Analyse des Kandidatenfragebogens

• •Google Sheets API-Anmeldedaten
• •OpenAI API Key

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        "content": "## 🔔 AUTOMATIC TRIGGER\n\n**Monitor New Questionnaire Responses**\n\n• **Purpose**: Automatically detects when candidates submit questionnaire forms\n• **Monitoring**: Polls Google Sheets every minute for new responses\n• **Source**: 'BD Questionarie' spreadsheet, 'Form Responses 1' sheet\n• **Trigger**: Activates immediately when new form submission is detected\n• **Reliability**: Continuous monitoring ensures no responses are missed\n• **Real-time Processing**: Enables immediate evaluation of candidate submissions"
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        "content": "## 🤖 AI EVALUATION ENGINE\n\n**AI Questionnaire Evaluator**\n\n• **Purpose**: Intelligently analyzes candidate responses to role-specific questions\n• **Evaluation Criteria**:\n  - Knowledge depth and accuracy\n  - Problem-solving ability\n  - Communication clarity and structure\n• **Scoring**: 0-30 points for questionnaire performance\n• **Questions Analyzed**:\n  - Business Development concepts\n  - SWOT analysis understanding\n• **Output**: JSON with score and detailed key takeaways"
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        "content": "## ⚙️ AI MODEL CONFIGURATION\n\n**Azure OpenAI GPT-4 Model**\n\n• **Model**: GPT-4o-mini for efficient evaluation\n• **Purpose**: Powers the questionnaire analysis engine\n• **Capabilities**: \n  - Natural language understanding\n  - Structured JSON output\n  - Business domain knowledge\n• **Connection**: Azure OpenAI service integration\n• **Performance**: Optimized for consistent evaluation quality"
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        "content": "## 🔧 DATA PROCESSING\n\n**Parse AI Evaluation Results**\n\n• **Purpose**: Converts AI text output into structured JSON format\n• **Process**: \n  - Removes markdown code fences (```json)\n  - Parses JSON structure safely\n  - Handles parsing errors gracefully\n• **Output**: Clean JSON object with questionnaire_score and key_takeaways\n• **Error Handling**: Returns error details if JSON parsing fails\n• **Data Quality**: Ensures consistent data structure for downstream processing"
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        "content": "## 📊 DATA RETRIEVAL\n\n**Lookup Candidate Profile Data**\n\n• **Purpose**: Retrieves existing candidate information from central database\n• **Source**: 'Resume store' spreadsheet, Sheet2\n• **Data Retrieved**: \n  - Current evaluation scores\n  - Candidate profile information\n  - Previous assessment results\n• **Matching**: Links questionnaire responses to existing candidate records\n• **Integration**: Enables combining multiple evaluation sources"
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        "content": "## 🧮 SCORE CALCULATION\n\n**Calculate Combined Scores**\n\n• **Purpose**: Combines questionnaire score with existing evaluation score\n• **Calculations**:\n  - **Final Score**: Existing Score + Questionnaire Score\n  - **Questionnaire Score**: Extracted from AI evaluation (0-30)\n• **Data Fields Created**:\n  - 'final score': Combined total score\n  - 'Questionarie Score': Individual questionnaire performance\n• **Scoring Logic**: Additive scoring model for comprehensive evaluation"
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        "content": "## 💾 DATABASE UPDATE\n\n**Update Candidate Database**\n\n• **Purpose**: Saves questionnaire results and updated scores to candidate database\n• **Update Method**: Append or update existing records using name matching\n• **Data Stored**:\n  - Questionnaire Score (0-30 points)\n  - Final Score (combined evaluation)\n  - Maintains all existing candidate data\n• **Matching Key**: Uses candidate name for record identification\n• **Database Integrity**: Preserves existing candidate information while adding new scores"
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        "content": "## 📝 CANDIDATE QUESTIONNAIRE ANALYSIS WORKFLOW\n\n**🎯 Purpose:** Automatically evaluates candidate questionnaire responses and integrates scores with existing evaluations for comprehensive assessment\n\n**🔄 Automated Process Flow:**\n1. **Real-time Monitoring**: Continuously watches for new questionnaire submissions\n2. **AI Analysis**: Evaluates responses using advanced language models\n3. **Score Processing**: Parses and validates evaluation results\n4. **Data Integration**: Combines questionnaire scores with existing candidate data\n5. **Score Calculation**: Creates comprehensive final scores\n6. **Database Update**: Maintains centralized candidate evaluation records\n\n**📊 Evaluation Framework:**\n• **Questionnaire Score**: 0-30 points based on:\n  - Knowledge depth and accuracy\n  - Problem-solving approach\n  - Communication clarity\n• **Final Score**: Combined evaluation (Resume + Questionnaire)\n\n**🏗️ System Integration:**\n• **Google Forms**: Questionnaire collection\n• **Google Sheets**: Data storage and monitoring\n• **Azure OpenAI**: Intelligent evaluation engine\n• **Automated Processing**: Real-time response handling\n\n**✨ Key Benefits:**\n• **Immediate Processing**: No delay between submission and evaluation\n• **Objective Analysis**: AI-powered consistent evaluation criteria\n• **Comprehensive Scoring**: Combines multiple assessment sources\n• **Scalable Solution**: Handles high volume of questionnaire responses\n• **Quality Insights**: Detailed takeaways for each candidate evaluation"
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        "content": "## ⚙️ CONFIGURATION & CUSTOMIZATION\n\n**🔧 Questionnaire Questions (Customizable):**\n• **Current Questions**:\n  - \"What is Business Development according to you?\"\n  - \"What is SWOT analysis?\"\n• **Question Types**: Role-specific knowledge assessment\n• **Scoring Range**: 0-30 points per questionnaire\n\n**📊 Scoring Configuration:**\n• **Questionnaire Weight**: 30 points maximum\n• **Combined Scoring**: Additive model (Resume + Questionnaire)\n• **Evaluation Criteria**:\n  - Knowledge depth (40%)\n  - Problem-solving ability (30%) \n  - Communication clarity (30%)\n\n**🔄 Monitoring Settings:**\n• **Poll Frequency**: Every minute\n• **Response Source**: Google Forms → Google Sheets\n• **Processing**: Real-time evaluation and scoring\n\n**📝 Maintenance Tasks:**\n• Update questions based on role requirements\n• Review AI evaluation criteria quarterly\n• Monitor response processing accuracy\n• Backup questionnaire data regularly"
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