# File Content Tracker Using AI A powerful file content tracking and search application built with Next.js, featuring AI-powered search capabilities using Ollama. ## 🚀 Quick Start ### Local Development 1. **Prerequisites** - Node.js 20+ - Docker Desktop - Ollama (for AI features) 2. **Run with Docker** (Recommended) ```bash docker compose up -d --build ``` - Application: http://localhost:3000 - Ollama API: http://localhost:11434 3. **Pull AI Model** ```bash docker compose exec ollama ollama pull gemma2:2b ``` ### Deploy to Cloud See deployment guides: - **HOW-TO-SHARE.md** - Complete guide to share online - **QUICK-DEPLOY-RAILWAY.md** - Railway deployment - **DEPLOYMENT.md** - Full deployment documentation ## 📚 Documentation - **HOW-TO-SHARE.md** - Share your project online - **NEXT-STEPS.md** - What to do after local setup - **DEPLOYMENT.md** - Complete deployment guide - **QUICK-START.md** - Quick reference ## 🛠️ Features - 🔍 Search across multiple file types (PDF, Word, Excel, PowerPoint) - 🤖 AI-powered search with Ollama - 📄 Document viewer with search highlights - 🎨 Modern, responsive UI - 🌙 Dark mode support ## 📝 Environment Variables Create a `.env` file: ```env PORT=3000 HOST=0.0.0.0 NODE_ENV=production OLLAMA_API_URL=http://localhost:11434 NEXT_PUBLIC_APP_URL=http://localhost:3000 ``` ## 🚢 Docker Deployment ```bash # Build and start docker compose up -d --build # View logs docker compose logs -f # Stop docker compose down ``` ## 📦 Tech Stack - **Framework**: Next.js 15 - **UI**: React 19, Tailwind CSS, Radix UI - **AI**: Ollama - **File Parsing**: pdfjs-dist, mammoth, xlsx - **OCR**: Tesseract.js ## 📄 License Private project --- **Ready to deploy?** Run `DEPLOY-SCRIPT.ps1` or see **HOW-TO-SHARE.md** # FileContent