#!/usr/bin/env python3
"""
Hugging Face Spaces compatible app for MemoryAI.
This is the main entry point for the Spaces deployment.
"""

import os
from flask import Flask, render_template, request, jsonify
from src.main import MemoryAI

# Load environment variables (with fallback if dotenv not available)
try:
    from dotenv import load_dotenv
    load_dotenv()
except ImportError:
    print("⚠️  python-dotenv not available, using environment variables directly")
    # Set default values if .env not loaded
    if not os.getenv("MODEL_NAME"):
        os.environ["MODEL_NAME"] = "microsoft/DialoGPT-small"

# Initialize Flask app
app = Flask(__name__)

# Initialize MemoryAI with better default model for Spaces
if not os.getenv("MODEL_NAME"):
    os.environ["MODEL_NAME"] = "microsoft/DialoGPT-small"

# Global MemoryAI instance
ai = MemoryAI()
ai.load_memories()

@app.route('/')
def home():
    """Render the main chat interface."""
    return render_template('spaces_chat.html')

@app.route('/api/memories', methods=['GET'])
def get_memories():
    """Get recent memories as JSON."""
    recent_memories = ai.get_recent_memories(10)
    return jsonify({
        'memories': recent_memories,
        'total_memories': len(ai.memories)
    })

@app.route('/api/clear', methods=['POST'])
def clear_memories():
    """Clear all memories."""
    ai.clear_memories()
    return jsonify({'status': 'success', 'message': 'All memories cleared'})

@app.route('/api/chat', methods=['POST'])
def chat():
    """Get AI response to user input."""
    data = request.json
    user_input = data.get('message', '')
    conversation_history = data.get('history', [])
    
    if not user_input.strip():
        return jsonify({'error': 'Empty message'}), 400
    
    # Generate AI response with conversation history
    response = ai.generate_response(user_input, conversation_history=conversation_history)
    
    return jsonify({
        'response': response,
        'memory_count': len(ai.memories),
        'conversation_stats': ai.get_conversation_stats() if hasattr(ai, 'get_conversation_stats') else {}
    })

@app.route('/api/summary', methods=['GET'])
def get_summary():
    """Get conversation summary."""
    summary = ai.get_conversation_summary()
    return jsonify({'summary': summary})

@app.route('/api/similar', methods=['POST'])
def find_similar():
    """Find similar memories."""
    data = request.json
    query = data.get('query', '')
    top_k = data.get('top_k', 3)
    
    if not query.strip():
        return jsonify({'error': 'Empty query'}), 400
    
    similar = ai.find_similar_memories(query, top_k)
    return jsonify({
        'similar_memories': [{'text': text, 'similarity': float(score)} for text, score in similar],
        'query': query
    })

@app.route('/api/reset', methods=['POST'])
def reset_conversation():
    """Reset conversation state."""
    ai.reset_conversation()
    return jsonify({'status': 'success', 'message': 'Conversation reset'})

@app.route('/api/save', methods=['POST'])
def save_memories():
    """Save memories to file."""
    ai.save_memories()
    return jsonify({'status': 'success', 'message': 'Memories saved'})

if __name__ == '__main__':
    # Hugging Face Spaces will run this with their own server
    # For local testing, you can use:
    app.run(debug=True, host='0.0.0.0', port=int(os.environ.get('PORT', 7860)))