SmolAgents
SmolAgents is a minimalist AI agent framework by Hugging Face that enables developers to create and run powerful AI agents with just a few lines of code, featuring code-first approach and seamless integration with various LLMs.
https://smolagents.org?ref=aipure
Product Information
Updated:Feb 16, 2025
SmolAgents Monthly Traffic Trends
SmolAgents received 6.1k visits last month, demonstrating a Significant Growth of Infinity%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history trafficWhat is SmolAgents
SmolAgents is a streamlined library developed by the Hugging Face team that simplifies the creation and deployment of AI agents. With its core functionality contained in approximately 1,000 lines of code, it maintains minimal abstractions while providing robust capabilities. The framework is designed to be LLM-agnostic, supporting models from the Hugging Face Hub, OpenAI, Anthropic, and others through LiteLLM integration. It represents a significant advancement in making agent development more accessible and efficient, particularly through its innovative code-first approach rather than traditional JSON-based actions.
Key Features of SmolAgents
SmolAgents is a minimalist AI agent framework developed by Hugging Face that enables developers to create and run powerful AI agents with minimal code. It features a compact codebase of around 1,000 lines, supports code agents that execute Python snippets directly, integrates seamlessly with various LLMs, and provides secure execution environments. The framework emphasizes simplicity and efficiency while allowing AI agents to interact effectively with real-world tasks through code execution rather than traditional JSON or text-based actions.
Code-First Approach: Agents write and execute Python code snippets directly instead of generating JSON/text actions, improving efficiency and reducing steps by about 30%
Universal LLM Integration: Seamlessly works with models from Hugging Face Hub, OpenAI, Anthropic, and others through LiteLLM integration
Secure Execution Environment: Supports sandboxed environments like E2B for safe code execution, ensuring system security
Hub Integration: Deep integration with Hugging Face Hub allows easy sharing and importing of tools, fostering community collaboration
Use Cases of SmolAgents
Travel Planning Assistant: Creates detailed itineraries by calculating travel times, suggesting locations, and optimizing schedules using real-time data and mapping tools
Text-to-SQL Generator: Converts natural language queries into SQL commands and tests them for database operations
Web Research Agent: Performs automated web searches and synthesizes information using tools like DuckDuckGo integration
Multi-Tool Task Automation: Orchestrates multiple tools and APIs to complete complex tasks like data analysis or content generation
Pros
Extremely simple implementation with minimal code required
Superior efficiency through code execution vs JSON actions
Flexible integration with various LLM providers
Cons
May not be ideal for complex multi-step or multi-agent scenarios
Limited to Python-based tools and actions
Experimental API subject to changes
How to Use SmolAgents
Install smolagents: Install the library using pip: 'pip install smolagents'
Import required components: Import necessary classes like CodeAgent, HfApiModel, and tools: 'from smolagents import CodeAgent, HfApiModel, tool'
Set up HuggingFace access: Get a HuggingFace access token if using HF models and authenticate with the Hub
Define tools: Create custom tools using the @tool decorator or import existing tools. Tools are functions that the agent can call to perform specific tasks
Initialize the model: Create an instance of HfApiModel with your chosen LLM, e.g.: model = HfApiModel(model_id='Qwen/Qwen2.5-Coder-32B-Instruct')
Create the agent: Initialize a CodeAgent with your tools and model: agent = CodeAgent(tools=[your_tools], model=model)
Run tasks: Execute tasks using the agent.run() method with your task description as input: agent.run('Your task description here')
Handle additional configurations: Optionally configure additional parameters like planning_interval, additional_authorized_imports, or add_base_tools based on your needs
Monitor execution: Use print statements or logging within tools to track execution progress and debug any issues
Share tools (optional): Share custom tools to Hugging Face Hub using the push_to_hub() method: your_tool.push_to_hub('username/tool-name')
SmolAgents FAQs
SmolAgents is a minimalist AI agent framework developed by Hugging Face that allows developers to create and run powerful agents with just a few lines of code. It features a compact codebase of about 1,000 lines and focuses on code agents that execute Python code snippets.
Analytics of SmolAgents Website
SmolAgents Traffic & Rankings
6.1K
Monthly Visits
#3394201
Global Rank
-
Category Rank
Traffic Trends: Nov 2024-Jan 2025
SmolAgents User Insights
00:00:57
Avg. Visit Duration
2.17
Pages Per Visit
25.17%
User Bounce Rate
Top Regions of SmolAgents
IN: 76.36%
TR: 8.97%
SG: 8.24%
US: 4.7%
BR: 1.04%
Others: 0.69%
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