dspy-advanced-module-composition

A collection of AI-powered skills for programming and optimizing LLM applications using the DSPy framework, including optimizers, RAG pipelines, evaluation suites, and fine-tuning tools targeting DSPy 3.1.2.

A collection of skills for programming and optimizing LLM applications using the DSPy framework (v3.1.2), covering optimizers, evaluation suites, and modular pipeline architectures for systematic LLM development.

A collection of AI-powered skills for building and optimizing LLM applications using the DSPy framework (v3.1.2). Covers optimizers, RAG pipelines, signature design, evaluation suites, and ReAct agent building for systematic, programmatic LLM development.

A comprehensive skill collection for programming and optimizing LLM applications using the DSPy framework, including optimizers, RAG pipelines, agent development, output validation, and advanced module composition patterns. Targets DSPy 3.1.2.

Part of the DSPy Skills Collection for programming and optimizing LLM applications with the DSPy framework. This skill focuses on designing type-safe input/output specifications for clean, validated outputs in DSPy programs.

Part of a comprehensive DSPy skills collection for programming and optimizing LLM applications, covering optimizers, RAG pipelines, evaluation suites, and debugging workflows targeting DSPy 3.1.2.

A comprehensive skills collection for programming and optimizing LLM applications using the DSPy framework (v3.1.2), covering optimizers, RAG pipelines, agent development, output validation, and custom module design for systematic, programmatic LLM development.

Skill

Skill

Skill