app.py

import os
import time
import torch
from flask import Flask, render_template, request, jsonify
from simple_salesforce import Salesforce
from transformers import pipeline
from gtts import gTTS
from pydub import AudioSegment
from pydub.silence import detect_nonsilent
from transformers import AutoConfig  # Import AutoConfig for the config object
from waitress import serve

# Flask setup
app = Flask(__name__, template_folder="templates")
app.secret_key = os.urandom(24)

# Check for available GPU
device = "cuda" if torch.cuda.is_available() else "cpu"

# Set up Whisper model config
config = AutoConfig.from_pretrained("openai/whisper-small")
config.update({"timeout": 60})  # Set timeout to 60 seconds

# Salesforce connection
try:
    print("Attempting to connect to Salesforce...")
    sf = Salesforce(username='your_username', password='your_password', security_token='your_security_token')
    print("Connected to Salesforce successfully!")
except Exception as e:
    print(f"Failed to connect to Salesforce: {str(e)}")

# Function to generate audio prompt using gTTS
def generate_audio_prompt(text, filename):
    try:
        tts = gTTS(text)
        tts.save(os.path.join("static", filename))
    except Exception as e:
        print(f"Error generating audio prompt: {e}")
        time.sleep(5)
        generate_audio_prompt(text, filename)

# Example prompts for voice interaction
prompts = {
    "welcome": "Welcome to Biryani Hub.",
    "ask_name": "Tell me your name.",
    "ask_email": "Please provide your email address.",
    "thank_you": "Thank you for registration."
}

# Generate audio prompts
for key, text in prompts.items():
    generate_audio_prompt(text, f"{key}.mp3")

# Function to check if the audio is silent
def is_silent_audio(audio_path):
    audio = AudioSegment.from_wav(audio_path)
    nonsilent_parts = detect_nonsilent(audio, min_silence_len=500, silence_thresh=audio.dBFS-16)
    return len(nonsilent_parts) == 0

# Function to fetch menu items from Salesforce
def get_menu_items():
    try:
        # Salesforce query to fetch all menu items
        query = """
            SELECT Name, Price__c, Ingredients__c, Category__c 
            FROM Menu_Item__c
        """
        result = sf.query(query)
        menu_items = []
        for item in result["records"]:
            menu_items.append({
                "name": item["Name"],
                "price": item["Price__c"],
                "ingredients": item["Ingredients__c"],
                "category": item["Category__c"]
            })
        return menu_items
    except Exception as e:
        print(f"Error fetching menu items: {str(e)}")
        return []

# Function to check if the customer exists in Salesforce (login check)
def get_customer_login(name, email, phone_number):
    try:
        # Salesforce query to fetch customer based on Name, Email, and Phone Number
        query = f"""
            SELECT Id, Name, Email__c, Phone_Number__c
            FROM Customer_Login__c
            WHERE Name = '{name}'
            AND Email__c = '{email}'
            AND Phone_Number__c = '{phone_number}'
        """
        result = sf.query(query)
        if result["records"]:
            customer = result["records"][0]
            return {
                "id": customer["Id"],
                "name": customer["Name"],
                "email": customer["Email__c"],
                "phone": customer["Phone_Number__c"]
            }
        else:
            return None
    except Exception as e:
        print(f"Error fetching customer login details: {str(e)}")
        return None

# Function to create a new customer login in Salesforce
def create_customer_login(name, email, phone):
    try:
        # Create a new customer login record in Salesforce
        customer_login = sf.Customer_Login__c.create({
            'Name': name,
            'Email__c': email,
            'Phone_Number__c': phone
        })
        return customer_login
    except Exception as e:
        print(f"Error creating customer login: {str(e)}")
        return None

# Home Route (loads index.html)
@app.route("/", methods=["GET"])
def index():
    return render_template("index.html")

# Dashboard Route
@app.route("/dashboard", methods=["GET"])
def dashboard():
    return render_template("dashboard.html")

# Menu Page Route
@app.route("/menu_page", methods=["GET"])
def menu_page():
    menu_items = get_menu_items()
    return render_template("menu_page.html", menu=menu_items)

# Login API
@app.route('/login', methods=['POST'])
def login():
    data = request.json
    name = data.get('name')
    email = data.get('email')
    phone_number = data.get('phone_number')

    if not name or not email or not phone_number:
        return jsonify({'error': 'Missing required fields'}), 400

    # Check if the customer exists in Salesforce
    customer = get_customer_login(name, email, phone_number)
    if customer:
        return jsonify({'success': True, 'customer': customer}), 200
    else:
        return jsonify({'error': 'Customer not found'}), 404

# Register API (Create customer login)
@app.route("/submit", methods=["POST"])
def submit():
    data = request.json
    name = data.get('name')
    email = data.get('email')
    phone = data.get('phone')

    if not name or not email or not phone:
        return jsonify({'error': 'Missing data'}), 400

    # Create customer login record in Salesforce
    customer_login = create_customer_login(name, email, phone)
    if customer_login:
        return jsonify({'success': True}), 200
    else:
        return jsonify({'error': 'Failed to create customer record'}), 500

# Transcribe Audio API
@app.route("/transcribe", methods=["POST"])
def transcribe():
    if "audio" not in request.files:
        return jsonify({"error": "No audio file provided"}), 400

    audio_file = request.files["audio"]
    input_audio_path = os.path.join("static", "temp_input.wav")
    output_audio_path = os.path.join("static", "temp.wav")
    audio_file.save(input_audio_path)

    try:
        # Convert the audio to WAV format and check if it contains speech
        convert_to_wav(input_audio_path, output_audio_path)
        if is_silent_audio(output_audio_path):
            return jsonify({"error": "No speech detected. Please try again."}), 400

        # Transcribe the audio using Whisper model
        asr_pipeline = pipeline("automatic-speech-recognition", model="openai/whisper-small", device=0 if torch.cuda.is_available() else -1, config=config)
        result = asr_pipeline(output_audio_path)

        transcribed_text = result["text"].strip().capitalize()

        # Extract details from transcribed text (Assumed format: Name Email Phone)
        parts = transcribed_text.split()
        name = parts[0] if len(parts) > 0 else "Unknown Name"
        email = parts[1] if '@' in parts[1] else "[email protected]"
        phone_number = parts[2] if len(parts) > 2 else "0000000000"

        confirmation = f"Is this correct? Name: {name}, Email: {email}, Phone: {phone_number}"
        generate_audio_prompt(confirmation, "confirmation.mp3")

        # Create a customer login record
        salesforce_response = sf.Customer_Login__c.create({
            'Name': name,
            'Email__c': email,
            'Phone_Number__c': phone_number
        })

        return jsonify({"text": transcribed_text, "salesforce_record": salesforce_response})

    except Exception as e:
        return jsonify({"error": f"Speech recognition error: {str(e)}"}), 500

# Start the Flask server
if __name__ == "__main__":
    print("Starting Flask API Server on port 7860...")
    serve(app, host="0.0.0.0", port=7860)