通义千问 7B Gradio

qwen_web.py

import gradio as gr
import mdtex2html
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from transformers.generation.utils import GenerationConfig

# 模型路径
MODEL_PATH = 'Qwen/Qwen-7B-Chat'

CONTEXT_SIZE = 8192
MAX_LENGTH = 2048
TOP_P = 0.8


# quantization configuration for NF4 (4 bits)
nf4_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type='nf4',
    bnb_4bit_compute_dtype=torch.bfloat16
)

# quantization configuration for Int8 (8 bits)
int8_config = BitsAndBytesConfig(load_in_8bit=True)

model = AutoModelForCausalLM.from_pretrained(
    MODEL_PATH,
    trust_remote_code=True,
    # quantization_config=int8_config,
    device_map="auto",
)

tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH, use_fast=False, trust_remote_code=True)

model.generation_config = GenerationConfig.from_pretrained(MODEL_PATH)
model.generation_config.max_context_size = CONTEXT_SIZE
model.generation_config.top_p = TOP_P
model.generation_config.max_new_tokens = MAX_LENGTH


def postprocess(self, y):
    if y is None:
        return []
    for i, (message, response) in enumerate(y):
        y[i] = (
            None if message is None else mdtex2html.convert((message)),
            None if response is None else mdtex2html.convert(response),
        )
    return y


gr.Chatbot.postprocess = postprocess


def parse_text(text):
    """copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
    lines = text.split("\n")
    lines = [line for line in lines if line != ""]
    count = 0
    for i, line in enumerate(lines):
        if "```" in line:
            count += 1
            items = line.split('`')
            if count % 2 == 1:
                lines[i] = f'<pre><code class="language-{items[-1]}">'
            else:
                lines[i] = f'<br></code></pre>'
        else:
            if i > 0:
                if count % 2 == 1:
                    line = line.replace("`", "\`")
                    line = line.replace("<", "&lt;")
                    line = line.replace(">", "&gt;")
                    line = line.replace(" ", "&nbsp;")
                    line = line.replace("*", "&ast;")
                    line = line.replace("_", "&lowbar;")
                    line = line.replace("-", "&#45;")
                    line = line.replace(".", "&#46;")
                    line = line.replace("!", "&#33;")
                    line = line.replace("(", "&#40;")
                    line = line.replace(")", "&#41;")
                    line = line.replace("$", "&#36;")
                lines[i] = "<br>"+line
    text = "".join(lines)
    return text


def predict(input, chatbot, history):
    chatbot.append((parse_text(input), ""))
    response, history = model.chat(tokenizer, parse_text(input), history)
    chatbot[-1] = (parse_text(input), parse_text(response))
    yield chatbot, history


def reset_user_input():
    return gr.update(value='')


def reset_state():
    return [], []


with gr.Blocks() as demo:
    gr.HTML("""通义千问 7B""")
    chatbot = gr.Chatbot()
    with gr.Row():
        with gr.Column(scale=4):
            user_input = gr.Textbox(show_label=False, placeholder="在此输入消息", lines=4, container=False)
        with gr.Column(scale=1):
            submitBtn = gr.Button("Submit", variant="primary")
            emptyBtn = gr.Button("重置会话")
    history = gr.State([])
    submitBtn.click(predict, [user_input, chatbot, history], [chatbot, history], show_progress=True)
    submitBtn.click(reset_user_input, [], [user_input])
    emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)

demo.queue().launch(share=True, inbrowser=True, server_name="0.0.0.0", server_port=9999)