rag-query-transformation

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Query expansion, HyDE, and multi-query generation for improved retrieval

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# RAG Query Transformation Skill ## Capabilities - Implement query expansion techniques - Configure Hypothetical Document Embeddings (HyDE) - Set up multi-query generation - Design query decomposition strategies - Implement step-back prompting - Configure query routing for specialized indices ## Target Processes - advanced-rag-patterns - knowledge-base-qa ## Implementation Details ### Transformation Techniques 1. **Multi-Query Generation**: Generate query variations 2. **HyDE**: Generate hypothetical answer, embed that 3. **Query Decomposition**: Break complex queries into sub-queries 4. **Step-Back Prompting**: Generate higher-level queries 5. **Query Expansion**: Add synonyms and related terms ### Configuration Options - Number of query variations - LLM for query generation - Decomposition depth - Query routing rules - Result fusion strategy ### Best Practices - Match technique to query complexity - Test with representative queries - Monitor retrieval quality changes - Balance latency vs quality tradeoffs ### Dependencies - langchain - LLM provider

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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