grepai-storage-postgreslisted

# GrepAI Storage with PostgreSQL This skill covers using PostgreSQL with the pgvector extension as the storage backend for GrepAI. ## When to Use This Skill - Team environments with shared index - Large codebases (10K+ files) - Need concurrent access - Integration with existing PostgreSQL infrastructure ## Prerequisites 1. PostgreSQL 14+ with pgvector extension 2. Database user with create table permissions 3. Network access to PostgreSQL server ## Advantages | Benefit | Description | |---------|-------------| | 👥 **Team sharing** | Multiple users can access same index | | 📏 **Scalable** | Handles large codebases | | 🔄 **Concurrent** | Multiple simultaneous searches | | 💾 **Persistent** | Data survives machine restarts | | 🔧 **Familiar** | Standard database tooling | ## Setting Up PostgreSQL with pgvector ### Option 1: Docker (Recommended for Development) ```bash # Run PostgreSQL with pgvector docker run -d \ --name grepai-postgres \ -e POSTGRES_USER=grepai \ -e POSTGRES_PASSWORD=grepai \ -e POSTGRES_DB=grepai \ -p 5432:5432 \ pgvector/pgvector:pg16 ``` ### Option 2: Install on Existing PostgreSQL ```bash # Install pgvector extension (Ubuntu/Debian) sudo apt install postgresql-16-pgvector # Or compile from source git clone https://github.com/pgvector/pgvector.git cd pgvector make sudo make install ``` Then enable the extension: ```sql -- Connect to your database CREATE EXTENSION IF NOT EXISTS vector; ``` ### Option 3: Managed Services - **Sup