LiteLLM Metrics

Inspect per-message and run-level token metrics from a LiteLLM agent using YFinance tools.

metrics.py
"""
Litellm Metrics
===============

Cookbook example for `litellm/metrics.py`.
"""

from agno.agent import Agent, RunOutput
from agno.models.litellm import LiteLLM
from agno.tools.yfinance import YFinanceTools
from agno.utils.pprint import pprint_run_response
from rich.pretty import pprint

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

agent = Agent(
    model=LiteLLM(
        id="gpt-5.6-luna",
    ),
    tools=[YFinanceTools()],
    markdown=True,
)

run_output: RunOutput = agent.run("What is the stock price of NVDA")
pprint_run_response(run_output, markdown=True)

# Print metrics per message
if run_output.messages:
    for message in run_output.messages:
        if message.role == "assistant":
            if message.content:
                print(f"Message: {message.content}")
            elif message.tool_calls:
                print(f"Tool calls: {message.tool_calls}")
            print("---" * 5, "Metrics", "---" * 5)
            pprint(message.metrics)
            print("---" * 20)

# Print the metrics
print("---" * 5, "Collected Metrics", "---" * 5)
pprint(run_output.metrics)  # type: ignore

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Install dependencies

uv pip install -U agno litellm yfinance

Set your OpenAI credentials

Use an OpenAI API key with access to the requested model. The LiteLLM SDK calls the provider directly. An existing LITELLM_API_KEY overrides provider-specific credentials, so clear it for this example.

unset LITELLM_API_KEY
export OPENAI_API_KEY="your_provider_api_key_here"

Set compatible sampling options

Add temperature=None, top_p=None to every LiteLLM(...) using id="gpt-5.6-luna" or id="openai/gpt-5.6-luna" in your saved file. The adapter defaults to temperature=0.7 and top_p=1.0; the LiteLLM SDK rejects those sampling settings for this model's default reasoning mode before sending a request.

Run the example

Save the code above as metrics.py, then run:

python metrics.py

Full source: cookbook/90_models/litellm/metrics.py