DSPy vs guidance

Side-by-side comparison of two AI agent tools

Short answer

  • DSPy is growing faster: +831 GitHub stars in the last 30 days vs +67 for guidance.
  • Pick DSPy for: dSPy: The framework for programming—not prompting—language models. Pick guidance for: a guidance language for controlling large language models.

From GitHub data refreshed daily.

DSPyopen-source

DSPy: The framework for programming—not prompting—language models

guidanceopen-source

A guidance language for controlling large language models.

Metrics

DSPyguidance
Stars38.5k21.8k
Star velocity /mo831.157894736842166.63157894736841
Commits (90d)1740
Releases (6m)70
Downloads (30d, npm + PyPI)5.2M11.8K
Overall score0.74506318549737390.253336309574155

Pros

  • +采用编程范式替代提示词工程，提供更稳定可靠的AI系统开发方式
  • +内置优化算法能够自动改进提示词和模型权重，实现系统自我优化
  • +支持模块化架构，可构建从简单分类器到复杂RAG管道的各种AI应用
  • +Pythonic interface that integrates naturally with existing Python workflows and familiar programming patterns
  • +Constrained generation capabilities that guarantee output syntax and structure using regex and context-free grammars
  • +Multi-backend support allowing seamless switching between different model providers and local/cloud deployments

Cons

  • -相比传统提示词方法有一定学习曲线，需要掌握框架特定的编程概念
  • -作为相对新的框架，生态系统和第三方集成可能不如成熟的AI开发工具丰富
  • -主要面向有编程经验的开发者，对非技术用户门槛较高
  • -Requires Python programming knowledge, limiting accessibility for non-technical users
  • -Learning curve for advanced constraint features like context-free grammars and complex regex patterns
  • -Dependent on backend availability and may require additional setup for specific model types

Use Cases

  • •构建企业级RAG（检索增强生成）系统，需要稳定可靠的文档问答能力
  • •开发复杂的AI Agent循环系统，处理多步骤推理和决策任务
  • •构建大规模分类和内容处理管道，需要高质量输出和可优化性能
  • •Structured data extraction from documents or conversations where output must conform to specific JSON schemas or formats
  • •Building conversational AI applications that require controlled dialogue flows and predictable response structures
  • •Cost-effective alternative to fine-tuning when you need specific output formatting without retraining models
View DSPy DetailsView guidance Details

FAQ

Which is more popular, DSPy or guidance?
DSPy has more GitHub stars (38,480 vs 21,786).
Which is more actively developed, DSPy or guidance?
DSPy had more commits in the last 90 days (174 vs 0).
Should I use DSPy or guidance?
Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.