main.py

import os
import io
import uuid
import re
import time
import json
import traceback
import wave
from datetime import datetime, timedelta

from flask import Flask, request, jsonify, Response
from flask_cors import CORS
import firebase_admin
from firebase_admin import credentials, db, storage, auth
from PIL import Image
from io import BytesIO
import requests
from elevenlabs import ElevenLabs
# Import and configure Google GenAI, matching the Streamlit app
from google import genai
from google.genai import types

# -----------------------------------------------------------------------------
# 1. CONFIGURATION & INITIALIZATION
# -----------------------------------------------------------------------------

# Initialize Flask app and CORS
app = Flask(__name__)
CORS(app)

# --- Firebase Initialization ---
try:
    credentials_json_string = os.environ.get("FIREBASE")
    if not credentials_json_string:
        raise ValueError("The FIREBASE environment variable is not set.")
    
    credentials_json = json.loads(credentials_json_string)
    firebase_db_url = os.environ.get("Firebase_DB")
    firebase_storage_bucket = os.environ.get("Firebase_Storage")

    if not firebase_db_url or not firebase_storage_bucket:
        raise ValueError("Firebase_DB and Firebase_Storage environment variables must be set.")

    cred = credentials.Certificate(credentials_json)
    firebase_admin.initialize_app(cred, {
        'databaseURL': firebase_db_url,
        'storageBucket': firebase_storage_bucket
    })
    print("Firebase Admin SDK initialized successfully.")
except Exception as e:
    print(f"FATAL: Error initializing Firebase: {e}")
    exit(1)

# Initialize Firebase services
bucket = storage.bucket()
db_ref = db.reference()


# --- Google GenAI Client Initialization (as per Streamlit app) ---
try:
    api_key = os.environ.get("Gemini")
    if not api_key:
        raise ValueError("The 'Gemini' environment variable for the API key is not set.")
    
    client = genai.Client(api_key=api_key)
    print("Google GenAI Client initialized successfully.")
except Exception as e:
    print(f"FATAL: Error initializing GenAI Client: {e}")
    exit(1)

# --- Model Constants (as per Streamlit app) ---
CATEGORY_MODEL = "gemini-2.0-flash-exp"
GENERATION_MODEL = "gemini-2.0-flash-exp-image-generation"
#TTS_MODEL = "gemini-2.5-flash-preview-tts"


# -----------------------------------------------------------------------------
# 2. HELPER FUNCTIONS (Adapted directly from Streamlit App & Template)
# -----------------------------------------------------------------------------

def verify_token(auth_header):
    """Verifies the Firebase ID token from the Authorization header."""
    if not auth_header or not auth_header.startswith('Bearer '):
        return None
    token = auth_header.split('Bearer ')[1]
    try:
        decoded_token = auth.verify_id_token(token)
        return decoded_token['uid']
    except Exception as e:
        print(f"Token verification failed: {e}")
        return None

def verify_admin(auth_header):
    """Verifies if the user is an admin."""
    uid = verify_token(auth_header)
    if not uid:
        raise PermissionError('Invalid or missing user token')
    
    user_ref = db_ref.child(f'users/{uid}')
    user_data = user_ref.get()
    if not user_data or not user_data.get('is_admin', False):
        raise PermissionError('Admin access required')
    return uid

def upload_to_storage(data_bytes, destination_blob_name, content_type):
    """Uploads a bytes object to Firebase Storage and returns its public URL."""
    blob = bucket.blob(destination_blob_name)
    blob.upload_from_string(data_bytes, content_type=content_type)
    blob.make_public()
    return blob.public_url

def parse_numbered_steps(text):
    """Helper to parse numbered steps out of Gemini text."""
    text = "\n" + text
    steps_found = re.findall(r"\n\s*(\d+)\.\s*(.*)", text, re.MULTILINE)
    return [{"stepNumber": int(num), "text": desc.strip()} for num, desc in steps_found]

def _convert_pcm_to_wav(pcm_data, sample_rate=24000, channels=1, sample_width=2):
    """Wraps raw PCM audio data in a WAV container in memory."""
    audio_buffer = io.BytesIO()
    with wave.open(audio_buffer, 'wb') as wf:
        wf.setnchannels(channels)
        wf.setsampwidth(sample_width)
        wf.setframerate(sample_rate)
        wf.writeframes(pcm_data)
    audio_buffer.seek(0)
    return audio_buffer.getvalue()

    
#Gemini tts implementation SOTA but slow
'''
def generate_tts_audio_and_upload(text_to_speak, uid, project_id, step_num):
    """Generates audio using the exact method from the Streamlit app and uploads it."""
    try:
        response = client.models.generate_content(
            model=TTS_MODEL,
            contents=f"""You are an articulate AI assistant — confident and precise like Jarvis.Rephrase the instruction naturally using simple expert language.
                         Speak with a brisk, clear British accent.
                         Avoid reading word for word — explain it like you know it.
                         No quips or acknowledging the prompt just narrate this step:
                      {text_to_speak}""",
            config=types.GenerateContentConfig(
                response_modalities=["AUDIO"],
                speech_config=types.SpeechConfig(
                    voice_config=types.VoiceConfig(
                        prebuilt_voice_config=types.PrebuiltVoiceConfig(voice_name='Sadaltager')
                    )
                ),
            )
        )
        audio_part = response.candidates[0].content.parts[0]
        audio_data = audio_part.inline_data.data
        mime_type = audio_part.inline_data.mime_type
        
        final_audio_bytes = _convert_pcm_to_wav(audio_data) if 'pcm' in mime_type else audio_data
        
        audio_path = f"users/{uid}/projects/{project_id}/narrations/step_{step_num}.wav"
        return upload_to_storage(final_audio_bytes, audio_path, 'audio/wav')
    except Exception as e:
        print(f"Error during TTS generation for step {step_num}: {e}")
        return None
'''

# DeepGram faster and efficient
def generate_tts_audio_and_upload(text_to_speak, uid, project_id, step_num):
    """
    Generates audio using the Deepgram TTS API and uploads it to Firebase Storage.
    This is a drop-in replacement for the previous Google GenAI TTS function.
    """
    try:
        # --- Step 1: Get the Deepgram API Key from environment variables ---
        api_key = os.environ.get("DEEPGRAM_API_KEY")
        if not api_key:
            print("FATAL: DEEPGRAM_API_KEY environment variable not set.")
            return None

        # --- Step 2: Define the API endpoint and headers ---
        # The model 'aura-2-draco-en' is specified as a query parameter in the URL.
        DEEPGRAM_URL = "https://api.deepgram.com/v1/speak?model=aura-2-draco-en"
        
        headers = {
            "Authorization": f"Token {api_key}",
            "Content-Type": "text/plain"  # As per Deepgram's requirement for this type of request
        }

        # --- Step 3: Make the API call to Deepgram ---
        # Deepgram expects the raw text as the request body, not in a JSON object.
        # We send the text directly in the 'data' parameter.
        response = requests.post(DEEPGRAM_URL, headers=headers, data=text_to_speak.encode('utf-8'))
        
        # Raise an exception for bad status codes (4xx or 5xx)
        response.raise_for_status()

        # The raw audio data is in the response content
        audio_data = response.content

        # --- Step 4: Upload the received audio to Firebase Storage ---
        # The output format from this Deepgram model is MP3.
        audio_path = f"users/{uid}/projects/{project_id}/narrations/step_{step_num}.mp3"
        
        # The MIME type for MP3 is 'audio/mpeg'.
        narration_url = upload_to_storage(audio_data, audio_path, 'audio/mpeg')
        
        return narration_url

    except requests.exceptions.RequestException as e:
        print(f"Error during Deepgram API call for step {step_num}: {e}")
        # Log the response body if available for more detailed error info
        if e.response is not None:
            print(f"Deepgram Error Response: {e.response.text}")
        return None
    except Exception as e:
        print(f"An unexpected error occurred during TTS generation for step {step_num}: {e}")
        return None


def send_text_request(model_name, prompt, image):
    """Helper to send requests that expect only a text response."""
    try:
        chat = client.chats.create(model=model_name)
        response = chat.send_message([prompt, image])
        response_text = "".join(part.text for part in response.candidates[0].content.parts if hasattr(part, 'text'))
        return response_text.strip()
    except Exception as e:
        print(f"Error with model {model_name}: {e}")
        return None


import logging

# Configure logging at the top of your file if not already done
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# =============================================================================
# OPEN IMAGE PROXY ENDPOINT (NO AUTHENTICATION)
# =============================================================================
@app.route('/api/image-proxy', methods=['GET'])
def image_proxy():
    image_url = request.args.get('url')
    logger.info(f"[IMAGE PROXY] Received URL: {image_url}")
    
    if not image_url:
        logger.error("[IMAGE PROXY] ERROR: URL parameter is missing")
        return jsonify({'error': 'URL parameter is missing.'}), 400

    try:
        # Parse Firebase Storage URL
        # Expected format: https://storage.googleapis.com/bucket-name/path/to/file.ext
        if 'storage.googleapis.com' not in image_url:
            logger.error(f"[IMAGE PROXY] ERROR: Invalid Firebase Storage URL: {image_url}")
            return jsonify({'error': 'Invalid Firebase Storage URL.'}), 400
        
        logger.info(f"[IMAGE PROXY] Parsing URL: {image_url}")
        
        # Extract bucket name and blob path from the URL
        url_parts = image_url.split('storage.googleapis.com/')[1]
        logger.info(f"[IMAGE PROXY] URL parts after split: {url_parts}")
        
        # Remove query parameters if present
        url_parts = url_parts.split('?')[0]
        logger.info(f"[IMAGE PROXY] URL parts after removing query params: {url_parts}")
        
        # Split into bucket name and blob path
        path_components = url_parts.split('/', 1)
        logger.info(f"[IMAGE PROXY] Path components: {path_components}")
        
        if len(path_components) < 2:
            logger.error(f"[IMAGE PROXY] ERROR: Invalid URL format - path_components: {path_components}")
            return jsonify({'error': 'Invalid URL format.'}), 400
            
        url_bucket_name = path_components[0]
        blob_path = path_components[1]
        
        logger.info(f"[IMAGE PROXY] Extracted bucket name: {url_bucket_name}")
        logger.info(f"[IMAGE PROXY] Extracted blob path: {blob_path}")
        
        # Verify bucket name matches (optional security check)
        expected_bucket_name = bucket.name
        logger.info(f"[IMAGE PROXY] Expected bucket name: {expected_bucket_name}")
        
        if url_bucket_name != expected_bucket_name:
            logger.error(f"[IMAGE PROXY] ERROR: Bucket name mismatch - URL: {url_bucket_name}, Expected: {expected_bucket_name}")
            return jsonify({'error': 'Bucket name mismatch.'}), 403
        
        logger.info(f"[IMAGE PROXY] Creating blob object for path: {blob_path}")
        
        # Get the blob
        blob = bucket.blob(blob_path)

        logger.info(f"[IMAGE PROXY] Checking if blob exists...")
        if not blob.exists():
            logger.error(f"[IMAGE PROXY] ERROR: Image not found at path: {blob_path}")
            return jsonify({'error': 'Image not found.'}), 404

        logger.info(f"[IMAGE PROXY] Downloading blob...")
        # Download and return the image
        image_bytes = blob.download_as_bytes()
        content_type = blob.content_type or 'application/octet-stream'
        
        logger.info(f"[IMAGE PROXY] Successfully downloaded {len(image_bytes)} bytes, content-type: {content_type}")
        
        # Add cache headers for better performance
        response = Response(image_bytes, content_type=content_type)
        response.headers['Cache-Control'] = 'public, max-age=3600'  # Cache for 1 hour
        return response

    except IndexError as e:
        logger.error(f"[IMAGE PROXY] URL parsing IndexError: {e}")
        logger.error(f"[IMAGE PROXY] URL was: {image_url}")
        return jsonify({'error': 'Invalid URL format.'}), 400
    except Exception as e:
        # This will catch parsing errors or other unexpected issues.
        logger.error(f"[IMAGE PROXY] Unexpected error: {e}")
        logger.error(f"[IMAGE PROXY] Error type: {type(e).__name__}")
        logger.error(f"[IMAGE PROXY] URL was: {image_url}")
        import traceback
        logger.error(f"[IMAGE PROXY] Full traceback: {traceback.format_exc()}")
        return jsonify({'error': 'Internal server error processing the image request.'}), 500

# -----------------------------------------------------------------------------
# 3. AUTHENTICATION & USER MANAGEMENT (Corrected Version)
# -----------------------------------------------------------------------------

@app.route('/api/auth/signup', methods=['POST'])
def signup():
    """
    Handles new user sign-up with email/password.
    ✅ FIX: Now accepts an optional 'displayName' and saves it.
    """
    try:
        data = request.get_json()
        email, password = data.get('email'), data.get('password')
        # Get the optional displayName
        display_name = data.get('displayName') # Will be None if not provided

        if not email or not password:
            return jsonify({'error': 'Email and password are required'}), 400

        # Create the user in Firebase Authentication, including the displayName if available
        user = auth.create_user(
            email=email,
            password=password,
            display_name=display_name
        )
        
        # Create the corresponding user profile in the Realtime Database
        user_ref = db_ref.child(f'users/{user.uid}')
        user_data = {
            'email': email,
            'displayName': display_name, # Save the name to the database
            'credits': 15,
            'is_admin': False,
            'createdAt': datetime.utcnow().isoformat()
        }
        user_ref.set(user_data)
        
        logger.info(f"New user signed up: {user.uid}, Name: {display_name}")
        return jsonify({'success': True, 'uid': user.uid, **user_data}), 201
        
    except Exception as e:
        logger.error(f"Signup failed: {e}")
        # Provide a more specific error for existing users
        if 'EMAIL_EXISTS' in str(e):
            return jsonify({'error': 'An account with this email already exists.'}), 409
        return jsonify({'error': str(e)}), 400

@app.route('/api/auth/social-signin', methods=['POST'])
def social_signin():
    """
    Ensures a user record exists and is up-to-date in the Realtime Database.
    ✅ IMPROVEMENT: Now backfills the displayName for existing social users
    if it's missing from the database.
    """
    uid = verify_token(request.headers.get('Authorization'))
    if not uid:
        return jsonify({'error': 'Invalid or expired token'}), 401

    user_ref = db_ref.child(f'users/{uid}')
    user_data = user_ref.get()

    if user_data:
        # User already exists. Check if their displayName is missing.
        if 'displayName' not in user_data or user_data['displayName'] is None:
            try:
                # The name is missing in our DB, let's sync it from Auth.
                firebase_user = auth.get_user(uid)
                if firebase_user.display_name:
                    logger.info(f"Backfilling missing displayName for existing user {uid}.")
                    user_ref.update({'displayName': firebase_user.display_name})
                    # Get the updated data to return to the client
                    user_data = user_ref.get()
            except Exception as e:
                logger.error(f"Could not backfill displayName for user {uid}: {e}")
        
        return jsonify({'uid': uid, **user_data}), 200
    else:
        # This is a new user (first social login), create their full profile.
        logger.info(f"New social user detected: {uid}. Creating database profile.")
        try:
            firebase_user = auth.get_user(uid)
            new_user_data = {
                'email': firebase_user.email,
                'displayName': firebase_user.display_name,
                'credits': 15,
                'is_admin': False,
                'createdAt': datetime.utcnow().isoformat()
            }
            user_ref.set(new_user_data)
            
            logger.info(f"Successfully created profile for new social user: {uid}")
            return jsonify({'success': True, 'uid': uid, **new_user_data}), 201
        except Exception as e:
            logger.error(f"Error creating profile for new social user {uid}: {e}")
            return jsonify({'error': f'Failed to create user profile: {str(e)}'}), 500


@app.route('/api/user/profile', methods=['GET'])
def get_user_profile():
    """
    Retrieves the user's profile from the Realtime Database.
    ✅ FIX: This now correctly includes the 'displayName' in the response.
    """
    uid = verify_token(request.headers.get('Authorization'))
    if not uid:
        return jsonify({'error': 'Invalid or expired token'}), 401
    
    user_data = db_ref.child(f'users/{uid}').get()
    if not user_data:
        return jsonify({'error': 'User not found'}), 404
    
    return jsonify({'uid': uid, **user_data})

@app.route('/api/user/profile', methods=['PUT'])
def update_user_profile():
    """
    ✅ NEW: Allows a logged-in user to update their profile, specifically their displayName.
    """
    uid = verify_token(request.headers.get('Authorization'))
    if not uid:
        return jsonify({'error': 'Invalid or expired token'}), 401

    data = request.get_json()
    new_display_name = data.get('displayName')

    if not new_display_name or not isinstance(new_display_name, str) or len(new_display_name.strip()) == 0:
        return jsonify({'error': 'A valid displayName is required.'}), 400

    try:
        # Step 1: Update the user record in Firebase Authentication
        auth.update_user(uid, display_name=new_display_name)
        
        # Step 2: Update the user profile in the Realtime Database
        user_ref = db_ref.child(f'users/{uid}')
        user_ref.update({'displayName': new_display_name})
        
        logger.info(f"User {uid} updated their displayName to '{new_display_name}'.")
        return jsonify({'success': True, 'message': 'Profile updated successfully.'}), 200

    except Exception as e:
        logger.error(f"Error updating profile for user {uid}: {e}")
        return jsonify({'error': f'Failed to update profile: {str(e)}'}), 500
        
# -----------------------------------------------------------------------------
# 4. FEEDBACK AND CREDIT REQUESTS (USER-FACING)
# -----------------------------------------------------------------------------

@app.route('/api/feedback', methods=['POST'])
def submit_feedback():
    uid = verify_token(request.headers.get('Authorization'))
    if not uid: return jsonify({'error': 'Invalid or expired token'}), 401

    try:
        data = request.get_json()
        if not data or not data.get('message'): return jsonify({'error': 'Message is required'}), 400

        user_email = (db_ref.child(f'users/{uid}').get() or {}).get('email', 'unknown')
        
        feedback_ref = db_ref.child('feedback').push()
        feedback_record = {
            "feedbackId": feedback_ref.key,
            "userId": uid,
            "userEmail": user_email,
            "type": data.get('type', 'general'),
            "message": data.get('message'),
            "createdAt": datetime.utcnow().isoformat(),
            "status": "open"
        }
        feedback_ref.set(feedback_record)
        return jsonify({"success": True, "feedbackId": feedback_ref.key}), 201
    except Exception as e:
        return jsonify({'error': str(e)}), 500

@app.route('/api/user/request-credits', methods=['POST'])
def request_credits():
    uid = verify_token(request.headers.get('Authorization'))
    if not uid: return jsonify({'error': 'Invalid or expired token'}), 401
    
    try:
        data = request.get_json()
        if not data or 'requested_credits' not in data: return jsonify({'error': 'requested_credits is required'}), 400

        request_ref = db_ref.child('credit_requests').push()
        request_ref.set({
            'requestId': request_ref.key,
            'userId': uid,
            'requested_credits': data['requested_credits'],
            'status': 'pending',
            'requestedAt': datetime.utcnow().isoformat()
        })
        return jsonify({'success': True, 'requestId': request_ref.key})
    except Exception as e:
        return jsonify({'error': str(e)}), 500

# -----------------------------------------------------------------------------
# 5. ADMIN ENDPOINTS
# -----------------------------------------------------------------------------

@app.route('/api/admin/profile', methods=['GET'])
def get_admin_profile():
    try:
        admin_uid = verify_admin(request.headers.get('Authorization'))
        
        # Fetch all necessary data from Firebase in one go
        all_users = db_ref.child('users').get() or {}
        all_projects = db_ref.child('projects').get() or {}
        all_feedback = db_ref.child('feedback').get() or {}
        all_credit_requests = db_ref.child('credit_requests').get() or {}

        # --- User Statistics Calculation ---
        total_users = len(all_users)
        admin_count = 0
        total_credits_in_system = 0
        new_users_last_7_days = 0
        seven_days_ago = datetime.utcnow() - timedelta(days=7)

        for user_data in all_users.values():
            if user_data.get('is_admin', False):
                admin_count += 1
            total_credits_in_system += user_data.get('credits', 0)
            
            # Check for new users
            try:
                created_at_str = user_data.get('createdAt')
                if created_at_str:
                    # Accommodate different possible ISO formats
                    user_created_at = datetime.fromisoformat(created_at_str.replace('Z', '+00:00'))
                    if user_created_at.replace(tzinfo=None) > seven_days_ago:
                        new_users_last_7_days += 1
            except (ValueError, TypeError):
                # Ignore if date format is invalid or missing
                pass

        # --- Project Statistics Calculation ---
        total_projects = len(all_projects)
        projects_by_status = {
            "awaiting_approval": 0,
            "awaiting_selection": 0,
            "ready": 0,
            "unknown": 0
        }
        projects_by_category = {}

        for project_data in all_projects.values():
            # Tally by status
            status = project_data.get('status', 'unknown')
            projects_by_status[status] = projects_by_status.get(status, 0) + 1
            
            # Tally by category
            category = project_data.get('category', 'N/A')
            projects_by_category[category] = projects_by_category.get(category, 0) + 1

        # --- System Health Calculation ---
        open_feedback_count = sum(1 for fb in all_feedback.values() if fb.get('status') == 'open')
        pending_requests_count = sum(1 for req in all_credit_requests.values() if req.get('status') == 'pending')

        # Assemble the final response object
        admin_personal_data = all_users.get(admin_uid, {})
        
        response_data = {
            'uid': admin_uid,
            'email': admin_personal_data.get('email'),
            'credits': admin_personal_data.get('credits'),
            'is_admin': True,
            'dashboardStats': {
                'users': {
                    'total': total_users,
                    'admins': admin_count,
                    'regular': total_users - admin_count,
                    'newLast7Days': new_users_last_7_days,
                    'totalCreditsInSystem': total_credits_in_system
                },
                'projects': {
                    'total': total_projects,
                    'byStatus': projects_by_status,
                    'byCategory': projects_by_category
                },
                'system': {
                    'openFeedback': open_feedback_count,
                    'pendingCreditRequests': pending_requests_count
                }
            }
        }
        
        return jsonify(response_data), 200

    except PermissionError as e:
        return jsonify({'error': str(e)}), 403 # Use 403 Forbidden for permission issues
    except Exception as e:
        print(traceback.format_exc())
        return jsonify({'error': f"An internal error occurred: {e}"}), 500

@app.route('/api/admin/credit_requests', methods=['GET'])
def list_credit_requests():
    try:
        verify_admin(request.headers.get('Authorization'))
        requests_data = db_ref.child('credit_requests').get() or {}
        return jsonify(list(requests_data.values()))
    except Exception as e:
        return jsonify({'error': str(e)}), 500

@app.route('/api/admin/credit_requests/<string:request_id>', methods=['PUT'])
def process_credit_request(request_id):
    try:
        admin_uid = verify_admin(request.headers.get('Authorization'))
        req_ref = db_ref.child(f'credit_requests/{request_id}')
        req_data = req_ref.get()
        if not req_data: return jsonify({'error': 'Credit request not found'}), 404

        decision = request.json.get('decision')
        if decision not in ['approved', 'declined']: return jsonify({'error': 'Decision must be "approved" or "declined"'}), 400

        if decision == 'approved':
            user_ref = db_ref.child(f'users/{req_data["userId"]}')
            user_data = user_ref.get()
            if user_data:
                new_total = user_data.get('credits', 0) + int(req_data.get('requested_credits', 0))
                user_ref.update({'credits': new_total})
        
        req_ref.update({'status': decision, 'processedBy': admin_uid, 'processedAt': datetime.utcnow().isoformat()})
        return jsonify({'success': True, 'message': f'Request {decision}.'})
    except Exception as e:
        return jsonify({'error': str(e)}), 500

@app.route('/api/admin/feedback', methods=['GET'])
def admin_view_feedback():
    try:
        verify_admin(request.headers.get('Authorization'))
        feedback_data = db_ref.child('feedback').get() or {}
        return jsonify(list(feedback_data.values()))
    except Exception as e:
        return jsonify({'error': str(e)}), 500

@app.route('/api/admin/users', methods=['GET'])
def admin_list_users():
    try:
        verify_admin(request.headers.get('Authorization'))
        all_users = db_ref.child('users').get() or {}
        user_list = [{'uid': uid, **data} for uid, data in all_users.items()]
        return jsonify(user_list)
    except Exception as e:
        return jsonify({'error': str(e)}), 500

@app.route('/api/admin/users/<string:uid>/credits', methods=['PUT'])
def admin_update_credits(uid):
    try:
        verify_admin(request.headers.get('Authorization'))
        add_credits = request.json.get('add_credits')
        if add_credits is None: return jsonify({'error': 'add_credits is required'}), 400

        user_ref = db_ref.child(f'users/{uid}')
        user_data = user_ref.get()
        if not user_data: return jsonify({'error': 'User not found'}), 404

        new_total = user_data.get('credits', 0) + float(add_credits)
        user_ref.update({'credits': new_total})
        return jsonify({'success': True, 'new_total_credits': new_total})
    except Exception as e:
        return jsonify({'error': str(e)}), 500

# -----------------------------------------------------------------------------
# 6. DIY PROJECT ENDPOINTS (Core Logic)
# -----------------------------------------------------------------------------
# (The project endpoints from the previous answer go here, unchanged)
@app.route('/api/projects', methods=['POST'])
def create_project():
    uid = verify_token(request.headers.get('Authorization'))
    if not uid: return jsonify({'error': 'Unauthorized'}), 401

    user_ref = db_ref.child(f'users/{uid}')
    user_data = user_ref.get()
    if not user_data or user_data.get('credits', 0) < 1:
        return jsonify({'error': 'Insufficient credits'}), 402

    if 'image' not in request.files:
        return jsonify({'error': 'Image file is required'}), 400
    
    image_file = request.files['image']
    context_text = request.form.get('contextText', '')
    image_bytes = image_file.read()
    pil_image = Image.open(io.BytesIO(image_bytes))

    try:
        category_prompt = (
            "You are an expert DIY assistant. Analyze the user's image and context. "
            f"Context: '{context_text}'. "
            "Categorize the project into ONE of the following: "
            "Home Appliance Repair, Automotive Maintenance, Gardening & Urban Farming, "
            "Upcycling & Sustainable Crafts, or DIY Project Creation. "
            "Reply with ONLY the category name."
        )
        category = send_text_request(CATEGORY_MODEL, category_prompt, pil_image)
        if not category: return jsonify({'error': 'Failed to get project category from AI.'}), 500

        plan_prompt = f"""
        You are an expert DIY assistant in the category: {category}.
        User Context: "{context_text if context_text else 'No context provided.'}"
        Based on the image and context, perform the following:
        1.  **Title:** Create a short, clear title for this project.
        2.  **Description:** Write a brief, one-paragraph description of the goal.
        3.  **Initial Plan:**
            - If 'Upcycling & Sustainable Crafts' AND no specific project is mentioned, propose three distinct project options as a numbered list under "UPCYCLING OPTIONS:".
            - For all other cases, briefly outline the main stages of the proposed solution.
        Structure your response EXACTLY like this:
        TITLE: [Your title]
        DESCRIPTION: [Your description]
        INITIAL PLAN:
        [Your plan or 3 options]
        """
        plan_response = send_text_request(GENERATION_MODEL, plan_prompt, pil_image)
        if not plan_response: return jsonify({'error': 'Failed to generate project plan from AI.'}), 500
        
        title = re.search(r"TITLE:\s*(.*)", plan_response).group(1).strip()
        description = re.search(r"DESCRIPTION:\s*(.*)", plan_response, re.DOTALL).group(1).strip()
        initial_plan_text = re.search(r"INITIAL PLAN:\s*(.*)", plan_response, re.DOTALL).group(1).strip()

        upcycling_options = re.findall(r"^\s*\d+\.\s*(.*)", initial_plan_text, re.MULTILINE) if "UPCYCLING OPTIONS:" in initial_plan_text else []
        initial_plan = initial_plan_text if not upcycling_options else ""
        status = "awaiting_selection" if upcycling_options else "awaiting_approval"
        
        project_id = str(uuid.uuid4())
        image_path = f"users/{uid}/projects/{project_id}/initial_image.png"
        image_url = upload_to_storage(image_bytes, image_path, content_type=image_file.content_type)

        project_data = {
            "uid": uid, "projectId": project_id, "status": status, "createdAt": datetime.utcnow().isoformat(),
            "userImageURL": image_url, "contextText": context_text, "projectTitle": title,
            "projectDescription": description, "category": category, "initialPlan": initial_plan,
            "upcyclingOptions": upcycling_options, "toolsList": [], "steps": []
        }
        db_ref.child(f'projects/{project_id}').set(project_data)

        user_ref.update({'credits': user_data.get('credits', 0) - 1})
        return jsonify(project_data), 201

    except Exception as e:
        print(traceback.format_exc())
        return jsonify({'error': f"An error occurred: {e}"}), 500


@app.route('/api/projects/<string:project_id>/approve', methods=['PUT'])
def approve_project_plan(project_id):
    start_time = time.time()
    logger.info(f"[PROJECT APPROVAL] Starting approval process for project: {project_id}")
    
    # Authorization timing
    auth_start = time.time()
    uid = verify_token(request.headers.get('Authorization'))
    if not uid:
        logger.error(f"[PROJECT APPROVAL] ERROR: Unauthorized access attempt for project: {project_id}")
        return jsonify({'error': 'Unauthorized'}), 401
    auth_time = time.time() - auth_start
    logger.info(f"[PROJECT APPROVAL] Authorization completed in {auth_time:.3f}s for user: {uid}")

    # User data fetch timing
    user_fetch_start = time.time()
    user_ref = db_ref.child(f'users/{uid}')
    user_data = user_ref.get()
    if not user_data or user_data.get('credits', 0) < 5:
        logger.error(f"[PROJECT APPROVAL] ERROR: Insufficient credits for user: {uid}, credits: {user_data.get('credits', 0) if user_data else 0}")
        return jsonify({'error': 'Insufficient credits'}), 402
    user_fetch_time = time.time() - user_fetch_start
    logger.info(f"[PROJECT APPROVAL] User data fetch completed in {user_fetch_time:.3f}s, credits: {user_data.get('credits', 0)}")

    # Project data fetch timing
    project_fetch_start = time.time()
    project_ref = db_ref.child(f'projects/{project_id}')
    project_data = project_ref.get()
    if not project_data or project_data.get('uid') != uid:
        logger.error(f"[PROJECT APPROVAL] ERROR: Project not found or access denied - project_id: {project_id}, uid: {uid}")
        return jsonify({'error': 'Project not found or access denied'}), 404
    project_fetch_time = time.time() - project_fetch_start
    logger.info(f"[PROJECT APPROVAL] Project data fetch completed in {project_fetch_time:.3f}s for project: {project_data.get('projectTitle', 'Unknown')}")

    # Image download and processing timing
    selected_option = request.json.get('selectedOption')
    logger.info(f"[PROJECT APPROVAL] Selected option: {selected_option}")
    
    image_download_start = time.time()
    response = requests.get(project_data['userImageURL'])
    image_download_time = time.time() - image_download_start
    logger.info(f"[PROJECT APPROVAL] Image download completed in {image_download_time:.3f}s, size: {len(response.content)} bytes")
    
    image_processing_start = time.time()
    pil_image = Image.open(io.BytesIO(response.content)).convert('RGB')
    image_processing_time = time.time() - image_processing_start
    logger.info(f"[PROJECT APPROVAL] Image processing completed in {image_processing_time:.3f}s")

    # Context preparation timing
    context_start = time.time()
    context = (
        f"The user chose the upcycling project: '{selected_option}'."
        if selected_option
        else f"The user has approved the plan for '{project_data['projectTitle']}'."
    )

    detailed_prompt = f"""
    You are a DIY expert. The user wants to proceed with the project titled "{project_data['projectTitle']}".
    {context}
    Provide a detailed guide. For each step, you MUST provide a simple, clear illustrative image.
    Format your response EXACTLY like this:
    TOOLS AND MATERIALS:
    - Tool A
    - Material B
    STEPS(Maximum 5 steps):
    1. First step instructions.
    2. Second step instructions...
    """
    context_time = time.time() - context_start
    logger.info(f"[PROJECT APPROVAL] Context preparation completed in {context_time:.3f}s")

    try:
        # AI generation timing
        ai_start = time.time()
        logger.info(f"[PROJECT APPROVAL] Starting AI generation with model: {GENERATION_MODEL}")
        
        chat = client.chats.create(
            model=GENERATION_MODEL,
            config=types.GenerateContentConfig(response_modalities=["Text", "Image"])
        )
        full_resp = chat.send_message([detailed_prompt, pil_image])
        ai_time = time.time() - ai_start
        logger.info(f"[PROJECT APPROVAL] AI generation completed in {ai_time:.3f}s")
        
        # Response parsing timing
        parsing_start = time.time()
        gen_parts = full_resp.candidates[0].content.parts

        combined_text = ""
        inline_images = []
        for part in gen_parts:
            if part.text is not None:
                combined_text += part.text + "\n"
            if part.inline_data is not None:
                img = Image.open(io.BytesIO(part.inline_data.data)).convert('RGB')
                inline_images.append(img)

        combined_text = combined_text.strip()
        parsing_time = time.time() - parsing_start
        logger.info(f"[PROJECT APPROVAL] Response parsing completed in {parsing_time:.3f}s, found {len(inline_images)} images")

        # Text extraction timing
        extraction_start = time.time()
        tools_section = re.search(r"TOOLS AND MATERIALS:\s*(.*?)\s*STEPS:", combined_text, re.DOTALL).group(1).strip()
        steps_section = re.search(r"STEPS:\s*(.*)", combined_text, re.DOTALL).group(1).strip()

        tools_list = [line.strip("- ").strip() for line in tools_section.split('\n') if line.strip()]
        parsed_steps = parse_numbered_steps(steps_section)
        extraction_time = time.time() - extraction_start
        logger.info(f"[PROJECT APPROVAL] Text extraction completed in {extraction_time:.3f}s, tools: {len(tools_list)}, steps: {len(parsed_steps)}")

        if len(parsed_steps) != len(inline_images):
            logger.error(f"[PROJECT APPROVAL] ERROR: AI response mismatch - Steps: {len(parsed_steps)}, Images: {len(inline_images)}")
            return jsonify({'error': 'AI response mismatch: Steps and images do not match.'}), 500

        # Step processing timing
        step_processing_start = time.time()
        final_steps = []
        total_upload_time = 0
        total_tts_time = 0
        
        for i, step_info in enumerate(parsed_steps):
            logger.info(f"[PROJECT APPROVAL] Processing step {i+1}/{len(parsed_steps)}")
            
            # Image upload timing
            image_upload_start = time.time()
            img_byte_arr = io.BytesIO()
            inline_images[i].save(img_byte_arr, format='JPEG', optimize=True, quality=70)
            img_path = f"users/{uid}/projects/{project_id}/steps/step_{i+1}_image.jpg"
            img_url = upload_to_storage(img_byte_arr.getvalue(), img_path, 'image/jpeg')
            image_upload_time = time.time() - image_upload_start
            total_upload_time += image_upload_time
            logger.info(f"[PROJECT APPROVAL] Step {i+1} image upload completed in {image_upload_time:.3f}s")

            # TTS generation timing
            tts_start = time.time()
            narration_url = generate_tts_audio_and_upload(step_info['text'], uid, project_id, i + 1)
            tts_time = time.time() - tts_start
            total_tts_time += tts_time
            logger.info(f"[PROJECT APPROVAL] Step {i+1} TTS generation completed in {tts_time:.3f}s")
            
            step_info.update({
                "imageUrl": img_url,
                "narrationUrl": narration_url,
                "isDone": False,
                "notes": ""
            })
            final_steps.append(step_info)

        step_processing_time = time.time() - step_processing_start
        logger.info(f"[PROJECT APPROVAL] All steps processing completed in {step_processing_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL] Total upload time: {total_upload_time:.3f}s, Total TTS time: {total_tts_time:.3f}s")

        # Database update timing
        db_update_start = time.time()
        update_data = {
            "status": "ready",
            "toolsList": tools_list,
            "steps": final_steps,
            "selectedOption": selected_option or ""
        }
        project_ref.update(update_data)
        logger.info(f"[PROJECT APPROVAL] uodating data in db: {update_data}")
        db_update_time = time.time() - db_update_start
        logger.info(f"[PROJECT APPROVAL] Database update completed in {db_update_time:.3f}s")

        # Final project fetch timing
        final_fetch_start = time.time()
        updated_project = project_ref.get()
        updated_project["projectId"] = project_id
        final_fetch_time = time.time() - final_fetch_start
        logger.info(f"[PROJECT APPROVAL] Final project fetch completed in {final_fetch_time:.3f}s")

        # Credits deduction timing
        credits_update_start = time.time()
        user_ref.update({'credits': user_data.get('credits', 0) - 5})
        credits_update_time = time.time() - credits_update_start
        logger.info(f"[PROJECT APPROVAL] Credits update completed in {credits_update_time:.3f}s")

        # Total time calculation
        total_time = time.time() - start_time
        logger.info(f"[PROJECT APPROVAL] SUCCESS: Project approval completed in {total_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL] TIMING BREAKDOWN:")
        logger.info(f"[PROJECT APPROVAL]   - Authorization: {auth_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - User fetch: {user_fetch_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Project fetch: {project_fetch_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Image download: {image_download_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Image processing: {image_processing_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Context prep: {context_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - AI generation: {ai_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Response parsing: {parsing_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Text extraction: {extraction_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Step processing: {step_processing_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]     - Total uploads: {total_upload_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]     - Total TTS: {total_tts_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - DB update: {db_update_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Final fetch: {final_fetch_time:.3f}s")
        logger.info(f"[PROJECT APPROVAL]   - Credits update: {credits_update_time:.3f}s")
        
        return jsonify(updated_project)

    except Exception as e:
        total_time = time.time() - start_time
        logger.error(f"[PROJECT APPROVAL] ERROR: Exception occurred after {total_time:.3f}s: {e}")
        logger.error(f"[PROJECT APPROVAL] Error type: {type(e).__name__}")
        logger.error(f"[PROJECT APPROVAL] Project ID: {project_id}, User ID: {uid}")
        import traceback
        logger.error(f"[PROJECT APPROVAL] Full traceback: {traceback.format_exc()}")
        return jsonify({'error': str(e)}), 500

@app.route('/api/projects', methods=['GET'])
def list_projects():
    uid = verify_token(request.headers.get('Authorization'))
    if not uid: return jsonify({'error': 'Unauthorized'}), 401
    projects = (db_ref.child('projects').order_by_child('uid').equal_to(uid).get() or {}).values()
    return jsonify(list(projects))

@app.route('/api/projects/<string:project_id>', methods=['GET'])
def get_project(project_id):
    uid = verify_token(request.headers.get('Authorization'))
    if not uid: return jsonify({'error': 'Unauthorized'}), 401
    project_data = db_ref.child(f'projects/{project_id}').get()
    if not project_data or project_data.get('uid') != uid:
        return jsonify({'error': 'Project not found or access denied'}), 404
    return jsonify(project_data)

@app.route('/api/projects/<string:project_id>/step/<int:step_number>', methods=['PUT'])
def update_step(project_id, step_number):
    uid = verify_token(request.headers.get('Authorization'))
    if not uid: return jsonify({'error': 'Unauthorized'}), 401
    data = request.get_json()
    if data is None: return jsonify({'error': 'JSON body is required'}), 400

    project_data = db_ref.child(f'projects/{project_id}').get()
    if not project_data or project_data.get('uid') != uid:
        return jsonify({'error': 'Project not found or access denied'}), 404

    steps = project_data.get('steps', [])
    step_index = next((i for i, s in enumerate(steps) if s.get('stepNumber') == step_number), -1)
    if step_index == -1: return jsonify({'error': f'Step number {step_number} not found'}), 404

    step_path = f'projects/{project_id}/steps/{step_index}'
    if 'isDone' in data: db_ref.child(f'{step_path}/isDone').set(bool(data['isDone']))
    if 'notes' in data: db_ref.child(f'{step_path}/notes').set(str(data['notes']))
    
    return jsonify({"success": True, "updatedStep": db_ref.child(step_path).get()})

@app.route('/api/projects/<string:project_id>', methods=['DELETE'])
def delete_project(project_id):
    uid = verify_token(request.headers.get('Authorization'))
    if not uid: return jsonify({'error': 'Unauthorized'}), 401
    
    project_ref = db_ref.child(f'projects/{project_id}')
    project_data = project_ref.get()
    if not project_data or project_data.get('uid') != uid:
        return jsonify({'error': 'Project not found or access denied'}), 404

    project_ref.delete()
    for blob in bucket.list_blobs(prefix=f"users/{uid}/projects/{project_id}/"):
        blob.delete()
    return jsonify({"success": True, "message": f"Project {project_id} deleted."})


#------------------------
# AI phone call ElevenLabs
#-------------------------
import math

# This code should be added to your existing main.py file.
# It assumes 'db_ref', 'client', 'logger', and 'verify_token' are already defined.

def summarize_user_history(uid):
    """
    Fetches all of a user's past transcripts, sends them to Gemini for analysis,
    and returns a concise, actionable summary for the AI agent.
    """
    try:
        logger.info(f"[BRIEFING] Fetching transcript history for user: {uid}")
        transcripts_ref = db_ref.child(f'transcripts/{uid}')
        all_transcripts = transcripts_ref.get()

        if not all_transcripts:
            logger.info(f"[BRIEFING] No history found for user {uid}. Returning 'new user' summary.")
            return "This is a new user."

        history_list = []
        for transcript_data in all_transcripts.values():
            history_list.append({
                "date": transcript_data.get("createdAt"),
                "project_title": transcript_data.get("projectId"),
                "transcript": transcript_data.get("transcript")
            })
        
        history_json = json.dumps(history_list, indent=2)

        analyst_prompt = """
        You are a world-class executive assistant and data analyst. Your job is to analyze a user's conversation history with a DIY expert AI named Alfred. Your goal is to produce a 'Pre-Call Briefing' for Alfred that is concise, insightful, and focuses on personal details.

        The history will be a JSON string containing a list of past conversations. Each conversation has a date, project title, and a full transcript.

        Your task is to identify patterns and extract the following key details. If a detail is not mentioned, omit that line from the output.
        - Personal Context: Identify who the projects are for (e.g., 'wife', 'son') and any mentioned personal details (e.g., 'has a dog', 'works as a teacher').
        - Preferences: Note any mentioned tastes or preferences (e.g., 'likes rustic style', 'favorite color is green').
        - Skill Assessment: Assess their DIY skill level (e.g., 'Beginner, hesitant with power tools', 'Intermediate, comfortable with plumbing').
        - Tool Inventory: List any specific tools they have mentioned owning or needing (e.g., 'Owns a power drill', 'Needed to buy a special wrench').
        - Recurring Themes: Identify any patterns in their questions or struggles (e.g., 'Often asks for clarification on measurements', 'Struggles with painting techniques').

        Your output MUST be a series of bullet points. Do not add any conversational text or greetings. Start the entire response with 'Here is your briefing on this user:'.
        
        Example Output:
        Here is your briefing on this user:
        * Is building this project for: their daughter
        * Personal context: has a golden retriever
        * Assessed skill level: Beginner, but learns quickly
        * Known tools: owns a basic screwdriver set
        * Recurring themes: frequently asks for pet-safe material recommendations
        """

        logger.info(f"[BRIEFING] Sending {len(history_list)} transcripts to Gemini for summarization.")
        
        # ✅ THE FIX: Using the exact model name and API call structure you provided.
        response = client.models.generate_content(
            model='gemini-2.0-flash-lite',
            contents=[analyst_prompt, history_json]
        )
        
        summary = response.text.strip()
        logger.info(f"[BRIEFING] Received summary from Gemini: {summary}")
        return summary

    except Exception as e:
        logger.error(f"[BRIEFING] Failed to generate user summary for {uid}: {e}")
        return "Could not retrieve user history."


@app.route('/api/user/call-briefing', methods=['GET'])
def get_call_briefing():
    """
    The single endpoint for the frontend to call before starting a conversation.
    It orchestrates getting the user's history and summarizing it.
    """
    logger.info("[BRIEFING] Received request for a new call briefing.")
    
    uid = verify_token(request.headers.get('Authorization'))
    if not uid:
        return jsonify({'error': 'Unauthorized'}), 401

    try:
        memory_summary = summarize_user_history(uid)
        
        return jsonify({"memory_summary": memory_summary}), 200

    except Exception as e:
        logger.error(f"An unexpected error occurred in get_call_briefing for user {uid}: {e}")
        return jsonify({'error': 'Failed to generate call briefing.'}), 500

@app.route('/api/debug/test-agent', methods=['GET'])
def test_agent():
    """
    Fixed debug endpoint that tests the CORRECT conversation endpoint.
    """
    if not ELEVENLABS_API_KEY:
        return jsonify({'error': 'API key not set on server'}), 500
    
    headers = {"xi-api-key": ELEVENLABS_API_KEY}
    results = {'agent_id': AGENT_ID, 'tests': {}}
    
    try:
        # Test 1: Check if the agent can be found by its ID.
        agent_url = f"https://api.elevenlabs.io/v1/convai/agents/{AGENT_ID}"
        agent_resp = requests.get(agent_url, headers=headers, timeout=10)
        results['tests']['agent_check'] = {
            'status': agent_resp.status_code,
            'exists': agent_resp.ok
        }
        
        # Test 2: Check if we can get a signed URL for this agent. This is the most important test.
        conv_url = f"https://api.elevenlabs.io/v1/convai/conversation/get-signed-url?agent_id={AGENT_ID}"
        conv_resp = requests.get(conv_url, headers=headers, timeout=10)
        results['tests']['get_signed_url_check'] = {
            'status': conv_resp.status_code,
            'url_received': 'signed_url' in conv_resp.json() if conv_resp.ok else False
        }
        
        return jsonify(results)
        
    except Exception as e:
        return jsonify({'error': str(e), 'agent_id': AGENT_ID})

@app.route('/api/projects/<project_id>/log-call-usage', methods=['POST'])
def log_call_usage(project_id):
    """
    ✅ MODIFIED: Now accepts and stores the full conversation transcript
    in addition to calculating credit cost.
    """
    logger.info(f"[LOGGING] Received usage log for project: {project_id}")
    
    uid = verify_token(request.headers.get('Authorization'))
    if not uid:
        return jsonify({'error': 'Unauthorized'}), 401

    data = request.get_json()
    duration_seconds = data.get("durationSeconds")
    transcript = data.get("transcript") # Get the new transcript field

    if duration_seconds is None:
        return jsonify({'error': 'Invalid duration provided.'}), 400

    # --- Credit Calculation ---
    minutes = math.ceil(duration_seconds / 60)
    cost = minutes * 3
    logger.info(f"[LOGGING] User '{uid}' call duration: {duration_seconds:.2f}s, Cost: {cost} credits.")

    try:
        # --- Transcript Storage ---
        if transcript and isinstance(transcript, str) and len(transcript) > 10:
            transcript_id = f"{project_id}_{int(time.time())}"
            transcript_ref = db_ref.child(f'transcripts/{uid}/{transcript_id}')
            transcript_data = {
                "transcript": transcript,
                "projectId": project_id,
                "userId": uid,
                "durationSeconds": duration_seconds,
                "createdAt": datetime.utcnow().isoformat()
            }
            transcript_ref.set(transcript_data)
            logger.info(f"[LOGGING] Successfully stored transcript {transcript_id} for user '{uid}'.")
        else:
            logger.warning(f"[LOGGING] No valid transcript provided for user '{uid}' on project {project_id}.")

        # --- Credit Deduction ---
        user_ref = db_ref.child(f'users/{uid}')
        user_data = user_ref.get()

        if user_data is None:
            return jsonify({'error': 'User not found.'}), 404

        current_credits = user_data.get('credits', 0)
        new_credits = max(0, current_credits - cost)
        user_ref.update({'credits': new_credits})
        
        logger.info(f"[LOGGING] Updated credits for user '{uid}'. New balance: {new_credits}")
        return jsonify({
            "status": "success",
            "creditsDeducted": cost,
            "remainingCredits": new_credits
        }), 200

    except Exception as e:
        logger.error(f"[LOGGING] A database error occurred for user '{uid}': {e}")
        return jsonify({'error': 'A server error occurred while updating credits.'}), 500



# -----------------------------------------------------------------------------
# 7. MAIN EXECUTION
# -----------------------------------------------------------------------------
if __name__ == '__main__':
    app.run(debug=True, host="0.0.0.0", port=int(os.environ.get("PORT", 7860)))