MohamedRashad commited on
Commit
fbd0e7d
Β·
1 Parent(s): 492c93e

Refactor search_leaderboard to use retrieval_df and update UI tab labels for clarity

Browse files
Files changed (1) hide show
  1. app.py +24 -19
app.py CHANGED
@@ -40,15 +40,15 @@ CITATION_BUTTON_TEXT = """
40
  }
41
  """
42
 
43
- df = None
44
  original_columns_order = None
45
 
46
  def search_leaderboard(model_name, columns_to_show):
47
  if len(model_name.strip()) == 0:
48
- return df.loc[:, columns_to_show]
49
 
50
  threshold = 95 # You can adjust this value to make the search more or less strict
51
- filtered_df = df.copy()
52
 
53
  def calculate_similarity(row):
54
  similarity = fuzz.partial_ratio(model_name.lower(), row["Model"].lower())
@@ -70,20 +70,20 @@ def search_leaderboard(model_name, columns_to_show):
70
 
71
 
72
  def main():
73
- global df, original_columns_order
74
- df = load_retrieval_results()
75
- df[["Model"]] = df[["Model"]].map(lambda x: f'<a href="https://huggingface.co/{x}" target="_blank">{x}</a>')
76
- df.drop(columns=["Revision", "Precision", "Task"], inplace=True)
77
- df.sort_values("Web Search Dataset (Overall Score)", ascending=False, inplace=True)
78
 
79
  columns_to_show = ["Model", "Web Search Dataset (Overall Score)", "Model Size (in Millions)", "Embedding Dimension", "Max Tokens", "Num Likes"]
80
  with gr.Blocks() as demo:
81
  gr.HTML(HEADER)
82
 
83
  with gr.Tabs():
84
- with gr.Tab("Retrieval"):
85
  with gr.Tabs():
86
- with gr.Tab("Leaderboard"):
87
  with gr.Row():
88
  search_box_retrieval = gr.Textbox(
89
  placeholder="Search for models...",
@@ -92,13 +92,13 @@ def main():
92
  )
93
  columns_to_show_input = gr.CheckboxGroup(
94
  label="Columns to Show",
95
- choices=df.columns.tolist(),
96
  value=columns_to_show,
97
  scale=4
98
  )
99
 
100
  retrieval_leaderboard = gr.Dataframe(
101
- value=df[columns_to_show],
102
  datatype="markdown",
103
  wrap=True,
104
  show_fullscreen_button=True,
@@ -112,17 +112,20 @@ def main():
112
  outputs=retrieval_leaderboard
113
  )
114
  columns_to_show_input.select(
115
- lambda columns: df.loc[:, columns],
116
  inputs=columns_to_show_input,
117
  outputs=retrieval_leaderboard
118
  )
119
 
120
- with gr.Tab("Submit Retriever"):
121
  submit_gradio_module("Retriever")
122
 
123
- with gr.Tab("Reranking"):
 
 
 
124
  with gr.Tabs():
125
- with gr.Tab("Leaderboard"):
126
  search_box_reranker = gr.Textbox(
127
  placeholder="Search for models...",
128
  label="Search",
@@ -130,7 +133,7 @@ def main():
130
  )
131
 
132
  reranker_leaderboard = gr.Dataframe(
133
- value=df[columns_to_show],
134
  datatype="markdown",
135
  wrap=True,
136
  show_fullscreen_button=True,
@@ -143,11 +146,13 @@ def main():
143
  outputs=reranker_leaderboard
144
  )
145
 
146
- with gr.Tab("Submit Reranker"):
147
  submit_gradio_module("Reranker")
148
 
 
 
149
 
150
- # with gr.Tab("LLM Context Answering"):
151
  # with gr.Tabs():
152
  # with gr.Tab("Leaderboard"):
153
  # pass
 
40
  }
41
  """
42
 
43
+ retrieval_df = None
44
  original_columns_order = None
45
 
46
  def search_leaderboard(model_name, columns_to_show):
47
  if len(model_name.strip()) == 0:
48
+ return retrieval_df.loc[:, columns_to_show]
49
 
50
  threshold = 95 # You can adjust this value to make the search more or less strict
51
+ filtered_df = retrieval_df.copy()
52
 
53
  def calculate_similarity(row):
54
  similarity = fuzz.partial_ratio(model_name.lower(), row["Model"].lower())
 
70
 
71
 
72
  def main():
73
+ global retrieval_df, original_columns_order
74
+ retrieval_df = load_retrieval_results()
75
+ retrieval_df[["Model"]] = retrieval_df[["Model"]].map(lambda x: f'<a href="https://huggingface.co/{x}" target="_blank">{x}</a>')
76
+ retrieval_df.drop(columns=["Revision", "Precision", "Task"], inplace=True)
77
+ retrieval_df.sort_values("Web Search Dataset (Overall Score)", ascending=False, inplace=True)
78
 
79
  columns_to_show = ["Model", "Web Search Dataset (Overall Score)", "Model Size (in Millions)", "Embedding Dimension", "Max Tokens", "Num Likes"]
80
  with gr.Blocks() as demo:
81
  gr.HTML(HEADER)
82
 
83
  with gr.Tabs():
84
+ with gr.Tab("πŸ•΅οΈβ€β™‚οΈ Retrieval"):
85
  with gr.Tabs():
86
+ with gr.Tab("πŸ‘‘ Leaderboard"):
87
  with gr.Row():
88
  search_box_retrieval = gr.Textbox(
89
  placeholder="Search for models...",
 
92
  )
93
  columns_to_show_input = gr.CheckboxGroup(
94
  label="Columns to Show",
95
+ choices=retrieval_df.columns.tolist(),
96
  value=columns_to_show,
97
  scale=4
98
  )
99
 
100
  retrieval_leaderboard = gr.Dataframe(
101
+ value=retrieval_df[columns_to_show],
102
  datatype="markdown",
103
  wrap=True,
104
  show_fullscreen_button=True,
 
112
  outputs=retrieval_leaderboard
113
  )
114
  columns_to_show_input.select(
115
+ lambda columns: retrieval_df.loc[:, columns],
116
  inputs=columns_to_show_input,
117
  outputs=retrieval_leaderboard
118
  )
119
 
120
+ with gr.Tab("🏡️ Submit Retriever"):
121
  submit_gradio_module("Retriever")
122
 
123
+ with gr.Tab("ℹ️ About"):
124
+ gr.Markdown(ABOUT_SECTION)
125
+
126
+ with gr.Tab("πŸ“Š Reranking"):
127
  with gr.Tabs():
128
+ with gr.Tab("πŸ‘‘ Leaderboard"):
129
  search_box_reranker = gr.Textbox(
130
  placeholder="Search for models...",
131
  label="Search",
 
133
  )
134
 
135
  reranker_leaderboard = gr.Dataframe(
136
+ value=retrieval_df[columns_to_show],
137
  datatype="markdown",
138
  wrap=True,
139
  show_fullscreen_button=True,
 
146
  outputs=reranker_leaderboard
147
  )
148
 
149
+ with gr.Tab("🏡️ Submit Reranker"):
150
  submit_gradio_module("Reranker")
151
 
152
+ with gr.Tab("ℹ️ About"):
153
+ gr.Markdown(ABOUT_SECTION)
154
 
155
+ # with gr.Tab("🧠 LLM Context Answering"):
156
  # with gr.Tabs():
157
  # with gr.Tab("Leaderboard"):
158
  # pass