Agent Extra Metrics

"""Show special token metrics like audio, cached and reasoning tokens"""

import requests
from agno.agent import Agent
from agno.media import Audio
from agno.models.openai import OpenAIChat
from agno.utils.pprint import pprint_run_response

# Fetch the audio file and convert it to a base64 encoded string
url = "https://openaiassets.blob.core.windows.net/$web/API/docs/audio/alloy.wav"
response = requests.get(url)
response.raise_for_status()
wav_data = response.content

agent = Agent(
    model=OpenAIChat(
        id="gpt-5-mini-audio-preview",
        modalities=["text", "audio"],
        audio={"voice": "sage", "format": "wav"},
    ),
    markdown=True,
)
run_response = agent.run(
    "What's in these recording?",
    audio=[Audio(content=wav_data, format="wav")],
)
pprint_run_response(run_response)
# Showing input audio, output audio and total audio tokens metrics
print(f"Input audio tokens: {run_response.metrics.audio_input_tokens}")
print(f"Output audio tokens: {run_response.metrics.audio_output_tokens}")
print(f"Audio tokens: {run_response.metrics.audio_total_tokens}")

agent = Agent(
    model=OpenAIChat(id="gpt-5-mini"),
    markdown=True,
    telemetry=False,
)
run_response = agent.run(
    "Solve the trolley problem. Evaluate multiple ethical frameworks. Include an ASCII diagram of your solution.",
    stream=False,
)
pprint_run_response(run_response)
# Showing reasoning tokens metrics
print(f"Reasoning tokens: {run_response.metrics.reasoning_tokens}")

agent = Agent(model=OpenAIChat(id="gpt-5-mini"), markdown=True, telemetry=False)
agent.run("Share a 2 sentence horror story" * 150)
run_response = agent.run("Share a 2 sentence horror story" * 150)
# Showing cached tokens metrics
print(f"Cached tokens: {run_response.metrics.cache_read_tokens}")