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Agency Swarm supports multiple observability approaches to help you track and analyze your agent’s behavior and performance.

Usage Payload

When usage tracking is enabled, responses include a usage object with token counts and cost.
{
  "response": "Test response",
  "new_messages": [],
  "usage": {
    "request_count": 1,
    "cached_tokens": 0,
    "input_tokens": 10,
    "output_tokens": 20,
    "total_tokens": 30,
    "total_cost": 0.0
  }
}
Fields:
  • request_count: Number of model requests
  • cached_tokens: Tokens served from cache (if available)
  • input_tokens: Tokens sent to the model
  • output_tokens: Tokens generated by the model
  • total_tokens: Total tokens for the request
  • total_cost: Estimated cost (USD)
  • reasoning_tokens (optional): Reasoning tokens (if available)
Where you’ll see it:
  • FastAPI Integration: POST /get_response returns JSON with usage, and the final event: messages in POST /get_response_stream includes usage.
  • Running an Agency: use /cost in the terminal demo to see session usage and cost.

Supported Observability Platforms

Agency Swarm supports three main observability approaches:

OpenAI Tracing

Built-in tracing using OpenAI’s native tools

Langfuse

Advanced tracing and debugging platform

AgentOps

Specialized agent monitoring and analytics

Getting Started

Let’s walk through setting up each tracing solution. You can use them individually or combine them for monitoring.
1

Basic Setup

OpenAI tracing is built into Agency Swarm and requires no additional packages.
2

Implementation

from agency_swarm import trace

async def openai_tracing(input_message: str) -> str:
    agency_instance = create_agency()
    with trace("OpenAI tracing"):
        response = await agency_instance.get_response(message=input_message)
    return response.final_output
3

View Traces

After running your code, view your traces at platform.openai.com/traces

Implementation Example

For a complete working example that demonstrates all three tracing methods with a multi-agent agency, see observability.py in the examples directory. The example shows:
  • How to set up a basic agency with CEO, Developer, and Data Analyst roles
  • Implementation of all three tracing methods (OpenAI, Langfuse, AgentOps)
  • A sample tool for data analysis
  • Error handling and proper tracing setup
You can run the example with:
python examples/observability_demo.py
For more information about each platform’s capabilities and configuration options, refer to their respective documentation: