Documentation Index
Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
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.
Google Colab
colab.research.google.com
Install
pip install openinference-instrumentation-smolagents smolagents
Setup
Add your HF_TOKEN as an environment variable:
os.environ["HF_TOKEN"] = "<your_hf_token_value>"
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=[WebSearchTool(), VisitWebpageTool()],
model=model,
name="managed_agent",
description="This is an agent that can do web search.",
)
managed_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
