smolagents
smolagents-06680ae0·6 events·first seen 28d agoAliases: smolagents
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Introducing smolagents: simple agents that write actions in code
Hugging Face has released smolagents, a lightweight agent framework where agents express actions as executable Python code rather than structured JSON tool calls. The library is designed for simplicity and composability, allowing agents to chain tool calls and manipulate outputs programmatically within a single code block. The release positions smolagents as a minimal alternative to heavier orchestration frameworks, with native integration into the Hugging Face ecosystem.
smolagents Now Supports Vision-Language Models
Hugging Face has added vision-language model (VLM) support to its smolagents framework, enabling agents to process and reason over visual inputs alongside text. This update extends the agentic tooling ecosystem to multimodal workflows. The announcement comes from the Hugging Face blog, which serves as the primary communication channel for the smolagents project.
Trace & Evaluate your Agent with Arize Phoenix
This Hugging Face blog post describes integrating Arize Phoenix with the smolagents framework to enable tracing and evaluation of AI agents. The post covers how to instrument agent runs, capture traces, and assess agent behavior using Phoenix's observability tooling. It targets developers building and debugging agentic pipelines who need visibility into multi-step reasoning and tool use.
DeepMath: A Lightweight Math Reasoning Agent with smolagents
Hugging Face published a blog post introducing DeepMath, a lightweight mathematical reasoning agent built on the smolagents framework. The post demonstrates how to construct a capable math reasoning agent using small models and tool-use patterns. This represents a practical application of the agent-tool ecosystem for specialized reasoning tasks.
Open-source DeepResearch – Freeing our search agents
Hugging Face published a blog post introducing Open Deep Research, an open-source replication of agentic deep research capabilities (similar to OpenAI's Deep Research). The project aims to build open-weight search agents capable of multi-step web research and synthesis. The post details the architecture, tooling, and early benchmark results of the system.
CodeAgents + Structure: A Better Way to Execute Actions
Hugging Face published a blog post exploring the combination of code-based agents with structured outputs to improve action execution reliability. The post examines how enforcing structured generation can reduce errors and improve the robustness of agentic code execution pipelines. This represents a practical engineering approach to making code agents more dependable in production settings.