#!/bin/bash

echo "🔧 Fixing HF Space build issues..."

# Copy fixed requirements
if [ -f "requirements_fixed.txt" ]; then
    cp requirements_fixed.txt requirements.txt
    echo "✅ Updated requirements.txt"
else
    echo "❌ requirements_fixed.txt not found"
    exit 1
fi

# Copy app with data integration
if [ -f "app_with_data.py" ]; then
    cp app_with_data.py app.py
    echo "✅ Updated app.py"
else
    echo "❌ app_with_data.py not found"
    exit 1
fi

# Create Dockerfile for HF Spaces
cat > Dockerfile << 'EOF'
FROM python:3.9

# Create user
RUN useradd -m -u 1000 user

# Set working directory
WORKDIR /app

# Copy requirements first for better caching
COPY --chown=user ./requirements.txt requirements.txt

# Install dependencies
RUN pip install --no-cache-dir --upgrade -r requirements.txt

# Create necessary directories
RUN mkdir -p /app/data /app/templates /app/configs

# Copy application files
COPY --chown=user . /app

# Switch to user
USER user

# Expose port
EXPOSE 8080

# Run the application
CMD ["python", "app.py"]
EOF

echo "✅ Created Dockerfile"

# Create README.md for HF Spaces
cat > README.md << 'EOF'
---
title: Textilindo AI Assistant
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: mit
app_port: 8080
---

# Textilindo AI Assistant

AI-powered customer service assistant for Textilindo textile company.

## Features

- 🤖 **Smart AI Assistant**: Answers customer questions about products, shipping, and company policies
- 📚 **Knowledge Base**: Uses 182+ training examples for context-aware responses
- 🇮🇩 **Indonesian Language**: Responds in friendly Indonesian language
- 🛍️ **Sales Focus**: Helps customers with product recommendations and ordering

## API Endpoints

- `GET /` - API documentation
- `GET /health` - Health check
- `POST /chat` - Chat with AI
- `GET /stats` - Dataset statistics

## Usage

Send a POST request to `/chat` with your message:

```json
{
  "message": "dimana lokasi textilindo?",
  "max_tokens": 300,
  "temperature": 0.7
}
```

## Dataset

The assistant is trained on 182+ examples covering:
- Company location and hours
- Product information
- Shipping and payment policies
- Customer service scenarios

## Technology

- **Backend**: Flask (Python)
- **AI**: Hugging Face Transformers
- **Data**: JSONL format with RAG (Retrieval-Augmented Generation)
- **Deployment**: Hugging Face Spaces
EOF

echo "✅ Created README.md"

# Add and commit changes
echo "📝 Committing changes..."
git add .
git commit -m "Fix build issues - remove problematic dependencies and add data integration

- Remove difflib2 dependency (doesn't exist)
- Use built-in difflib module instead
- Add comprehensive dataset integration
- Create proper Dockerfile for HF Spaces
- Add README with documentation"

# Push to Hugging Face Space
echo "🚀 Pushing to Hugging Face Space..."
git push hf main

echo "✅ Build fix complete!"
echo ""
echo "📋 Next steps:"
echo "1. Check your HF Space build status: https://huggingface.co/spaces/harismlnaslm/Textilindo"
echo "2. Monitor the build logs"
echo "3. Test your application once build completes"