Update app.py

app.py

@@ -3,58 +3,65 @@ from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
 import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
 from huggingface_hub import snapshot_download
-
 from src.about import (
-    CITATION_BUTTON_LABEL,
-    CITATION_BUTTON_TEXT,
-    EVALUATION_QUEUE_TEXT,
-    INTRODUCTION_TEXT,
-    LLM_BENCHMARKS_TEXT,
-    TITLE,
+  CITATION_BUTTON_LABEL,
+  CITATION_BUTTON_TEXT,
+  EVALUATION_QUEUE_TEXT,
+  INTRODUCTION_TEXT,
+  LLM_BENCHMARKS_TEXT,
+  TITLE,
 )
 from src.display.css_html_js import custom_css
 from src.display.utils import (
-    BENCHMARK_COLS,
-    COLS,
-    EVAL_COLS,
-    EVAL_TYPES,
-    AutoEvalColumn,
-    ModelType,
-    fields,
-    WeightType,
-    Precision
+  BENCHMARK_COLS,
+  COLS,
+  EVAL_COLS,
+  EVAL_TYPES,
+  AutoEvalColumn,
+  ModelType,
+  fields,
+  WeightType,
+  Precision,
 )
 from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REPO_ID, RESULTS_REPO, TOKEN
 from src.populate import get_evaluation_queue_df, get_leaderboard_df
 from src.submission.submit import add_new_eval
 
-
 def restart_space():
-    API.restart_space(repo_id=REPO_ID)
+  API.restart_space(repo_id=REPO_ID)
 
 ### Space initialisation
 try:
-    print(EVAL_REQUESTS_PATH)
-    snapshot_download(
-        repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
-    )
+  print(EVAL_REQUESTS_PATH)
+  snapshot_download(
+    repo_id=QUEUE_REPO,
+    local_dir=EVAL_REQUESTS_PATH,
+    repo_type="dataset",
+    tqdm_class=None,
+    etag_timeout=30,
+    token=TOKEN,
+  )
 except Exception:
-    restart_space()
+  restart_space()
+
 try:
-    print(EVAL_RESULTS_PATH)
-    snapshot_download(
-        repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
-    )
+  print(EVAL_RESULTS_PATH)
+  snapshot_download(
+    repo_id=RESULTS_REPO,
+    local_dir=EVAL_RESULTS_PATH,
+    repo_type="dataset",
+    tqdm_class=None,
+    etag_timeout=30,
+    token=TOKEN,
+  )
 except Exception:
-    restart_space()
-
+  restart_space()
 
 LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
-
 (
-    finished_eval_queue_df,
-    running_eval_queue_df,
-    pending_eval_queue_df,
+  finished_eval_queue_df,
+  running_eval_queue_df,
+  pending_eval_queue_df,
 ) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
 
 def init_leaderboard(dataframe):
@@ -70,117 +77,40 @@ def init_leaderboard(dataframe):
     ),
     search_columns=[AutoEvalColumn.model.name, AutoEvalColumn.license.name],
     hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden],
-    filter_columns=[
-      ColumnFilter(AutoEvalColumn.model_type.name, type="checkboxgroup", label="Model types"),
-      ColumnFilter(AutoEvalColumn.precision.name, type="checkboxgroup", label="Precision"),
-      ColumnFilter(AutoEvalColumn.params.name, type="slider", min=0.01, max=150, label="Select the number of parameters (B)"),
-      ColumnFilter(AutoEvalColumn.still_on_hub.name, type="boolean", label="Deleted/incomplete", default=True),
-    ],
-    bool_checkboxgroup_label="Hide models",
-    interactive=False,
-  )
-  def display_user_data(user_id):
+    filter_columns=[            ColumnFilter(AutoEvalColumn.model_type.name, type="checkboxgroup", label="Model types"),
+            ColumnFilter(AutoEvalColumn.precision.name, type="checkboxgroup", label="Precision"),
+            ColumnFilter(
+                AutoEvalColumn.params.name, type="slider", min=0.01, max=150, label="Select the number of parameters (B)"
+            ),
+            ColumnFilter(AutoEvalColumn.still_on_hub.name, type="boolean", label="Deleted/incomplete", default=True),
+        ],
+        bool_checkboxgroup_label="Hide models",
+        interactive=False,
+    )
+
+def display_user_data(user_id):
     user_data = data.load_data()
     if user_id in user_data:
-      return f"Points: {user_data[user_id]['points']}\nReferrals: {len(user_data[user_id]['referrals'])}"
+        return f"Points: {user_data[user_id]['points']}\nReferrals: {len(user_data[user_id]['referrals'])}"
     else:
-      return "User not found"
-import gradio as gr # No indentation before this line!
-from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
-import pandas as pd
-# ... (Rest of your code)
-revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
-model_type = gr.Dropdown(
-  choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
-  label="Model type",
-  multiselect=False,
-  value=None,
-  interactive=True,
-)
-with gr.Column():
-  precision = gr.Dropdown(
-    choices=[i.value.name for i in Precision if i != Precision.Unknown],
-    label="Precision",
-    multiselect=False,
-    value="float16",
-    interactive=True,
-  )
-  weight_type = gr.Dropdown(
-    choices=[i.value.name for i in WeightType],
-    label="Weights type",
-    multiselect=False,
-    value="Original",
-    interactive=True,
-  )
-  base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
-  model_name_textbox = gr.Textbox(label="Model name") # Add this line
-
-submit_button = gr.Button("Submit Eval")
-submission_result = gr.Markdown()
+        return "User not found"
 
-# Indent the entire `with gr.Row()` section
-with gr.Row(): 
-  with gr.Accordion("📙 Citation", open=False):
-    citation_button = gr.Textbox(
-      value=CITATION_BUTTON_TEXT,
-      label=CITATION_BUTTON_LABEL,
-      lines=20,
-      elem_id="citation-button",
-      show_copy_button=True,
-    )
-
-# ... (Rest of your code)
-
-submit_button.click(
-  add_new_eval,
-  [
-    model_name_textbox,
-    base_model_name_textbox,
-    revision_name_textbox,
-    precision,
-    weight_type,
-    model_type,
-  ],
-  submission_result,
-)
-
-# ... (Scheduler)
-        start_button = gr.Button("Start", elem_id="start_button")  
-   claim_image = gr.Image(value="path/to/your/claim_image.png", interactive=True, elem_id="claim_image")
-   start_button.click(fn=display_user_data, inputs=[gr.inputs.Textbox(label="Enter your Telegram User ID")], outputs=user_data_output)
-   claim_image.click(fn=lambda: "You have claimed your reward!", outputs=gr.outputs.Textbox(label="Message"))
-  iface = gr.Interface(
-    fn=None, # You can add functions for tasks later
-    inputs=[
-      join_channel_section,
-      invite_friends_section,
-    ],
-    outputs=[user_data_output],
-    title="Mukera",
-  )
-  iface.launch(share=True, inline=True)
 demo = gr.Blocks(css=custom_css)
+
 with demo:
     gr.HTML(TITLE)
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
-
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
         with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
             leaderboard = init_leaderboard(LEADERBOARD_DF)
-
         with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
             gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
-
         with gr.TabItem("🚀 Submit here! ", elem_id="llm-benchmark-tab-table", id=3):
             with gr.Column():
                 with gr.Row():
                     gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
-
                 with gr.Column():
-                    with gr.Accordion(
-                        f"✅ Finished Evaluations ({len(finished_eval_queue_df)})",
-                        open=False,
-                    ):
+                    with gr.Accordion(f"✅ Finished Evaluations ({len(finished_eval_queue_df)})", open=False):
                         with gr.Row():
                             finished_eval_table = gr.components.Dataframe(
                                 value=finished_eval_queue_df,
@@ -188,22 +118,14 @@ with demo:
                                 datatype=EVAL_TYPES,
                                 row_count=5,
                             )
-                    with gr.Accordion(
-                        f"🔄 Running Evaluation Queue ({len(running_eval_queue_df)})",
-                        open=False,
-                    ):
+                    with gr.Accordion(f"🔄 Running Evaluation Queue ({len(running_eval_queue_df)})", open=False):
                         with gr.Row():
-                            running_eval_table = gr.components.Dataframe(
-                                value=running_eval_queue_df,
+                            running_eval_table = gr.components.Dataframe(                                value=running_eval_queue_df,
                                 headers=EVAL_COLS,
                                 datatype=EVAL_TYPES,
                                 row_count=5,
                             )
-
-                    with gr.Accordion(
-                        f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})",
-                        open=False,
-                    ):
+                    with gr.Accordion(f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})", open=False):
                         with gr.Row():
                             pending_eval_table = gr.components.Dataframe(
                                 value=pending_eval_queue_df,
@@ -211,40 +133,47 @@ with demo:
                                 datatype=EVAL_TYPES,
                                 row_count=5,
                             )
-            with gr.Row():
-                gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
-
-            with gr.Row():
-                with gr.Column():
-                    model_name_textbox = gr.Textbox(label="Model name")
-                    revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
-                    model_type = gr.Dropdown(
-                        choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
-                        label="Model type",
-                        multiselect=False,
-                        value=None,
-                        interactive=True,
-                    )
-
-                with gr.Column():
-                    precision = gr.Dropdown(
-                        choices=[i.value.name for i in Precision if i != Precision.Unknown],
-                        label="Precision",
-                        multiselect=False,
-                        value="float16",
-                        interactive=True,
-                    )
-                    weight_type = gr.Dropdown(
-                        choices=[i.value.name for i in WeightType],
-                        label="Weights type",
-                        multiselect=False,
-                        value="Original",
-                        interactive=True,
-                    )
-                    base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
-
+                with gr.Row():
+                    gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
+                with gr.Row():
+                    with gr.Column():
+                        revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
+                        model_type = gr.Dropdown(
+                            choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
+                            label="Model type",
+                            multiselect=False,
+                            value=None,
+                            interactive=True,
+                        )
+                    with gr.Column():
+                        precision = gr.Dropdown(
+                            choices=[i.value.name for i in Precisi
+                                    on if i != Precision.Unknown],
+                            label="Precision",
+                            multiselect=False,
+                            value="float16",
+                            interactive=True,
+                        )
+                        weight_type = gr.Dropdown(
+                            choices=[i.value.name for i in WeightType],
+                            label="Weights type",
+                            multiselect=False,
+                            value="Original",
+                            interactive=True,
+                        )
+                        base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
+                        model_name_textbox = gr.Textbox(label="Model name")  # Add this line
             submit_button = gr.Button("Submit Eval")
             submission_result = gr.Markdown()
+            with gr.Row():
+                with gr.Accordion("📙 Citation", open=False):
+                    citation_button = gr.Textbox(
+                        value=CITATION_BUTTON_TEXT,
+                        label=CITATION_BUTTON_LABEL,
+                        lines=20,
+                        elem_id="citation-button",
+                        show_copy_button=True,
+                    )
             submit_button.click(
                 add_new_eval,
                 [
@@ -257,18 +186,8 @@ with demo:
                 ],
                 submission_result,
             )
-
-    with gr.Row():
-        with gr.Accordion("📙 Citation", open=False):
-            citation_button = gr.Textbox(
-                value=CITATION_BUTTON_TEXT,
-                label=CITATION_BUTTON_LABEL,
-                lines=20,
-                elem_id="citation-button",
-                show_copy_button=True,
-            )
-
-scheduler = BackgroundScheduler()
-scheduler.add_job(restart_space, "interval", seconds=1800)
-scheduler.start()
-demo.queue(default_concurrency_limit=40).launch()
+    start_button = gr.Button("Start", elem_id="start_button") 
+    scheduler = BackgroundScheduler()
+    scheduler.add_job(restart_space, "interval", seconds=1800)
+    scheduler.start()
+demo.queue(default_concurrency_limit=40).launch()