File size: 2,495 Bytes
6d05e55 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 |
import gradio as gr
import argparse
import os
import json
from vllm import LLM, SamplingParams
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--base_model", type=str) # model path
parser.add_argument("--n_gpus", type=int, default=1) # n_gpu
return parser.parse_args()
def predict(message, history, system_prompt, temperature, max_tokens):
instruction = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. "
for human, assistant in history:
instruction += 'USER: '+ human + ' ASSISTANT: '+ assistant + '</s>'
instruction += 'USER: '+ message + ' ASSISTANT:'
problem = [instruction]
stop_tokens = ["USER:", "USER", "ASSISTANT:", "ASSISTANT"]
sampling_params = SamplingParams(temperature=temperature, top_p=1, max_tokens=max_tokens, stop=stop_tokens)
completions = llm.generate(problem, sampling_params)
for output in completions:
prompt = output.prompt
print('==========================question=============================')
print(prompt)
generated_text = output.outputs[0].text
print('===========================answer=============================')
print(generated_text)
for idx in range(len(generated_text)):
yield generated_text[:idx+1]
if __name__ == "__main__":
args = parse_args()
llm = LLM(model=args.base_model, tensor_parallel_size=args.n_gpus)
gr.ChatInterface(
predict,
title="LLM playground - WizardLM-13B-V1.2",
description="This is a LLM playground for WizardLM-13B-V1.2, github: https://github.com/nlpxucan/WizardLM, huggingface: https://huggingface.co/WizardLM",
theme="soft",
chatbot=gr.Chatbot(height=1400, label="Chat History",),
textbox=gr.Textbox(placeholder="input", container=False, scale=7),
retry_btn=None,
undo_btn="Delete Previous",
clear_btn="Clear",
additional_inputs=[
gr.Textbox("A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.", label="System Prompt"),
gr.Slider(0, 1, 0.9, label="Temperature"),
gr.Slider(100, 2048, 1024, label="Max Tokens"),
],
additional_inputs_accordion_name="Parameters",
).queue().launch(share=False, server_port=7870)
|