# --- START OF FILE GeminiChatbot/app.py ---

import os
import logging
import base64
import json
import uuid
import google.generativeai as genai
from datetime import datetime
from functools import wraps
from flask import Flask, render_template, request, jsonify, session, redirect
from dotenv import load_dotenv
from werkzeug.utils import secure_filename

# Configure logging
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

# Load environment variables
load_dotenv()

# Configure Google Gemini API
api_key = os.environ.get("GEMINI_API_KEY")
if not api_key:
    logger.warning("GEMINI_API_KEY not found in environment variables")
else:
    genai.configure(api_key=api_key)
    logger.info("GEMINI_API_KEY found. API configured successfully.")


# Initialize Flask app
app = Flask(__name__)
app.secret_key = os.environ.get("SESSION_SECRET", "default-dev-secret-key")
app.config['UPLOAD_FOLDER'] = 'static/uploads'
app.config['MAX_CONTENT_LENGTH'] = 10 * 1024 * 1024  # 10 MB max

# Middleware to ensure user has a session_id
def session_required(f):
    @wraps(f)
    def decorated_function(*args, **kwargs):
        if 'session_id' not in session:
            session['session_id'] = str(uuid.uuid4())
            logger.info(f"Created new session: {session['session_id']}")
        return f(*args, **kwargs)
    return decorated_function

# Ensure upload directory exists
os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)

# Initialize models only if API key is present
model = None
vision_model = None
if api_key:
    # Configure Gemini model with specific parameters for better responses
    model = genai.GenerativeModel(
        model_name='gemini-1.0-pro', # Changed model name as 'gemini-2.0-flash' is not standard
        generation_config={
            'temperature': 0.7,  # Slightly creative but still focused
            'top_p': 0.9,        # Diverse output but not too random
            'top_k': 40,         # Reasonable range of tokens to consider
            'max_output_tokens': 2048  # Allow longer responses
        }
    )

    # Configure Gemini vision model for image processing
    # Using gemini-1.5-flash as it's generally available and supports vision
    vision_model = genai.GenerativeModel('gemini-1.5-flash')
else:
     logger.error("Cannot initialize Gemini models: API Key is missing.")


@app.route('/')
@session_required
def index():
    """Render the chat interface."""
    if not api_key:
         return "Erreur: Clé API Gemini manquante. Veuillez configurer GEMINI_API_KEY.", 500
    return render_template('index.html')

@app.route('/api/chat', methods=['POST'])
@session_required
def chat():
    """Process chat messages and get responses from Gemini API."""
    if not api_key:
        logger.error("Chat request failed: API Key is missing.")
        return jsonify({'error': 'Configuration serveur incomplète (clé API manquante).'}), 500
    if not model or not vision_model:
        logger.error("Chat request failed: Models not initialized.")
        return jsonify({'error': 'Configuration serveur incomplète (modèles non initialisés).'}), 500

    try:
        data = request.json
        user_message = data.get('message', '')
        chat_history = data.get('history', [])
        image_data = data.get('image', None) # Expecting a single image base64 string for now

        if not user_message and not image_data:
            return jsonify({'error': 'Veuillez entrer un message ou joindre une image.'}), 400

        # Log the incoming request (but not full chat history for privacy)
        session_id = session.get('session_id')
        logger.info(f"Received chat request from session {session_id}. Message length: {len(user_message)}. Image attached: {'Yes' if image_data else 'No'}")

        # Handle image processing if an image is included
        if image_data:
            if not vision_model:
                 logger.error("Vision model not available.")
                 return jsonify({'error': 'Le modèle de vision n\'est pas configuré.'}), 500
            try:
                # Decode image data
                # Assuming image_data is "data:image/jpeg;base64,..."
                image_info, image_base64 = image_data.split(',', 1)
                mime_type = image_info.split(':')[1].split(';')[0] # Extract mime type like "image/jpeg"
                image_bytes = base64.b64decode(image_base64) # Get raw bytes

                # Create the image part as a dictionary (CORRECTED METHOD)
                image_part = {
                    "mime_type": mime_type,
                    "data": image_bytes
                }

                # --- Save image (optional but good practice) ---
                session_dir = os.path.join(app.config['UPLOAD_FOLDER'], session_id)
                os.makedirs(session_dir, exist_ok=True)
                timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
                # Try to get extension from mime type
                extension = mime_type.split('/')[-1] if '/' in mime_type else 'jpg'
                filename = secure_filename(f"image_{timestamp}.{extension}")
                filepath = os.path.join(session_dir, filename)
                with open(filepath, "wb") as f:
                    f.write(image_bytes)
                logger.info(f"Saved uploaded image to {filepath}")
                # --- End Save image ---

                # Create message parts list for generate_content (CORRECTED METHOD)
                parts = []
                if user_message: # Add text first if it exists
                     parts.append(user_message)
                parts.append(image_part) # Add the image dictionary

                # Generate response using vision model
                logger.debug(f"Sending parts to vision model: {[type(p) if not isinstance(p, dict) else 'dict(image)' for p in parts]}")
                response = vision_model.generate_content(parts)
                logger.info(f"Generated vision response successfully. Response length: {len(response.text)}")
                return jsonify({'response': response.text})

            except (ValueError, IndexError) as decode_error:
                 logger.error(f"Error decoding image data: {str(decode_error)}")
                 return jsonify({'error': 'Format de données d\'image invalide.'}), 400
            except Exception as img_error:
                # Log the full traceback for better debugging
                logger.exception(f"Error processing image: {str(img_error)}")
                return jsonify({
                    'error': 'Désolé, une erreur est survenue lors du traitement de l\'image. Veuillez réessayer.'
                }), 500
        else:
            # Text-only processing
            if not model:
                 logger.error("Text model not available.")
                 return jsonify({'error': 'Le modèle de texte n\'est pas configuré.'}), 500

            # Format conversation history for context
            formatted_history = []
            for msg in chat_history[-15:]:  # Use the last 15 messages for more context
                role = "user" if msg['sender'] == 'user' else "model"
                # Ensure message text is not None or empty before adding
                if msg.get('text'):
                    formatted_history.append({"role": role, "parts": [msg['text']]})
                # Note: History currently doesn't include images sent previously.
                # Handling multimodal history requires storing image references/data
                # and formatting them correctly for the API on subsequent turns.

            try:
                # Create a chat session with history
                chat_session = model.start_chat(history=formatted_history)

                # Generate response
                response = chat_session.send_message(user_message)

                # Log successful response
                logger.info(f"Generated text response successfully. Response length: {len(response.text)}")

                # Return the response
                return jsonify({'response': response.text})

            except genai.types.generation_types.BlockedPromptException as be:
                 logger.warning(f"Content blocked for session {session_id}: {str(be)}")
                 return jsonify({
                    'error': 'Votre message ou la conversation contient du contenu potentiellement inapproprié et ne peut pas être traité.'
                 }), 400
            except Exception as e:
                 logger.exception(f"Error during text generation for session {session_id}: {str(e)}")
                 return jsonify({
                    'error': 'Désolé, une erreur est survenue lors de la génération de la réponse texte.'
                 }), 500

    except Exception as e:
        # Catch-all for unexpected errors (like issues reading request JSON)
        logger.exception(f"Unhandled error in chat endpoint: {str(e)}")
        return jsonify({
            'error': 'Désolé, j\'ai rencontré une erreur inattendue. Veuillez réessayer.'
        }), 500


@app.route('/api/save-chat', methods=['POST'])
@session_required
def save_chat():
    """Save the current chat history."""
    try:
        session_id = session.get('session_id')
        if not session_id:
             return jsonify({'error': 'Session introuvable.'}), 400

        # Create session-specific directory
        session_dir = os.path.join(app.config['UPLOAD_FOLDER'], session_id)
        os.makedirs(session_dir, exist_ok=True)

        data = request.json
        chat_history = data.get('history', [])

        if not chat_history:
            return jsonify({'error': 'Aucune conversation à sauvegarder.'}), 400

        # Generate filename with timestamp
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        filename = f"chat_{timestamp}.json"
        filepath = os.path.join(session_dir, filename)

        # Save chat history to file
        with open(filepath, 'w', encoding='utf-8') as f:
            json.dump(chat_history, f, ensure_ascii=False, indent=2)

        logger.info(f"Chat history saved for session {session_id} to {filename}")
        return jsonify({'success': True, 'filename': filename, 'timestamp': timestamp}) # Return timestamp too

    except Exception as e:
        logger.exception(f"Error saving chat for session {session_id}: {str(e)}")
        return jsonify({
            'error': 'Désolé, une erreur est survenue lors de la sauvegarde de la conversation.'
        }), 500

@app.route('/api/load-chats', methods=['GET'])
@session_required
def load_chats():
    """Get a list of saved chat files for current session."""
    try:
        session_id = session.get('session_id')
        if not session_id:
            return jsonify({'error': 'Session introuvable.'}), 400

        # Get session-specific directory
        session_dir = os.path.join(app.config['UPLOAD_FOLDER'], session_id)

        # If the directory doesn't exist yet, return empty list
        if not os.path.exists(session_dir):
            logger.info(f"No chat directory found for session {session_id}")
            return jsonify({'chats': []})

        chat_files = []
        for filename in os.listdir(session_dir):
            # Ensure we only list chat files, not uploaded images etc.
            if filename.startswith('chat_') and filename.endswith('.json'):
                try:
                    # Extract timestamp from filename 'chat_YYYYMMDD_HHMMSS.json'
                    timestamp_str = filename[5:-5] # Remove 'chat_' and '.json'
                    # Validate timestamp format (optional but good)
                    datetime.strptime(timestamp_str, "%Y%m%d_%H%M%S")
                    chat_files.append({
                        'filename': filename,
                        'timestamp': timestamp_str # Keep original string for sorting/display
                    })
                except ValueError:
                    logger.warning(f"Skipping file with unexpected format: {filename} in {session_dir}")


        # Sort by timestamp string (lexicographical sort works for YYYYMMDD_HHMMSS)
        chat_files.sort(key=lambda x: x['timestamp'], reverse=True)

        logger.info(f"Loaded {len(chat_files)} chats for session {session_id}")
        return jsonify({'chats': chat_files})

    except Exception as e:
        logger.exception(f"Error loading chat list for session {session_id}: {str(e)}")
        return jsonify({
            'error': 'Désolé, une erreur est survenue lors du chargement des conversations.'
        }), 500

@app.route('/api/load-chat/<filename>', methods=['GET'])
@session_required
def load_chat(filename):
    """Load a specific chat history file."""
    try:
        session_id = session.get('session_id')
        if not session_id:
            return jsonify({'error': 'Session introuvable.'}), 400

        # Secure the filename before using it
        safe_filename = secure_filename(filename)
        if not safe_filename.startswith('chat_') or not safe_filename.endswith('.json'):
             logger.warning(f"Attempt to load invalid chat filename: {filename} (secured: {safe_filename}) for session {session_id}")
             return jsonify({'error': 'Nom de fichier de conversation invalide.'}), 400

        # Load from session-specific directory
        session_dir = os.path.join(app.config['UPLOAD_FOLDER'], session_id)
        filepath = os.path.join(session_dir, safe_filename)

        if not os.path.exists(filepath):
            logger.warning(f"Chat file not found: {filepath} for session {session_id}")
            return jsonify({'error': 'Conversation introuvable.'}), 404

        # Check if path is still within the intended directory (security measure)
        if not os.path.abspath(filepath).startswith(os.path.abspath(session_dir)):
            logger.error(f"Attempt to access file outside session directory: {filepath}")
            return jsonify({'error': 'Accès non autorisé.'}), 403

        with open(filepath, 'r', encoding='utf-8') as f:
            chat_history = json.load(f)

        # Basic validation of loaded history format (optional)
        if not isinstance(chat_history, list):
            raise ValueError("Invalid chat history format in file.")
        for item in chat_history:
            if not isinstance(item, dict) or 'sender' not in item or 'text' not in item:
                 # Allow for messages that might only have text or image data later
                 if 'sender' not in item:
                     raise ValueError("Invalid message format in chat history.")


        logger.info(f"Loaded chat {safe_filename} for session {session_id}")
        return jsonify({'history': chat_history})

    except json.JSONDecodeError:
        logger.error(f"Error decoding JSON from chat file: {safe_filename} for session {session_id}")
        return jsonify({'error': 'Le fichier de conversation est corrompu.'}), 500
    except ValueError as ve:
         logger.error(f"Invalid content in chat file {safe_filename}: {str(ve)}")
         return jsonify({'error': f'Format invalide dans le fichier de conversation: {str(ve)}'}), 500
    except Exception as e:
        logger.exception(f"Error loading chat file {safe_filename} for session {session_id}: {str(e)}")
        return jsonify({
            'error': 'Désolé, une erreur est survenue lors du chargement de la conversation.'
        }), 500

if __name__ == '__main__':
    # Use 0.0.0.0 to be accessible on the network, debug=False for production
    # Port 8080 is often used as an alternative to 5000
    app.run(host='0.0.0.0', port=int(os.environ.get('PORT', 8080)), debug=os.environ.get('FLASK_DEBUG', 'False').lower() == 'true')
# --- END OF FILE GeminiChatbot/app.py ---