LangGraph vs. Hugging Face smolagents
A side-by-side comparison based on G2 review data.
| Metric | LangGraph | Hugging Face smolagents |
|---|---|---|
| Overall rating | 4.5 | 4.4 |
| Review count | 37 | 47 |
| Ease of use | 8.7 | 9.1 |
| Ease of setup | 9.0 | 8.8 |
| Quality of support | 8.6 | 8.5 |
| Meets requirements | 9.0 | 8.8 |
| NPS | 62.857143 | 57.446809 |
| Small Business | 51.4% | 59.6% |
| Mid-Market | 21.6% | 27.7% |
| Enterprise | 27.0% | 12.8% |
| Total page views | 285 | 430 |
| Total LLM citations | 128 | 98 |
LangGraph
LangGraph is a low-level orchestration framework and runtime designed for building, managing, and deploying long-running, stateful agents. It provides developers with the tools to create agents capable of handling complex tasks reliably. LangGraph focuses on agent orchestration, offering capabilities such as durable execution, streaming, and human-in-the-loop interactions. It integrates seamlessly with LangChain components but can also function independently, allowing for flexible and customizable agent development.
Hugging Face smolagents
Smolagents is an open-source Python library developed by Hugging Face, designed to simplify the creation and execution of AI agents with minimal code. With a core logic comprising approximately 1,000 lines, smolagents emphasizes simplicity and efficiency, enabling developers to build powerful agents swiftly. The library is model-agnostic, allowing integration with various large language models (LLMs), including those from Hugging Face, OpenAI, Anthropic, and others via LiteLLM integration.