Description
smolagents is an open-source Python library designed to make it extremely easy to build and run agents using just a few lines of code. The library aims to advance and democratize artificial intelligence through open source and open science. With smolagents, developers can create intelligent applications without the complexity often associated with AI frameworks.
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One of the key capabilities of smolagents is its simplicity. The logic for agents fits in approximately a thousand lines of code, keeping abstractions to their minimal shape above raw code. This allows developers to focus on building their applications rather than getting bogged down in intricate details.
smolagents offers first-class support for Code Agents, which write their actions in code rather than using agents to write code. This enables natural composability, allowing for function nesting, loops, and conditionals. To ensure security, smolagents supports executing in a sandboxed environment via Modal, Blaxel, E2B, or Docker.
In addition to Code Agents, smolagents includes Common Tool-Calling Agent Support. This feature allows for usual JSON/text-based tool-calling for scenarios where that paradigm is preferred. The library also provides seamless integration with the Hub, allowing users to share and load agents and tools as Gradio Spaces.
Another significant advantage of smolagents is its model-agnostic approach. Developers can easily integrate any large language model (LLM), whether hosted on the Hub via Inference providers, accessed via APIs such as OpenAI or Anthropic, or run locally using Transformers or Ollama. This flexibility makes powering an agent with a preferred LLM straightforward.
Moreover, smolagents is modality-agnostic, meaning agents can handle vision, video, and audio inputs, broadening the range of possible applications. The library also supports tool-agnostic functionality, allowing users to utilize tools from any MCP server or even a Hub Space as a tool. Additionally, smolagents comes with command-line utilities (smolagent, webagent) for quickly running agents without writing boilerplate code.
Getting started with smolagents is quick and easy, with a guide available to help users create and run their first agent in just a few minutes. The library also provides practical guides and tutorials to assist users in achieving specific goals, such as generating and testing SQL queries.
- CategoryAI Agent Builders
- Pricing ModelOpen source
- DeploymentCloud
- PlatformsWeb
smolagents's Core Features
Simplicity: ~1000 lines of code
First-class support for Code Agents
Common Tool-Calling Agent Support
Hub integrations for sharing agents
Model-agnostic: integrate any LLM
Modality-agnostic: handle vision, video, audio
Tool-agnostic: use tools from any MCP server
CLI Tools for quick agent execution
Getting Started with smolagents
Install via pip: Install smolagents using pip package manager.
Create Your First Agent: Follow the minimal example to create and run an agent.
Add Tools: Enhance your agent's capabilities by adding tools.
Use Different Models: Integrate various models with your agent.
smolagents's Use Cases
- Building Intelligent Applications
- Integrating LLMs
- Handling Multiple Modalities
- Rapid Prototyping
- Creating Multi-Agent Systems
