Omartificial-Intelligence-Space
commited on
Commit
•
08f6cbe
1
Parent(s):
bdb77ab
update app.py
Browse files
app.py
CHANGED
@@ -1,5 +1,3 @@
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# app.py
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import gradio as gr
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from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
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import pandas as pd
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@@ -49,16 +47,13 @@ try:
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except Exception:
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restart_space()
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LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
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print("LEADERBOARD_DF Shape:", LEADERBOARD_DF.shape) # Debug
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print("LEADERBOARD_DF Columns:", LEADERBOARD_DF.columns.tolist()) # Debug
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running_eval_queue_df,
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pending_eval_queue_df,
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) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
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demo = gr.Blocks(css=custom_css)
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with demo:
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@@ -95,7 +90,6 @@ with demo:
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"still_on_hub", type="boolean", label="Deleted/incomplete", default=True
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),
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],
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bool_checkboxgroup_label="Hide models",
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interactive=False,
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)
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@@ -127,12 +121,6 @@ with demo:
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value=None,
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interactive=True,
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)
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# Removed num_examples_input since we're using a fixed number
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# num_examples_input = gr.Number(
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# label="Number of Examples per Subject (e.g., 10)",
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# value=10,
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# precision=0
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# )
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with gr.Column():
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precision = gr.Dropdown(
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@@ -162,7 +150,6 @@ with demo:
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precision,
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weight_type,
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model_type,
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# num_examples_input # Removed
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],
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submission_result,
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)
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import gradio as gr
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from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
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import pandas as pd
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except Exception:
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restart_space()
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# Load the leaderboard DataFrame
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LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
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print("LEADERBOARD_DF Shape:", LEADERBOARD_DF.shape) # Debug
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print("LEADERBOARD_DF Columns:", LEADERBOARD_DF.columns.tolist()) # Debug
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# Load the evaluation queue DataFrames
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finished_eval_queue_df, running_eval_queue_df, pending_eval_queue_df = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
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demo = gr.Blocks(css=custom_css)
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with demo:
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"still_on_hub", type="boolean", label="Deleted/incomplete", default=True
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),
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],
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bool_checkboxgroup_label="Hide models",
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interactive=False,
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)
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value=None,
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interactive=True,
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)
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with gr.Column():
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precision = gr.Dropdown(
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precision,
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weight_type,
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model_type,
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],
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submission_result,
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)
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