Skip to main content
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.
https://ssl.gstatic.com/colaboratory-static/common/e2b7758e110827a5ed289fa36b2a079b/img/favicon.ico

Google Colab

colab.research.google.com

​
Launch Phoenix

  • Phoenix Cloud
  • Command Line
  • Docker
  • Notebook
Sign up for Phoenix:
  1. Sign up for an Arize Phoenix account at https://app.phoenix.arize.com/login
  2. 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
  1. Create your API key from the Settings page
  2. Copy your Hostname from the Settings page
  3. In 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')}"
Having trouble finding your endpoint? Check out Finding your Phoenix Endpoint

​
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