app.py

# coding=utf-8
# author: xusong
# time: 2022/8/23 16:06

"""
## TODO:
- http get方式获取参数，
- 自启动
- iter_vocab 的 warmup
- add_special_token 开关
- theme 开关 light/dark
- token_id/tokens/bytes 开关
- 通过 javascript 添加 hover_text
-



plots

table

## related demo
- [](http://text-processing.com/demo/tokenize/)
- [gpt-tokenizer](https://gpt-tokenizer.dev/)
- [llama-tokenizer-js](https://belladoreai.github.io/llama-tokenizer-js/example-demo/build/)
- [](https://huggingface.co/spaces/Xenova/the-tokenizer-playground)

## 可视化

[ The, 2, QUICK, Brown, Foxes, jumped, over, the, lazy, dog's, bone ]
"""


import gradio as gr

from vocab import all_tokenizers
from util import *

example_text = """Replace this text in the input field to see how tokenization works
华为智能音箱发布：华为Sound X"""

# llama chatglm_6b gpt_nexo_20b baichuan  baichuan_7b
examples = [
    # ["空格测试：  2个空格        8个空格", "llama", "chatglm_6b"],  # chatglm 有blank_n,
    ["标点测试：，。！？；", "baichuan_7b", "llama"],
    ["符号测试：🦙❤❥웃유♋☮✊☏☢☚✔☑♚▢♪✈✞÷↑↓▤▥⊙■□▣▽¿─│♥❣▬▫☿Ⓐ ✋✉☣☤", "baichuan_7b", "llama"],
    ["中文简体：宽带，繁体：樂來", "baichuan_7b", "llama"],
    ["数字测试：(10086 + 98) = 100184", "baichuan_7b", "llama"],
]


def example_fn(example_idx):
    return examples[example_idx]



with gr.Blocks(css="style.css") as demo:
    gr.HTML("""<h1 align="center">Tokenizer Arena ⚔️</h1>""")
    # links: https://www.coderstool.com/utf8-encoding-decoding
    # 功能：输入文本，进行分词
    # 分词器：常见的分词器有集中，
    # 背景：方便分词、看词粒度、对比
    #
    # Byte: 表示分词

    with gr.Row():
        gr.Markdown("## Input Text")
        dropdown_examples = gr.Dropdown(
            ["Example1", "Example2", "Example3"],
            value="Examples",
            type="index",
            show_label=False,
            container=False,
            scale=0,
            elem_classes="example-style"
        )

    user_input = gr.Textbox(
        value=example_text,
        label="Input Text",
        lines=5,
        show_label=False,
    )  # placeholder="Enter sentence here..."
    # gr.Examples(
    #     examples,
    #     None,
    # )


    gr.Markdown("## Tokenization")

    with gr.Row():
        with gr.Column(scale=6):
            with gr.Group():
                tokenizer_type_1 = gr.Dropdown(
                    all_tokenizers,
                    value="llama",
                    label="Tokenizer 1",
                )
                with gr.Group():
                    """
                    <div class="stat"><div class="stat-value">69</div><div class="stat-label">Characters</div></div>
                    """
                    with gr.Row():
                        stats_vocab_size_1 = gr.TextArea(
                            label="VocabSize",
                            lines=1,
                            elem_classes="statistics"
                        )
                        stats_zh_token_size_1 = gr.TextArea(
                            # value="1252/1455",
                            label="ZH char/word",
                            lines=1,
                            elem_classes="statistics"
                        )
                        stats_overlap_token_size_1 = gr.TextArea(
                            label="Overlap Tokens",
                            lines=1,
                            elem_classes="statistics"
                        )
                        # stats_3 = gr.TextArea(
                        #     label="Compress Rate",
                        #     lines=1,
                        #     elem_classes="statistics"
                        # )
        # https://www.onlinewebfonts.com/icon/418591
        gr.Image("images/VS.svg", scale=1, show_label=False, show_download_button=False, container=False)  # height=10,
        with gr.Column(scale=6):
            with gr.Group():
                tokenizer_type_2 = gr.Dropdown(
                    all_tokenizers,
                    value="baichuan_7b",
                    label="Tokenizer 2",
                )
                with gr.Group():
                    with gr.Row():
                        stats_vocab_size_2 = gr.TextArea(
                            label="VocabSize",
                            lines=1,
                            elem_classes="statistics"
                        )
                        stats_zh_token_size_2 = gr.TextArea(  # 中文单子数，
                            # value="12/45",
                            label="ZH char/word",
                            lines=1,
                            elem_classes="statistics"
                        )
                        # stats_6 = gr.TextArea(
                        #     label="Compress Rate",
                        #     lines=1,
                        #     elem_classes="statistics"
                        # )
                        stats_overlap_token_size_2 = gr.TextArea(
                            label="Overlap Tokens",
                            lines=1,
                            elem_classes="statistics"
                        )

    # TODO: 图 表 压缩率
    with gr.Row():
        with gr.Column():
            output_text_1 = gr.Highlightedtext(
                label="Tokens 1",
                show_legend=True,
                elem_classes="space-show"
            )
        with gr.Column():
            output_text_2 = gr.Highlightedtext(
                label="Tokens 2",
                show_legend=True,
                elem_classes="space-show"
            )

    with gr.Row():
        output_table_1 = gr.Dataframe(
            headers=["TokenID", "Byte", "Text"],
            datatype=["str", "str", "str"],
            # elem_classes="space-show",   # 给整个Dataframe加这个css不起作用，因此直接修改cell-wrap
        )
        output_table_2 = gr.Dataframe(
            headers=["TokenID", "Token", "Text"],
            datatype=["str", "str", "str"],
        )

    tokenizer_type_1.change(tokenize, [user_input, tokenizer_type_1],
                            [output_text_1, output_table_1])
    # 下面两个好像可以合并
    tokenizer_type_1.change(basic_count, [tokenizer_type_1], [stats_vocab_size_1, stats_zh_token_size_1])
    tokenizer_type_1.change(get_overlap_token_size, [tokenizer_type_1, tokenizer_type_2],
                            [stats_overlap_token_size_1, stats_overlap_token_size_2])

    user_input.change(tokenize_pair,
                      [user_input, tokenizer_type_1, tokenizer_type_2],
                      [output_text_1, output_table_1, output_text_2, output_table_2])

    tokenizer_type_2.change(tokenize, [user_input, tokenizer_type_2],
                            [output_text_2, output_table_2])
    tokenizer_type_2.change(basic_count, [tokenizer_type_2], [stats_vocab_size_2, stats_zh_token_size_2])
    tokenizer_type_2.change(get_overlap_token_size, [tokenizer_type_1, tokenizer_type_2],
                            [stats_overlap_token_size_1, stats_overlap_token_size_2])

    dropdown_examples.change(
        example_fn,
        dropdown_examples,
        [user_input, tokenizer_type_1, tokenizer_type_2]
    )

    # start up 初始化
    # user_input.update(user_input.value + "___")


if __name__ == "__main__":
    demo.queue(max_size=20).launch()
    # demo.launch()