app.py

import torch
from flask import Flask, render_template, request, jsonify, send_from_directory
import json
import os
from transformers import pipeline
from gtts import gTTS
from pydub import AudioSegment
from pydub.silence import detect_nonsilent
from transformers import AutoConfig
import time
from waitress import serve
from simple_salesforce import Salesforce
import requests

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

# Use whisper-small for faster processing and better speed
device = "cuda" if torch.cuda.is_available() else "cpu"

# Create config object to set timeout and other parameters
config = AutoConfig.from_pretrained("openai/whisper-small")
config.update({"timeout": 60})  # Set timeout to 60 seconds

# Salesforce connection details
try:
    print("Attempting to connect to Salesforce...")
    sf = Salesforce(username='[email protected]', password='Sati@1020', security_token='sSSjyhInIsUohKpG8sHzty2q')
    print("Connected to Salesforce successfully!")
except Exception as e:
    print(f"Failed to connect to Salesforce: {str(e)}")

# ✅ 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():
    return render_template("menu_page.html")
# ✅ MENU PAGE ROUTE (NEWLY ADDED)
@app.route("/menu_page", methods=["GET"])
def menu_page():
    try:
        query = "SELECT Name, Price__c, Ingredients__c, Category__c, Image_URL__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"],
                "image_url": item.get("Image_URL__c", "default_image.jpg")  # Fallback if no image is found
            })

        return render_template("menu_page.html", menu=menu_items)
    except Exception as e:
        return jsonify({"error": f"Failed to fetch menu: {str(e)}"}), 500

# ✅ STATIC IMAGES ROUTE
@app.route("/static/images/<path:filename>")
def static_images(filename):
    return send_from_directory(os.path.join(app.root_path, 'static/images'), filename)

# ✅ REGISTER API
@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

    try:
        customer_login = sf.Customer_Login__c.create({
            'Name': name,
            'Email__c': email,
            'Phone_Number__c': phone
        })
        return jsonify({'success': True}), 200
    except Exception as e:
        return jsonify({'error': str(e)}), 500

# ✅ 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

    try:
        customer_login = sf.Customer_Login__c.create({
            'Name': name,
            'Email__c': email,
            'Phone_Number__c': phone_number
        })
        return jsonify({'success': True, 'id': customer_login['id']}), 200
    except Exception as e:
        return jsonify({'error': f'Failed to create record in Salesforce: {str(e)}'}), 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_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

        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()

        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")

        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 PRODUCTION SERVER
if __name__ == "__main__":
    print("✅ Starting Flask API Server on port 7860...")
    serve(app, host="0.0.0.0", port=7860)