AIVoice12 / app.py
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Update app.py
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from flask import Flask, render_template_string, request, jsonify
import speech_recognition as sr
from tempfile import NamedTemporaryFile
import os
import ffmpeg
from fuzzywuzzy import process, fuzz
from metaphone import doublemetaphone
import logging
app = Flask(__name__)
logging.basicConfig(level=logging.INFO)
# Global variables
cart = {} # Stores items and their quantities in the cart
menu_preferences = "all" # Tracks the current menu preference
default_menu_preferences = "all" # To reset menu preferences
prices = {
"samosa": 9,
"onion pakoda": 10,
"chilli gobi": 12,
"chicken biryani": 14,
"mutton biryani": 16,
"veg biryani": 12,
"paneer butter": 10,
"fish curry": 12,
"chicken manchurian": 14,
"veg manchurian": 12,
"chilli chicken": 14,
"paneer biryani": 13,
"chicken curry": 14
}
menus = {
"all": list(prices.keys()),
"vegetarian": [
"samosa", "onion pakoda", "chilli gobi", "veg biryani", "paneer butter", "veg manchurian", "paneer biryani"
],
"non-vegetarian": [
"chicken biryani", "mutton biryani", "fish curry", "chicken manchurian", "chilli chicken", "chicken curry"
],
"guilt-free": ["samosa", "onion pakoda"]
}
@app.route("/")
def index():
return render_template_string(html_code)
@app.route("/reset-cart", methods=["GET"])
def reset_cart():
global cart, menu_preferences
cart = {}
menu_preferences = default_menu_preferences # Reset menu preferences
return "Cart reset successfully."
@app.route("/process-audio", methods=["POST"])
def process_audio():
try:
# Handle audio input
audio_file = request.files.get("audio")
if not audio_file:
return jsonify({"response": "No audio file provided."}), 400
# Save audio file and convert to WAV format
temp_file = NamedTemporaryFile(delete=False, suffix=".webm")
audio_file.save(temp_file.name)
converted_file = NamedTemporaryFile(delete=False, suffix=".wav")
ffmpeg.input(temp_file.name).output(
converted_file.name, acodec="pcm_s16le", ac=1, ar="16000"
).run(overwrite_output=True)
# Recognize speech
recognizer = sr.Recognizer()
recognizer.dynamic_energy_threshold = True
recognizer.energy_threshold = 100
with sr.AudioFile(converted_file.name) as source:
recognizer.adjust_for_ambient_noise(source, duration=1)
audio_data = recognizer.record(source)
raw_command = recognizer.recognize_google(audio_data).lower()
logging.info(f"Raw recognized command: {raw_command}")
# Preprocess the command
all_menu_items = menus["all"]
command = preprocess_command(raw_command, all_menu_items)
# Process the command and get a response
response = process_command(command)
except sr.UnknownValueError:
response = "Sorry, I couldn't understand. Please try again."
except Exception as e:
response = f"An error occurred: {str(e)}"
finally:
os.unlink(temp_file.name)
os.unlink(converted_file.name)
return jsonify({"response": response})
def preprocess_command(command, menu_items):
"""
Preprocess the user command to improve matching:
- Use fuzzy matching for menu items.
- Use phonetic matching as a fallback.
"""
def phonetic_match(word, options):
word_phonetic = doublemetaphone(word)[0]
for option in options:
if doublemetaphone(option)[0] == word_phonetic:
return option
return None
# First, try fuzzy matching
closest_match = process.extractOne(command, menu_items, scorer=fuzz.token_set_ratio)
if closest_match and closest_match[1] > 60:
return closest_match[0]
# Fallback to phonetic matching
words = command.split()
for word in words:
match = phonetic_match(word, menu_items)
if match:
return match
return command
def process_command(command):
"""
Process the user command based on the current menu and cart.
"""
global cart, menu_preferences
command = command.lower()
# Handle menu preferences
if menu_preferences == "all":
if "non-vegetarian" in command:
menu_preferences = "non-vegetarian"
return "You have chosen the Non-Vegetarian menu. To view the menu, say 'menu'."
elif "vegetarian" in command and "non-vegetarian" not in command:
menu_preferences = "vegetarian"
return "You have chosen the Vegetarian menu. To view the menu, say 'menu'."
elif "guilt-free" in command:
menu_preferences = "guilt-free"
return "You have chosen the Guilt-Free menu. To view the menu, say 'menu'."
elif "all" in command:
menu_preferences = "all"
return "You have chosen the complete menu. To view the menu, say 'menu'."
# Handle commands related to the current menu
menu = menus.get(menu_preferences, menus["all"])
if "price of" in command:
item = command.replace("price of", "").strip()
closest_match = process.extractOne(item, prices.keys(), scorer=fuzz.token_set_ratio)
if closest_match and closest_match[1] > 60:
matched_item = closest_match[0]
return f"The price of {matched_item} is ${prices[matched_item]}."
return "Sorry, I couldn't find that item in the menu."
elif "menu" in command:
return f"Here is your menu: {', '.join(menu)}. To select an item, say the item name."
elif "remove" in command:
item = command.replace("remove", "").strip() # Extract item name
closest_match = process.extractOne(item, list(cart.keys()), scorer=fuzz.token_set_ratio) # Match in cart
if closest_match and closest_match[1] > 60: # If match is strong
matched_item = closest_match[0]
# Check the specific remove command
if "one" in command or "1" in command:
if cart[matched_item] > 1:
cart[matched_item] -= 1
return f"One {matched_item} has been removed. Current cart: {dict(cart)}."
else:
del cart[matched_item]
return f"{matched_item.capitalize()} has been completely removed from your cart."
elif "all" in command or "entire" in command:
del cart[matched_item]
return f"All {matched_item}s have been removed from your cart. Current cart: {dict(cart)}."
else:
del cart[matched_item]
return f"{matched_item.capitalize()} has been removed from your cart. Current cart: {dict(cart)}."
return "Sorry, that item is not in your cart."
elif "clear cart" in command or "empty cart" in command:
if cart:
cart.clear()
return "Your cart has been cleared."
return "Your cart is already empty."
elif "increase" in command:
item = command.replace("increase", "").strip()
closest_match = process.extractOne(item, list(cart.keys()), scorer=fuzz.token_set_ratio)
if closest_match and closest_match[1] > 60:
matched_item = closest_match[0]
cart[matched_item] += 1
return f"Quantity of {matched_item} increased to {cart[matched_item]}. Current cart: {dict(cart)}."
return "Sorry, that item is not in your cart."
elif "decrease" in command:
item = command.replace("decrease", "").strip()
closest_match = process.extractOne(item, list(cart.keys()), scorer=fuzz.token_set_ratio)
if closest_match and closest_match[1] > 60:
matched_item = closest_match[0]
if cart[matched_item] > 1:
cart[matched_item] -= 1
return f"Quantity of {matched_item} decreased to {cart[matched_item]}. Current cart: {dict(cart)}."
else:
del cart[matched_item]
return f"{matched_item.capitalize()} has been removed from your cart. Current cart: {dict(cart)}."
return "Sorry, that item is not in your cart."
elif any(item in command for item in menu):
closest_match = process.extractOne(command, menu, scorer=fuzz.token_set_ratio)
if closest_match and closest_match[1] > 60:
matched_item = closest_match[0]
cart[matched_item] = cart.get(matched_item, 0) + 1
return f"{matched_item.capitalize()} added to your cart. Current cart: {dict(cart)}. To finalize, say 'final order'."
return "Sorry, I couldn't recognize the item. Could you try again?"
elif "final order" in command:
if cart:
total = sum(prices[item] * count for item, count in cart.items())
response = f"Your final order is: {', '.join(f'{item} x{count}' for item, count in cart.items())}. Your total bill is ${total}. Thank you for ordering! To exit this conversation, say 'goodbye'."
cart.clear()
return response
return "Your cart is empty. Please add items to your cart first."
elif "goodbye" in command:
cart.clear()
menu_preferences = default_menu_preferences
return "Goodbye! Thank you for using AI Dining Assistant."
return "Sorry, I couldn't understand that. Please try again."
html_code = """
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>AI Dining Assistant</title>
<style>
body {
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
min-height: 100vh;
margin: 0;
font-family: Arial, sans-serif;
background-color: #f4f4f9;
}
h1 {
color: #333;
}
.mic-button {
font-size: 2rem;
padding: 1rem 2rem;
color: white;
background-color: #007bff;
border: none;
border-radius: 50px;
cursor: pointer;
transition: background-color 0.3s;
}
.mic-button:hover {
background-color: #0056b3;
}
.status, .response {
margin-top: 1rem;
text-align: center;
color: #555;
font-size: 1.2rem;
}
.response {
background-color: #e8e8ff;
padding: 1rem;
border-radius: 10px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
display: none;
}
</style>
</head>
<body>
<h1>AI Dining Assistant</h1>
<button class="mic-button" id="mic-button">🎤</button>
<div class="status" id="status">Press the mic button to start...</div>
<div class="response" id="response">Response will appear here...</div>
<script>
const micButton = document.getElementById('mic-button');
const status = document.getElementById('status');
const response = document.getElementById('response');
let mediaRecorder;
let audioChunks = [];
let isConversationActive = false;
micButton.addEventListener('click', () => {
if (!isConversationActive) {
isConversationActive = true;
startConversation();
}
});
function startConversation() {
const utterance = new SpeechSynthesisUtterance('Please choose your preference: All, Vegetarian, Non-Vegetarian, or Guilt-Free.');
speechSynthesis.speak(utterance);
utterance.onend = () => {
status.textContent = 'Listening...';
startListening();
};
}
function startListening() {
navigator.mediaDevices.getUserMedia({ audio: true }).then(stream => {
mediaRecorder = new MediaRecorder(stream, { mimeType: 'audio/webm;codecs=opus' });
mediaRecorder.start();
audioChunks = [];
mediaRecorder.ondataavailable = event => audioChunks.push(event.data);
mediaRecorder.onstop = async () => {
const audioBlob = new Blob(audioChunks, { type: 'audio/webm' });
const formData = new FormData();
formData.append('audio', audioBlob);
status.textContent = 'Processing...';
try {
const result = await fetch('/process-audio', { method: 'POST', body: formData });
const data = await result.json();
response.textContent = data.response;
response.style.display = 'block';
const utterance = new SpeechSynthesisUtterance(data.response);
speechSynthesis.speak(utterance);
utterance.onend = () => {
console.log("Speech synthesis completed.");
if (data.response.includes("Goodbye")) {
status.textContent = 'Conversation ended. Press the mic button to start again.';
isConversationActive = false;
fetch('/reset-cart'); // Reset the cart dynamically on end
} else if (data.response.includes("Your order is complete")) {
status.textContent = 'Order complete. Thank you for using AI Dining Assistant.';
isConversationActive = false;
fetch('/reset-cart'); // Reset the cart after final order
} else {
status.textContent = 'Listening...';
setTimeout(() => {
startListening();
}, 100);
}
};
utterance.onerror = (e) => {
console.error("Speech synthesis error:", e.error);
status.textContent = 'Error with speech output.';
isConversationActive = false;
};
} catch (error) {
response.textContent = 'Sorry, I could not understand. Please try again.';
response.style.display = 'block';
status.textContent = 'Press the mic button to restart the conversation.';
isConversationActive = false;
}
};
setTimeout(() => mediaRecorder.stop(), 5000);
}).catch(() => {
status.textContent = 'Microphone access denied.';
isConversationActive = false;
});
}
</script>
</body>
</html>
"""
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860)