qdrant-integration | babysitter | ClaudePluginHub

Skill

Community

qdrant-integration

From babysitter

411

Description

Qdrant vector database with filtering, payloads, and quantization support

AI Summary

Manages Qdrant vector databases for semantic search, filtering, and RAG pipeline operations.

Install

1

Run in your terminal

$

npx claudepluginhub a5c-ai/babysitter

Tool Access

This skill is limited to using the following tools:

ReadWriteEditBashGlobGrep

Supporting Assets

View in Repository

README.md

Skill Content

Qdrant Integration Skill

Capabilities

Set up Qdrant (local, cloud, self-hosted)
Create collections with configuration
Implement advanced filtering with payloads
Configure quantization for efficiency
Set up sparse vectors for hybrid search
Implement batch operations and optimization

Target Processes

vector-database-setup
rag-pipeline-implementation

Implementation Details

Deployment Modes

Local Memory: For testing
Local Disk: Persistent local storage
Qdrant Cloud: Managed service
Self-Hosted: Docker/Kubernetes deployment

Core Operations

Collection management with parameters
Point upsert with vectors and payloads
Search with filters (must, should, must_not)
Scroll for pagination
Batch operations

Configuration Options

Vector parameters (size, distance)
Quantization (scalar, product)
Sparse vector configuration
Payload indexes
Replication and sharding

Best Practices

Use quantization for large collections
Design payload indexes for filters
Implement proper batch sizes
Configure appropriate distance metrics

Dependencies

qdrant-client
langchain-qdrant

Links

GitHub Stats

21 forks

Updated 1 month ago

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