rag-embedding-generation
Batch embedding generation with caching, rate limiting, and multiple provider support
它会碰到什么
扫了多少2 个文本文件，2 KB
它会碰到什么不碰外部（只输出文字）
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0
这一栏是扫描器报的事实，不是结论。命中多不等于有毒（安全工具、规则库、示例脚本本来就会包含危险写法），命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系，需要你自己看。
技能内容
RAG Embedding Generation Skill
Capabilities
- Generate embeddings with multiple providers
- Implement batch processing for large datasets
- Configure caching for embedding reuse
- Handle rate limiting and retries
- Support various embedding models
- Implement embedding quality validation
Target Processes
- rag-pipeline-implementation
- vector-database-setup
Implementation Details
Embedding Providers
- OpenAI Embeddings: text-embedding-ada-002, text-embedding-3-*
- HuggingFace: sentence-transformers models
- Cohere: embed-v3 models
- Voyage AI: voyage-2 models
- Local Models: GGUF/ONNX embedding models
Configuration Options
- Model selection and parameters
- Batch size optimization
- Cache backend configuration
- Rate limit settings
- Retry policies
- Dimensionality settings
Best Practices
- Use appropriate model for domain
- Implement caching for cost reduction
- Monitor embedding quality
- Handle API errors gracefully
Dependencies
- langchain-openai / langchain-huggingface
- numpy
- Caching backend (Redis, SQLite)
想直接用这个技能？
本站把开放许可（MIT / Apache 等）的技能按仓库打包整理到网盘，点一下转存到你自己的网盘，不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接，不打包。
它属于哪个仓库
星标★ 1,796
本站分层T1
该仓技能数2115
原文件路径
library/specializations/ai-agents-conversational/skills/rag-embedding-generation/SKILL.md