Update app.py

app.py

@@ -1,38 +1,45 @@
+import os
+import time
 import torch
 from flask import Flask, render_template, request, jsonify
-import json
-import os
+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
-import time
 from waitress import serve
-from simple_salesforce import Salesforce
-import requests  # Import requests for exception handling
 
+# Flask setup
 app = Flask(__name__, template_folder="templates")
 app.secret_key = os.urandom(24)
 
-# Use whisper-small for faster processing and better speed
+# Check for available GPU
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-# Create config object to set timeout and other parameters
+# Set up Whisper model config
 config = AutoConfig.from_pretrained("openai/whisper-small")
 config.update({"timeout": 60})  # Set timeout to 60 seconds
 
-# Function to generate audio prompts
+# 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: {e}")
-        time.sleep(5)  # Wait before retrying
+        print(f"Error generating audio prompt: {e}")
+        time.sleep(5)
         generate_audio_prompt(text, filename)
 
-# Generate required voice prompts
+# Example prompts for voice interaction
 prompts = {
     "welcome": "Welcome to Biryani Hub.",
     "ask_name": "Tell me your name.",
@@ -40,48 +47,95 @@ prompts = {
     "thank_you": "Thank you for registration."
 }
 
+# Generate audio prompts
 for key, text in prompts.items():
     generate_audio_prompt(text, f"{key}.mp3")
 
-# Function to convert audio to WAV format
-def convert_to_wav(input_path, output_path):
-    try:
-        audio = AudioSegment.from_file(input_path)
-        audio = audio.set_frame_rate(16000).set_channels(1)  # Convert to 16kHz, mono
-        audio.export(output_path, format="wav")
-    except Exception as e:
-        raise Exception(f"Audio conversion failed: {str(e)}")
-
-# Function to check if audio contains actual speech
+# 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
 
-# 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)}")
+# 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`)
+# Home Route (loads index.html)
 @app.route("/", methods=["GET"])
 def index():
     return render_template("index.html")
 
-# ✅ DASHBOARD ROUTE
+# Dashboard Route
 @app.route("/dashboard", methods=["GET"])
 def dashboard():
     return render_template("dashboard.html")
 
-# ✅ MENU PAGE ROUTE
+# Menu Page Route
 @app.route("/menu_page", methods=["GET"])
 def menu_page():
-    return render_template("menu_page.html")
+    menu_items = get_menu_items()
+    return render_template("menu_page.html", menu=menu_items)
 
-# ✅ LOGIN API
+# Login API
 @app.route('/login', methods=['POST'])
 def login():
     data = request.json
@@ -92,17 +146,14 @@ def login():
     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
+    # 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
+# Register API (Create customer login)
 @app.route("/submit", methods=["POST"])
 def submit():
     data = request.json
@@ -113,17 +164,14 @@ def submit():
     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
-        })
+    # Create customer login record in Salesforce
+    customer_login = create_customer_login(name, email, phone)
+    if customer_login:
         return jsonify({'success': True}), 200
-    except Exception as e:
-        return jsonify({'error': str(e)}), 500
+    else:
+        return jsonify({'error': 'Failed to create customer record'}), 500
 
-# ✅ TRANSCRIBE AUDIO API
+# Transcribe Audio API
 @app.route("/transcribe", methods=["POST"])
 def transcribe():
     if "audio" not in request.files:
@@ -135,15 +183,18 @@ def transcribe():
     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]"
@@ -152,6 +203,7 @@ def transcribe():
         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,
@@ -163,30 +215,7 @@ def transcribe():
     except Exception as e:
         return jsonify({"error": f"Speech recognition error: {str(e)}"}), 500
 
-# ✅ MENU API
-@app.route("/menu", methods=["GET"])
-def get_menu():
-    try:
-        # Fetch menu items from Salesforce
-        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"]
-            })
-
-        # Pass the menu items to the template
-        return render_template("menu_page.html", menu=menu_items)
-
-    except Exception as e:
-        return jsonify({"error": f"Failed to fetch menu: {str(e)}"}), 500
-
-# ✅ START PRODUCTION SERVER
+# Start the Flask server
 if __name__ == "__main__":
-    print("✅ Starting Flask API Server on port 7860...")
+    print("Starting Flask API Server on port 7860...")
     serve(app, host="0.0.0.0", port=7860)