mkdir -p ~/.praison/templates/customer-support-reply-drafter
cd ~/.praison/templates/customer-support-reply-drafter

name: customer-support-reply-drafter
version: "1.0.0"
description: "Generate professional support reply drafts"
author: "PraisonAI"
license: "MIT"

tags:
  - support
  - customer-service
  - text-generation

requires:
  env:
    - OPENAI_API_KEY
  packages:
    - praisonaiagents

inputs:
  ticket_id:
    type: string
    description: "Support ticket identifier"
    required: true
  message:
    type: string
    description: "Customer message to respond to"
    required: true
  tone:
    type: string
    description: "Response tone"
    default: "professional"
    enum:
      - professional
      - friendly
      - formal

outputs:
  reply:
    type: string
    description: "Generated reply draft"
  confidence:
    type: number
    description: "Confidence score (0-1)"

cli:
  command: "praison recipes run customer-support-reply-drafter"
  examples:
    - 'praison recipes run customer-support-reply-drafter --input ''{"ticket_id": "T-123", "message": "I need help"}'''

safety:
  dry_run_default: false
  requires_consent: false
  overwrites_files: false
  network_access: true
  pii_handling: true

# recipe.py
from praisonaiagents import Agent, Task, PraisonAIAgents

def run(input_data: dict, config: dict = None) -> dict:
    """Generate a support reply draft."""
    ticket_id = input_data.get("ticket_id")
    message = input_data.get("message")
    tone = input_data.get("tone", "professional")
    
    if not ticket_id:
        return {"ok": False, "error": {"code": "MISSING_INPUT", "message": "ticket_id is required"}}
    
    if not message:
        return {"ok": False, "error": {"code": "MISSING_INPUT", "message": "message is required"}}
    
    try:
        tone_guidelines = {
            "professional": "Clear, courteous, and business-appropriate",
            "friendly": "Warm, approachable, and conversational",
            "formal": "Polished, respectful, and traditional"
        }
        
        # Create support agent
        support_agent = Agent(
            name="Support Specialist",
            role="Customer Support Expert",
            goal=f"Draft a {tone} reply to customer inquiries",
            instructions=f"""
            You are an expert customer support specialist.
            Tone: {tone} - {tone_guidelines[tone]}
            
            Guidelines:
            - Be helpful and empathetic
            - Address the customer's concern directly
            - Provide clear next steps if applicable
            - Keep responses concise but complete
            - Never make promises you can't keep
            - Acknowledge the customer's frustration if present
            """,
        )
        
        # Create quality checker
        quality_agent = Agent(
            name="Quality Reviewer",
            role="Support Quality Analyst",
            goal="Ensure reply quality and assign confidence",
            instructions="""
            You are a support quality analyst.
            - Check for completeness
            - Verify tone consistency
            - Ensure no inappropriate content
            - Assign confidence score (0-1)
            - Flag any concerns
            """,
        )
        
        # Define tasks
        draft_task = Task(
            name="draft_reply",
            description=f"""
            Draft a {tone} reply to this customer message:
            
            Ticket: {ticket_id}
            Message: {message}
            
            Provide a professional, helpful response.
            """,
            expected_output="A well-crafted support reply",
            agent=support_agent,
        )
        
        review_task = Task(
            name="review_reply",
            description="""
            Review the draft reply for quality.
            Assign a confidence score from 0 to 1 where:
            - 0.9-1.0: Excellent, ready to send
            - 0.7-0.9: Good, minor review recommended
            - 0.5-0.7: Acceptable, review before sending
            - Below 0.5: Needs revision
            
            Output format: CONFIDENCE: X.XX
            """,
            expected_output="Confidence score and any notes",
            agent=quality_agent,
            context=[draft_task],
        )
        
        # Execute
        agents = PraisonAIAgents(
            agents=[support_agent, quality_agent],
            tasks=[draft_task, review_task],
        )
        
        result = agents.start()
        
        # Parse confidence
        review_text = result.get("review_reply", "")
        confidence = parse_confidence(review_text)
        
        return {
            "ok": True,
            "reply": result.get("draft_reply", ""),
            "confidence": confidence,
            "artifacts": [],
            "warnings": [] if confidence >= 0.7 else ["Low confidence - review before sending"],
        }
        
    except Exception as e:
        return {"ok": False, "error": {"code": "PROCESSING_ERROR", "message": str(e)}}


def parse_confidence(text: str) -> float:
    """Extract confidence score from review text."""
    import re
    match = re.search(r'CONFIDENCE:\s*([\d.]+)', text, re.IGNORECASE)
    if match:
        try:
            return min(1.0, max(0.0, float(match.group(1))))
        except ValueError:
            pass
    
    # Default confidence based on text analysis
    if "excellent" in text.lower() or "ready" in text.lower():
        return 0.9
    elif "good" in text.lower():
        return 0.8
    elif "acceptable" in text.lower():
        return 0.6
    return 0.7

# test_recipe.py
import pytest
from recipe import run, parse_confidence

def test_missing_ticket_id():
    result = run({"message": "Help me"})
    assert result["ok"] is False
    assert result["error"]["code"] == "MISSING_INPUT"

def test_missing_message():
    result = run({"ticket_id": "T-123"})
    assert result["ok"] is False
    assert result["error"]["code"] == "MISSING_INPUT"

def test_parse_confidence():
    assert parse_confidence("CONFIDENCE: 0.85") == 0.85
    assert parse_confidence("The reply is excellent") == 0.9
    assert parse_confidence("This is good") == 0.8

def test_confidence_bounds():
    assert parse_confidence("CONFIDENCE: 1.5") == 1.0
    assert parse_confidence("CONFIDENCE: -0.5") == 0.0

@pytest.mark.integration
def test_end_to_end():
    result = run({
        "ticket_id": "T-123",
        "message": "I can't log into my account",
        "tone": "professional"
    })
    
    assert result["ok"] is True
    assert len(result["reply"]) > 50
    assert 0 <= result["confidence"] <= 1

@pytest.mark.integration
def test_different_tones():
    tones = ["professional", "friendly", "formal"]
    for tone in tones:
        result = run({
            "ticket_id": "T-124",
            "message": "How do I reset my password?",
            "tone": tone
        })
        assert result["ok"] is True