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import os | |
import requests | |
import json | |
import time | |
import gradio as gr | |
from transformers import AutoTokenizer | |
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 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. | |
The current release version of Breeze-7B is v1.0. | |
*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: MediaTek Research Breeze-7B 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") | |
TOKENIZER_REPO = "MediaTek-Research/Breeze-7B-Instruct-v1_0" | |
API_MODEL_TYPE = "breeze-7b-instruct-v10" | |
HEADERS = { | |
"Authorization": f"Bearer {TOKEN}", | |
"Content-Type": "application/json", | |
"accept": "application/json" | |
} | |
MAX_SEC = 30 | |
MAX_INPUT_LENGTH = 5000 | |
tokenizer = AutoTokenizer.from_pretrained(TOKENIZER_REPO, use_auth_token=os.environ.get("HF_TOKEN")) | |
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 | |
print(message) | |
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": API_MODEL_TYPE, | |
"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: 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(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() | |