AgentSkillsCN

rag-embedding-generation

通过缓存、速率限制以及多供应商支持，批量生成嵌入向量

SKILL.md
--- frontmatter
name: rag-embedding-generation
description: Batch embedding generation with caching, rate limiting, and multiple provider support
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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

  1. •OpenAI Embeddings: text-embedding-ada-002, text-embedding-3-*
  2. •HuggingFace: sentence-transformers models
  3. •Cohere: embed-v3 models
  4. •Voyage AI: voyage-2 models
  5. •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)