n build: (m) => ({ type: 'text', text: m[1], style: { code: true } }),\n },\n { // bold **...**\n re: /\\*\\*([^*]+)\\*\\*/g,\n build: (m) => ({ type: 'text', text: m[1], style: { bold: true } }),\n },\n { // bold *...* (先頭の箇条書き \"* \" と衝突しないよう調整)\n re: /(^|[^*])\\*([^*\\n]+)\\*(?!\\*)/g,\n build: (m) => [{ type: 'text', text: m[1] || '' }, { type: 'text', text: m[2], style: { bold: true } }],\n isComposite: true,\n },\n { // italic _..._\n re: /_([^_]+)_/g,\n build: (m) => ({ type: 'text', text: m[1], style: { italic: true } }),\n },\n { // link [text](url)\n re: /\\[([^\\]]+)\\]\\((https?:\\/\\/[^\\s)]+)\\)/g,\n build: (m) => ({ type: 'link', url: m[2], text: m[1] }),\n },\n ];\n\n while (i < text.length) {\n let earliest = null, pat = null;\n for (const p of patterns) {\n p.re.lastIndex = i;\n const m = p.re.exec(text);\n if (m && (!earliest || m.index < earliest.index)) {\n earliest = m; pat = p;\n }\n }\n if (!earliest) { pushPlain(text.slice(i)); break; }\n\n if (earliest.index > i) pushPlain(text.slice(i, earliest.index));\n\n if (pat.isComposite) {\n const built = pat.build(earliest);\n for (const b of built) if (b.text !== '') tokens.push(b);\n } else {\n tokens.push(pat.build(earliest));\n }\n\n i = earliest.index + earliest[0].length;\n }\n\n return tokens.length ? tokens : [{ type: 'text', text }];\n}\n\nfunction makeSectionElementsFromText(t) {\n return tokenizeInline(t);\n}\n\n// ===== Block builders =====\nfunction headerBlock(text) {\n return { type: 'header', text: { type: 'plain_text', text: text.slice(0, 150) } };\n}\nfunction paragraphBlock(text) {\n return { type: 'rich_text', elements: [{ type: 'rich_text_section', elements: makeSectionElementsFromText(text) }] };\n}\nfunction quoteBlock(lines) {\n const elements = lines.map(l => ({ type: 'rich_text_section', elements: makeSectionElementsFromText(l) }));\n return { type: 'rich_text', elements: [{ type: 'rich_text_quote', elements }] };\n}\nfunction preBlock(lines) {\n return { type: 'rich_text', elements: [{ type: 'rich_text_preformatted', elements: [{ type: 'text', text: lines.join('\\n') }] }] };\n}\nfunction listBlock(style, indent, sections) {\n return { type: 'rich_text', elements: [{ type: 'rich_text_list', style, indent, elements: sections }] };\n}\n\n// ===== Parser =====\nfunction convertMarkdownToBlocks(mdRaw) {\n const md = toActualNewlines(mdRaw);\n const lines = md.split('\\n');\n const blocks = [];\n\n let inCode = false, codeBuf = [];\n let inQuote = false, quoteBuf = [];\n\n // リスト状態(style/indent で束ねる)\n let listActive = false, listStyle = null, listIndent = 0, listItems = [];\n\n const flushQuote = () => {\n if (inQuote && quoteBuf.length) blocks.push(quoteBlock(quoteBuf));\n inQuote = false; quoteBuf = [];\n };\n const flushList = () => {\n if (listActive && listItems.length) blocks.push(listBlock(listStyle, listIndent, listItems));\n listActive = false; listStyle = null; listIndent = 0; listItems = [];\n };\n const startList = (style, indent) => {\n if (!listActive || listStyle !== style || listIndent !== indent) {\n flushList();\n listActive = true; listStyle = style; listIndent = indent; listItems = [];\n }\n };\n\n const parseListLine = (line) => {\n const leading = (line.match(/^\\s*/)[0] || '').length;\n const trimmed = line.trim();\n if (/^[-*•]\\s+/.test(trimmed)) {\n return { style: 'bullet', indent: Math.floor(leading / 2), text: trimmed.replace(/^[-*•]\\s+/, '') };\n }\n const m = trimmed.match(/^(\\d+)\\.\\s+(.+)$/);\n if (m) {\n return { style: 'ordered', indent: Math.floor(leading / 2), text: m[2] };\n }\n return null;\n };\n\n for (let i = 0; i < lines.length; i++) {\n const raw = lines[i];\n\n // ``` code fence\n if (/^\\s*```/.test(raw)) {\n flushQuote(); flushList();\n if (!inCode) { inCode = true; codeBuf = []; }\n else { blocks.push(preBlock(codeBuf)); inCode = false; codeBuf = []; }\n continue;\n }\n if (inCode) { codeBuf.push(raw); continue; }\n\n // 空行は区切り\n if (/^\\s*$/.test(raw)) {\n flushQuote(); flushList();\n continue;\n }\n\n // 引用\n if (/^\\s*>+\\s?/.test(raw)) {\n flushList();\n const q = raw.replace(/^\\s*>+\\s?/, '');\n inQuote = true; quoteBuf.push(q);\n continue;\n } else if (inQuote) {\n flushQuote();\n }\n\n // 見出し(#〜### or **見出し** 単独行)\n if (/^\\s*#{1,3}\\s+/.test(raw) || /^\\s*\\*\\*(.+?)\\*\\*\\s*$/.test(raw)) {\n flushQuote(); flushList();\n const text = /^\\s*#{1,3}\\s+/.test(raw)\n ? raw.replace(/^\\s*#{1,3}\\s+/, '').trim()\n : (raw.match(/^\\s*\\*\\*(.+?)\\*\\*\\s*$/)[1] || '').trim();\n blocks.push(headerBlock(text));\n continue;\n }\n\n // リスト\n const li = parseListLine(raw);\n if (li) {\n flushQuote();\n startList(li.style, li.indent);\n listItems.push({ type: 'rich_text_section', elements: makeSectionElementsFromText(li.text) });\n continue;\n } else {\n flushList();\n }\n\n // 通常段落\n blocks.push(paragraphBlock(raw));\n }\n\n // 残り\n if (inCode && codeBuf.length) blocks.push(preBlock(codeBuf));\n flushQuote(); flushList();\n\n return blocks;\n}\n\n// ===== Main =====\nconst items = $input.all();\nconst first = $input.first();\nconst source = first?.json?.output ?? '';\n\nconst blocks = convertMarkdownToBlocks(source);\n\n// text_fallback: 最初の header / paragraph を抽出\nlet textFallback = 'Message';\nfor (const b of blocks) {\n if (b.type === 'header') { textFallback = b.text?.text?.slice(0, 300) || textFallback; break; }\n if (b.type === 'rich_text') {\n const el = b.elements?.[0];\n if (el?.type === 'rich_text_section') {\n const s = (el.elements || [])\n .map(e => e.type === 'text' ? e.text : (e.type === 'link' ? (e.text || e.url) : ''))\n .join('');\n if (s) { textFallback = s.slice(0, 300); break; }\n }\n }\n}\n\n// 返却フォーマット(UI Builder と同じトップに blocks)\nfirst.json.blocks = blocks; // 配列(必要ならこちらを直接使う)\nfirst.json.slackPayload = { blocks }; // ← 期待どおりの { \"blocks\": [...] }\nfirst.json.text_fallback = textFallback;\n\nreturn items;\n"
},
"typeVersion": 2
},
{
"id": "bc7b5908-d4b5-4d91-b682-59b98c30d79b",
"name": "If",
"type": "n8n-nodes-base.if",
"position": [
-160,
240
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "6385b3c0-7c81-46f4-81cd-3693ea460ab1",
"operator": {
"type": "boolean",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $json.attachment }} ",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "d7a63115-97ba-4022-9338-f7ab40252b56",
"name": "Keine Operation, do nothing",
"type": "n8n-nodes-base.noOp",
"position": [
112,
448
],
"parameters": {},
"typeVersion": 1
},
{
"id": "71f79653-49b9-4faa-bd5b-2787ab8bb30a",
"name": "Haftnotiz",
"type": "n8n-nodes-base.stickyNote",
"position": [
-752,
-48
],
"parameters": {
"width": 768,
"height": 656,
"content": "## Triggers\n* End of Google Calendar Event\n* Chat Trigger for testing"
},
"typeVersion": 1
},
{
"id": "a42391fb-cda2-438e-957b-8c342f505842",
"name": "Haftnotiz1",
"type": "n8n-nodes-base.stickyNote",
"position": [
48,
-48
],
"parameters": {
"color": 4,
"height": 464,
"content": "## Adjust format\nAdjust input format for next node that is AI Agent"
},
"typeVersion": 1
},
{
"id": "5f128546-5780-48c4-967e-eb81fff4f611",
"name": "Haftnotiz2",
"type": "n8n-nodes-base.stickyNote",
"position": [
320,
-48
],
"parameters": {
"color": 5,
"width": 496,
"height": 656,
"content": "## AI node\nThis AI Agent analyze your meeting transcription, and give a feedback."
},
"typeVersion": 1
},
{
"id": "65be1eda-c622-4bd6-83b9-1c066b55427d",
"name": "Haftnotiz3",
"type": "n8n-nodes-base.stickyNote",
"position": [
848,
-48
],
"parameters": {
"color": 3,
"width": 384,
"height": 656,
"content": "## Output node \n* Changet format from regular markdown to Slack mrkdown by code node\n* Post a slack message\n* You can change the settings to send other channels"
},
"typeVersion": 1
}
],
"pinData": {},
"connections": {
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"main": [
[
{
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"type": "main",
"index": 0
}
],
[
{
"node": "No Operation, do nothing",
"type": "main",
"index": 0
}
]
]
},
"398412f8-29fa-49eb-ac55-cfef96469809": {
"main": [
[
{
"node": "9d1fa3ac-5030-416e-8020-b2eec0c1f1b4",
"type": "main",
"index": 0
}
]
]
},
"e468e662-b2fa-4f8a-b01d-e0213cdb4d40": {
"main": [
[
{
"node": "8cbf5fe5-879c-456a-9b4d-66d1f04f0b26",
"type": "main",
"index": 0
}
]
]
},
"4a61eb43-d664-493b-887e-c412d6652dfc": {
"ai_tool": [
[
{
"node": "650def54-b86d-444f-9d0f-0b20aa6ec372",
"type": "ai_tool",
"index": 0
}
]
]
},
"650def54-b86d-444f-9d0f-0b20aa6ec372": {
"main": [
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"Simple Memory": {
"ai_memory": [
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"OpenAI Chat Model": {
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"Google Calendar Trigger": {
"main": [
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}Häufig gestellte Fragen
Wie verwende ich diesen Workflow?
Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.
Für welche Szenarien ist dieser Workflow geeignet?
Experte - Content-Erstellung, Multimodales KI
Ist es kostenpflichtig?
Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.
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