Keywords AI
Compare DSPy and Smolagents side by side. Both are tools in the Agent Frameworks category.
| Category | Agent Frameworks | Agent Frameworks |
| Website | dspy.ai | huggingface.co |
Key criteria to evaluate when comparing Agent Frameworks solutions:
DSPy is a framework from Stanford for programming—not prompting—foundation models. It replaces manual prompt engineering with composable, optimizable modules. DSPy compilers automatically tune prompts and weights for your specific pipeline and dataset, enabling more reliable LLM applications.
Smolagents is Hugging Face minimalist agent framework for building AI agents with code-based actions.
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
Browse all Agent Frameworks tools →An agent framework provides the building blocks for creating AI agents that can autonomously plan, use tools, and complete multi-step tasks. Instead of building tool use, memory, and orchestration from scratch, you get pre-built components that handle the common patterns.
For simple single-tool agents, raw API calls work fine. Frameworks become valuable when you need multi-step planning, tool orchestration, error recovery, memory, or multi-agent coordination. They save significant development time for complex agent architectures.
LangChain and LlamaIndex are the most mature with the largest ecosystems. CrewAI is best for multi-agent workflows. Vercel AI SDK is ideal for TypeScript/Next.js applications. Evaluate based on your language preference, use case complexity, and integration needs.