init

.gitattributes

@@ -33,4 +33,3 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
-*.whl filter=lfs diff=lfs merge=lfs -text

Dockerfile

@@ -1,10 +1,7 @@
-# 使用 Python 3.11 slim 镜像作为基础镜像
-FROM python:3.11-slim
+FROM python:3.9-slim
 
-# 设置工作目录
 WORKDIR /app
 
-# 安装系统依赖
 RUN apt-get update && apt-get install -y \
     build-essential \
     curl \
@@ -12,27 +9,13 @@ RUN apt-get update && apt-get install -y \
     git \
     && rm -rf /var/lib/apt/lists/*
 
-# 复制依赖文件
 COPY requirements.txt ./
+COPY src/ ./src/
 
-# 安装 Python 依赖
-RUN pip install --no-cache-dir -r requirements.txt
+RUN pip3 install -r requirements.txt
 
-# 复制应用代码
-COPY app/ ./app/
-COPY utils/ ./utils/
-COPY app.py ./
-
-# 暴露 Streamlit 默认端口
 EXPOSE 8501
 
-# 健康检查
-HEALTHCHECK CMD curl --fail http://localhost:8501 || exit 1
-
-# 设置环境变量
-ENV PYTHONPATH=/app
-ENV STREAMLIT_SERVER_PORT=8501
-ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
+HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
 
-# 启动命令
-ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]

README.md

@@ -1,12 +1,19 @@
 ---
-title: RTEB
-emoji: 📊
-colorFrom: yellow
-colorTo: gray
-sdk: streamlit
-sdk_version: 1.44.1
-app_file: app.py
+title: Streamlit Rteb
+emoji: 🚀
+colorFrom: red
+colorTo: red
+sdk: docker
+app_port: 8501
+tags:
+- streamlit
 pinned: false
+short_description: Streamlit template space
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Welcome to Streamlit!
+
+Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).

app.py

@@ -1,46 +0,0 @@
-import os
-
-import streamlit as st
-
-from st_pages import get_nav_from_toml, add_page_title
-
-from app.backend.app_init_func import LI_CSS, init_leaderboard, init_pages
-from app.backend.data_engine import DataEngine
-
-# init global data engine
-data_engine = DataEngine()
-
-st.session_state["data_engine"] = data_engine
-st.set_page_config(layout="wide")
-
-# init leaderboard and pages
-leaderboard_change, page_change = init_leaderboard()
-
-init_pages(leaderboard_change, page_change)
-
-# load page tree
-nav = get_nav_from_toml(
-    "app/ui/pages_sections.toml"
-)
-
-# Add custom CSS
-css = "\n".join(LI_CSS)
-st.markdown(f"""
-    <style>
-
-        div[data-testid="stToolbar"] {{visibility: hidden; height: 0px;}}
-
-        footer {{visibility: hidden;}}
-    </style>
-
-    <style>
-        {css}
-    </style>
-    """
-            , unsafe_allow_html=True)
-
-pg = st.navigation(nav)
-
-# add_page_title(pg)
-
-pg.run()

app/__init__.py

@@ -1 +0,0 @@
-

app/backend/__init__.py

@@ -1 +0,0 @@
-

app/backend/app_init_func.py

@@ -1,84 +0,0 @@
-import streamlit as st
-import os
-
-from app.backend.constant import LEADERBOARD_ICON_MAP
-
-LEADERBOARD_MAP = {}
-LI_CSS = []
-PAGE_SECTIONS = []
-
-
-def init_leaderboard():
-    data_engine = st.session_state["data_engine"]
-    leaderboard_map = {}
-    page_sections = []
-    li_css = []
-    sort_id = 0
-    leaderboard_change = False
-    page_change = False
-
-    for dataset in data_engine.datasets:
-        sort_id += 1
-        leaderboard = dataset["leaderboard"]
-        name = dataset["name"]
-
-        leaderboard_section = f"{leaderboard.capitalize()} Leaderboard"
-        if leaderboard_section not in leaderboard_map:
-            leaderboard_map[leaderboard_section] = []
-        if name.lower() == leaderboard.lower():
-            leaderboard_map[leaderboard_section].append((name, 0))
-        else:
-            leaderboard_map[leaderboard_section].append((name, sort_id))
-            li_css.append(f"""
-            ul[data-testid="stSidebarNavItems"] li:nth-child({sort_id}) {{
-            text-indent: 2rem;
-        }}
-            """)
-        page_name = leaderboard_section if name.lower() == leaderboard.lower() else name.capitalize()
-        page_sections.append(f"""
-        [[pages]]
-        path = "app/ui/pages/{name}.py"
-        name = "{page_name}"
-        icon = "{LEADERBOARD_ICON_MAP.get(page_name, "")}"
-        """)
-
-    # ensure leaderboard is first
-    for k, v in leaderboard_map.items():
-        v.sort(key=lambda x: x[1])
-
-    if leaderboard_map != LEADERBOARD_MAP:
-        LEADERBOARD_MAP.update(leaderboard_map)
-        leaderboard_change = True
-    if page_sections != PAGE_SECTIONS:
-        PAGE_SECTIONS.clear()
-        PAGE_SECTIONS.extend(page_sections)
-        page_change = True
-    if li_css != LI_CSS:
-        LI_CSS.clear()
-        LI_CSS.extend(li_css)
-
-    return leaderboard_change, page_change
-
-
-def init_pages(leaderboard_change, page_change):
-    # init pages
-    if leaderboard_change:
-        with open("app/ui/pages/data_page.py", "r", encoding="utf-8") as f:
-            data_page = f.read()
-        for leaderboard, group_names in LEADERBOARD_MAP.items():
-
-            for group_name in group_names:
-                path = os.path.join("app/ui/pages", f"{group_name[0]}.py")
-                with open(path, "w", encoding="utf-8") as f:
-                    f.write(data_page.replace("$group_name$", group_name[0])
-                            )
-    if page_change:
-        with open("app/ui/pages_sections.toml", "w", encoding="utf-8") as f:
-            f.write("\n".join(PAGE_SECTIONS))
-
-
-if __name__ == '__main__':
-    init_leaderboard()
-    init_pages()
-    print("\n".join(PAGE_SECTIONS))
-    print("\n".join(LI_CSS))

app/backend/constant.py

@@ -1,90 +0,0 @@
-from enum import Enum
-
-
-class Navigation(Enum):
-    TEXT_LEADERBOARD = "Text Leaderboard"
-    MULTIMODAL_LEADERBOARD = "Multimodal Leaderboard"
-
-
-class TaskCategory(Enum):
-    LAW = "Law"
-    CODE = "Code"
-    CONVERSATIONAL = "Conversational"
-    TECH = "Tech"
-    LONG_CONTEXT = "Long-context"
-    MULTILINGUAL = "Multilingual"
-
-
-class ModelProvider(Enum):
-    OPENAI = "OpenAI"
-    VOYAGEAI = "VoyageAI"
-    COHERE = "Cohere"
-    OTHERS = "Others"
-
-
-class EvaluationMetric(Enum):
-    NDCG_1 = "NDCG@1"
-    NDCG_3 = "NDCG@3"
-    NDCG_5 = "NDCG@5"
-    NDCG_10 = "NDCG@10"
-    NDCG_20 = "NDCG@20"
-    NDCG_50 = "NDCG@50"
-    NDCG_100 = "NDCG@100"
-    RECALL_1 = "RECALL@1"
-    RECALL_3 = "RECALL@3"
-    RECALL_5 = "RECALL@5"
-    RECALL_10 = "RECALL@10"
-    RECALL_20 = "RECALL@20"
-    RECALL_50 = "RECALL@50"
-    RECALL_100 = "RECALL@100"
-    PRECISION_1 = "PRECISION@1"
-    PRECISION_3 = "PRECISION@3"
-    PRECISION_5 = "PRECISION@5"
-    PRECISION_10 = "PRECISION@10"
-    PRECISION_20 = "PRECISION@20"
-    PRECISION_50 = "PRECISION@50"
-    PRECISION_100 = "PRECISION@100"
-
-
-class EmbdDtype(Enum):
-    ALL = "all"
-    FLOAT_32 = "float32"
-    INT_8 = "int8"
-    BINARY = "binary"
-
-
-class EmbdDim(Enum):
-    OP1 = "<=1k"
-    OP2 = "1k-2k"
-    OP3 = "2k-5k"
-    OP4 = ">=5k"
-
-
-class Similarity(Enum):
-    ALL = "all"
-    COSINE = "cosine"
-    DOT = "dot"
-    EUCLIDEAN = "euclidean"
-
-
-LEADERBOARD_ICON_MAP = {
-    "Text Leaderboard": "📚",
-    "Law": "⚖️",
-    "Multilingual": "🌎",
-    "German": "🇩🇪",
-    "Code": "💻",
-    "Tech": "🛠️",
-    "Legal": "📜",
-    "English": "🇬🇧",
-    "Healthcare": "🏥",
-    "Finance": "💰",
-    "French": "🇫🇷",
-    "Japanese": "🇯🇵",
-
-}
-
-USERNAME = "embedding-benchmark"
-SPACENAME = "RTEB"
-
-# https://{UserName}-{SpaceName}.hf.space/
-BASE_URL = f"https://{USERNAME}-{SPACENAME}.hf.space/"

app/backend/data_engine.py

@@ -1,179 +0,0 @@
-"""
-Data service provider
-"""
-import json
-from typing import List
-
-import pandas as pd
-
-from utils.cache_decorator import cache_df_with_custom_key, cache_dict_with_custom_key
-from utils.http_utils import get
-
-COLUMNS = ['model_name',
-           'embd_dtype', 'embd_dim', 'num_params', 'max_tokens', 'similarity',
-           'query_instruct', 'corpus_instruct',
-
-           ]
-COLUMNS_TYPES = ["markdown",
-                 'str', 'str', 'number', 'number', 'str',
-                 'str', 'str',
-
-                 ]
-
-BRANCH = 'main'
-GIT_URL = f"https://raw.githubusercontent.com/embedding-benchmark/rteb/refs/heads/{BRANCH}/results/"
-DATASET_URL = f"{GIT_URL}datasets.json"
-MODEL_URL = f"{GIT_URL}models.json"
-RESULT_URL = f"{GIT_URL}results.json"
-
-
-class DataEngine:
-
-    def __init__(self):
-        self.df = self.init_dataframe()
-
-    @property
-    @cache_dict_with_custom_key("models")
-    def models(self):
-        """
-        Get models data
-        """
-        res = get(MODEL_URL)
-        if res.status_code == 200:
-            return res.json()
-        return {}
-
-    @property
-    @cache_dict_with_custom_key("datasets")
-    def datasets(self):
-        """
-        Get tasks data
-        """
-        res = get(DATASET_URL)
-        if res.status_code == 200:
-            return res.json()
-        return {}
-
-    @property
-    @cache_dict_with_custom_key("results")
-    def results(self):
-        """
-        Get results data
-        """
-        res = get(RESULT_URL)
-        if res.status_code == 200:
-            return res.json()
-        return {}
-
-    def init_dataframe(self):
-        """
-        Initialize DataFrame
-        """
-        d = {"hello": [123], "world": [456]}
-        return pd.DataFrame(d)
-
-    @cache_df_with_custom_key("json_result")
-    def jsons_to_df(self):
-
-        results_list = self.results
-        df_results_list = []
-        for result_dict in results_list:
-            dataset_name = result_dict["dataset_name"]
-            df_result_row = pd.DataFrame(result_dict["results"])
-            df_result_row["dataset_name"] = dataset_name
-            df_results_list.append(df_result_row)
-        df_result = pd.concat(df_results_list)
-
-        df_result = df_result[["model_name", "dataset_name", "ndcg_at_10", "embd_dim", "embd_dtype"]]
-
-        df_result["ndcg_at_10"] = (df_result["ndcg_at_10"] * 100).round(2)
-
-        df_datasets_list = []
-        for item in self.datasets:
-            dataset_names = item["datasets"]
-            df_dataset_row = pd.DataFrame(
-                {
-                    "group_name": [item["name"] for _ in range(len(dataset_names))],
-                    "dataset_name": dataset_names,
-                    "leaderboard": [item["leaderboard"] for _ in range(len(dataset_names))]
-                }
-            )
-            df_datasets_list.append(df_dataset_row)
-        df_dataset = pd.concat(df_datasets_list).drop_duplicates()
-
-        models_list = self.models
-
-        df_model = pd.DataFrame(models_list)
-        
-        # Replace None values in num_params with "Unknown"
-        if 'num_params' in df_model.columns:
-            df_model['num_params'] = df_model['num_params'].fillna("Unknown")
-        
-        # Replace blank/None values in vendor with "Open source"
-        if 'vendor' in df_model.columns:
-            df_model['vendor'] = df_model['vendor'].fillna("Open source")
-            df_model['vendor'] = df_model['vendor'].replace('', "Open source")
-            # Also handle whitespace-only strings
-            df_model['vendor'] = df_model['vendor'].apply(lambda x: "Open source" if isinstance(x, str) and x.strip() == '' else x)
-
-        # Create mapping for model names/aliases
-        if 'alias' in df_model.columns:
-            # Create a lookup table for alias to model_name mapping
-            alias_mapping = df_model[df_model['alias'].notna()].set_index('alias')['model_name'].to_dict()
-
-            # Add rows for aliases to enable joining
-            alias_rows = []
-            for _, row in df_model[df_model['alias'].notna()].iterrows():
-                alias_row = row.copy()
-                alias_row['model_name'] = row['alias']
-                alias_rows.append(alias_row)
-
-            if alias_rows:
-                df_model_extended = pd.concat([df_model, pd.DataFrame(alias_rows)], ignore_index=True)
-            else:
-                df_model_extended = df_model
-        else:
-            df_model_extended = df_model
-
-        df = pd.merge(df_result, df_dataset, on=["dataset_name"], how="inner")
-
-        # set dataset default value to 0
-        df = df.pivot(index=["model_name", "embd_dim", "embd_dtype", "group_name"], columns="dataset_name",
-                 values=["ndcg_at_10"]).fillna(0).stack(level=1).reset_index()
-        df = pd.merge(df, df_dataset, on=["group_name","dataset_name"], how="inner")
-
-        # dataset_num_map = {}
-        # grouped_dataset_count = df.groupby(["group_name"]).agg({
-        #     "dataset_name": "nunique"
-        # }).reset_index()
-        #
-        # for _, row in grouped_dataset_count.iterrows():
-        #     dataset_num_map[row["group_name"]] = row["dataset_name"]
-
-        grouped_model = df.groupby(["model_name", "group_name", "embd_dim", "embd_dtype"]).agg({
-            "ndcg_at_10": "mean",
-        }).reset_index()
-
-        pivot = grouped_model.pivot(index=["model_name", "embd_dim", "embd_dtype"], columns="group_name",
-                                    values=["ndcg_at_10"]).round(2).fillna(0)
-
-        # Rename columns
-        pivot.columns = list(
-            map(lambda x: f"{x[1].capitalize()} Average" if x[1] != 'text' else f"Average", pivot.columns))
-
-        pivot_dataset = df_result.pivot(index=["model_name", "embd_dim", "embd_dtype"], columns="dataset_name", values="ndcg_at_10").fillna(0)
-
-        df = pd.merge(df_model_extended, pivot, on=["model_name", "embd_dim", "embd_dtype"])
-        df = pd.merge(df, pivot_dataset, on=["model_name", "embd_dim", "embd_dtype"])
-
-        if df.empty:
-            return pd.DataFrame(columns=COLUMNS + ["reference"])
-        return df
-
-    def filter_df(self, group_name: str):
-        """
-        filter_by_providers
-        """
-        df = self.jsons_to_df()
-
-        return df[df["group_name"] == group_name][COLUMNS][:]

app/backend/data_page.py

@@ -1,442 +0,0 @@
-# -*- coding: utf-8 -*-
-# @Date     : 2025/2/5 16:26
-# @Author   : q275343119
-# @File     : data_page.py
-# @Description:
-import io
-
-from st_aggrid import AgGrid, JsCode, ColumnsAutoSizeMode
-
-import streamlit as st
-
-from app.backend.data_engine import DataEngine
-from app.backend.multi_header_util import get_header_options
-from utils.st_copy_to_clipboard import st_copy_to_clipboard
-from streamlit_theme import st_theme
-
-from app.backend.app_init_func import LEADERBOARD_MAP
-from app.backend.constant import LEADERBOARD_ICON_MAP, BASE_URL
-from app.backend.json_util import compress_msgpack, decompress_msgpack
-
-COLUMNS = ['model_name', 'vendor',
-           'embd_dtype', 'embd_dim', 'num_params', 'max_tokens', 'similarity',
-           'query_instruct', 'corpus_instruct', 'reference'
-
-           ]
-HEADER_STYLE = {'fontSize': '18px'}
-CELL_STYLE = {'fontSize': '18px'}
-
-
-def is_section(group_name):
-    for k, v in LEADERBOARD_MAP.items():
-        leaderboard_name = v[0][0]
-
-        if group_name == leaderboard_name:
-            return True
-    return False
-
-
-def get_closed_dataset():
-    data_engine = st.session_state.get("data_engine", DataEngine())
-    closed_list = []
-    results = data_engine.results
-    for result in results:
-        if result.get("is_closed"):
-            closed_list.append(result.get("dataset_name"))
-    return closed_list
-
-
-def convert_df_to_csv(df):
-    output = io.StringIO()
-    df.to_csv(output, index=False)
-    return output.getvalue()
-
-
-def get_column_state():
-    """
-    get column state from url
-    """
-    query_params = st.query_params.get("grid_state", None)
-    sider_bar_hidden = st.query_params.get("sider_bar_hidden", "False")
-    table_only = st.query_params.get("table_only", "False")
-    if query_params:
-        grid_state = decompress_msgpack(query_params)
-        st.session_state.grid_state = grid_state
-    if sider_bar_hidden.upper() == 'FALSE':
-        st.session_state.sider_bar_hidden = False
-    if table_only.upper() == 'FALSE':
-        st.session_state.table_only = False
-    return None
-
-
-def sidebar_css():
-    """
-
-    :return:
-    """
-    if st.session_state.get("sider_bar_hidden"):
-        st.markdown("""
-            <style>
-            [data-testid="stSidebar"] {
-                display: none !important;
-            }
-            [data-testid="stSidebarNav"] {
-                display: none !important;
-            }
-
-            [data-testid="stBaseButton-headerNoPadding"] {
-                display: none !important;
-            }
-
-           h1#retrieval-embedding-benchmark-rteb {
-                text-align: center;
-            }
-
-            </style>
-        """, unsafe_allow_html=True)
-
-
-def table_only_css():
-    if st.session_state.get("table_only"):
-        st.markdown("""
-                <style>
-
-                [data-testid="stMainBlockContainer"] {
-                    padding-top: 0px;
-                    padding-left: 0px;
-                    padding-bottom: 0px;
-                    padding-right: 0px;
-                }
-
-                [data-testid="stHeader"] {
-                    height: 0px;
-                }
-
-                [data-testid="stApp"] {
-                    height: 456px;
-                }
-
-                .st-emotion-cache-1dp5vir {
-
-                    height: 0px;
-
-                }
-            """, unsafe_allow_html=True)
-
-
-def table_area(group_name, grid_state, data_engine=None, df=None):
-    """
-    table_area
-    :param group_name:
-    :param grid_state:
-    :param data_engine:
-    :param df:
-    :return:
-    """
-    table_only_css()
-
-    if data_engine is None:
-        data_engine = st.session_state.get("data_engine", DataEngine())
-    if df is None:
-        df = data_engine.jsons_to_df().copy()
-
-    # get columns
-    column_list = []
-    avg_column = None
-    if is_section(group_name):
-        avg_columns = []
-        for column in df.columns:
-
-            if column.startswith("Average"):
-                avg_columns.insert(0, column)
-                continue
-            if "Average" in column:
-                avg_columns.append(column)
-                continue
-        avg_column = avg_columns[0]
-        column_list.extend(avg_columns)
-    else:
-        for column in df.columns:
-
-            if column.startswith(group_name.capitalize() + " "):
-                avg_column = column
-
-                column_list.append(avg_column)
-
-    dataset_list = []
-
-    for dataset_dict in data_engine.datasets:
-        if dataset_dict["name"] == group_name:
-            dataset_list = dataset_dict["datasets"]
-    if not is_section(group_name):
-        column_list.extend(dataset_list)
-    closed_list = get_closed_dataset()
-    close_avg_list = list(set(dataset_list) & set(closed_list))
-    df["Closed average"] = df[close_avg_list].mean(axis=1).round(2)
-    column_list.append("Closed average")
-
-    open_avg_list = list(set(dataset_list) - set(closed_list))
-    df["Open average"] = df[open_avg_list].mean(axis=1).round(2)
-    column_list.append("Open average")
-
-    df = df[COLUMNS + column_list].sort_values(by=avg_column, ascending=False)
-
-    # rename avg column  name
-    if not is_section(group_name):
-        new_column = avg_column.replace(group_name.capitalize(), "").strip()
-        df.rename(columns={avg_column: new_column}, inplace=True)
-        column_list.remove(avg_column)
-        avg_column = new_column
-
-    # setting column config - 优化缓存机制，减少不必要的session_state更新
-    grid_options = st.session_state.get(f"{group_name}_grid_options")
-    if grid_options is None:
-        grid_options = get_header_options(column_list, avg_column, is_section(group_name))
-        st.session_state[f"{group_name}_grid_options"] = grid_options
-
-    grid_options["initialState"] = grid_state
-
-    custom_css = {
-        # Model Name Cell
-        ".a-cell": {
-            "display": "inline-block",
-            # "white-space": "nowrap",
-            # "overflow": "hidden",
-            # "text-overflow": "ellipsis",
-            "width": "100%",
-            "min-width": "0"
-        },
-        # Header
-        ".ag-header": {
-            "overflow": "visible !important",
-        },
-        ".multi-line-header": {
-            "text-overflow": "clip",
-            "overflow": "visible",
-            "white-space": "nowrap",
-            "height": "auto",
-            "font-family": 'Arial',
-            "font-size": "14px",
-            "font-weight": "bold",
-            "padding": "10px",
-            "text-align": "left",
-        },
-        # Custom header and cell styles to replace headerStyle and cellStyle
-        ".custom-header-style": {
-            "text-overflow": "clip",
-            "overflow": "visible",
-            "white-space": "normal",
-            "height": "auto",
-            "font-family": 'Arial',
-            "font-size": "14px",
-            "font-weight": "bold",
-            "padding": "10px",
-            "text-align": "left",
-            # "width": "100%"
-        },
-        ".custom-cell-style": {
-            "font-size": "14px",
-            "color": "inherit",
-        },
-        # Filter Options and Input
-        ".ag-theme-streamlit .ag-popup": {
-            "font-family": 'Arial',
-            "font-size": "14px",
-
-        }
-        , ".ag-picker-field-display": {
-            "font-family": 'Arial',
-            "font-size": "14px",
-
-        },
-        ".ag-input-field-input .ag-text-field-input": {
-            "font-family": 'Arial',
-            "font-size": "14px",
-
-        }
-        # , ".link-header-component": {
-        #     "overflow": "visible !important",
-        #     "min-width": "auto !important",
-        # }
-        #
-        # , ".link-header-component > span ": {
-        #     "overflow": "visible !important",
-        #     "white-space": "nowrap !important",
-        #     "text-overflow": "unset !important",
-        #     "flex": "unset !important",
-        # },
-        # ,".custom-link-header-style": {
-        #
-        #     "display": "inline-block",
-        # }
-        , ".ag-header-cell-text": {
-            "overflow": "visible !important",
-            "width": "fit-content"
-
-        }
-        , ".ag-header-cell-label": {
-            "overflow": "visible !important",
-            "width": "fit-content"
-
-        }
-        , "div.link-header-component > span": {
-            "white-space": "pre-wrap !important"
-        }
-    }
-
-    grid = AgGrid(
-        df,
-        enable_enterprise_modules=False,
-        gridOptions=grid_options,
-        allow_unsafe_jscode=True,
-        columns_auto_size_mode=ColumnsAutoSizeMode.FIT_ALL_COLUMNS_TO_VIEW,
-        theme="streamlit",
-        custom_css=custom_css,
-        update_on=["selectionChanged", "filterChanged"],  # 减少WebSocket触发频率，只在重要变化时触发
-    )
-
-    return grid
-
-
-def main_page(group_name, grid_state):
-    """
-    main_page
-    :param group_name:
-    :param grid_state:
-    :return:
-    """
-
-    # Add theme color and grid styles
-    st.title("Retrieval Embedding Benchmark (RTEB)")
-    st.markdown("""
-        <style>
-            :root {
-                --theme-color: rgb(129, 150, 64);
-                --theme-color-light: rgba(129, 150, 64, 0.2);
-            }
-
-            /* AG Grid specific overrides */
-            .ag-theme-alpine {
-                --ag-selected-row-background-color: var(--theme-color-light) !important;
-                --ag-row-hover-color: var(--theme-color-light) !important;
-                --ag-selected-tab-color: var(--theme-color) !important;
-                --ag-range-selection-border-color: var(--theme-color) !important;
-                --ag-range-selection-background-color: var(--theme-color-light) !important;
-            }
-
-            .ag-row-hover {
-                background-color: var(--theme-color-light) !important;
-            }
-
-            .ag-row-selected {
-                background-color: var(--theme-color-light) !important;
-            }
-
-            .ag-row-focus {
-                background-color: var(--theme-color-light) !important;
-            }
-
-            .ag-cell-focus {
-                border-color: var(--theme-color) !important;
-            }
-
-            /* Keep existing styles */
-            .center-text {
-                text-align: center;
-                color: var(--theme-color);
-            }
-            .center-image {
-                display: block;
-                margin-left: auto;
-                margin-right: auto;
-            }
-            h2 {
-                color: var(--theme-color) !important;
-            }
-            .ag-header-cell {
-                background-color: var(--theme-color) !important;
-                color: white !important;
-            }
-            a {
-                color: var(--theme-color) !important;
-            }
-            a:hover {
-                color: rgba(129, 150, 64, 0.8) !important;
-            }
-            /* Download Button */
-            button[data-testid="stBaseButton-secondary"] {
-                float: right;
-
-            }
-            /* Toast On The Top*/
-            div[data-testid="stToastContainer"] {
-                position: fixed !important;
-                z-index: 2147483647 !important;
-            }
-
-        </style>
-
-    """, unsafe_allow_html=True)
-
-    #  logo
-    # st.markdown('<img src="https://www.voyageai.com/logo.svg" class="center-image" width="200">', unsafe_allow_html=True)
-    title = f'<h2 class="center-text">{LEADERBOARD_ICON_MAP.get(group_name.capitalize(), "")} {group_name.capitalize()}</h2>'
-    if is_section(group_name):
-        title = f'<h2 class="center-text">{LEADERBOARD_ICON_MAP.get(group_name.capitalize() + " Leaderboard", "")} {group_name.capitalize() + " Leaderboard"}</h2>'
-    # title
-    st.markdown(title, unsafe_allow_html=True)
-
-    data_engine = st.session_state.get("data_engine", DataEngine())
-
-    df = data_engine.jsons_to_df().copy()
-
-    csv = convert_df_to_csv(df)
-    file_name = f"{group_name.capitalize()} Leaderboard" if is_section(group_name) else group_name.capitalize()
-
-    grid = table_area(group_name, grid_state, data_engine, df)
-
-    @st.dialog("URL")
-    def share_url():
-        state = grid.grid_state
-        if state:
-            share_link = f'{BASE_URL.replace("_", "-")}{group_name}/?grid_state={compress_msgpack(state)}' if not is_section(
-                group_name) else f'{BASE_URL.replace("_", "-")}?grid_state={compress_msgpack(state)}'
-        else:
-            share_link = f'{BASE_URL.replace("_", "-")}{group_name}'
-        st.write(share_link)
-        theme = st_theme()
-        if theme:
-            theme = theme.get("base")
-        else:
-            theme = "light"
-        st_copy_to_clipboard(share_link, before_copy_label='📋Push to copy', after_copy_label='✅Text copied!',
-                             theme=theme)
-
-    col1, col2 = st.columns([1, 1])
-    with col1:
-        st.download_button(
-            label="Download CSV",
-            data=csv,
-            file_name=f"{file_name}.csv",
-            mime="text/csv",
-            icon=":material/download:",
-        )
-    with col2:
-        share_btn = st.button("Share this page", icon=":material/share:")
-
-    if share_btn:
-        share_url()
-
-
-def render_page(group_name):
-    grid_state = st.session_state.get("grid_state", {})
-    st.session_state.sider_bar_hidden = True
-    st.session_state.table_only = True
-    get_column_state()
-
-    sidebar_css()
-
-    if st.session_state.get("table_only"):
-        table_area(group_name, grid_state)
-    else:
-        main_page(group_name, grid_state)

app/backend/json_util.py

@@ -1,15 +0,0 @@
-import msgpack
-import gzip
-import base64
-
-
-def compress_msgpack(data):
-    packed = msgpack.packb(data)
-    compressed = gzip.compress(packed)
-    return base64.urlsafe_b64encode(compressed).decode('utf-8')
-
-
-def decompress_msgpack(compressed_str):
-    compressed = base64.urlsafe_b64decode(compressed_str)
-    unpacked = gzip.decompress(compressed)
-    return msgpack.unpackb(unpacked, raw=False)

app/backend/multi_header_util.py

@@ -1,286 +0,0 @@
-"""
-handle multi_header options
-"""
-from st_aggrid import JsCode
-from streamlit_theme import st_theme
-
-HEADER_STYLE = {'fontSize': '18px'}
-CELL_STYLE = {'fontSize': '18px'}
-LINK = ' https://huggingface.co/datasets/embedding-benchmark/'
-
-
-def get_dataset_url_name(field_name):
-    """Convert field name to proper URL format for closed datasets"""
-    # Handle field names like "ClosedDataset 2 (German Legal Sentences)"
-    if field_name.startswith("ClosedDataset "):
-        # Extract the number and format it as ClosedDataset_X
-        if "(" in field_name:
-            # Extract number from "ClosedDataset 2 (description)" -> "2"
-            number_part = field_name.split("ClosedDataset ")[1].split(" ")[0]
-            return f"ClosedDataset_{number_part}"
-        else:
-            # Handle cases where it might already be in the right format or no parentheses
-            return field_name.replace(" ", "_")
-
-    # Return original field_name for open datasets
-    return field_name
-
-
-def get_closed_dataset_column_name(field_name: str):
-    """Convert field name to tow-line for closed datasets"""
-    if field_name.startswith("ClosedDataset ") and "(" in field_name:
-        idx = field_name.find("(")
-
-        return field_name[:idx] + '\r\n' + field_name[idx:]
-
-    return field_name
-
-
-def mutil_header_options(column_list: list, avg_column: str, is_section: bool):
-    """
-    get mutil_header_options - 优化版本，减少组件实例化
-    :param column_list:
-    :param avg_column:
-    :param is_section:
-    :return:
-    """
-    if is_section:
-        column_def_list = [
-            {'headerName': column if "Average" not in column else column.replace("Average", "").strip().capitalize(),
-             'field': column,
-             'headerClass': 'custom-header-style',
-             'cellClass': 'custom-cell-style',
-             'headerTooltip': column if "Average" not in column else column.replace("Average",
-                                                                                    "").strip().capitalize()
-             # 'suppressSizeToFit': True
-             } for column in column_list if
-            column not in (avg_column, "Closed average", "Open average")]
-
-        return column_def_list
-
-    mutil_column_list = [column for column in column_list if
-                         column not in (avg_column, "Closed average", "Open average")]
-    close_group_list = list(filter(lambda x: x.startswith('_') or x.startswith("ClosedDataset "), mutil_column_list))
-    open_group_list = list(
-        filter(lambda x: not x.startswith('_') and not x.startswith("ClosedDataset "), mutil_column_list))
-
-    close_group_def = {
-        'headerName': 'CLOSED DATASETS',
-        'width': 'fit-content',
-        'headerClass': 'custom-header-style',
-        'cellClass': 'custom-cell-style',
-        'autoHeaderHeight': True,
-        'children': [
-            {'headerName': get_closed_dataset_column_name(column.replace('_', '')),
-             'field': column,
-
-             "headerComponentParams": {
-                 "innerHeaderComponent": "linkHeaderComponent",
-                 "url": LINK + get_dataset_url_name(column),
-                 "headerName": get_closed_dataset_column_name(column.replace('_', ''))
-             },
-
-             'headerClass': 'custom-header-style',
-             'cellClass': 'custom-cell-style',
-             'sortable': True,
-             # 'width': 150,
-             "suppressColumnVirtualisation": True,
-
-             } for column in close_group_list
-        ],
-
-    }
-    open_group_def = {
-        'headerName': 'OPEN DATASETS',
-        'width': 'fit-content',
-        'headerClass': 'custom-header-style',
-        'cellClass': 'custom-cell-style',
-        'autoHeaderHeight': True,
-        'children': [
-            {'headerName': column,
-             'field': column,
-             "headerComponentParams": {
-                 "innerHeaderComponent": "linkHeaderComponent",
-                 "url": LINK + get_dataset_url_name(column),
-                 "headerName": column
-             },
-             'headerClass': 'custom-header-style',
-             'cellClass': 'custom-cell-style',
-             'sortable': True,
-             # 'width': 150,
-             "suppressColumnVirtualisation": True,
-
-             } for column in open_group_list
-        ],
-
-    }
-    return [close_group_def, open_group_def]
-
-
-def get_header_options(column_list: list, avg_column: str, is_section: bool):
-    grid_options = {
-        'columnDefs': [
-            {
-                'headerName': 'Model Name',
-                'field': 'model_name',
-                'pinned': 'left',
-                'sortable': False,
-                'headerClass': 'custom-header-style',
-                'cellClass': 'custom-cell-style',
-                'autoHeaderHeight': True,
-                "tooltipValueGetter": JsCode(
-                    """
-                    function(p) {
-                    const value = p.value || "";
-                    const link = p.data && p.data.reference ? p.data.reference : "";
-                    return link ? `${value} (${link})` : value;
-    }
-                    """
-                ),
-                "width": 250,
-                'cellRenderer': JsCode("""class CustomHTML {
-                            init(params) {
-                                const link = params.data.reference;
-                                this.eGui = document.createElement('div');
-                                this.eGui.innerHTML = link ? 
-                                    `<a href="${link}" class="a-cell" target="_blank">${params.value} </a>` : 
-                                    params.value;
-                            }
-
-                            getGui() {
-                                return this.eGui;
-                            }
-                        }"""),
-                'suppressSizeToFit': True,
-                'headerTooltip': 'Model Name',
-
-            },
-            {'headerName': "Vendor",
-             'field': 'vendor',
-             'headerClass': 'custom-header-style',
-             'cellClass': 'custom-cell-style',
-             # 'suppressSizeToFit': True,
-             'headerTooltip': 'Vendor',
-             },
-            {'headerName': "Overall Score",
-             'field': avg_column,
-             'headerClass': 'custom-header-style',
-             'cellClass': 'custom-cell-style',
-             # 'suppressSizeToFit': True,
-             'headerTooltip': 'Overall Score',
-
-             },
-
-            # Add Open average column definition
-            {'headerName': 'Open Average',
-             'field': 'Open average',
-             'headerClass': 'custom-header-style',
-             'cellClass': 'custom-cell-style',
-             # 'suppressSizeToFit': True,
-             'headerTooltip': 'Open Average',
-
-             },
-
-            {'headerName': 'Closed Average',
-             'field': 'Closed average',
-             'headerClass': 'custom-header-style',
-             'cellClass': 'custom-cell-style',
-             # 'suppressSizeToFit': True,
-             'headerTooltip': 'Closed Average',
-
-             },
-
-            {
-                'headerName': 'Embd Dtype',
-                'field': 'embd_dtype',
-                'headerClass': 'custom-header-style',
-                'cellClass': 'custom-cell-style',
-                # 'suppressSizeToFit': True,
-                'headerTooltip': 'Embd Dtype',
-
-            },
-            {
-                'headerName': 'Embd Dim',
-                'field': 'embd_dim',
-                'headerClass': 'custom-header-style',
-                'cellClass': 'custom-cell-style',
-                # 'suppressSizeToFit': True,
-                'valueFormatter': JsCode(
-                    """
-                    function(params) {
-                            const num = params.value;
-                            if (typeof num !== "number") return num;
-                            if (Math.abs(num) >= 10000) {
-                                return num.toLocaleString("en-US");
-                            }
-                            return num;
-                        }
-                    """
-                ),
-                'headerTooltip': 'Embd Dim',
-
-            },
-            {
-                'headerName': 'Number of Parameters',
-                'field': 'num_params',
-                'cellDataType': 'number',
-                "colId": "num_params",
-                'headerClass': 'custom-header-style',
-                'cellClass': 'custom-cell-style',
-                'valueFormatter': JsCode(
-                    """function(params) {
-                    const num = params.value;
-                    if (num >= 1e9) return (num / 1e9).toFixed(2) + "B";
-                    if (num >= 1e6) return (num / 1e6).toFixed(2) + "M";
-                    if (num >= 1e3) return (num / 1e3).toFixed(2) + "K";
-                    return num;
-                    }"""
-                ),
-                "width": 120,
-                # 'suppressSizeToFit': True,
-                'headerTooltip': 'Number of Parameters',
-
-            },
-            {
-                'headerName': 'Context Length',
-                'field': 'max_tokens',
-                'headerClass': 'custom-header-style',
-                'cellClass': 'custom-cell-style',
-                # 'suppressSizeToFit': True,
-                'valueFormatter': JsCode(
-                    """
-                    function(params) {
-                            const num = params.value;
-                            if (typeof num !== "number") return num;
-                            if (Math.abs(num) >= 10000) {
-                                return num.toLocaleString("en-US");
-                            }
-                            return num;
-                        }
-                    """
-                ),
-                'headerTooltip': 'Context Length',
-
-            },
-
-            *mutil_header_options(column_list, avg_column, is_section)
-        ],
-        'defaultColDef': {
-            'filter': True,
-            'sortable': True,
-            'resizable': True,
-            'headerClass': "multi-line-header",
-            'autoHeaderHeight': True,
-            'width': 105
-        },
-
-        "autoSizeStrategy": {
-            "type": 'fitCellContents',
-            "colIds": [column for column in column_list if column not in (avg_column, "Closed average", "Open average")]
-        },
-        "tooltipShowDelay": 500,
-        "suppressColumnVirtualisation": True
-
-    }
-
-    return grid_options

app/ui/pages/data_page.py

@@ -1,3 +0,0 @@
-from app.backend.data_page import render_page
-
-render_page("$group_name$")

app/ui/pages_sections.toml

@@ -1,54 +0,0 @@
-
-        [[pages]]
-        path = "app/ui/pages/text.py"
-        name = "Text Leaderboard"
-        icon = "📚"
-        
-
-        [[pages]]
-        path = "app/ui/pages/legal.py"
-        name = "Legal"
-        icon = "📜"
-        
-
-        [[pages]]
-        path = "app/ui/pages/english.py"
-        name = "English"
-        icon = "🇬🇧"
-        
-
-        [[pages]]
-        path = "app/ui/pages/code.py"
-        name = "Code"
-        icon = "💻"
-        
-
-        [[pages]]
-        path = "app/ui/pages/healthcare.py"
-        name = "Healthcare"
-        icon = "🏥"
-        
-
-        [[pages]]
-        path = "app/ui/pages/french.py"
-        name = "French"
-        icon = "🇫🇷"
-        
-
-        [[pages]]
-        path = "app/ui/pages/finance.py"
-        name = "Finance"
-        icon = "💰"
-        
-
-        [[pages]]
-        path = "app/ui/pages/german.py"
-        name = "German"
-        icon = "🇩🇪"
-        
-
-        [[pages]]
-        path = "app/ui/pages/japanese.py"
-        name = "Japanese"
-        icon = "🇯🇵"
-        

requirements.txt

@@ -1,6 +1,3 @@
-streamlit==1.47.1
-st-pages==1.0.1
-msgpack==1.1.0
-zstandard==0.23.0
-st-theme==1.2.3
-https://github.com/embedding-benchmark/streamlit-aggrid/releases/download/v0.01/streamlit_aggrid-1.1.7-py3-none-any.whl
+altair
+pandas
+streamlit

src/streamlit_app.py

@@ -0,0 +1,40 @@
+import altair as alt
+import numpy as np
+import pandas as pd
+import streamlit as st
+
+"""
+# Welcome to Streamlit!
+
+Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).
+
+In the meantime, below is an example of what you can do with just a few lines of code:
+"""
+
+num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
+num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
+
+indices = np.linspace(0, 1, num_points)
+theta = 2 * np.pi * num_turns * indices
+radius = indices
+
+x = radius * np.cos(theta)
+y = radius * np.sin(theta)
+
+df = pd.DataFrame({
+    "x": x,
+    "y": y,
+    "idx": indices,
+    "rand": np.random.randn(num_points),
+})
+
+st.altair_chart(alt.Chart(df, height=700, width=700)
+    .mark_point(filled=True)
+    .encode(
+        x=alt.X("x", axis=None),
+        y=alt.Y("y", axis=None),
+        color=alt.Color("idx", legend=None, scale=alt.Scale()),
+        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
+    ))

utils/cache_decorator.py

@@ -1,54 +0,0 @@
-import time
-from functools import wraps
-import pandas as pd
-
-CACHE = {}
-TTL = 3600
-
-
-def cache_df_with_custom_key(cache_key: str):
-    def decorator(func):
-        @wraps(func)
-        def wrapper(*args, **kwargs):
-            if cache_key in CACHE and CACHE[cache_key].get("expiry") - time.time() < TTL:
-                return CACHE[cache_key]["data"]
-
-            result: pd.DataFrame = func(*args, **kwargs)
-            if result is not None and not result.empty:
-                d = {"expiry": time.time(), "data": result}
-                CACHE[cache_key] = d
-                return result
-
-            CACHE[cache_key]["expiry"] += TTL
-            return CACHE[cache_key]["data"]
-
-        return wrapper
-
-    return decorator
-
-
-def cache_dict_with_custom_key(cache_key: str):
-    def decorator(func):
-        @wraps(func)
-        def wrapper(*args, **kwargs):
-            if cache_key in CACHE and time.time() - CACHE[cache_key].get("expiry") < TTL:
-                return CACHE[cache_key]["data"]
-
-            result: dict = func(*args, **kwargs)
-            if result:
-                d = {"expiry": time.time(), "data": result}
-                CACHE[cache_key] = d
-                return result
-
-            CACHE[cache_key]["expiry"] += TTL
-            return CACHE[cache_key]["data"]
-
-        return wrapper
-
-    return decorator
-
-
-if __name__ == '__main__':
-    a = time.time()
-    time.sleep(5)
-    print(time.time() - a)

utils/http_utils.py

@@ -1,7 +0,0 @@
-import requests
-
-
-def get(url: str, params: str = None, verify: bool = False):
-    return requests.get(url, params, verify=verify)
-
-

utils/st_copy_to_clipboard/__init__.py

@@ -1,66 +0,0 @@
-from pathlib import Path
-from typing import Optional
-
-import streamlit as st
-import streamlit.components.v1 as components
-
-# Tell streamlit that there is a component called streamlit_copy_to_clipboard,
-# and that the code to display that component is in the "frontend" folder
-frontend_dir = (Path(__file__).parent / "frontend").absolute()
-_component_func = components.declare_component(
-    "streamlit_copy_to_clipboard", path=str(frontend_dir)
-)
-
-
-def st_copy_to_clipboard(
-    text: str,
-    before_copy_label: str = "📋",
-    after_copy_label: str = "✅",
-    show_text: bool = False,
-    key: Optional[str] = None,
-    theme: str = 'light', # default theme is 'light'
-    
-):
-    """
-    Streamlit component to copy text to clipboard.
-
-    Parameters
-    ----------
-    text : str
-        The text to be copied to the clipboard.
-    before_copy_label : str
-        Label of the button before text is copied.
-    after_copy_label : str
-        Label of the button after text is copied.
-    show_text: bool
-        If True, show text right before the button and make it clickable as well
-    key : str or None
-        An optional key that uniquely identifies the component.
-    theme: str
-        Set the current theme for the button.
-    """
-    component_value = _component_func(
-        key=key,
-        text=text,
-        before_copy_label=before_copy_label,
-        after_copy_label=after_copy_label,
-        show_text=show_text,
-        theme=theme,
-    )
-
-    return component_value
-
-
-def main():
-    st.write("## Example")
-    text = st.text_input("Enter text to copy to clipboard", value="Hello World")
-    st_copy_to_clipboard(text)
-    st_copy_to_clipboard(text, before_copy_label='📋Push to copy', after_copy_label='✅Text copied!')
-    st_copy_to_clipboard(text, before_copy_label='Push to copy', after_copy_label='Text copied!', show_text=True)
-    st_copy_to_clipboard(text, before_copy_label='Push to copy', after_copy_label='copied!', show_text=True, theme="dark")
-
-
-
-
-if __name__ == "__main__":
-    main()

utils/st_copy_to_clipboard/frontend/index.html

@@ -1,19 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-	<head>
-		<meta charset="UTF-8" />
-		<meta http-equiv="X-UA-Compatible" content="IE=edge" />
-		<meta name="viewport" content="width=device-width, initial-scale=1.0" />
-		<title>st-copy-to-clipboard</title>
-		<script src="./streamlit-component-lib.js"></script>
-		<script src="./main.js"></script>
-		<link rel="stylesheet" href="./style.css" />
-	</head>
-
-	<body>
-		<div id="root">
-			<button id="text-element" class="st-copy-to-clipboard-btn"></button>
-			<button id="copy-button" class="st-copy-to-clipboard-btn">📋</button>
-		</div>
-	</body>
-</html>

utils/st_copy_to_clipboard/frontend/main.js

@@ -1,61 +0,0 @@
-// The `Streamlit` object exists because our html file includes
-// `streamlit-component-lib.js`.
-// If you get an error about "Streamlit" not being defined, that
-// means you're missing that file.
-
-function sendValue(value) {
-	Streamlit.setComponentValue(value);
-}
-
-/**
- * The component's render function. This will be called immediately after
- * the component is initially loaded, and then again every time the
- * component gets new data from Python.
- */
-function onRender(event) {
-	// Only run the render code the first time the component is loaded.
-	if (!window.rendered) {
-		const { text, before_copy_label, after_copy_label, show_text, theme } = event.detail.args;
-
-		const container = document.querySelector('#container');
-		const button = document.querySelector('#copy-button');
-		const textElement = document.querySelector('#text-element');
-
-		if (theme == 'dark') {
-			button.style.border = '1px solid rgba(250, 250, 250, 0.2)';
-			button.style.color = 'white';
-		}
-
-		button.textContent = before_copy_label; // Set initial label
-
-		// Show text if show_text is true
-		if (show_text) {
-			textElement.textContent = text;
-			textElement.style.display = 'inline';
-		} else {
-			textElement.style.display = 'none';
-		}
-
-		function copyToClipboard() {
-			navigator.clipboard.writeText(text);
-
-			button.textContent = after_copy_label; // Change label after copying
-
-			setTimeout(() => {
-				if (!button) return;
-				button.textContent = before_copy_label; // Revert to original label after 1 second
-			}, 1000);
-		}
-		button.addEventListener('click', copyToClipboard);
-		textElement.addEventListener('click', copyToClipboard);
-
-		window.rendered = true;
-	}
-}
-
-// Render the component whenever python send a "render event"
-Streamlit.events.addEventListener(Streamlit.RENDER_EVENT, onRender);
-// Tell Streamlit that the component is ready to receive events
-Streamlit.setComponentReady();
-// Render with the correct height, if this is a fixed-height component
-Streamlit.setFrameHeight(100);

utils/st_copy_to_clipboard/frontend/streamlit-component-lib.js

@@ -1,36 +0,0 @@
-// Borrowed minimalistic Streamlit API from Thiago
-// https://discuss.streamlit.io/t/code-snippet-create-components-without-any-frontend-tooling-no-react-babel-webpack-etc/13064
-function sendMessageToStreamlitClient(type, data) {
-	console.log(type, data);
-	const outData = Object.assign(
-		{
-			isStreamlitMessage: true,
-			type: type,
-		},
-		data
-	);
-	window.parent.postMessage(outData, '*');
-}
-
-const Streamlit = {
-	setComponentReady: function () {
-		sendMessageToStreamlitClient('streamlit:componentReady', { apiVersion: 1 });
-	},
-	setFrameHeight: function (height) {
-		sendMessageToStreamlitClient('streamlit:setFrameHeight', { height: height });
-	},
-	setComponentValue: function (value) {
-		sendMessageToStreamlitClient('streamlit:setComponentValue', { value: value });
-	},
-	RENDER_EVENT: 'streamlit:render',
-	events: {
-		addEventListener: function (type, callback) {
-			window.addEventListener('message', function (event) {
-				if (event.data.type === type) {
-					event.detail = event.data;
-					callback(event);
-				}
-			});
-		},
-	},
-};

utils/st_copy_to_clipboard/frontend/style.css

@@ -1,31 +0,0 @@
-.st-copy-to-clipboard-btn {
-	display: inline-flex;
-	-moz-box-align: center;
-	align-items: center;
-	-moz-box-pack: center;
-	justify-content: center;
-	font-weight: 400;
-	padding: 0.25rem 0.75rem;
-	border-radius: 0.5rem;
-	min-height: 38.4px;
-	margin: 0px;
-	line-height: 1.6;
-	color: inherit;
-	width: auto;
-	user-select: none;
-	background-color: transparent; /* set bgcolor to transparent to adjust to any theme */
-	border: 1px solid rgba(49, 51, 63, 0.2);
-	cursor: pointer;
-	float: right;
-}
-
-.st-copy-to-clipboard-btn:hover {
-	border-color: rgb(255, 75, 75);
-	color: rgb(255, 75, 75);
-}
-
-.st-copy-to-clipboard-btn:active {
-	border-color: rgb(255, 75, 75);
-	background-color: rgb(255, 75, 75);
-	color: rgb(255, 255, 255);
-}