test / app.py
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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=os.path.join(API_URL, "v1/"),
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()