yanacuti1121/Yana-AI - 40페이지

qdrant

Qdrant vector database — collections, upsert, search, filtering, payloads, sparse vectors, BM25

원문 언어: 영어

ragas

Evaluate RAG pipelines with Ragas — measure faithfulness, answer relevancy, context precision/recall, and noise sensitivity using LLM-as-judge metrics; run automated test suite generation with TestsetGenerator; integrate with LangChain, LlamaIndex, and CI…

원문 언어: 영어

smolagents

Build lightweight AI agents with HuggingFace Smolagents — use CodeAgent (writes Python to act) or ToolCallingAgent (JSON tool calls), add built-in or custom Tools, orchestrate multi-agent pipelines with ManagedAgent, and run locally or via HF Inference API.

원문 언어: 영어

testing-strategy

Testing strategy — unit/integration/e2e pyramid, TDD workflow, mocking best practices, test isolation, coverage targets

원문 언어: 영어

type-safety-patterns

Type safety — Python type hints with mypy/pyright, TypeScript strict mode, branded types, Zod validation, runtime checks

원문 언어: 영어

vercel-ai-sdk

Use when building AI-powered web apps with Next.js, React, or Node.js — streaming chat, tool calling, structured output, multi-modal. Triggers on: 'vercel ai', 'ai sdk', 'streaming chat', 'useChat', 'generateText', 'streamText', 'ai chatbot nextjs', 'LLM in…

원문 언어: 영어