enclava/backend/modules/chatbot/examples/customer_support_workflow.json

{
  "name": "Customer Support Workflow",
  "description": "Intelligent customer support workflow with intent classification, knowledge base search, and chatbot response generation",
  "version": "1.0",
  "variables": {
    "support_chatbot_id": "cs-bot-001",
    "escalation_threshold": 0.3,
    "max_attempts": 3
  },
  "steps": [
    {
      "id": "classify_intent",
      "name": "Classify Customer Intent",
      "type": "llm_call",
      "model": "gpt-3.5-turbo",
      "messages": [
        {
          "role": "system",
          "content": "You are an intent classifier for customer support. Classify the customer message into one of these categories: technical_issue, billing_question, feature_request, complaint, general_inquiry. Also provide a confidence score between 0 and 1. Respond with JSON: {\"intent\": \"category\", \"confidence\": 0.95, \"reasoning\": \"explanation\"}"
        },
        {
          "role": "user", 
          "content": "{{ inputs.customer_message }}"
        }
      ],
      "output_variable": "intent_classification"
    },
    
    {
      "id": "search_knowledge_base",
      "name": "Search Knowledge Base",
      "type": "workflow_step",
      "module": "rag",
      "action": "search",
      "config": {
        "query": "{{ inputs.customer_message }}",
        "collection": "support_documentation",
        "top_k": 5,
        "include_metadata": true
      },
      "output_variable": "knowledge_results"
    },
    
    {
      "id": "check_confidence",
      "name": "Check Intent Confidence",
      "type": "condition",
      "condition": "JSON.parse(steps.classify_intent.result).confidence > variables.escalation_threshold",
      "true_steps": [
        {
          "id": "generate_chatbot_response",
          "name": "Generate Chatbot Response",
          "type": "workflow_step",
          "module": "chatbot",
          "action": "workflow_chat_step", 
          "config": {
            "message": "{{ inputs.customer_message }}",
            "chatbot_id": "{{ variables.support_chatbot_id }}",
            "use_rag": true,
            "context": {
              "intent": "{{ steps.classify_intent.result }}",
              "knowledge_base_results": "{{ steps.search_knowledge_base.result }}",
              "customer_history": "{{ inputs.customer_history }}",
              "additional_instructions": "Be empathetic and professional. If you cannot fully resolve the issue, offer to escalate to a human agent."
            }
          },
          "output_variable": "chatbot_response"
        },
        
        {
          "id": "analyze_response_quality",
          "name": "Analyze Response Quality",
          "type": "llm_call",
          "model": "gpt-3.5-turbo",
          "messages": [
            {
              "role": "system",
              "content": "Analyze if this customer support response adequately addresses the customer's question. Consider completeness, accuracy, and helpfulness. Respond with JSON: {\"quality_score\": 0.85, \"is_adequate\": true, \"requires_escalation\": false, \"reasoning\": \"explanation\"}"
            },
            {
              "role": "user",
              "content": "Customer Question: {{ inputs.customer_message }}\\n\\nChatbot Response: {{ steps.generate_chatbot_response.result.response }}\\n\\nKnowledge Base Context: {{ steps.search_knowledge_base.result }}"
            }
          ],
          "output_variable": "response_quality"
        },
        
        {
          "id": "final_response_decision",
          "name": "Final Response Decision", 
          "type": "condition",
          "condition": "JSON.parse(steps.analyze_response_quality.result).is_adequate === true",
          "true_steps": [
            {
              "id": "send_chatbot_response",
              "name": "Send Chatbot Response",
              "type": "output",
              "config": {
                "response_type": "chatbot_response",
                "message": "{{ steps.generate_chatbot_response.result.response }}",
                "sources": "{{ steps.generate_chatbot_response.result.sources }}",
                "confidence": "{{ JSON.parse(steps.classify_intent.result).confidence }}",
                "quality_score": "{{ JSON.parse(steps.analyze_response_quality.result).quality_score }}"
              }
            }
          ],
          "false_steps": [
            {
              "id": "escalate_to_human",
              "name": "Escalate to Human Agent",
              "type": "output",
              "config": {
                "response_type": "human_escalation",
                "message": "I'd like to connect you with one of our human support agents who can better assist with your specific situation. Please hold on while I transfer you.",
                "escalation_reason": "Response quality below threshold",
                "intent": "{{ steps.classify_intent.result }}",
                "attempted_response": "{{ steps.generate_chatbot_response.result.response }}",
                "priority": "normal"
              }
            }
          ]
        }
      ],
      "false_steps": [
        {
          "id": "low_confidence_escalation",
          "name": "Low Confidence Escalation",
          "type": "output", 
          "config": {
            "response_type": "human_escalation",
            "message": "I want to make sure you get the best possible help. Let me connect you with one of our human support agents.",
            "escalation_reason": "Low intent classification confidence",
            "intent": "{{ steps.classify_intent.result }}",
            "priority": "high"
          }
        }
      ]
    },
    
    {
      "id": "log_interaction",
      "name": "Log Customer Interaction",
      "type": "workflow_step",
      "module": "analytics",
      "action": "log_event",
      "config": {
        "event_type": "customer_support_interaction",
        "data": {
          "customer_message": "{{ inputs.customer_message }}",
          "intent_classification": "{{ steps.classify_intent.result }}",
          "response_generated": "{{ steps.generate_chatbot_response.result.response }}",
          "knowledge_base_used": "{{ steps.search_knowledge_base.result }}",
          "escalated": "{{ outputs.response_type === 'human_escalation' }}",
          "workflow_execution_time": "{{ execution_time }}",
          "timestamp": "{{ current_timestamp }}"
        }
      }
    }
  ],
  
  "outputs": {
    "response_type": "string",
    "message": "string", 
    "sources": "array",
    "escalation_reason": "string",
    "confidence": "number",
    "quality_score": "number"
  },
  
  "error_handling": {
    "retry_failed_steps": true,
    "max_retries": 2,
    "fallback_response": "I apologize, but I'm experiencing technical difficulties. Please contact our support team directly for assistance."
  },
  
  "metadata": {
    "created_by": "support_team",
    "use_case": "customer_support_automation",
    "tags": ["customer_support", "chatbot", "rag", "escalation"],
    "estimated_execution_time": "5-15 seconds"
  }
}