[MW] Assistant AI de support client - Version Cloud

• •Compte Google et informations d'identification Gmail API
• •Informations d'identification Google Drive API
• •Peut nécessiter les informations d'identification d'authentification de l'API cible
• •Informations d'identification Google Sheets API
• •Clé API OpenAI

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  "name": "[MW] AI Customer Support Assistant - Cloud Version",
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        "content": "# 🌐 AI Customer Support Assistant - Cloud Version\n\n## What this workflow does:\nThis AI-powered customer support automation processes incoming support requests via email or chat, analyzes them using AI, retrieves relevant context, and generates draft responses for support agents.\n\n## Key Features:\n✅ **Multi-channel Input**: Email & chat triggers\n✅ **AI-powered Analysis**: Extracts sentiment, urgency, and key information\n✅ **Context Integration**: Combines product manuals, ERP data, and support history\n✅ **Draft Response Generation**: Creates professional responses in German\n✅ **Human-in-the-loop**: Approval workflow before sending to customers\n\n## Demo Instructions:\n1. Use the Chat interface to test with sample customer queries\n2. Or send test emails to trigger the email workflow\n3. Watch how AI analyzes and generates contextual responses\n\n**🌐 This is the CLOUD version using OpenAI and Google services**"
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        "content": "## 📧 Email Trigger\n\n**Purpose**: Monitors Gmail for incoming customer support requests\n\n**How it works**:\n• Polls Gmail every minute for new emails\n• Filters can be configured for specific labels/criteria\n• Extracts email content, sender info, and metadata\n\n**Demo tip**: Send a test email to see this in action!"
      },
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      "name": "📧 Email de Support Reçu",
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        "content": "## 💬 Chat Trigger\n\n**Purpose**: Provides a real-time chat interface for testing\n\n**How it works**:\n• Creates a webhook URL for chat interactions\n• Ideal for demos and testing scenarios\n• Processes messages instantly\n\n**Demo tip**: Perfect for live demonstrations!"
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        "content": "## 🧠 AI Information Extractor\n\n**Purpose**: Analyzes customer messages with AI to extract structured data\n\n**Extracts**:\n• Category (technical, billing, sales, etc.)\n• Urgency level (low, medium, high, critical)\n• Customer sentiment\n• Keywords for context search\n• Product identifiers\n• Required action type\n\n**AI Model**: OpenAI GPT-4o-mini"
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      "name": "🤖 Modèle OpenAI (Extracteur)",
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        "content": "## 📊 Historical Support Data\n\n**Purpose**: Retrieves previous support cases for context\n\n**Data Source**: Google Sheets with historical customer interactions\n\n**Contains**:\n• Previous questions & answers\n• Common issues & solutions\n• Response templates\n• Product-specific guidance\n\n**Why important**: Ensures consistent, high-quality responses"
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        "content": "## 📚 Product Knowledge Base\n\n**Purpose**: Accesses comprehensive product documentation\n\n**Data Source**: Google Drive (Primotech Manual PDF)\n\n**Contains**:\n• Technical specifications\n• Operating instructions\n• Troubleshooting guides\n• Safety information\n\n**Processing**: PDF text extraction for AI analysis\n\n**Cloud advantage**: Always up-to-date documentation"
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      "name": "📄 Extraire le Contenu PDF",
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    {
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      "name": "🏢 Intégration ERP",
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        "content": "## 🏢 ERP System Integration\n\n**Purpose**: Retrieves customer & inventory data\n\n**Data Source**: Mock ERP API (demo purposes)\n\n**Provides**:\n• Customer account information\n• Order history\n• Product availability\n• Spare part pricing\n\n**Note**: In production, this would connect to your real ERP system\n\n**Cloud benefit**: Real-time data access"
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    {
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      "name": "🤖 Génération de Réponse IA",
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        "content": "## 🤖 Response Generation\n\n**Purpose**: Creates professional customer responses using AI\n\n**AI Model**: OpenAI GPT-4o-mini\n\n**Input Context**:\n• Customer's original message\n• Extracted information (sentiment, urgency, etc.)\n• Product manual content\n• Historical support cases\n• ERP data (pricing, availability)\n\n**Output**: Professional German response following company standards"
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      "name": "🤖 Générer une Réponse Client",
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        "text": "=This GPT acts as an expert customer support agent designed to draft thoughtful, accurate responses to customer queries. It takes in customer questions and leverages internal product documentation and a history of previously answered queries to prewrite complete and contextually appropriate replies. The GPT uses the full content of \n\n1. the uploaded Primotech Instruction Manual (in German): \n\n2. a CSV dataset of historical customer questions: {{ $('📋 Aggregate Support Data').item.json.data.toJsonString() }}\n\n3. Customer's original query: {{ \n$('Chat Message Received').isExecuted && $('Chat Message Received').last().json.chatInput;\n$('📧 Support Email Received') && $('📧 Support Email Received').item.json.snippet \n$('When clicking ‘Execute workflow’').isExecuted && $('When clicking ‘Execute workflow’').item.json.snippet\n}} \n\nand answers related to ZEISS Primotech microscopes. These sources provide comprehensive technical, usage, troubleshooting, and product-specific guidance.\n\nThe assistant aims to reduce agent workload by anticipating common follow-up questions, referencing appropriate product knowledge, and maintaining a polite, clear, and supportive tone. It is optimized for high response accuracy, minimal ambiguity, and internal efficiency.\n\nThe assistant never performs web searches. When the available context is insufficient to fully answer a query, it does not generate a customer email. Instead, it presents a warning for the human agent and offers any possibly relevant internal context that may assist in formulating a manual response.\n\nIt avoids answering questions that cannot be supported by available documentation and flags those for manual review. When generating responses, it uses complete, customer-facing sentences, structured for easy review and editing by human support agents, and may include links or references when based on internal content. Clarification is only requested when strictly necessary. If required data is missing, the assistant highlights placeholders for agent completion.\n\nAll responses that are complete must follow this structure:\n- Use a proper salutation starting with 'Sehr geehrter Herr' or 'Sehr geehrte Frau' followed by the customer's last name, if available. If no name is provided, use 'Sehr geehrte/r Kunde/in,'.\n- Begin with 'herzlichen Dank für Ihre Nachricht.'\n- Then insert the drafted response body.\n- If the request involves a spare part, the assistant uses the following API response and includes the relevant spare part name and price from the returned JSON: {{ $json.inventory.toJsonString() }}\n- Close with: 'Bei weiteren Fragen stehen wir Ihnen gerne zur Verfügung, gerne können sie auch unsere (HILFE Seite)[http://www.zeiss.de] besuchen.' and 'Ich wünsche Ihnen einen schönen Tag!'\n\nThe assistant uses professional and accessible language, aligned with the tone expected in technical product support, and maintains a helpful and competent demeanor throughout.",
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      "name": "🤖 Modèle OpenAI (Générateur)",
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        "content": "## 👥 Human-in-the-Loop Approval\n\n**Purpose**: Ensures quality control before sending responses\n\n**Process**:\n1. AI-generated response is sent to support agent\n2. Agent reviews and can approve/reject/modify\n3. Only approved responses are sent to customers\n\n**Benefits**:\n• Quality assurance\n• Learning from modifications\n• Regulatory compliance\n\n**Note**: Critical for maintaining customer trust"
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        "content": "## How to run a demo\n- add google / openai credentials\n- change email of approver to something you can access"
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