A side-by-side of two agent frameworks for building AI agents — live GitHub data, languages, and what each is best at.
Short answer: DSPy leads OpenAI Agents SDK vs DSPy by community traction (★ 37k vs ★ 29k). Pick OpenAI Agents SDK for minimal orchestration; pick DSPy for prompt optimization.
✓ Live data verified
| OpenAI Agents SDK | DSPy | |
|---|---|---|
| GitHub stars | ★ 29k | ★ 37k |
| Language | Python | Python |
| Category | Agent frameworks | Agent frameworks |
| Best for | minimal orchestration | prompt optimization |
| Repository | openai/openai-agents-python | stanfordnlp/dspy |
OpenAI Agents SDK and DSPy are both credible choices. By community traction, DSPy leads (★ 37k). Pick OpenAI Agents SDK for minimal orchestration; pick DSPy for prompt optimization.
Both are credible agent frameworks. By community traction DSPy leads (★ 37k). Pick OpenAI Agents SDK for minimal orchestration; pick DSPy for prompt optimization.
OpenAI Agents SDK is OpenAI's lightweight agent framework — a small set of primitives (Agents, Handoffs, Guardrails, Sessions); provider-agnostic via LiteLLM. Evolved from Swarm.. DSPy is Programming — not prompting — language models: compile declarative pipelines into optimized prompts/weights..
DSPy has more — ★ 37k vs ★ 29k (live counts).
Often yes — many teams combine agent frameworks. Check each tool's docs for interop; they solve overlapping but not identical problems.
OpenAI Agents SDK is primarily Python; DSPy is primarily Python.
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