claude

llm-app-patterns

Patterns for AI-powered apps: retrieval evaluation, grounded generation with citations, SSE streaming UI, and the OpenAI API.

0 on GitHubby Piotr Mieszczakv1.0.0updated 9 days agodevelopment
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Plugin llm-app-patterns from marketplace llm-utils in PiotrMieszczak/llm_utils. Commands read from the repo's manifest — 9 days ago.

What it installs

Skills (4)

  • grounded-generation

    Make an assistant answer only from supplied source material, refuse when the material does not cover the question, and cite what it used. Use when building a RAG assistant, a docs Q&A bot, or any feature where a confidently wrong answer is worse than no answer, and when adding citations or testing r

  • openai-api

    Reference for the OpenAI API and SDKs - the Responses API, Chat Completions, streaming, tool calling, structured outputs, embeddings, and model or pricing selection. Use whenever OpenAI, GPT, the openai package, or an OpenAI model id appears in the task, and before answering any question about OpenA

  • rag-evaluation

    Measure whether a retrieval system actually finds the right material, before and after changing it. Use when building or debugging RAG, when deciding between keyword and vector search, when someone proposes adding embeddings, when answers are wrong and you need to know whether retrieval or generatio

  • streaming-ui

    Stream LLM responses to a browser over Server-Sent Events, including tool-call progress, citations, cancellation, and error handling mid-stream. Use when building a chat UI, adding token streaming, handling SSE in React, deciding between SSE and WebSockets, or debugging a stream that hangs, duplicat

View source on GitHub

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