app.py

import os
import re
import gradio as gr
from gtts import gTTS
from datetime import datetime
from openpyxl import Workbook, load_workbook
import google.generativeai as genai

# LangChain memory
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage, AIMessage
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain.memory import ConversationBufferMemory
from langchain.chains import ConversationChain

# ========== SETUP ==========
genai.configure(api_key="AIzaSyBJFmohAmhmqXQlM3fVxj8MLegVb26kyJk")

llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash", convert_system_message_to_human=True)
memory = ConversationBufferMemory(return_messages=True)
chain = ConversationChain(llm=llm, memory=memory, verbose=False)

# Menu & State
MENU = {
    "Cheeseburger": 5.99,
    "Fries": 2.99,
    "Coke": 1.99,
    "Pizza": 12.99,
    "Chicken Wings": 7.99,
    "Salad": 6.99
}
order = []
customer_name = ""

# Excel Setup
EXCEL_FILE = "orders.xlsx"
def setup_excel():
    if not os.path.exists(EXCEL_FILE):
        wb = Workbook()
        ws = wb.active
        ws.title = "Orders"
        ws.append(["Order ID", "Date", "Customer", "Items", "Total", "Time"])
        wb.save(EXCEL_FILE)
setup_excel()

def save_to_excel(name, items):
    wb = load_workbook(EXCEL_FILE)
    ws = wb.active
    order_id = f"ORD{ws.max_row:04d}"
    now = datetime.now()
    total = sum(qty * MENU[item] for item, qty in items)
    items_str = ", ".join(f"{qty} x {item}" for item, qty in items)
    ws.append([order_id, now.strftime("%Y-%m-%d"), name, items_str, f"${total:.2f}", now.strftime("%H:%M:%S")])
    wb.save(EXCEL_FILE)
    return order_id

# Voice

def clean_text(text):
    text = re.sub(r"\*\*(.*?)\*\*", r"\1", text)
    text = re.sub(r"Bot\s*:\s*", "", text, flags=re.IGNORECASE)
    return text.strip()

def speak(text, filename="response.mp3"):
    cleaned = clean_text(text)
    tts = gTTS(text=cleaned)
    tts.save(filename)
    return filename

# Prompt Template
system_prompt = """
You are a helpful restaurant assistant at 'Systaurant'.

Your job is to:
- Greet the user and ask their name if not known.
- Show the menu if requested.
- Extract food items and quantities from the customer's message.
- If the user says 'done', summarize the order and ask for confirmation.
- If confirmed, respond with a thank you and order ID.
- Keep the tone friendly and human. Do not prefix with "Bot:".

Menu:
{menu}
Customer name: {name}
Order so far: {summary}
"""

prompt = ChatPromptTemplate.from_messages([
    ("system", system_prompt),
    ("human", "{input}")
])

def generate_response(user_input):
    global customer_name, order

    # Track name
    if "my name is" in user_input.lower():
        customer_name = user_input.split("my name is")[-1].strip().split()[0].title()

    # Track items
    for item in MENU:
        if item.lower() in user_input.lower():
            qty = 1
            for word in user_input.lower().split():
                if word.isdigit():
                    qty = int(word)
                    break
            order.append((item, qty))

    # Confirmation
    if "confirm" in user_input.lower() or "yes" in user_input.lower():
        if customer_name and order:
            order_id = save_to_excel(customer_name, order)
            memory.chat_memory.add_user_message(user_input)
            memory.chat_memory.add_ai_message(f"✅ Your order ID is {order_id}. Thank you for ordering from Saad's Restaurant!")
            return f"✅ Your order ID is {order_id}. Thank you for ordering from Saad's Restaurant!"

    menu_text = "\n".join([f"{item}: ${price}" for item, price in MENU.items()])
    summary = ", ".join([f"{qty} x {item}" for item, qty in order]) if order else "No items yet"

    filled_prompt = prompt.invoke({
        "input": user_input,
        "menu": menu_text,
        "name": customer_name or "Not provided",
        "summary": summary
    })

    return chain.invoke(filled_prompt.to_string())

def handle_chat(user_input):
    bot_reply = generate_response(user_input)
    audio_file = speak(bot_reply)
    return bot_reply, audio_file

# Gradio Interface
gr.Interface(
    fn=handle_chat,
    inputs=gr.Textbox(label="👤 You", placeholder="Type your order..."),
    outputs=[
        gr.Textbox(label="🤖 Bot Response"),
        gr.Audio(label="🔊 Speaking", autoplay=True)
    ],
    title="🍔 SysTaurant Voice Bot with Memory",
    description="Place your restaurant order through chat with memory.",
    theme="soft"
).launch(share=True)