import os
import requests
import gradio as gr
from gtts import gTTS
from datetime import datetime
from openpyxl import Workbook, load_workbook
import re

from langchain.memory import ConversationBufferMemory

# ========== CONFIGURATION ==========
API_KEY = "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"
MODEL = "google/gemma-3n-e2b-it:free"

MENU = {
    "Cheeseburger": 5.99,
    "Fries": 2.99,
    "Coke": 1.99,
    "Pizza": 12.99,
    "Chicken Wings": 7.99,
    "Salad": 6.99
}

memory = ConversationBufferMemory(return_messages=True)
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

# ========== Text-to-Speech ==========
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

# ========== OpenRouter API ==========
def generate_response(user_input):
    global customer_name, order

    memory.chat_memory.add_user_message(user_input)

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

    context = f"""
You are a helpful, kind restaurant assistant at 'PandaAI'.
MENU:
{menu_description}
Customer name: {customer_name}
Current order: {order_summary}
Instructions:
- Ask for name if not known.
- Show menu if requested.
- Extract item names and quantities from messages.
- Say 'Order summary' and ask 'Confirm?' when user is done.
- Respond only as the bot, no need to prefix with \"Bot:\".
- Keep tone human, natural, and friendly.
Conversation:
"""

    for msg in memory.chat_memory.messages:
        if msg.type == "human":
            context += f"\nCustomer: {msg.content}"
        else:
            context += f"\nBot: {msg.content}"

    context += f"\nCustomer: {user_input}\nBot:"

    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }

    payload = {
        "model": MODEL,
        "messages": [{"role": "user", "content": context}],
    }

    try:
        response = requests.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=payload)
        response.raise_for_status()
        reply = response.json()["choices"][0]["message"]["content"]
        memory.chat_memory.add_ai_message(reply)
        return reply
    except Exception as e:
        return f"❌ OpenRouter Error: {str(e)}"

# ========== Chat Logic ==========
def handle_chat(user_input):
    global customer_name, order

    bot_reply = generate_response(user_input)

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

    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))

    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)
            bot_reply += f"\n✅ Your order ID is {order_id}. Thank you for ordering from Saad's Restaurant!"

    audio_file = speak(bot_reply)
    return bot_reply, audio_file

# ========== Gradio UI ==========
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="🍔 PandaAI",
    description="Smart restaurant assistant powered by LangChain memory and OpenRouter API.",
    theme="soft"
).launch(share=True)