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Running
on
CPU Upgrade
hanhainebula
commited on
Commit
•
93fda91
1
Parent(s):
394f64e
fix bugs - 0819
Browse files1) no hyperlink for "BM25" -> add hyperlink
2) unique key of df -> set to timestamp
- app.py +57 -15
- src/display/formatting.py +1 -1
- src/display/gradio_formatting.py +3 -3
- src/envs.py +10 -1
- src/read_evals.py +2 -2
- src/utils.py +2 -2
app.py
CHANGED
@@ -8,15 +8,57 @@ from src.about import (
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TITLE,
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EVALUATION_QUEUE_TEXT
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)
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from src.benchmarks import
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-
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from src.display.css_html_js import custom_css
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from src.display.utils import
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from src.display.gradio_listener import set_listeners
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def restart_space():
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@@ -32,7 +74,7 @@ except Exception as e:
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print(f'failed to download')
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restart_space()
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-
raw_data = get_raw_eval_results(f"{EVAL_RESULTS_PATH}/
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original_df_qa = get_leaderboard_df(
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raw_data, task='qa', metric=DEFAULT_METRIC_QA)
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@@ -190,7 +232,7 @@ with demo:
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queue=True
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)
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with gr.TabItem("Reranking Only", id=12):
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lb_df_reranker = leaderboard_df_qa[leaderboard_df_qa[COL_NAME_RETRIEVAL_MODEL] ==
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lb_df_reranker = reset_rank(lb_df_reranker)
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reranking_models_reranker = lb_df_reranker[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
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with gr.Row():
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@@ -199,7 +241,7 @@ with demo:
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with gr.Column(scale=1):
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search_bar_reranker = gr.Textbox(show_label=False, visible=False)
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lb_table_reranker = get_leaderboard_table(lb_df_reranker, types_qa)
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hidden_lb_df_reranker = original_df_qa[original_df_qa[COL_NAME_RETRIEVAL_MODEL] ==
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hidden_lb_df_reranker = reset_rank(hidden_lb_df_reranker)
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hidden_lb_table_reranker = get_leaderboard_table(
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hidden_lb_df_reranker, types_qa, visible=False
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@@ -345,7 +387,7 @@ with demo:
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)
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with gr.TabItem("Reranking Only", id=22):
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lb_df_reranker_ldoc = leaderboard_df_long_doc[
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leaderboard_df_long_doc[COL_NAME_RETRIEVAL_MODEL] ==
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]
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lb_df_reranker_ldoc = reset_rank(lb_df_reranker_ldoc)
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reranking_models_reranker_ldoc = lb_df_reranker_ldoc[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
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@@ -355,7 +397,7 @@ with demo:
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with gr.Column(scale=1):
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search_bar_reranker_ldoc = gr.Textbox(show_label=False, visible=False)
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lb_table_reranker_ldoc = get_leaderboard_table(lb_df_reranker_ldoc, types_long_doc)
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hidden_lb_df_reranker_ldoc = original_df_long_doc[original_df_long_doc[COL_NAME_RETRIEVAL_MODEL] ==
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hidden_lb_df_reranker_ldoc = reset_rank(hidden_lb_df_reranker_ldoc)
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hidden_lb_table_reranker_ldoc = get_leaderboard_table(
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hidden_lb_df_reranker_ldoc, types_long_doc, visible=False
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@@ -414,8 +456,8 @@ with demo:
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with gr.Row():
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with gr.Column():
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benchmark_version = gr.Dropdown(
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value=
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interactive=True,
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label="AIR-Bench Version")
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with gr.Row():
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TITLE,
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EVALUATION_QUEUE_TEXT
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)
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from src.benchmarks import (
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DOMAIN_COLS_QA,
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LANG_COLS_QA,
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DOMAIN_COLS_LONG_DOC,
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LANG_COLS_LONG_DOC,
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METRIC_LIST,
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DEFAULT_METRIC_QA,
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DEFAULT_METRIC_LONG_DOC
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)
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from src.display.css_html_js import custom_css
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from src.display.utils import (
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COL_NAME_IS_ANONYMOUS,
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COL_NAME_REVISION,
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COL_NAME_TIMESTAMP,
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COL_NAME_RERANKING_MODEL,
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COL_NAME_RETRIEVAL_MODEL
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)
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from src.envs import (
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API,
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EVAL_RESULTS_PATH,
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REPO_ID,
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RESULTS_REPO,
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TOKEN,
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BM25_LINK,
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BENCHMARK_VERSION_LIST,
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LATEST_BENCHMARK_VERSION
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)
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from src.read_evals import (
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get_raw_eval_results,
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get_leaderboard_df
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)
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from src.utils import (
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update_metric,
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upload_file,
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get_default_cols,
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submit_results,
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reset_rank,
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remove_html
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)
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from src.display.gradio_formatting import (
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get_version_dropdown,
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get_search_bar,
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get_reranking_dropdown,
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get_metric_dropdown,
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get_domain_dropdown,
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get_language_dropdown,
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get_anonymous_checkbox,
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get_revision_and_ts_checkbox,
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get_leaderboard_table,
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get_noreranking_dropdown
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)
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from src.display.gradio_listener import set_listeners
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def restart_space():
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print(f'failed to download')
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restart_space()
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raw_data = get_raw_eval_results(f"{EVAL_RESULTS_PATH}/{LATEST_BENCHMARK_VERSION}")
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original_df_qa = get_leaderboard_df(
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raw_data, task='qa', metric=DEFAULT_METRIC_QA)
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queue=True
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)
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with gr.TabItem("Reranking Only", id=12):
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lb_df_reranker = leaderboard_df_qa[leaderboard_df_qa[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK]
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lb_df_reranker = reset_rank(lb_df_reranker)
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reranking_models_reranker = lb_df_reranker[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
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with gr.Row():
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with gr.Column(scale=1):
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search_bar_reranker = gr.Textbox(show_label=False, visible=False)
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lb_table_reranker = get_leaderboard_table(lb_df_reranker, types_qa)
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hidden_lb_df_reranker = original_df_qa[original_df_qa[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK]
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hidden_lb_df_reranker = reset_rank(hidden_lb_df_reranker)
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hidden_lb_table_reranker = get_leaderboard_table(
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hidden_lb_df_reranker, types_qa, visible=False
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)
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with gr.TabItem("Reranking Only", id=22):
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lb_df_reranker_ldoc = leaderboard_df_long_doc[
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leaderboard_df_long_doc[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK
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]
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lb_df_reranker_ldoc = reset_rank(lb_df_reranker_ldoc)
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reranking_models_reranker_ldoc = lb_df_reranker_ldoc[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
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with gr.Column(scale=1):
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search_bar_reranker_ldoc = gr.Textbox(show_label=False, visible=False)
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lb_table_reranker_ldoc = get_leaderboard_table(lb_df_reranker_ldoc, types_long_doc)
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hidden_lb_df_reranker_ldoc = original_df_long_doc[original_df_long_doc[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK]
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hidden_lb_df_reranker_ldoc = reset_rank(hidden_lb_df_reranker_ldoc)
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hidden_lb_table_reranker_ldoc = get_leaderboard_table(
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hidden_lb_df_reranker_ldoc, types_long_doc, visible=False
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with gr.Row():
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with gr.Column():
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benchmark_version = gr.Dropdown(
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BENCHMARK_VERSION_LIST,
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value=LATEST_BENCHMARK_VERSION,
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interactive=True,
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label="AIR-Bench Version")
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with gr.Row():
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src/display/formatting.py
CHANGED
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def make_clickable_model(model_name: str, model_link: str):
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# link = f"https://huggingface.co/{model_name}"
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if not model_link or not model_link.startswith("https://")
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return model_name
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return model_hyperlink(model_link, model_name)
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def make_clickable_model(model_name: str, model_link: str):
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# link = f"https://huggingface.co/{model_name}"
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if not model_link or not model_link.startswith("https://"):
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return model_name
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return model_hyperlink(model_link, model_name)
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src/display/gradio_formatting.py
CHANGED
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import gradio as gr
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def get_version_dropdown():
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return gr.Dropdown(
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choices=
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value=
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label="Select the version of AIR-Bench",
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interactive=True
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)
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import gradio as gr
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from src.envs import BENCHMARK_VERSION_LIST, LATEST_BENCHMARK_VERSION
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def get_version_dropdown():
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return gr.Dropdown(
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choices=BENCHMARK_VERSION_LIST,
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value=LATEST_BENCHMARK_VERSION,
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label="Select the version of AIR-Bench",
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interactive=True
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)
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src/envs.py
CHANGED
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import os
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from huggingface_hub import HfApi
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# Info to change for your repository
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EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval_results")
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API = HfApi(token=TOKEN)
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import os
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from display.formatting import model_hyperlink
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from huggingface_hub import HfApi
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# Info to change for your repository
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EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval_results")
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API = HfApi(token=TOKEN)
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BM25_LINK = model_hyperlink("https://github.com/castorini/pyserini", "BM25")
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BENCHMARK_VERSION_LIST = [
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"AIR-Bench_24.04",
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# "AIR-Bench_24.05",
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]
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LATEST_BENCHMARK_VERSION = BENCHMARK_VERSION_LIST[-1]
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src/read_evals.py
CHANGED
@@ -174,8 +174,8 @@ def get_raw_eval_results(results_path: str) -> List[FullEvalResult]:
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print(f"loading file failed. {model_result_filepath}")
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continue
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print(f'file loaded: {model_result_filepath}')
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eval_results[
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results = []
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for k, v in eval_results.items():
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print(f"loading file failed. {model_result_filepath}")
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continue
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print(f'file loaded: {model_result_filepath}')
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timestamp = eval_result.timestamp
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eval_results[timestamp] = eval_result
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results = []
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for k, v in eval_results.items():
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src/utils.py
CHANGED
@@ -10,7 +10,7 @@ from src.benchmarks import BENCHMARK_COLS_QA, BENCHMARK_COLS_LONG_DOC, Benchmark
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from src.display.formatting import styled_message, styled_error
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from src.display.utils import COLS_QA, TYPES_QA, COLS_LONG_DOC, TYPES_LONG_DOC, COL_NAME_RANK, COL_NAME_AVG, \
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COL_NAME_RERANKING_MODEL, COL_NAME_RETRIEVAL_MODEL, COL_NAME_IS_ANONYMOUS, COL_NAME_TIMESTAMP, COL_NAME_REVISION, get_default_auto_eval_column_dict
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from src.envs import API, SEARCH_RESULTS_REPO
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from src.read_evals import FullEvalResult, get_leaderboard_df, calculate_mean
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import re
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model_url: str,
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reranking_model: str="",
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reranking_model_url: str="",
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version: str=
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is_anonymous=False):
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if not filepath.endswith(".zip"):
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return styled_error(f"file uploading aborted. wrong file type: {filepath}")
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from src.display.formatting import styled_message, styled_error
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from src.display.utils import COLS_QA, TYPES_QA, COLS_LONG_DOC, TYPES_LONG_DOC, COL_NAME_RANK, COL_NAME_AVG, \
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COL_NAME_RERANKING_MODEL, COL_NAME_RETRIEVAL_MODEL, COL_NAME_IS_ANONYMOUS, COL_NAME_TIMESTAMP, COL_NAME_REVISION, get_default_auto_eval_column_dict
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from src.envs import API, SEARCH_RESULTS_REPO, LATEST_BENCHMARK_VERSION
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from src.read_evals import FullEvalResult, get_leaderboard_df, calculate_mean
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import re
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model_url: str,
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reranking_model: str="",
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reranking_model_url: str="",
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version: str=LATEST_BENCHMARK_VERSION,
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is_anonymous=False):
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if not filepath.endswith(".zip"):
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return styled_error(f"file uploading aborted. wrong file type: {filepath}")
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