import gradio as gr

def generate_ielts_essay(prompt):
    # You may want to customize the max_length and other parameters according to your needs
    return "Hello " + prompt + "!!"
def format_chat_prompt(message, band, chat_history, instruction):
    prompt = f"System:{instruction}"
    for turn in chat_history:
        user_message, bot_message = turn
        prompt = f"{prompt}\nUser: {user_message}\nAssistant: {bot_message}"
    prompt = f"{prompt}\nUser: IELTS Writing Band {band} - {message}\nAssistant:"
    return prompt

def respond(message, band, chat_history, instruction, temperature=0.7):
    prompt = format_chat_prompt(message, band, chat_history, instruction)
    chat_history = chat_history + [[message, ""]]
    max_tokens = {6: 100, 7: 200, 8: 300, 9: 400}[int(band)]  # Change these values as needed
    stream = client.generate_stream(prompt,
                                    max_new_tokens=max_tokens,
                                    stop_sequences=["\nUser:", ""],
                                    temperature=temperature)
    acc_text = ""
    for idx, response in enumerate(stream):
            text_token = response.token.text

            if response.details:
                return

            if idx == 0 and text_token.startswith(" "):
                text_token = text_token[1:]

            acc_text += text_token
            last_turn = list(chat_history.pop(-1))
            last_turn[-1] += acc_text
            chat_history = chat_history + [last_turn]
            yield "", chat_history
            acc_text = ""

with gr.Blocks() as demo:
    chatbot = gr.Chatbot(height=240)
    msg = gr.Textbox(label="IELTS Writing Prompt")
    band = gr.Radio([6, 7, 8, 9], label="Band")
    with gr.Accordion(label="Advanced options",open=False):
        system = gr.Textbox(label="System message", lines=2, value="A conversation between a user and an LLM-based AI assistant. The assistant writes IELTS articles of various bands.")
        temperature = gr.Slider(label="Temperature", minimum=0.1, maximum=1, value=0.7, step=0.1)
    btn = gr.Button("Submit")
    clear = gr.ClearButton(components=[msg, chatbot], value="Clear console")

    btn.click(respond, inputs=[msg, band, chatbot, system], outputs=[msg, chatbot])
    msg.submit(respond, inputs=[msg, band, chatbot, system], outputs=[msg, chatbot]) 
gr.close_all()
demo.queue().launch(share=True)