stanfordnlp/dspy
DSPy: The framework for programming—not prompting—language models
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 18 days ago, with 411 contributors on GitHub.
Peaked at #48 in the weekly ranking the week of Jul 5, its best in the past year.
Use Cases & Benefits
- Provides a Python framework for programming language models through compositional code instead of prompt engineering.
- Enables fast iteration and optimization of modular AI systems by combining prompt and weight tuning for improved output quality.
- Use for building complex retrieval-augmented generation pipelines that integrate multiple language model components.
- Use for developing self-improving agent loops that refine their behavior through declarative programming.
- Use for creating customizable classifiers and AI workflows that benefit from automated prompt and parameter optimization.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
DSPy is the framework for programming—rather than prompting—language models. It allows you to iterate fast on building modular AI systems and offers algorithms for optimizing their prompts and weights, whether you're building simple classifiers, sophisticated RAG pipelines, or Agent loops.
DSPy stands for Declarative Self-improving Python. Instead of brittle prompts, you write compositional Python code and use DSPy to teach your LM to deliver high-quality outputs. Learn more via our official documentation site or meet the community, seek help, or start contributing via this GitHub repo and our Discord server.
Please go to the DSPy Docs at dspy.ai
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+2,342 stars over 90 days across 13 snapshot days; best day +160 on Aug 10.
Forks
3.5K+307
Open issues
739+111
Compared with peers in Backend
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
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| anthropics/skills | 188.8K | +2.9K | 15 | — |
| NationalSecurityAgency/ghidra | 98.4K | +2.2K | 64 | 15 days ago |
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| DuarteSantos8/openGym | 20.2K | +1.9K | 60 | 4 days ago |
| microsoft/VibeVoice | 56.7K | +1.4K | 28 | — |
| stanfordnlp/dspy | 38.9K | — | 59 | 18 days ago |
| Category median | 56.7K | +2.2K | 28 | — |
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