React CRM Business Predictor

AI-powered CRM application with business forecasting, risk management, and event scheduling capabilities. Supports fully local operation with auto-downloading of dependencies, local NVIDIA GPU inference, and optional OpenAI integration.

✨ New: Fully Local Setup with Auto-Download

🚀 Quick Start (Recommended):

npm run setup && npm start

That's it! The application will automatically:

• ✓ Download and install all Node.js dependencies
• ✓ Download and install all Python packages
• ✓ Auto-download and initialize AI models
• ✓ Start both frontend and backend servers
• ✓ Run completely offline (no internet required after setup)

📖 For detailed instructions, see LOCAL_SETUP.md

Features

• 🌐 Fully Local Operation: Runs completely offline with local AI models
• 📦 Auto-Download: Automatically downloads all required modules
• 🤗 Hugging Face Models: Pre-trained models for NLP tasks (sentiment, NER, etc.)
• Business Applicant Management: Upload and manage applicant data
• AI-Powered Risk Assessment: Predict business opportunities and assess risk
• Event Scheduling: Manage meetings and events
• Wedding Reservations: Specialized wedding booking system
• Local GPU Inference: Utilize NVIDIA GPU for fast predictions (optional)
• OpenAI Integration: Optional cloud-based AI processing
• Real-time Analytics: Business forecasting and trend analysis

Prerequisites

Minimum Requirements:

• Node.js 18+ and npm
• Python 3.9+

Optional (For GPU Acceleration):

• NVIDIA GPU with CUDA 12.x support
• CUDA Toolkit 12.1+ (automatically configured during installation)

Note: The installer now uses CUDA 12.1 for optimal performance and compatibility with the latest PyTorch versions. Environment variables are set up automatically!

Quick Start Options

Option 1: Fully Local with Auto-Setup (Recommended)

Perfect for running completely locally without internet dependency:

# One command setup and start
npm run setup && npm start

See LOCAL_SETUP.md for detailed local setup instructions.

Option 2: Windows Auto-Launcher (One-Click Start) 🎯

Perfect for Windows users who want the easiest possible setup:

Simply double-click: auto-run.bat

The auto-launcher will:

• ✓ Automatically check and install all dependencies
• ✓ Start both backend and frontend servers
• ✓ Open in separate windows with clear status
• ✓ Create configuration files if needed

Advanced Launcher Options:

• auto-run.cmd - Quick launcher for regular use
• launcher.vbs - Auto-opens browser after starting
• launcher-silent.vbs - Silent background startup
• CRM-Launcher.exe - Custom executable with icon (build with create-exe.ps1)

📖 See LAUNCHER_GUIDE.md for complete launcher documentation including:

• Creating custom executable with icon
• Adding to Windows startup
• Desktop shortcuts
• Silent background operation
• And more!

Option 3: Traditional Installation

Automated Installation

Run the auto-installer script:

# Linux/Mac
./install.sh

# Windows
install.bat

Manual Installation

1. Install Frontend Dependencies

npm install

2. Install Backend Dependencies

cd backend
pip install -r requirements.txt

3. Configure Environment

cp backend/.env.example backend/.env
# Edit backend/.env with your settings

4. Start the Application

Terminal 1 - Backend:

npm run backend

Terminal 2 - Frontend:

npm run dev

Access the application at http://localhost:5173

Configuration

Edit backend/.env:

# Server Configuration
HOST=0.0.0.0
PORT=8000

# AI Configuration
USE_LOCAL_GPU=true
CUDA_VISIBLE_DEVICES=0

# OpenAI (Optional)
OPENAI_API_KEY=your_api_key_here
USE_OPENAI=false

# Model Configuration
MODEL_TYPE=local  # local or openai

GPU Support

The application automatically detects NVIDIA GPU availability and sets up CUDA 12.1:

Automatic Setup:

1. Install CUDA Toolkit 12.1 or higher from NVIDIA's website
2. Run the installation script (install.bat or install.sh)
3. The installer will:
   • Detect your GPU automatically
   • Install PyTorch with CUDA 12.1 support
   • Configure CUDA environment variables automatically
   • Set USE_LOCAL_GPU=true in .env

Manual Configuration (if needed):

# Windows
setx CUDA_PATH "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1"
setx CUDA_HOME "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1"

# Linux
export CUDA_HOME=/usr/local/cuda-12.1
export PATH=$CUDA_HOME/bin:$PATH
export LD_LIBRARY_PATH=$CUDA_HOME/lib64:$LD_LIBRARY_PATH

Verify GPU Setup:

nvidia-smi  # Check GPU is detected
python -c "import torch; print(f'CUDA Available: {torch.cuda.is_available()}')"

Hugging Face Models

The application supports pre-trained models from Hugging Face for advanced NLP tasks:

Quick Setup

Download recommended models for business applications:

cd backend
python -m services.model_downloader download-recommended

This downloads models for:

• Sentiment analysis
• Emotion detection
• Named Entity Recognition (NER)
• Financial sentiment analysis

Available Models

The application includes 8 pre-trained models:

• sentiment: Positive/negative sentiment analysis
• emotion: Detect joy, sadness, anger, fear, etc.
• ner: Extract person, organization, location entities
• qa: Question answering
• financial-sentiment: Specialized for financial text
• text-generation: Text completion (GPT-2)
• summarization: Text summarization
• zero-shot: Zero-shot classification

📖 For detailed documentation, see HUGGINGFACE_MODELS.md

Usage Example

from services.huggingface_service import HuggingFaceService

hf = HuggingFaceService()

# Analyze sentiment
result = hf.analyze_sentiment("This is a great opportunity!")
# {'sentiment': 'POSITIVE', 'confidence': 0.9998}

# Extract entities
entities = hf.extract_entities("Apple Inc. is in Cupertino, CA")
# [{'text': 'Apple Inc.', 'type': 'ORG'}, ...]

API Endpoints

• POST /api/predict - Business prediction
• POST /api/risk-analysis - Risk assessment
• GET /api/events - List events
• POST /api/events - Create event
• GET /api/weddings - List wedding reservations
• POST /api/weddings - Create wedding reservation

Project Structure

.
├── src/                    # React frontend
│   ├── components/        # React components
│   ├── pages/            # Page components
│   ├── services/         # API services
│   └── store/            # State management
├── backend/              # Python backend
│   ├── app.py           # FastAPI application
│   ├── models/          # ML models
│   ├── routes/          # API routes
│   └── services/        # Business logic
└── public/              # Static assets

License

MIT

Contributing

Contributions are welcome. Read CONTRIBUTING.md and use the issue templates. Good first contributions include lightweight test fixtures, CPU-only setup improvements, accessibility fixes, and model-provider abstractions.

Security

Report vulnerabilities privately as described in SECURITY.md.