import gradio as gr
import pandas as pd
import time
import gtts
import os
import sounddevice as sd
import numpy as np
import speech_recognition as sr
import tempfile
import scipy.io.wavfile as wav

# Function to convert text to speech
def speak_text(text):
    tts = gtts.gTTS(text)
    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
    tts.save(temp_file.name)
    data, samplerate = wav.read(temp_file.name)
    sd.play(data, samplerate)
    sd.wait()
    os.remove(temp_file.name)

# Function to recognize speech input
def recognize_speech():
    recognizer = sr.Recognizer()
    with sr.Microphone() as source:
        print("Listening...")
        try:
            audio = recognizer.listen(source, timeout=5)
            text = recognizer.recognize_google(audio)
            print("You said:", text)
            return text.lower()
        except sr.UnknownValueError:
            print("Could not understand audio")
            return ""
        except sr.RequestError:
            print("Speech service is down")
            return ""

# Function to load the menu data
def load_menu():
    menu_file = "menu.xlsx"  # Ensure this file exists in the same directory
    try:
        return pd.read_excel(menu_file)
    except Exception as e:
        raise ValueError(f"Error loading menu file: {e}")

# Function to filter menu items based on preference
def filter_menu(preference):
    menu_data = load_menu()
    if preference == "Halal/Non-Veg":
        filtered_data = menu_data[menu_data["Ingredients"].str.contains("Chicken|Mutton|Fish|Prawns|Goat", case=False, na=False)]
        speak_text("Here are the non-vegetarian dishes")
    elif preference == "Vegetarian":
        filtered_data = menu_data[~menu_data["Ingredients"].str.contains("Chicken|Mutton|Fish|Prawns|Goat", case=False, na=False)]
        speak_text("Here are the vegetarian dishes")
    elif preference == "Guilt-Free":
        filtered_data = menu_data[menu_data["Description"].str.contains(r"Fat: ([0-9]|10)g", case=False, na=False)]
        speak_text("Here are the guilt-free options")
    else:
        filtered_data = menu_data
        speak_text("Showing all dishes")

    html_content = ""
    for _, item in filtered_data.iterrows():
        html_content += f"""
        <div style="display: flex; align-items: center; border: 1px solid #ddd; border-radius: 8px; padding: 15px; margin-bottom: 10px; box-shadow: 0px 4px 8px rgba(0, 0, 0, 0.1);">
            <div style="flex: 1; margin-right: 15px;">
                <h3 style="margin: 0; font-size: 18px;">{item['Dish Name']}</h3>
                <p style="margin: 5px 0; font-size: 16px; color: #888;">${item['Price ($)']}</p>
                <p style="margin: 5px 0; font-size: 14px; color: #555;">{item['Description']}</p>
            </div>
        </div>
        """
    return html_content

# Function to announce menu page entry
def announce_menu():
    speak_text("Welcome to Biryani Hub")
    time.sleep(2)
    speak_text("Choose a preference: All, Vegetarian, Non-Veg, or Guilt-Free")

# Gradio App
def app():
    with gr.Blocks() as demo:
        gr.Markdown("### Menu Page")
        announce_menu()
        
        # Radio button for selecting preference
        selected_preference = gr.Radio(
            choices=["All", "Vegetarian", "Halal/Non-Veg", "Guilt Free"],
            value="All",
            label="Choose a Preference",
        )

        # Output area for menu items
        menu_output = gr.HTML(value=filter_menu("All"))

        # Update menu dynamically based on preference
        selected_preference.change(filter_menu, inputs=[selected_preference], outputs=[menu_output])

        # Layout
        gr.Row([selected_preference])
        gr.Row(menu_output)

    return demo

if __name__ == "__main__":
    app().launch()