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import time | |
import os | |
import gradio as gr | |
from text_generation import Client | |
from conversation import get_default_conv_template | |
from transformers import AutoTokenizer | |
endpoint_url = os.environ.get("ENDPOINT_URL", "http://127.0.0.1:8080") | |
client = Client(endpoint_url, timeout=120) | |
eos_token = "</s>" | |
max_prompt_length = 4096 - 512 - 10 | |
tokenizer = AutoTokenizer.from_pretrained("yentinglin/Taiwan-LLaMa-v1.0") | |
with gr.Blocks() as demo: | |
chatbot = gr.Chatbot() | |
msg = gr.Textbox() | |
clear = gr.Button("Clear") | |
def user(user_message, history): | |
return "", history + [[user_message, None]] | |
def bot(history): | |
conv = get_default_conv_template("vicuna").copy() | |
roles = {"human": conv.roles[0], "gpt": conv.roles[1]} # map human to USER and gpt to ASSISTANT | |
for user, bot in history: | |
conv.append_message(roles['human'], user) | |
conv.append_message(roles["gpt"], bot) | |
msg = conv.get_prompt() | |
prompt_tokens = tokenizer.encode(msg) | |
length_of_prompt = len(prompt_tokens) | |
if length_of_prompt > max_prompt_length: | |
msg = tokenizer.decode(prompt_tokens[-max_prompt_length+1:]) | |
history[-1][1] = "" | |
for response in client.generate_stream( | |
msg, | |
max_new_tokens=512, | |
): | |
if not response.token.special: | |
character = response.token.text | |
history[-1][1] += character | |
yield history | |
def generate_response(history, max_new_token=512, top_p=0.9, temperature=0.8, do_sample=True): | |
conv = get_default_conv_template("vicuna").copy() | |
roles = {"human": conv.roles[0], "gpt": conv.roles[1]} # map human to USER and gpt to ASSISTANT | |
for user, bot in history: | |
conv.append_message(roles['human'], user) | |
conv.append_message(roles["gpt"], bot) | |
msg = conv.get_prompt() | |
for response in client.generate_stream( | |
msg, | |
max_new_tokens=max_new_token, | |
top_p=top_p, | |
temperature=temperature, | |
do_sample=do_sample, | |
): | |
history[-1][1] = "" | |
# if not response.token.special: | |
character = response.token.text | |
history[-1][1] += character | |
print(history[-1][1]) | |
time.sleep(0.05) | |
yield history | |
msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then( | |
bot, chatbot, chatbot | |
) | |
clear.click(lambda: None, None, chatbot, queue=False) | |
demo.queue() | |
demo.launch() | |
# | |
# with gr.Blocks() as demo: | |
# chatbot = gr.Chatbot() | |
# with gr.Row(): | |
# with gr.Column(scale=4): | |
# with gr.Column(scale=12): | |
# user_input = gr.Textbox( | |
# show_label=False, | |
# placeholder="Shift + Enter傳送...", | |
# lines=10).style( | |
# container=False) | |
# with gr.Column(min_width=32, scale=1): | |
# submitBtn = gr.Button("Submit", variant="primary") | |
# with gr.Column(scale=1): | |
# emptyBtn = gr.Button("Clear History") | |
# max_new_token = gr.Slider( | |
# 1, | |
# 1024, | |
# value=128, | |
# step=1.0, | |
# label="Maximum New Token Length", | |
# interactive=True) | |
# top_p = gr.Slider(0, 1, value=0.9, step=0.01, | |
# label="Top P", interactive=True) | |
# temperature = gr.Slider( | |
# 0, | |
# 1, | |
# value=0.5, | |
# step=0.01, | |
# label="Temperature", | |
# interactive=True) | |
# top_k = gr.Slider(1, 40, value=40, step=1, | |
# label="Top K", interactive=True) | |
# do_sample = gr.Checkbox( | |
# value=True, | |
# label="Do Sample", | |
# info="use random sample strategy", | |
# interactive=True) | |
# repetition_penalty = gr.Slider( | |
# 1.0, | |
# 3.0, | |
# value=1.1, | |
# step=0.1, | |
# label="Repetition Penalty", | |
# interactive=True) | |
# | |
# params = [user_input, chatbot] | |
# predict_params = [ | |
# chatbot, | |
# max_new_token, | |
# top_p, | |
# temperature, | |
# top_k, | |
# do_sample, | |
# repetition_penalty] | |
# | |
# submitBtn.click( | |
# generate_response, | |
# [user_input, max_new_token, top_p, top_k, temperature, do_sample, repetition_penalty], | |
# [chatbot], | |
# queue=False | |
# ) | |
# | |
# user_input.submit( | |
# generate_response, | |
# [user_input, max_new_token, top_p, top_k, temperature, do_sample, repetition_penalty], | |
# [chatbot], | |
# queue=False | |
# ) | |
# | |
# submitBtn.click(lambda: None, [], [user_input]) | |
# | |
# emptyBtn.click(lambda: chatbot.reset(), outputs=[chatbot], show_progress=True) | |
# | |
# demo.launch() |