Default Tracing

Demonstrates the built-in automatic tracing system that captures all agent workflow events without any setup required.

🎯 What This Demonstrates

• Automatic Tracing: Built-in workflow monitoring (enabled by default)
• Trace IDs: Unique identifiers for each agent run
• OpenAI Dashboard: Free trace visualization platform
• Tracing Configuration: Enabling and disabling trace capture

🚀 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:

   import asyncio
   from agent import main
   
   # Test default tracing (automatic)
   asyncio.run(main())
   

💡 Key Concepts

• Zero Setup Required: Tracing works automatically out of the box
• Unique Run IDs: Each Runner.run() gets a unique trace identifier
• Automatic Capture: LLM calls, tool executions, performance metrics
• Free Dashboard: View traces at platform.openai.com/traces

🧪 Automatic Capture

What Gets Traced Automatically

• LLM Generations: Input prompts, model responses, token usage
• Tool Calls: Function executions, parameters, results
• Handoffs: Agent-to-agent delegations
• Performance: Execution time, latency metrics
• Errors: Exceptions and failure modes

Trace Information

result = await Runner.run(agent, "Hello")
print(f"Trace ID: {result.run_id}")
# Each run gets a unique identifier for dashboard lookup

Separate Traces

• Each Runner.run() call = One trace
• Multiple runs = Multiple separate traces
• Independent workflow tracking

💻 Tracing Examples

Basic Automatic Tracing

# Tracing happens automatically - no setup required!
result = await Runner.run(agent, "Explain machine learning")
print(f"View trace: https://platform.openai.com/traces/{result.run_id}")

Tracing Configuration

# Disable tracing for specific runs
result = await Runner.run(
    agent,
    "Private conversation",
    run_config=RunConfig(tracing_disabled=True)
)

Multiple Traces

# Each run creates a separate trace
result1 = await Runner.run(agent, "Question 1")  # Trace 1
result2 = await Runner.run(agent, "Question 2")  # Trace 2

🔍 Dashboard Features

OpenAI Traces Dashboard

• Workflow Timeline: Visual execution flow
• Performance Metrics: Response times, token usage
• Error Tracking: Exception details and stack traces
• Content Inspection: Input/output content review

Free Access

• No additional setup required
• Accessible with OpenAI API key
• Real-time trace availability
• Historical trace retention

🔗 Next Steps

• Custom Tracing - Advanced tracing patterns
• Tutorial 11: Production Patterns - Real-world deployment