import os
import re
import logging
import gradio as gr
import openai

print(os.environ)
openai.api_base = os.environ.get("OPENAI_API_BASE")
openai.api_key = os.environ.get("OPENAI_API_KEY")

def make_prediction(prompt, max_tokens=None, temperature=None, top_p=None, top_k=None, repetition_penalty=None):
    completion = openai.Completion.create(model="Open-Orca/OpenOrcaxOpenChat-Preview2-13B", prompt=prompt, max_tokens=max_tokens, temperature=temperature, top_p=top_p, top_k=top_k, repetition_penalty=repetition_penalty, stream=True)
    for chunk in completion:
        yield chunk["choices"][0]["text"]

def delay_typer(words, delay=0.8):
    tokens = re.findall(r'\s*\S+\s*', words)
    for s in tokens:
        yield s
        sleep(delay)


def clear_chat(chat_history_state, chat_message):
    chat_history_state = []
    chat_message = ''
    return chat_history_state, chat_message


def user(message, history):
    history = history or []
    # Append the user's message to the conversation history
    history.append([message, ""])
    return "", history


def chat(history, system_message, max_tokens, temperature, top_p, top_k, repetition_penalty):
    history = history or []

    messages = system_message.strip() + "\n" + \
               "\n".join(["\n".join(["User: "+item[0]+"<|end_of_turn|>", "Assistant: "+item[1]+"<|end_of_turn|>"])
                          for item in history])
    # strip the last `<|end_of_turn|>` from the messages
    messages = messages.rstrip("<|end_of_turn|>")
    # remove last space from assistant, some models output a ZWSP if you leave a space
    messages = messages.rstrip()

    prediction = make_prediction(
        messages,
        max_tokens=max_tokens,
        temperature=temperature,
        top_p=top_p,
        top_k=top_k,
        repetition_penalty=repetition_penalty,
    )
    for tokens in prediction:
        tokens = re.findall(r'\s*\S+\s*', tokens)
        for s in tokens:
            answer = s
            history[-1][1] += answer
            # stream the response
            yield history, history, ""


start_message = ""

with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            gr.Markdown(f"""
                    ### Brought to you by OpenChat x OpenOrca
                    """)
    with gr.Tab("Chatbot"):
        gr.Markdown("# 🐋 OpenChat x OpenOrca-Preview2 GGML Playground Space! 🐋")
        chatbot = gr.Chatbot()
        with gr.Row():
            message = gr.Textbox(
                label="What do you want to chat about?",
                placeholder="Ask me anything.",
                lines=3,
            )
        with gr.Row():
            submit = gr.Button(value="Send message", variant="secondary").style(full_width=True)
            clear = gr.Button(value="New topic", variant="secondary").style(full_width=False)
            stop = gr.Button(value="Stop", variant="secondary").style(full_width=False)
        with gr.Row():
            with gr.Column():
                max_tokens = gr.Slider(20, 1000, label="Max Tokens", step=20, value=300)
                temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=0.8)
                top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.95)
                top_k = gr.Slider(0, 100, label="Top K", step=1, value=40)
                repetition_penalty = gr.Slider(0.0, 2.0, label="Repetition Penalty", step=0.1, value=1.1)

        system_msg = gr.Textbox(
            start_message, label="System Message", interactive=True, visible=True, placeholder="system prompt, useful for RP", lines=5)

        chat_history_state = gr.State()
        clear.click(clear_chat, inputs=[chat_history_state, message], outputs=[chat_history_state, message], queue=False)
        clear.click(lambda: None, None, chatbot, queue=False)

        submit_click_event = submit.click(
            fn=user, inputs=[message, chat_history_state], outputs=[message, chat_history_state], queue=True
        ).then(
            fn=chat, inputs=[chat_history_state, system_msg, max_tokens, temperature, top_p, top_k, repetition_penalty], outputs=[chatbot, chat_history_state, message], queue=True
        )
        stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_click_event], queue=False)

demo.queue(max_size=48, concurrency_count=16).launch(debug=True, server_name="0.0.0.0", server_port=7860)