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__all__ = ['block', 'make_clickable_model', 'make_clickable_user', 'get_submissions'] | |
import os | |
import gradio as gr | |
import pandas as pd | |
import json | |
import tempfile | |
from constants import * | |
from huggingface_hub import Repository | |
HF_TOKEN = os.environ.get("HF_TOKEN") | |
global data_component, filter_component | |
def upload_file(files): | |
file_paths = [file.name for file in files] | |
return file_paths | |
def add_new_eval( | |
input_file, | |
model_name_textbox: str, | |
revision_name_textbox: str, | |
model_type: str, | |
model_link: str, | |
model_size: str, | |
LLM_type: str, | |
LLM_name_textbox: str, | |
): | |
if input_file is None: | |
return "Error! Empty file!" | |
upload_data=json.loads(input_file) | |
submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset") | |
submission_repo.git_pull() | |
csv_data = pd.read_csv(CSV_DIR) | |
if LLM_type == 'Other': | |
LLM_name = LLM_name_textbox | |
else: | |
LLM_name = LLM_type | |
if revision_name_textbox == '': | |
col = csv_data.shape[0] | |
model_name = model_name_textbox | |
else: | |
model_name = revision_name_textbox | |
model_name_list = csv_data['Model'] | |
name_list = [name.split(']')[0][1:] for name in model_name_list] | |
if revision_name_textbox not in name_list: | |
col = csv_data.shape[0] | |
else: | |
col = name_list.index(revision_name_textbox) | |
if model_link == '': | |
model_name = model_name # no url | |
else: | |
model_name = '[' + model_name + '](' + model_link + ')' | |
# add new data | |
new_data = [ | |
model_type, | |
model_name, | |
LLM_name | |
] | |
for key in TASK_INFO: | |
if key in upload_data: | |
new_data.append(upload_data[key]) | |
else: | |
new_data.append(0) | |
csv_data.loc[col] = new_data | |
csv_data = csv_data.to_csv(CSV_DIR, index=False) | |
submission_repo.push_to_hub() | |
return 0 | |
def get_baseline_df(): | |
submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset") | |
submission_repo.git_pull() | |
df = pd.read_csv(CSV_DIR) | |
df = df.sort_values(by="Avg", ascending=False) | |
present_columns = MODEL_INFO + checkbox_group.value | |
df = df[present_columns] | |
return df | |
def get_all_df(): | |
submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset") | |
submission_repo.git_pull() | |
df = pd.read_csv(CSV_DIR) | |
df = df.sort_values(by="Avg", ascending=False) | |
return df | |
def on_filter_model_size_method_change(selected_columns): | |
updated_data = get_all_df() | |
# columns: | |
selected_columns = [item for item in TASK_INFO if item in selected_columns] | |
present_columns = MODEL_INFO + selected_columns | |
print("selected_columns",'|'.join(selected_columns)) | |
updated_data = updated_data[present_columns] | |
updated_data = updated_data.sort_values(by=selected_columns[0], ascending=False) | |
updated_headers = present_columns | |
update_datatype = [DATA_TITILE_TYPE[COLUMN_NAMES.index(x)] for x in updated_headers] | |
print(updated_data,present_columns,update_datatype) | |
filter_component = gr.components.Dataframe( | |
value=updated_data, | |
headers=updated_headers, | |
type="pandas", | |
datatype=update_datatype, | |
interactive=False, | |
visible=True, | |
) | |
return filter_component#.value | |
block = gr.Blocks() | |
with block: | |
gr.Markdown( | |
LEADERBORAD_INTRODUCTION | |
) | |
with gr.Tabs(elem_classes="tab-buttons") as tabs: | |
with gr.TabItem("π MVBench", elem_id="mvbench-tab-table", id=1): | |
with gr.Row(): | |
with gr.Accordion("Citation", open=False): | |
citation_button = gr.Textbox( | |
value=CITATION_BUTTON_TEXT, | |
label=CITATION_BUTTON_LABEL, | |
elem_id="citation-button", | |
) | |
gr.Markdown( | |
TABLE_INTRODUCTION | |
) | |
# selection for column part: | |
checkbox_group = gr.CheckboxGroup( | |
choices=TASK_INFO, | |
value=AVG_INFO, | |
label="Evaluation Dimension", | |
interactive=True, | |
) | |
data_component = gr.components.Dataframe( | |
value=get_baseline_df, | |
headers=COLUMN_NAMES, | |
type="pandas", | |
datatype=DATA_TITILE_TYPE, | |
interactive=False, | |
visible=True, | |
) | |
checkbox_group.change(fn=on_filter_model_size_method_change, inputs=[ checkbox_group], outputs=data_component) | |
# table 2 | |
with gr.TabItem("π About", elem_id="mvbench-tab-table", id=2): | |
gr.Markdown(LEADERBORAD_INFO, elem_classes="markdown-text") | |
# table 3 | |
with gr.TabItem("π Submit here! ", elem_id="mvbench-tab-table", id=3): | |
gr.Markdown(LEADERBORAD_INTRODUCTION, elem_classes="markdown-text") | |
with gr.Row(): | |
gr.Markdown(SUBMIT_INTRODUCTION, elem_classes="markdown-text") | |
with gr.Row(): | |
gr.Markdown("# βοΈβ¨ Submit your model evaluation json file here!", elem_classes="markdown-text") | |
with gr.Row(): | |
with gr.Column(): | |
model_name_textbox = gr.Textbox( | |
label="Model name", placeholder="LLaMA-7B" | |
) | |
revision_name_textbox = gr.Textbox( | |
label="Revision Model Name", placeholder="LLaMA-7B" | |
) | |
model_type = gr.Dropdown( | |
choices=[ | |
"LLM", | |
"ImageLLM", | |
"VideoLLM", | |
"Other", | |
], | |
label="Model type", | |
multiselect=False, | |
value="ImageLLM", | |
interactive=True, | |
) | |
with gr.Column(): | |
LLM_type = gr.Dropdown( | |
choices=["Vicuna-7B", "Flan-T5-XL", "LLaMA-7B", "InternLM-7B", "Other"], | |
label="LLM type", | |
multiselect=False, | |
value="LLaMA-7B", | |
interactive=True, | |
) | |
LLM_name_textbox = gr.Textbox( | |
label="LLM model (for Other)", | |
placeholder="LLaMA-13B" | |
) | |
model_link = gr.Textbox( | |
label="Model Link", placeholder="https://huggingface.co/decapoda-research/llama-7b-hf" | |
) | |
model_size = gr.Textbox( | |
label="Model size", placeholder="7B(Input content format must be 'number+B' or '-')" | |
) | |
with gr.Column(): | |
input_file = gr.components.File(label = "Click to Upload a json File", file_count="single", type='binary') | |
submit_button = gr.Button("Submit Eval") | |
submission_result = gr.Markdown() | |
submit_button.click( | |
add_new_eval, | |
inputs = [ | |
input_file, | |
model_name_textbox, | |
revision_name_textbox, | |
model_type, | |
model_link, | |
model_size, | |
LLM_type, | |
LLM_name_textbox, | |
], | |
) | |
def refresh_data(): | |
value1 = get_baseline_df() | |
return value1 | |
with gr.Row(): | |
data_run = gr.Button("Refresh") | |
data_run.click(on_filter_model_size_method_change, inputs=[checkbox_group], outputs=data_component) | |
block.launch() |