app.py

import os
import requests
import json
import time

import gradio as gr
from transformers import AutoTokenizer
import psycopg2


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


DESCRIPTION = """
# MediaTek Research Breexe-8x7B  

Breexe-8x7B is a language model family that builds on top of [Mixtral-8x7B](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), 
specifically intended for Traditional Chinese use. 
[Breexe-8x7B-Instruct-v0_1](https://huggingface.co/MediaTek-Research/Breexe-8x7B-Instruct-v0_1) demonstrates impressive performance in benchmarks for Traditional Chinese and English, on par with OpenAI's  gpt-3.5-turbo-1106.  


*A project by the members (in alphabetical order): Chan-Jan Hsu 許湛然, Chang-Le Liu 劉昶樂, Feng-Ting Liao 廖峰挺, Po-Chun Hsu 許博竣, Yi-Chang Chen 陳宜昌, and the supervisor Da-Shan Shiu 許大山.*  

**免責聲明: Breexe-8x7B-Instruct 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。**
"""

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")

HEADERS = {
    "Authorization": f"Bearer {TOKEN}", 
    "Content-Type": "application/json",
    "accept": "application/json"
}


MAX_SEC = 30
MAX_INPUT_LENGTH = 5000

tokenizer = AutoTokenizer.from_pretrained("MediaTek-Research/Breexe-8x7B-Instruct-v0_1", use_auth_token=os.environ.get("HF_TOKEN"))

def insert_to_db(prompt, response, temperature, top_p):
    try:
        #Establishing the connection
        conn = psycopg2.connect(
           database=os.environ.get("DB"), user=os.environ.get("USER"), password=os.environ.get("DB_PASS"), host=os.environ.get("DB_HOST"), port= '5432'
        )
        #Setting auto commit false
        conn.autocommit = True
        
        #Creating a cursor object using the cursor() method
        cursor = conn.cursor()
    
        # Preparing SQL queries to INSERT a record into the database.
        cursor.execute(f"INSERT INTO breezedata(prompt, response, temperature, top_p) VALUES ('{prompt}', '{response}', {temperature}, {top_p})")
    
        # Commit your changes in the database
        conn.commit()
    
        # Closing the connection
        conn.close()
    except:
        pass


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:
    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 connect_server(data):
        for _ in range(3):
            s = requests.Session()
            r = s.post(API_URL, headers=HEADERS, json=data, stream=True, timeout=30)
            time.sleep(1)
            if r.status_code == 200:
                return r
        return None


    def stream_response_from_server(r):
        # start_time = time.time()
        keep_streaming = True
        for line in r.iter_lines():
            # if time.time() - start_time > MAX_SEC:
            #     keep_streaming = False
            #     break
            
            if line and keep_streaming:
                if r.status_code != 200:
                    continue
                json_response = json.loads(line)

                if "fragment" not in json_response["result"]:
                    keep_streaming = False
                    break

                delta = json_response["result"]["fragment"]["data"]["text"]
                yield delta

            # start_time = time.time()

    
    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 ''})

        message = tokenizer.apply_chat_template(chat_data, tokenize=False)
        message = message[3:]  # remove SOT token

        if len(message) > MAX_INPUT_LENGTH:
            raise Exception()

        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:
            data = {
                "model_type": "breexe-8x7b-instruct-v01",
                "prompt": str(message),
                "parameters": {
                    "temperature": float(temperature),
                    "top_p": float(top_p),
                    "max_new_tokens": int(max_new_tokens),
                    "repetition_penalty": 1.1
                }
            }
            
            r = connect_server(data)
            if r is not None:
                for delta in stream_response_from_server(r):
                    if history[-1][1] is None:
                        history[-1][1] = ''
                    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: Breexe-8x7B-Instruct 和 Breexe-8x7B-Instruct-64k 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(message), 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(concurrency_count=4, max_size=128)
demo.launch()