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Agno vs DSPy

Side-by-side comparison with live GitHub signals. Last updated May 26, 2026.

A

Agno

Build, run, and manage agentic software at scale with 38K+ stars

OSSFree
40.4Ktoday436
D

DSPy

Framework for programming — not prompting — LLMs — 33K+ stars

OSSFree
34.7Ktoday394
MetricAgnoDSPy
GitHub Stars40.4K34.7K
Contributors436394
Last CommitMay 26, 2026May 26, 2026
Open Issues932514
Licenseopen-sourceopen-source
Pricingopen-sourceopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Shared Tags

pythonragopen-source

Only in Agno

agent-frameworkfastapimulti-agentorchestrationtool-usememoryself-hosted

Only in DSPy

prompt-optimizationprogrammingresearchstanford

About Agno

Agno is a full-stack platform for agentic software comprising three layers: a Python framework for building agents and teams with memory, knowledge, and 100+ tool integrations; a production-ready FastAPI runtime with 50+ APIs, horizontal scaling, native tracing, and human-in-the-loop approval workflows; and AgentOS, a control plane UI for monitoring and managing deployed agents. Supports per-user and per-session isolation, role-based access control, guardrails, evaluations, and immutable audit trails. All data stays in your database — no vendor lock-in.

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About DSPy

DSPy replaces prompt engineering with programming. Instead of writing prompts, you define modules with input/output signatures and DSPy automatically optimizes the prompts and weights for your pipeline. Supports chain-of-thought, retrieval-augmented generation, and multi-hop reasoning patterns. From Stanford NLP.

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