import os
import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch

# Clone the Gradio repository
os.system("git clone https://github.com/gradio-app/gradio.git")

# Install Gradio
os.system("cd gradio && pip install .")

# Install transformers
os.system("pip install transformers")

# Install PyTorch
os.system("pip install torch==1.10.0+cpu torchvision==0.11.1+cpu torchaudio==0.10.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html")

class ArabicAssistant:
    def __init__(self):
        self.model_name = "EleutherAI/gpt-neo-2.7B"
        self.tokenizer = GPT2Tokenizer.from_pretrained(self.model_name)
        self.model = GPT2LMHeadModel.from_pretrained(self.model_name)

    def generate_response(self, input_text):
        input_ids = self.tokenizer.encode(input_text, return_tensors="pt")
        output = self.model.generate(input_ids, max_length=100, num_beams=5, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7)
        response = self.tokenizer.decode(output[0], skip_special_tokens=True)
        return response

assistant = ArabicAssistant()

def chatbot_interaction(user_input):
    user_input = user_input.strip()
    
    # Check if the user input is in Arabic-Egyptian dialect
    if not any(char in "اأإآبتثجحخدذرزسشصضطظعغفقكلمنهوي" for char in user_input):
        return "عذرًا، أنا أتحدث فقط باللهجة المصرية. يرجى استخدام اللهجة المصرية في التفاعل معي."

    # Generate response using the chatbot model
    response = assistant.generate_response(user_input)

    # Add an open-ended question to encourage further conversation
    response += " أهلاً! كيف يمكنني مساعدتك اليوم؟"

    return response

iface = gr.Interface(fn=chatbot_interaction, inputs=gr.Textbox(), outputs=gr.Textbox(), live=True, theme="huggingface", layout="vertical", title="Arabic Assistant Chatbot", description="Chat with the Arabic Assistant in the Egyptian dialect.")
iface.launch()