qdrant-hybrid-search-prefetches
OfficialOptimize hybrid search performance in Qdrant.
Authorqdrant
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the need for constructing effective prefetch queries for hybrid retrieval in Qdrant, enhancing both performance and accuracy for specific query types.
Core Features & Use Cases
- Hybrid Search Query Construction: Guidance on combining dense and sparse vector search and multi-field retrieval scenarios.
- Sparse Vector Choice: Recommendations for the best sparse vector models for text search based on the context of the use case.
- Combining Multiple Representations: Strategies for when the same item has multiple embeddings across various fields or languages.
Quick Start
Use this skill to create a hybrid search query by combining a sparse BM25 model with a dense model for 'keyword_and_semantic_search' in your project.
Dependency Matrix
Required Modules
FastEmbed
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: qdrant-hybrid-search-prefetches Download link: https://github.com/qdrant/skills/archive/main.zip#qdrant-hybrid-search-prefetches Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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