「declarative programming」の検索結果

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

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Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

日本語の概要は準備中です。原文の説明を表示しています。

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

日本語の概要は準備中です。原文の説明を表示しています。

Declarative programming framework for optimizing LLM prompts through compilation and automatic tuning

日本語の概要は準備中です。原文の説明を表示しています。

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

日本語の概要は準備中です。原文の説明を表示しています。

Reactive streams and event-driven programming in Golang using samber/ro — ReactiveX implementation with 150+ type-safe operators, cold/hot observables, 5 subject types (Publish, Behavior, Replay, Async, Unicast), declarative pipelines via Pipe, 40+ plugins (HTTP, cron, fsnotify, JSON, logging), automatic backpressure, error propagation, and Go context integration. Apply when using or adopting samber/ro, when the codebase imports github.com/samber/ro, or when building asynchronous event-driven pipelines, real-time data processing, streams, or reactive architectures in Go. Not for finite slice transforms (→ See `samber/cc-skills-golang@golang-samber-lo` skill).

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Operating SOP for DSPy (Stanford NLP) — the declarative framework for "programming, not prompting" language models. Activate when the user says any of: "use DSPy", "compile a prompt", "optimize prompts/programs", "MIPRO/MIPROv2", "BootstrapFewShot", "GEPA", "Signatures + Modules", "teleprompter", "auto-tune prompts for a different LM", or whenever a brittle hand-crafted prompt pipeline needs to be turned into a *compiled*, measurable, swappable program. Do NOT activate for one-shot prompt tweaks, no-metric exploratory work, or pipelines where prompts must remain human-authored verbatim — use raw prompting or LangChain templates instead.

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Refactor Swift code toward declarative functional programming with immutability, value types, pure functions, transformations, and closure-based APIs. Use when asked for functional refactoring or `/refactor:functional`.

日本語の概要は準備中です。原文の説明を表示しています。