Documentation IndexFetch the complete documentation index at: /llms.txtUse this file to discover all available pages before exploring further.
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
ToolCallMetrics
ToolExecution
from agno.agent import Agent from agno.models.openai import OpenAIChat from agno.tools.yfinance import YFinanceTools from rich.pretty import pprint agent = Agent( model=OpenAIChat(id="gpt-4o-mini"), tools=[YFinanceTools()], markdown=True, ) if __name__ == "__main__": run_output = agent.run("What is the stock price of AAPL and NVDA?") # Run-level metrics print("=" * 50) print("RUN METRICS") print("=" * 50) pprint(run_output.metrics) # Each tool call carries its own timing metrics print("=" * 50) print("TOOL CALL METRICS") print("=" * 50) if run_output.tools: for tool_call in run_output.tools: print(f"Tool: {tool_call.tool_name}") if tool_call.metrics: pprint(tool_call.metrics) print("-" * 40) # Per-model breakdown print("=" * 50) print("MODEL DETAILS") print("=" * 50) if run_output.metrics and run_output.metrics.details: for model_type, model_metrics_list in run_output.metrics.details.items(): print(f"\n{model_type}:") for model_metric in model_metrics_list: pprint(model_metric)
Create a Python file
tool_call_metrics.py
Set up your virtual environment
uv venv --python 3.12 source .venv/bin/activate
Install dependencies
uv pip install -U agno openai yfinance
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
Run Agent
python tool_call_metrics.py
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