Agent Extra Metrics

1import requests
2from kern.agent import Agent
3from kern.media import Audio
4from kern.models.openai import OpenAIChat, OpenAIResponses
5from kern.utils.pprint import pprint_run_response
6
7# Fetch the audio file and convert it to a base64 encoded string
8url = "https://openaiassets.blob.core.windows.net/$web/API/docs/audio/alloy.wav"
9response = requests.get(url)
10response.raise_for_status()
11wav_data = response.content
12
13agent = Agent(
14    model=OpenAIChat(
15        id="gpt-4o-audio-preview",
16        modalities=["text", "audio"],
17        audio={"voice": "sage", "format": "wav"},
18    ),
19    markdown=True,
20)
21run_response = agent.run(
22    "What's in this recording?",
23    audio=[Audio(content=wav_data, format="wav")],
24)
25pprint_run_response(run_response)
26# Showing input audio and output audio tokens metrics
27print(f"Input audio tokens: {run_response.metrics.audio_input_tokens}")
28print(f"Output audio tokens: {run_response.metrics.audio_output_tokens}")
29
30agent = Agent(
31    model=OpenAIResponses(id="gpt-5.2"),
32    markdown=True,
33    telemetry=False,
34)
35run_response = agent.run(
36    "Solve the trolley problem. Evaluate multiple ethical frameworks. Include an ASCII diagram of your solution.",
37    stream=False,
38)
39pprint_run_response(run_response)
40# Showing reasoning tokens metrics
41print(f"Reasoning tokens: {run_response.metrics.reasoning_tokens}")
42
43agent = Agent(model=OpenAIResponses(id="gpt-5.2"), markdown=True, telemetry=False)
44agent.run("Share a 2 sentence horror story" * 150)
45run_response = agent.run("Share a 2 sentence horror story" * 150)
46# Showing cached tokens metrics
47print(f"Cached tokens: {run_response.metrics.cache_read_tokens}")