Support Ticket Agent

A structured output agent demonstrating Pydantic schema-based responses for customer support ticket creation.

🎯 What This Demonstrates

• Structured Output: Using Pydantic models to define response schemas
• Enum Types: Priority levels with controlled values
• Optional Fields: Flexible schema with required and optional properties
• Field Validation: Input validation and description metadata

🚀 Quick Start

1. Install OpenAI Agents SDK:

   pip install openai-agents
   

2. Set up environment:

   cp ../env.example .env
   # Edit .env and add your OpenAI API key
   

3. Run the agent:

   from agents import Runner
   from agent import root_agent
   
   result = Runner.run_sync(root_agent, "I can't log into my account and it's urgent!")
   print(result.final_output)  # Returns SupportTicket object
   

💡 Key Concepts

• Pydantic Models: Defining structured response schemas
• Enum Validation: Priority levels (low, medium, high, critical)
• Field Descriptions: Helping the LLM understand field requirements
• Optional Fields: Handling optional vs required data

🧪 Example Usage

# The agent will return a SupportTicket object like:
{
    "title": "Account Login Issue",
    "description": "User unable to access account",
    "priority": "high",
    "category": "account_access",
    "steps_to_reproduce": ["Go to login page", "Enter credentials", "Error occurs"],
    "estimated_resolution_time": "2-4 hours"
}

🔗 Next Steps

• Product Review Agent - Complex structured output
• Email Generator Agent - Simple structured output
• Tutorial 3: Tool Using Agent - Adding tools to agents