smolagents Tracing
How to use the SmolagentsInstrumentor to trace smolagents by Hugging Face
smolagents is a minimalist AI agent framework developed by Hugging Face, designed to simplify the creation and deployment of powerful agents with just a few lines of code. It focuses on simplicity and efficiency, making it easy for developers to leverage large language models (LLMs) for various applications.
Phoenix provides auto-instrumentation, allowing you to track and visualize every step and call made by your agent.
Launch Phoenix
We have several code samples below on different ways to integrate with smolagents, based on how you want to use Phoenix.
Sign up for Phoenix:
Sign up for an Arize Phoenix account at https://app.phoenix.arize.com/login
Click
Create Space
, then follow the prompts to create and launch your space.
Install packages:
pip install arize-phoenix-otel
Set your Phoenix endpoint and API Key:
From your new Phoenix Space
Create your API key from the Settings page
Copy your
Hostname
from the Settings pageIn your code, set your endpoint and API key:
import os
os.environ["PHOENIX_API_KEY"] = "ADD YOUR PHOENIX API KEY"
os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "ADD YOUR PHOENIX HOSTNAME"
# If you created your Phoenix Cloud instance before June 24th, 2025,
# you also need to set the API key as a header:
# os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={os.getenv('PHOENIX_API_KEY')}"
Install
pip install openinference-instrumentation-smolagents smolagents
Setup
Add your HF_TOKEN
as an environment variable:
os.environ["HF_TOKEN"] = "<your_hf_token_value>"
Connect to your Phoenix instance using the register function.
from phoenix.otel import register
# configure the Phoenix tracer
tracer_provider = register(
project_name="my-llm-app", # Default is 'default'
auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)
Create & Run an Agent
Create your Hugging Face Model, and at every run, traces will be sent to Phoenix.
from smolagents import (
CodeAgent,
InferenceClientModel,
ToolCallingAgent,
VisitWebpageTool,
WebSearchTool,
)
model = InferenceClientModel()
managed_agent = ToolCallingAgent(
tools=[DuckDuckGoSearchTool(), VisitWebpageTool()],
model=model,
name="managed_agent",
description="This is an agent that can do web search.",
)
manager_agent.run("Based on the latest news, what is happening in extraterrestrial life?")
Observe
Now that you have tracing setup, all invocations and steps of your Agent will be streamed to your running Phoenix for observability and evaluation.
Resources
Last updated
Was this helpful?