grepai-storage-qdrantlisted

# GrepAI Storage with Qdrant This skill covers using Qdrant as the storage backend for GrepAI, offering high-performance vector search. ## When to Use This Skill - Need fastest possible search performance - Very large codebases (50K+ files) - Already using Qdrant infrastructure - Want advanced vector search features ## What is Qdrant? Qdrant is a purpose-built vector database offering: - ⚡ Extremely fast vector similarity search - 📏 Excellent scalability - 🔧 Advanced filtering capabilities - 🐳 Easy Docker deployment ## Prerequisites 1. Qdrant server running 2. Network access to Qdrant ## Advantages | Benefit | Description | |---------|-------------| | ⚡ **Performance** | Fastest vector search | | 📏 **Scalability** | Handles millions of vectors | | 🔍 **Advanced** | Filtering, payloads, sharding | | 🐳 **Easy deploy** | Docker-ready | | ☁️ **Cloud option** | Qdrant Cloud available | ## Setting Up Qdrant ### Option 1: Docker (Recommended) ```bash # Run Qdrant with persistent storage docker run -d \ --name grepai-qdrant \ -p 6333:6333 \ -p 6334:6334 \ -v qdrant_storage:/qdrant/storage \ qdrant/qdrant ``` Ports: - `6333`: REST API - `6334`: gRPC API (used by GrepAI) ### Option 2: Docker Compose ```yaml # docker-compose.yml version: '3.8' services: qdrant: image: qdrant/qdrant ports: - "6333:6333" - "6334:6334" volumes: - qdrant_storage:/qdrant/storage environment: - QDRANT__SERVICE__GRPC_PORT=6334 volumes: