Classer les messages Intercom en utilisant GPT-4o-mini et les router vers ClickUp ou Slack

• •Token Bot Slack ou URL Webhook
• •Point de terminaison HTTP Webhook (généré automatiquement par n8n)
• •Clé API OpenAI

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      "name": "📨 Réception Intercom Webhook",
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        "text": "You are an AI assistant designed to analyze customer conversations from Intercom. Your task is to classify each conversation into structured fields for workflow automation.\n\nConversation: {{ $json[\"data\"][\"item\"] }}\n\nBased on the provided conversation JSON, respond ONLY with a valid JSON object in the following format:\n\n{\n  \"category\": \"<Support | Product | Sales | Other>\",\n  \"sentiment\": \"<Positive | Neutral | Negative>\",\n  \"urgency\": \"<High | Medium | Low>\",\n  \"reasoning\": \"<Brief explanation of how you classified it>\",\n  \"tags\": [\"tag1\", \"tag2\"]\n}\n\nGuidelines:\n- \"category\": Determine the main topic. Use:\n  - \"Support\" for help requests, bugs, technical issues, etc.\n  - \"Product\" for feature requests, feedback, or UX issues.\n  - \"Sales\" for pricing, demo, onboarding, or enterprise inquiries.\n  - \"Other\" if it doesn't fit above.\n- \"sentiment\": Analyze customer tone. Choose Positive, Neutral, or Negative.\n- \"urgency\": \n  - High = frustrated users, urgent bug, blocked access.\n  - Medium = requesting help soon, moderately concerned.\n  - Low = casual inquiry, general feedback.\n- \"reasoning\": Explain how you decided on the classification.\n- \"tags\": Suggest 2–4 keywords as tags based on context (e.g., \"billing\", \"login\", \"onboarding\").\n\nOnly output valid JSON. Do NOT include explanations or extra text outside the JSON.",
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    },
    {
      "id": "6ba00f81-e6af-45b5-86ba-875fec8e30b1",
      "name": "📣 Slack – Notifier l'équipe commerciale",
      "type": "n8n-nodes-base.slack",
      "position": [
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      ],
      "webhookId": "your-slack-webhook-id",
      "parameters": {
        "text": "🚨 New Sales Inquiry Alert!\n\n**Customer:** {{ $json.customer_name }} ({{ $json.customer_email }})\n**Subject:** {{ $json.subject }}\n**Sentiment:** {{ $json.sentiment }}\n**Urgency:** {{ $json.urgency }}\n\n**Message:**\n{{ $json.message }}\n\n**AI Reasoning:** {{ $json.reasoning }}\n\n**Conversation ID:** {{ $json.conversation_id }}",
        "select": "channel",
        "channelId": {
          "__rl": true,
          "mode": "id",
          "value": "YOUR_SLACK_CHANNEL_ID"
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        "otherOptions": {}
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      "credentials": {
        "slackApi": {
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          "name": "Slack API"
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        "content": "## 📨 1. Webhook Intake\n\nPurpose:\n\n*Receives incoming conversation data from Intercom via a webhook (triggered on new messages).\n\nInput:\n\nFull conversation JSON\nCustomer name, email, and message content*"
      },
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        "content": "## 🤖 2. AI Classification Engine\n\nHow it works:\n\n*The conversation is sent to an AI model with a prompt to classify it.\n\nAI responds with a structured JSON containing:\ncategory: Support | Product | Sales | Other\nsentiment: Positive | Neutral | Negative\nurgency: High | Medium | Low\nreasoning: Explanation for classification\ntags: Relevant keywords\n\nA code node parses this AI output and merges it with user + conversation details to prepare for task creation or routing.*"
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      "parameters": {
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        "content": "## 🔀 3. Conditional Routing\n\nLogic:\n\n*Each path checks the category returned by the AI.\n\nBased on category, it routes the conversation to the appropriate action.*"
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      "typeVersion": 1
    },
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      "parameters": {
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        "content": "## 📌 4. Action Handling 🧾 \n\n**🧾Support:**\n\nCreates a ClickUp task with title, description, priority, and tags.\n\n**📦 Product:**\nSame as Support – task created in ClickUp with relevant details.\n\n**📣 Sales:**\nSends a Slack message to the Sales team with AI's reasoning."
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