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import os | |
import gradio as gr | |
from text_generation import Client | |
from conversation import get_default_conv_template, SeparatorStyle | |
eos_token = "</s>" | |
def _concat_messages(messages): | |
message_text = "" | |
for message in messages: | |
if message["role"] == "system": | |
message_text += "<|system|>\n" + message["content"].strip() + "\n" | |
elif message["role"] == "user": | |
message_text += "<|user|>\n" + message["content"].strip() + "\n" | |
elif message["role"] == "assistant": | |
message_text += "<|assistant|>\n" + message["content"].strip() + eos_token + "\n" | |
else: | |
raise ValueError("Invalid role: {}".format(message["role"])) | |
return message_text | |
endpoint_url = os.environ.get("ENDPOINT_URL") | |
client = Client(endpoint_url, timeout=120) | |
def generate_response(user_input, max_new_token, top_p, top_k, temperature, do_sample, repetition_penalty): | |
user_input = user_input.strip() | |
conv = get_default_conv_template("vicuna").copy() | |
roles = {"human": conv.roles[0], "gpt": conv.roles[1]} # map human to USER and gpt to ASSISTANT | |
role = roles["human"] | |
conv.append_message(role, user_input) | |
msg = conv.get_prompt() | |
res = client.generate( | |
msg, | |
stop_sequences=["<|assistant|>", eos_token, "<|system|>", "<|user|>"], | |
max_new_tokens=max_new_token, | |
top_p=top_p, | |
top_k=top_k, | |
do_sample=do_sample, | |
temperature=temperature, | |
repetition_penalty=repetition_penalty, | |
) | |
return [("assistant", res.generated_text)] | |
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() |