Keywords AI
Compare Dify and OpenAI Agents SDK side by side. Both are tools in the Agent Frameworks category.
| Category | Agent Frameworks | Agent Frameworks |
| Pricing | Open Source | — |
| Best For | Technical teams who want a visual builder for AI applications with the option to self-host | — |
| Website | dify.ai | github.com |
| Key Features |
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| Use Cases |
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Key criteria to evaluate when comparing Agent Frameworks solutions:
Dify is an open-source platform for building LLM applications with both visual and code-based interfaces. It provides a workflow orchestration engine, RAG pipeline builder, agent framework, and model management—all accessible through a web UI. Dify supports 50+ LLM providers, offers enterprise features like SSO and access control, and can be self-hosted or used as a cloud service.
The OpenAI Agents SDK is a lightweight Python framework for building multi-agent workflows with built-in tracing and guardrails. It provides primitives for defining agents with instructions and tools, orchestrating handoffs between agents, and implementing input/output guardrails for safety.
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.