Build complex AI systems with declarative language model programming.
npx skills add https://github.com/danmartinez78/echo-ghost-backup --skill dspy-danmartinez78
Please help me install this Agent Skill. Skill: dspy Source: https://github.com/danmartinez78/echo-ghost-backup/tree/main/skills/mlops/research/dspy Command: npx skills add https://github.com/danmartinez78/echo-ghost-backup --skill dspy-danmartinez78
Builds complex AI systems by composing modular, declarative language-model programs that self-improve over time.
Create a simple QA pipeline by declaring a signature and a module, then run a test question.
High-intent search queries and answers about installing and using this skill.
Declarative language model programming builds complex AI systems by composing modular pipelines using signatures, modules, and optimizers that enforce structured outputs and self-improve over time.
You can build a modular RAG system by declaring signatures and modules to construct end-to-end retrieval-augmented workflows, ensuring type safety and structured outputs across multiple LM providers.
Yes, declarative LM programming supports agent-driven tasks and multi-step reasoning pipelines, allowing you to compose modular workflows that apply optimizers across various language model providers.
Yes, declarative LM programming works with multiple LM providers, allowing you to build and optimize scalable AI pipelines while maintaining modular architecture and structured outputs.
The best way to optimize multi-stage AI pipelines is using declarative optimizers that automatically improve modular language model programs, ensuring robust and maintainable AI tooling through self-improving workflows.
NITISH-gitbitProgram language models declaratively and optimize prompts automatically with dspy.
jayteealaoDefine type-safe contracts and modular pipelines for LLM applications.
zhangzhang-111-iDesigns RAG pipelines with chunking, embedding, retrieval, and evaluation strategies.
SignmanalDefine type-safe LM task signatures and automatically optimize prompts with teleprompters.
