Create app.py

app.py

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+from flask import Flask, render_template, request, redirect, url_for, jsonify
+from simple_salesforce import Salesforce
+import os
+from gtts import gTTS
+import time
+from transformers import AutoConfig, pipeline
+from werkzeug.exceptions import BadRequest
+from pydub import AudioSegment
+from pydub.silence import detect_nonsilent
+
+app = Flask(__name__)
+
+# Salesforce connection setup
+sf = Salesforce(
+    username='diggavalli98@gmail.com', 
+    password='Sati@1020', 
+    security_token='sSSjyhInIsUohKpG8sHzty2q', 
+    consumer_key='3MVG9WVXk15qiz1JbtW1tT9a7Wnkos2RuGamw6p1lC5uPescT5NB2nPygpo6rQ87K1T.zBEn.wR.A6JdgHnIU', 
+    consumer_secret='A75C6B7801D5D20BED0E46631CF58C4F7FF28E4DAF442FE667553D29C35C0451'
+)
+
+# Global variables
+cart = []  # To store items, quantities, and prices
+MENU = {}
+
+# Fetching menu items dynamically from Salesforce
+def get_menu_items():
+    menu_items = {}
+    query = "SELECT Name, Category__c, Price__c, Ingredients__c FROM Menu_Item__c"
+    results = sf.query_all(query)
+    for record in results['records']:
+        category = record['Category__c']
+        item_name = record['Name']
+        price = record['Price__c']
+        if category not in menu_items:
+            menu_items[category] = {}
+        menu_items[category][item_name] = price
+    return menu_items
+
+# Fetch menu on app load
+MENU = get_menu_items()
+
+# Index route for login/signup page
+@app.route("/", methods=["GET", "POST"])
+def index():
+    if request.method == "POST":
+        name = request.form["name"]
+        email = request.form["email"]
+        phone = request.form["phone"]
+        
+        if not name or not email or not phone:
+            return jsonify({"error": "All fields are required"}), 400
+        
+        # Create Salesforce record for new customer
+        try:
+            customer_login = sf.Customer_Login__c.create({
+                'Name': name,
+                'Email__c': email,
+                'Phone_Number__c': phone
+            })
+            return redirect(url_for('menu'))  # Redirect to the menu page after successful login
+        except Exception as e:
+            return jsonify({"error": f"Failed to create record: {str(e)}"}), 500
+    return render_template("login.html")  # Render login page
+
+# Menu route to show menu page
+@app.route("/menu", methods=["GET"])
+def menu():
+    return render_template("menu.html", menu=MENU)
+
+# Function to extract quantity from a speech command
+def extract_quantity(command):
+    number_words = {
+        "one": 1, "two": 2, "three": 3, "four": 4, "five": 5,
+        "six": 6, "seven": 7, "eight": 8, "nine": 9, "ten": 10,
+        "1": 1, "2": 2, "3": 3, "4": 4, "5": 5, "6": 6, "7": 7, "8": 8, "9": 9, "10": 10
+    }
+    
+    command_words = command.split()
+    for word in command_words:
+        if word in number_words:
+            return number_words[word]
+    return None
+
+# Audio processing function to convert and check audio
+def convert_to_wav(input_path, output_path):
+    try:
+        audio = AudioSegment.from_file(input_path)
+        audio = audio.set_frame_rate(16000).set_channels(1)
+        audio.export(output_path, format="wav")
+    except Exception as e:
+        print(f"Error: {str(e)}")
+        raise Exception(f"Audio conversion failed: {str(e)}")
+
+# Audio transcription function
+@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)
+        audio = AudioSegment.from_wav(output_audio_path)
+        nonsilent_parts = detect_nonsilent(audio, min_silence_len=500, silence_thresh=audio.dBFS-16)
+        if len(nonsilent_parts) == 0:
+            return jsonify({"error": "No speech detected. Please try again."}), 400
+
+        result = pipeline("automatic-speech-recognition", model="openai/whisper-small", device=0 if torch.cuda.is_available() else -1)
+        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 "unknown@domain.com"
+        phone_number = parts[2] if len(parts) > 2 else "0000000000"
+        
+        confirmation = f"Is this correct? Name: {name}, Email: {email}, Phone: {phone_number}"
+        return jsonify({"text": confirmation})
+
+    except Exception as e:
+        return jsonify({"error": f"Speech recognition error: {str(e)}"}), 500
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)