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358411f
1
Parent(s):
e40dbad
Update app.py
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app.py
CHANGED
@@ -1,5 +1,4 @@
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import openai
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import requests
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import speech_recognition as sr
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import gradio as gr
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@@ -20,7 +19,7 @@ restaurants = {
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"Chicken Sandwich": 4.99,
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"Onion Rings": 2.99,
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"Fountain Drink": 1.99,
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"
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},
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"Taco Bell": {
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"Crunchwrap Supreme": 4.99,
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@@ -62,19 +61,32 @@ def recognize_speech(audio):
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return transcript["text"]
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# Chatbot function
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def chatbot(command):
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# Get menu for a specific restaurant
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def get_menu_items(restaurant):
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return restaurants[restaurant]
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@@ -85,27 +97,7 @@ def identify_food_command(text):
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if keyword in text:
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return keyword
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return None
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restaurant_prices = {}
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# Iterate through the `restaurants` dictionary and create a list of restaurants that contain the food item
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for restaurant, menu_items in restaurants.items():
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if food_item.lower() in menu_items:
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restaurant_prices[restaurant] = menu_items[food_item.lower()]
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if len(restaurant_prices) == 0:
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# If no restaurants contain the food item, return an appropriate message
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return "Sorry, we could not find any restaurants that serve that item."
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# Find the restaurant with the least price for the food item
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min_price = min(restaurant_prices.values())
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restaurant_names = [restaurant for restaurant, price in restaurant_prices.items() if price == min_price]
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# If there are multiple restaurants with the same price, return all of them
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if len(restaurant_names) > 1:
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return "You can order that item from the following restaurants: " + ', '.join(restaurant_names)
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else:
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return restaurant_names[0]
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# Main function to handle user inputs and chatbot responses
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def main(audio):
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while True:
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print("What can I help you with?")
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command = recognize_speech(audio)
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print(f"You said: {command}")
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menu_items = get_menu_items(restaurant_name)
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print(f"Sure, here's the menu for {restaurant_name}: {menu_items} What would you like to order?")
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max_tries = 3
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break
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else:
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print("Sorry, that item is not available at this restaurant. Please try again.")
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elif food_command in ['menu' , 'menus']:
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for restaurant in restaurants:
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if restaurant in command:
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menu_items = get_menu_items(restaurant)
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break
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else:
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response= "Sorry, I didn't catch the restaurant name. Could you please repeat that?"
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elif
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response=chatbot(
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else:
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response=chatbot(command)
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return response
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except sr.UnknownValueError:
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print("Sorry, I did not understand what you said.")
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interface = gr.Interface(
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main,
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inputs=gr.Audio(source="microphone", type="filepath", label="Input Audio"),
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description="Talk to the Foodie Chatbot and get restaurant recommendations and menus!",
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)
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if __name__ == "__main__":
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interface.launch(
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import openai
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import speech_recognition as sr
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import gradio as gr
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"Chicken Sandwich": 4.99,
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"Onion Rings": 2.99,
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"Fountain Drink": 1.99,
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"Apple Pie": 1.49
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},
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"Taco Bell": {
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"Crunchwrap Supreme": 4.99,
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return transcript["text"]
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def chatbot(command):
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You are a Restaurants chatbot Who takes order,shows menus and answers users food related querry's presiously"},
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{"role": "user", "content": command},
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]
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)
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result = ''
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for choice in response.choices:
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result += choice.message.content
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return result
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def nlp(txt_summ):
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completion = openai.Completion.create(
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model="text-davinci-003",
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prompt= txt_summ ,
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temperature=0.7,
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max_tokens=64,
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top_p=1.0,
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frequency_penalty=0.0,
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presence_penalty=0.0
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)
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response = completion.choices[0].text
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return response
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# Get menu for a specific restaurant
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def get_menu_items(restaurant):
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return restaurants[restaurant]
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if keyword in text:
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return keyword
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return None
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# Main function to handle user inputs and chatbot responses
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def main(audio):
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while True:
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print("What can I help you with?")
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command = recognize_speech(audio)
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print(f"You said: {command}")
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txt_command ="extract the food related command keyword from the sentence :\n\n"+command
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food_command = nlp(txt_command).strip()
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restaurant_name = ''
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txt_extract = "extract the restaurants name keyword from the sentence :\n\n"+command
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restaurant_name = ((nlp(txt_extract)).strip()).title()
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found_rest = False
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if(restaurant_name in restaurants.keys()):
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found_rest = True
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item_name = ''
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txt_extract = "extract the food item from the sentence :\n\n"+command
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item_name = ((nlp(txt_extract)).strip()).title()
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found_item = False
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if(restaurant_name in restaurants.keys()):
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found_item = True
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if food_command in ['order', 'eat' , 'want' , 'serve' , 'prepare' ]:
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if not found_rest and found_item:
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temp_val = {}
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for restaurant, rest_info in restaurants.items():
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if item_name in rest_info:
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temp_val[restaurant] = int(rest_info[item_name])
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if temp_val:
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min_price = min(temp_val.values())
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res = [key for key in temp_val if temp_val[key] == min_price]
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response = f"You have ordered {item_name} from {res[0]} with price of {min_price}"
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elif found_rest and found_item:
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response = f"\nYou ordered {item_name} from {restaurant_name}\nGreat! Thank you for ordering."
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elif found_rest and not found_item :
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menu_items = get_menu_items(restaurant_name)
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print(f"Sure, here's the menu for {restaurant_name}: {menu_items} What would you like to order?")
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max_tries = 3
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break
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else:
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print("Sorry, that item is not available at this restaurant. Please try again.")
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else :
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resp = "Respond properly and Try to make the Customer buy some food and for the valid response"
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response = chatbot(resp)
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elif food_command in ['menu' , 'menus' , 'catalogue' , 'items' , 'something']:
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for restaurant in restaurants:
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if restaurant in command:
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menu_items = get_menu_items(restaurant)
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break
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else:
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response= "Sorry, I didn't catch the restaurant name. Could you please repeat that?"
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elif identify_food_command(command) == 'food':
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response=chatbot("Respond a person properly who has come to your restaurant asking food")
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else:
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response=chatbot("Response, as if you cannot understand and make the person salivate so that he buys a food . Also Give proper reply for the output\n"+command)
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return response
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except sr.UnknownValueError:
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print("Sorry, I did not understand what you said.")
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except sr.RequestError:
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print("Sorry, I am unable to process your request.")
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except Exception as e:
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print("An error occurred:", e)
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interface = gr.Interface(
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main,
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inputs=gr.Audio(source="microphone", type="filepath", label="Input Audio"),
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description="Talk to the Foodie Chatbot and get restaurant recommendations and menus!",
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)
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if __name__ == "__main__":
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interface.launch(share=True ,debug=True)
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