내 워크플로우 2

• •HTTP Webhook 엔드포인트(n8n이 자동으로 생성)
• •Google Sheets API 인증 정보

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  "name": "My workflow 2",
  "tags": [],
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    {
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      "name": "연구 요청 웹훅",
      "type": "n8n-nodes-base.webhook",
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    {
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        "jsCode": "// Extract and validate research parameters\nconst body = $input.all()[0].json.body;\n\n// Default research configuration\nconst researchConfig = {\n  topic: body.topic || 'artificial intelligence trends',\n  depth: body.depth || 'comprehensive', // basic, detailed, comprehensive\n  sources: body.sources || ['web', 'academic', 'news'],\n  timeframe: body.timeframe || '6months',\n  language: body.language || 'en',\n  maxSources: body.maxSources || 10,\n  analysisType: body.analysisType || 'summary' // summary, detailed, comparative\n};\n\n// Generate search queries based on topic\nconst baseQueries = [\n  `${researchConfig.topic} latest developments`,\n  `${researchConfig.topic} research findings`,\n  `${researchConfig.topic} market analysis`,\n  `${researchConfig.topic} expert opinions`,\n  `${researchConfig.topic} case studies`\n];\n\n// Add specific queries based on depth\nif (researchConfig.depth === 'comprehensive') {\n  baseQueries.push(\n    `${researchConfig.topic} academic papers`,\n    `${researchConfig.topic} industry reports`,\n    `${researchConfig.topic} statistical data`,\n    `${researchConfig.topic} future predictions`\n  );\n}\n\nreturn [{\n  json: {\n    ...researchConfig,\n    searchQueries: baseQueries,\n    timestamp: new Date().toISOString(),\n    sessionId: `research_${Date.now()}`\n  }\n}];"
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      "name": "검색 쿼리 분할",
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      "name": "뉴스 소스 스크래퍼",
      "type": "n8n-nodes-scrapegraphai.scrapegraphAi",
      "position": [
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        "userPrompt": "Extract recent news articles about this topic. For each article provide: headline, publication date, source, brief summary, and direct URL. Focus on credible news sources and recent publications within the last 6 months.",
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        "jsCode": "// Combine and process all research data\nconst allItems = $input.all();\nconst researchData = allItems[0].json;\nconst newsData = allItems[1]?.json || {};\nconst academicData = allItems[2]?.json || {};\n\n// Extract and structure the research findings\nconst processedData = {\n  sessionId: researchData.sessionId,\n  query: researchData.currentQuery,\n  batchIndex: researchData.batchIndex,\n  timestamp: new Date().toISOString(),\n  \n  // General research findings\n  generalFindings: {\n    title: researchData.result?.title || 'Research Findings',\n    summary: researchData.result?.summary || '',\n    keyPoints: researchData.result?.keyPoints || [],\n    statistics: researchData.result?.statistics || [],\n    credibilityScore: researchData.result?.credibilityScore || 0\n  },\n  \n  // News findings\n  newsFindings: {\n    articles: newsData.result?.articles || [],\n    totalArticles: newsData.result?.articles?.length || 0\n  },\n  \n  // Academic findings\n  academicFindings: {\n    papers: academicData.result?.papers || [],\n    totalPapers: academicData.result?.papers?.length || 0\n  },\n  \n  // Meta information\n  sourceTypes: ['general', 'news', 'academic'],\n  totalSources: (researchData.result?.sources?.length || 0) + \n                (newsData.result?.articles?.length || 0) + \n                (academicData.result?.papers?.length || 0)\n};\n\nreturn [{\n  json: processedData\n}];"
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      "type": "n8n-nodes-base.respondToWebhook",
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        "content": "# Step 1: Research Request Webhook 🎯\n\nThis webhook endpoint receives research requests and initiates the deep research process.\n\n## Request Format\n```json\n{\n  \"topic\": \"artificial intelligence in healthcare\",\n  \"depth\": \"comprehensive\",\n  \"sources\": [\"web\", \"academic\", \"news\"],\n  \"timeframe\": \"6months\",\n  \"maxSources\": 15,\n  \"analysisType\": \"detailed\"\n}\n```\n\n## Configuration\n- **Method**: POST\n- **Path**: /research-trigger\n- **Authentication**: Optional API key\n- **Rate Limiting**: Configurable\n\n## Depth Levels\n- **Basic**: Quick overview with 3-5 sources\n- **Detailed**: Comprehensive analysis with 8-12 sources\n- **Comprehensive**: Deep dive with 15+ sources and academic papers\n\n## Source Types\n- **Web**: General web content and industry sites\n- **News**: Recent news articles and press releases\n- **Academic**: Peer-reviewed papers and research studies"
      },
      "typeVersion": 1
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    {
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      "name": "구성 가이드",
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        "content": "# Step 2: Research Configuration Processor 🔧\n\nThis node processes and validates the incoming research request, setting up the research parameters.\n\n## What it does\n- Validates and sanitizes input parameters\n- Sets default values for missing parameters\n- Generates multiple search queries based on topic\n- Creates unique session ID for tracking\n- Configures research depth and scope\n\n## Query Generation Strategy\n- **Base Queries**: Core topic searches\n- **Depth-Specific**: Additional queries for comprehensive research\n- **Time-Sensitive**: Recent developments and trends\n- **Multi-Angle**: Different perspectives and viewpoints\n\n## Customization Options\n- Modify query generation logic\n- Add industry-specific search patterns\n- Implement custom validation rules\n- Configure default research parameters"
      },
      "typeVersion": 1
    },
    {
      "id": "47a160d4-d829-4133-93fa-aa4dbd41f785",
      "name": "AI 스크래핑 가이드",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      "parameters": {
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        "content": "# Step 3: Multi-Source AI Scraping 🤖\n\nThree parallel AI-powered scrapers collect data from different source types for comprehensive research coverage.\n\n## AI Research Scraper\n- **Purpose**: General web research and industry insights\n- **Focus**: Key findings, statistics, expert opinions\n- **Output**: Structured insights with credibility scores\n\n## News Sources Scraper\n- **Purpose**: Recent news and current developments\n- **Focus**: Headlines, publication dates, credible sources\n- **Output**: Timestamped news articles with summaries\n\n## Academic Sources Scraper\n- **Purpose**: Peer-reviewed research and scholarly articles\n- **Focus**: Academic papers, citations, research studies\n- **Output**: Scientific literature with metadata\n\n## ScrapeGraphAI Benefits\n- **AI-Powered**: Intelligent content extraction\n- **Structured Output**: Consistent data format\n- **Source Validation**: Credibility assessment\n- **Multi-Language**: Global research capability"
      },
      "typeVersion": 1
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    {
      "id": "503cdf42-cee7-4b44-a2fd-4f4a4a134f60",
      "name": "처리 및 분석 가이드",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      "parameters": {
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        "content": "# Step 4: Data Processing & AI Analysis 🧠\n\nAdvanced data processing and AI-powered analysis to generate actionable insights from collected research data.\n\n## Research Data Processor\n- **Combines**: All source types into unified structure\n- **Validates**: Data quality and completeness\n- **Enriches**: Metadata and source attribution\n- **Structures**: For optimal analysis and storage\n\n## AI Research Analyst\n- **Model**: GPT-4 for sophisticated analysis\n- **Analysis Types**: Summary, trends, conflicts, reliability\n- **Output**: Executive summary with actionable insights\n- **Temperature**: Low (0.3) for consistent, factual analysis\n\n## Analysis Components\n1. **Executive Summary**: High-level overview\n2. **Key Insights**: Major findings and trends\n3. **Reliability Assessment**: Source credibility evaluation\n4. **Recommendations**: Actionable next steps\n5. **Further Research**: Suggested investigation areas"
      },
      "typeVersion": 1
    },
    {
      "id": "0105d893-94ce-465d-9ef8-8f144280f0c9",
      "name": "저장 및 응답 가이드",
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      "parameters": {
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        "width": 840,
        "height": 1716,
        "content": "# Step 5: Data Storage & Response 📊\n\nSecure storage of research findings and structured response delivery for seamless integration with other systems.\n\n## Google Sheets Storage\n- **Sheet Structure**: Research_Data with comprehensive columns\n- **Data Retention**: Historical research for trend analysis\n- **Access Control**: Secure OAuth2 authentication\n- **Format**: Structured data ready for analysis and reporting\n\n## Response Delivery\n- **Format**: JSON with status and metadata\n- **Content**: Session ID, completion status, source count\n- **Integration**: Ready for webhook consumers and APIs\n- **Tracking**: Unique session IDs for research correlation\n\n## Data Management Features\n- **Versioning**: Track research iterations\n- **Export**: Multiple format support\n- **Sharing**: Team collaboration capabilities\n- **Analytics**: Built-in Google Sheets analysis tools\n\n## Use Cases\n- **Market Research**: Competitive analysis and trends\n- **Academic Research**: Literature reviews and citations\n- **Business Intelligence**: Industry insights and reports"
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      "typeVersion": 1
    }
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