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 DSPy vs OpenAI Agents SDK by community traction (★ 37k vs ★ 29k). Pick DSPy for prompt optimization; pick OpenAI Agents SDK for minimal orchestration.
✓ Live data verified
| DSPy | OpenAI Agents SDK | |
|---|---|---|
| GitHub stars | ★ 37k | ★ 29k |
| Language | Python | Python |
| Category | Agent frameworks | Agent frameworks |
| Best for | prompt optimization | minimal orchestration |
| Repository | stanfordnlp/dspy | openai/openai-agents-python |
DSPy and OpenAI Agents SDK are both credible choices. By community traction, DSPy leads (★ 37k). Pick DSPy for prompt optimization; pick OpenAI Agents SDK for minimal orchestration.
Both are credible agent frameworks. By community traction DSPy leads (★ 37k). Pick DSPy for prompt optimization; pick OpenAI Agents SDK for minimal orchestration.
DSPy is Programming — not prompting — language models: compile declarative pipelines into optimized prompts/weights.. 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 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.
DSPy is primarily Python; OpenAI Agents SDK is primarily Python.
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