rag-pipeline
Use when building Retrieval-Augmented Generation systems. Covers document chunking, embedding generation, vector indexing, semantic search, context building, and integration of retrieval with LLM completion for...
浏览 muhammad-anas35 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
4收录技能的仓库 Stars 合计
0仓库 Forks
0平均每个技能的仓库 Stars
0同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Use when building Retrieval-Augmented Generation systems. Covers document chunking, embedding generation, vector indexing, semantic search, context building, and integration of retrieval with LLM completion for...
Use when integrating OpenAI GPT models for conversational AI. Covers chat completions, streaming responses, function calling, system prompts, token management, cost optimization, error handling, and building sp...
Use when working with Qdrant vector database for semantic search and RAG. Covers collection setup, embedding generation, vector upsert/search, HNSW indexing, filtering, and integration with OpenAI embeddings fo...
Use when working with Neon serverless PostgreSQL database. Covers database setup, CLI commands, Drizzle ORM integration, schema migrations, connection pooling, and user data storage patterns for authentication...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。