Update app.py

app.py

@@ -1,5 +1,5 @@
 import torch
-from flask import Flask, render_template, request, jsonify
+from flask import Flask, render_template, request, jsonify, session
 import json
 import os
 from transformers import pipeline
@@ -13,6 +13,7 @@ from simple_salesforce import Salesforce
 import requests  # Import requests for exception handling
 
 app = Flask(__name__)
+app.secret_key = 'your_secret_key'
 
 # Use whisper-small for faster processing and better speed
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -30,6 +31,9 @@ try:
 except Exception as e:
     print(f"Failed to connect to Salesforce: {str(e)}")
 
+# Global cart variable to store cart items
+cart = []
+
 # Function for Salesforce operations
 def create_salesforce_record(name, email, phone_number):
     try:
@@ -78,13 +82,51 @@ def is_silent_audio(audio_path):
     return len(nonsilent_parts) == 0  # If no speech detected
 
 # Routes and Views
-@app.route("/")
-def index():
-    return render_template("index.html")
+@app.route("/menu", methods=["GET"])
+def menu_page():
+    menu_items = get_menu_items()
+    menu_data = [{"name": item['Name'], "price": item['Price__c'], "ingredients": item['Ingredients__c'], "category": item['Category__c']} for item in menu_items]
+    return render_template("menu_page.html", menu_items=menu_data)
+
+@app.route("/add_to_cart", methods=["POST"])
+def add_to_cart():
+    item_name = request.json.get('item_name')
+    quantity = request.json.get('quantity')
+
+    # Find item price
+    for category, items in MENU.items():
+        if item_name in items:
+            price = items[item_name]
+            cart_item = {
+                'name': item_name,
+                'price': price,
+                'quantity': quantity
+            }
+            cart.append(cart_item)
+            return jsonify({"message": f"Added {quantity} x {item_name} to the cart."})
+    
+    return jsonify({"message": "Item not found in menu."}), 404
+
+# Route for handling order
+@app.route("/order", methods=["POST"])
+def place_order():
+    item_name = request.json.get('item_name')
+    quantity = request.json.get('quantity')
+    order_data = {"Item__c": item_name, "Quantity__c": quantity}
+    sf.Order__c.create(order_data)
+    return jsonify({"success": True, "message": f"Order for {item_name} placed successfully."})
+
+# Route to handle the cart
+@app.route("/cart", methods=["GET"])
+def cart():
+    cart_items = []  # Placeholder for cart items
+    return render_template("cart_page.html", cart_items=cart_items)
 
-@app.route("/dashboard", methods=["GET"])
-def dashboard():
-    return render_template("dashboard.html")  # Render the dashboard template
+# Route for the order summary page
+@app.route("/order-summary", methods=["GET"])
+def order_summary():
+    order_details = []  # Placeholder for order details
+    return render_template("order_summary.html", order_details=order_details)
 
 @app.route('/submit', methods=['POST'])
 def submit():
@@ -169,95 +211,20 @@ def menu_page():
 # Route for handling order
 @app.route("/order", methods=["POST"])
 def place_order():
-    item_name = request.json.get('item_name')
-    quantity = request.json.get('quantity')
-    order_data = {"Item__c": item_name, "Quantity__c": quantity}
-    sf.Order__c.create(order_data)
-    return jsonify({"success": True, "message": f"Order for {item_name} placed successfully."})
+    cart_items = request.json.get("cart_items")
+    total_price = sum([item['price'] * item['quantity'] for item in cart_items])
+    customer_id = session.get('customer_id')
 
-# Route to handle the cart
-@app.route("/cart", methods=["GET"])
-def cart():
-    cart_items = []  # Placeholder for cart items
-    return render_template("cart_page.html", cart_items=cart_items)
-
-# Route for the order summary page
-@app.route("/order-summary", methods=["GET"])
-def order_summary():
-    order_details = []  # Placeholder for order details
-    return render_template("order_summary.html", order_details=order_details)
-
-@app.route("/transcribe", methods=["POST"])
-def transcribe():
-    if "audio" not in request.files:
-        print("No audio file provided")
-        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)
+    if not customer_id:
+        return jsonify({"message": "User not logged in"}), 400
 
     try:
-        # Convert to WAV
-        convert_to_wav(input_audio_path, output_audio_path)
-
-        # Check for silence
-        if is_silent_audio(output_audio_path):
-            return jsonify({"error": "No speech detected. Please try again."}), 400
-        else:
-            print("Audio contains speech, proceeding with transcription.")
-
-        # Use Whisper ASR model for transcription
-        result = None
-        retry_attempts = 3
-        for attempt in range(retry_attempts):
-            try:
-                result = pipeline("automatic-speech-recognition", model="openai/whisper-small", device=0 if torch.cuda.is_available() else -1, config=config)
-                print(f"Transcribed text: {result['text']}")
-                break
-            except requests.exceptions.ReadTimeout:
-                print(f"Timeout occurred, retrying attempt {attempt + 1}/{retry_attempts}...")
-                time.sleep(5)
-
-        if result is None:
-            return jsonify({"error": "Unable to transcribe audio after retries."}), 500
-
-        transcribed_text = result["text"].strip().capitalize()
-        print(f"Transcribed text: {transcribed_text}")
-
-        # Extract name, email, and phone number from the transcribed text
-        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"
-        print(f"Parsed data - Name: {name}, Email: {email}, Phone Number: {phone_number}")
-
-        # Confirm details before submission
-        confirmation = f"Is this correct? Name: {name}, Email: {email}, Phone: {phone_number}"
-        generate_audio_prompt(confirmation, "confirmation.mp3")
-
-        # Simulate confirmation via user action
-        user_confirms = True  # Assuming the user confirms, you can replace this with actual user input logic
-
-        if user_confirms:
-            # Create record in Salesforce
-            salesforce_response = create_salesforce_record(name, email, phone_number)
-
-            # Log the Salesforce response
-            print(f"Salesforce record creation response: {salesforce_response}")
-
-            # Check if the response contains an error
-            if "error" in salesforce_response:
-                print(f"Error creating record in Salesforce: {salesforce_response['error']}")
-                return jsonify(salesforce_response), 500
-
-            return jsonify({"text": transcribed_text, "salesforce_record": salesforce_response})
+        # Create order in Salesforce
+        order = create_salesforce_order(cart_items, total_price, customer_id)
+        return jsonify({"message": "Order placed successfully!", "order": order})
 
     except Exception as e:
-        print(f"Error in transcribing or processing: {str(e)}")
-        return jsonify({"error": f"Speech recognition error: {str(e)}"}), 500
+        return jsonify({"message": f"Failed to create order: {str(e)}"}), 500
 
-# Start Production Server
 if __name__ == "__main__":
-    serve(app, host="0.0.0.0", port=7860)
+    app.run(debug=True)