semantic-search

功能与用途

Build production-ready semantic search systems using vector databases, embeddings, and retrieval-augmented generation (RAG). Covers vector DB selection (Pinecone/Qdrant/Weaviate), embedding models (OpenAI/Voyage/Cohere), chunking strategies, hybrid search, and reranking for high-quality retrieval. Use when ", vector-search, embeddings, rag, pinecone, qdrant, weaviate, llama-index, langchain, hybrid-search, reranking" mentioned.

快速开始

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。