app.py

import os
from openai import OpenAI
import gradio as gr


import socket
hostname=socket.gethostname()
IPAddr=socket.gethostbyname(hostname)
print("Your Computer Name is:" + hostname)
print("Your Computer IP Address is:" + IPAddr)


DESCRIPTION = """
# Cloned from MediaTek Research Breeze-7B
MediaTek Research Breeze-7B (hereinafter referred to as Breeze-7B) is a language model family that builds on top of [Mistral-7B](https://huggingface.co/mistralai/Mistral-7B-v0.1), specifically intended for Traditional Chinese use.
[Breeze-7B-Base](https://huggingface.co/MediaTek-Research/Breeze-7B-Base-v1_0) is the base model for the Breeze-7B series. 
It is suitable for use if you have substantial fine-tuning data to tune it for your specific use case.
[Breeze-7B-Instruct](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v1_0) derives from the base model Breeze-7B-Base, making the resulting model amenable to be used as-is for commonly seen tasks.

This App is cloned from [Demo-MR-Breeze-7B](https://huggingface.co/spaces/MediaTek-Research/Demo-MR-Breeze-7B)

"""

LICENSE = """
"""

DEFAULT_SYSTEM_PROMPT = "You are a helpful AI assistant built by MediaTek Research. The user you are helping speaks Traditional Chinese and comes from Taiwan."

API_URL = os.environ.get("API_URL")
TOKEN = os.environ.get("TOKEN")
TOKENIZER_REPO = "MediaTek-Research/Breeze-7B-Instruct-v1_0"
MODEL_NAME = os.environ.get("MODEL_NAME")
MAX_SEC = 30
MAX_INPUT_LENGTH = 5000


def chat_with_openai(model_name, system_message, user_message, temperature=0.5, max_tokens=1024, top_p=0.5):
    client = OpenAI(
        base_url=API_URL,
        api_key=TOKEN
    )    

    chat_completion = client.chat.completions.create(
        model=model_name,
        messages=[
            {
                "role": "system",
                "content": system_message
            },
            {
                "role": "user",
                "content": user_message
            }
        ],
        temperature=temperature,
        max_tokens=max_tokens,
        top_p=top_p,
        stream=True
    )

    for message in chat_completion:
        yield message.choices[0].delta.content

def refusal_condition(query):
    # 不要再問這些問題啦！

    query_remove_space = query.replace(' ', '').lower()
    is_including_tw = False
    for x in ['台灣', '台湾', 'taiwan', 'tw', '中華民國', '中华民国']:
        if x in query_remove_space:
            is_including_tw = True
    is_including_cn = False
    for x in ['中國', '中国', 'cn', 'china', '大陸', '內地', '大陆', '内地', '中華人民共和國', '中华人民共和国']:
        if x in query_remove_space:
            is_including_cn = True
    if is_including_tw and is_including_cn:
        return True

    for x in ['一個中國', '兩岸', '一中原則', '一中政策', '一个中国', '两岸', '一中原则']:
        if x in query_remove_space:
            return True

    return False

with gr.Blocks() as demo:
    # Check if the API_URL and TOKEN are set
    if API_URL is None:
        raise gr.Error("API_URL is not set as an environment variable.")
    if TOKEN is None:
        raise gr.Error("TOKEN is not set as an environment variable.")
    if MODEL_NAME is None:
        raise gr.Error("MODEL_NAME is not set as an environment variable.")

    gr.Markdown(DESCRIPTION)

    system_prompt = gr.Textbox(label='System prompt',
                               value=DEFAULT_SYSTEM_PROMPT,
                               lines=1)
    
    with gr.Accordion(label='Advanced options', open=False):

        max_new_tokens = gr.Slider(
            label='Max new tokens',
            minimum=32,
            maximum=2048,
            step=1,
            value=1024,
        )
        temperature = gr.Slider(
            label='Temperature',
            minimum=0.01,
            maximum=0.5,
            step=0.01,
            value=0.01,
        )
        top_p = gr.Slider(
            label='Top-p (nucleus sampling)',
            minimum=0.01,
            maximum=0.99,
            step=0.01,
            value=0.01,
        )

    chatbot = gr.Chatbot(show_copy_button=True, show_share_button=True, )
    with gr.Row():
        msg = gr.Textbox(
            container=False,
            show_label=False,
            placeholder='Type a message...',
            scale=10,
            lines=6
        )
        submit_button = gr.Button('Submit',
                                  variant='primary',
                                  scale=1,
                                  min_width=0)

    with gr.Row():
        retry_button = gr.Button('🔄  Retry', variant='secondary')
        undo_button = gr.Button('↩️ Undo', variant='secondary')
        clear = gr.Button('🗑️  Clear', variant='secondary')

    saved_input = gr.State()

    def user(user_message, history):
        return "", history + [[user_message, None]]

    def bot(history, max_new_tokens, temperature, top_p, system_prompt):
        chat_data = []
        system_prompt = system_prompt.strip()
        if system_prompt:
            chat_data.append({"role": "system", "content": system_prompt})
        for user_msg, assistant_msg in history:
            chat_data.append({"role": "user", "content": user_msg if user_msg is not None else ''})
            chat_data.append({"role": "assistant", "content": assistant_msg if assistant_msg is not None else ''})

        response = '[ERROR]'
        if refusal_condition(history[-1][0]):
            history = [['[安全拒答啟動]', '[安全拒答啟動] 請清除再開啟對話']]
            response = '[REFUSAL]'
            yield history
        else:
            r = chat_with_openai(
                MODEL_NAME,
                system_prompt,
                history[-1][0],
                temperature,
                max_new_tokens,
                top_p)
            if r is not None:
                for delta in r:
                    if history[-1][1] is None:
                        history[-1][1] = ''
                    if delta is None:
                        delta = ''
                    history[-1][1] += delta
                    yield history

                if history[-1][1].endswith('</s>'):
                    history[-1][1] = history[-1][1][:-4]
                    yield history
    
                response = history[-1][1]
    
                if refusal_condition(history[-1][1]):
                    history[-1][1] = history[-1][1] + '\n\n**[免責聲明: 此模型並未針對問答進行安全保護，因此語言模型的任何回應不代表 MediaTek Research 立場。]**'
                    yield history
            else:
                del history[-1]
                yield history

        print('== Record ==\nQuery: {query}\nResponse: {response}'.format(query=repr(history[-1][0]), response=repr(history[-1][1])))
        
    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
        fn=bot,
        inputs=[
            chatbot,
            max_new_tokens,
            temperature,
            top_p,
            system_prompt,
        ],
        outputs=chatbot
    )

    submit_button.click(
        user, [msg, chatbot], [msg, chatbot], queue=False
    ).then(
        fn=bot,
        inputs=[
            chatbot,
            max_new_tokens,
            temperature,
            top_p,
            system_prompt,
        ],
        outputs=chatbot
    )


    def delete_prev_fn(
            history: list[tuple[str, str]]) -> tuple[list[tuple[str, str]], str]:
        try:
            message, _ = history.pop()
        except IndexError:
            message = ''
        return history, message or ''


    def display_input(message: str,
                      history: list[tuple[str, str]]) -> list[tuple[str, str]]:
        history.append((message, ''))
        return history

    retry_button.click(
        fn=delete_prev_fn,
        inputs=chatbot,
        outputs=[chatbot, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=display_input,
        inputs=[saved_input, chatbot],
        outputs=chatbot,
        api_name=False,
        queue=False,
    ).then(
        fn=bot,
        inputs=[
            chatbot,
            max_new_tokens,
            temperature,
            top_p,
            system_prompt,
        ],
        outputs=chatbot,
    )

    undo_button.click(
        fn=delete_prev_fn,
        inputs=chatbot,
        outputs=[chatbot, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=lambda x: x,
        inputs=[saved_input],
        outputs=msg,
        api_name=False,
        queue=False,
    )

    clear.click(lambda: None, None, chatbot, queue=False)

    gr.Markdown(LICENSE)

demo.queue(default_concurrency_limit=10)
demo.launch()