Update app.py

app.py

@@ -1,22 +1,15 @@
-########################################
-# Gradio schema patch (optional)
-# Place this at the very top to avoid "bool not iterable" issues
-########################################
 import gradio_client.utils as gc_utils
 
 _original_json_schema_to_python_type = gc_utils._json_schema_to_python_type
 
 def patched_json_schema_to_python_type(schema, defs=None):
     if isinstance(schema, bool):
-        # If we find a boolean schema (e.g. additionalProperties: false), return {}
         return {}
     return _original_json_schema_to_python_type(schema, defs)
 
 gc_utils._json_schema_to_python_type = patched_json_schema_to_python_type
 
-########################################
-# Standard imports
-########################################
+
 import logging
 import os
 os.makedirs("tmp", exist_ok=True)
@@ -30,7 +23,6 @@ from apscheduler.schedulers.background import BackgroundScheduler
 import json
 from io import BytesIO
 
-# Additional imports from your code
 from src.radial.radial import create_plot
 from gradio_leaderboard import Leaderboard, SelectColumns
 from gradio_space_ci import enable_space_ci
@@ -41,22 +33,18 @@ from src.envs import API, H4_TOKEN, HF_HOME, REPO_ID, RESET_JUDGEMENT_ENV
 from src.leaderboard.build_leaderboard import build_leadearboard_df, download_openbench, download_dataset
 import huggingface_hub
 
-# huggingface_hub.login(token=H4_TOKEN)
 
 os.environ["GRADIO_ANALYTICS_ENABLED"] = "false"
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
 enable_space_ci()
 
-########################################
-# File handlers
-########################################
+
 def handle_file_upload(file_bytes):
     """
     Read the uploaded bytes and parse JSON directly, 
     avoiding ephemeral disk paths or file read issues.
     """
     logging.info("File uploaded (bytes). Size: %d bytes", len(file_bytes))
-    # Convert from bytes to JSON (assuming valid JSON input).
     v = json.loads(file_bytes.decode("utf-8"))
     return v
 
@@ -67,7 +55,6 @@ def submit_file(v, mn):
     """
     print('START SUBMITTING!!!')
     
-    # Validate that 'results' exists in v
     if 'results' not in v:
         return "Invalid JSON: missing 'results' key"
     
@@ -82,14 +69,12 @@ def submit_file(v, mn):
     ]
 
     for column in columns:
-        # Validate data structure
         if column not in new_file or not isinstance(new_file[column], dict):
             return f"Missing or invalid column: {column}"
         if 'acc,none' not in new_file[column]:
             return f"Missing 'acc,none' key in column: {column}"
         new_file[column] = new_file[column]['acc,none']
 
-    # Validate 'config'
     if 'config' not in v or 'model_dtype' not in v['config']:
         return "Missing 'config' or 'model_dtype' in JSON"
 
@@ -98,10 +83,9 @@ def submit_file(v, mn):
 
     print('WE READ FILE: ', new_file)
     
-    # Convert to JSON and upload
     buf = BytesIO()
     buf.write(json.dumps(new_file).encode('utf-8'))
-    buf.seek(0)  # Rewind
+    buf.seek(0)
     API.upload_file(
         path_or_fileobj=buf,
         path_in_repo="model_data/external/" + mn.replace('/', '__') + ".json",
@@ -112,9 +96,7 @@ def submit_file(v, mn):
     os.environ[RESET_JUDGEMENT_ENV] = "1"
     return "Success!"
 
-########################################
-# Utility functions
-########################################
+
 def restart_space():
     API.restart_space(repo_id=REPO_ID)
     download_openbench()
@@ -122,9 +104,7 @@ def restart_space():
 def update_plot(selected_models):
     return create_plot(selected_models)
 
-########################################
-# Build Gradio app
-########################################
+
 def build_demo():
     download_openbench()
     demo = gr.Blocks(title="Kaz LLM LB", css=custom_css)
@@ -155,13 +135,11 @@ def build_demo():
                 with gr.Column():
                     model_name_textbox = gr.Textbox(label="Model name")
 
-                    # Use 'bytes' so we load file content in memory.
                     file_output = gr.File(
                         label="Drag and drop JSON file judgment here",
                         type="binary"
                     )
 
-                    # We'll store the returned JSON object in uploaded_file (NOT the path).
                     uploaded_file = gr.State()
 
                     with gr.Row():
@@ -170,14 +148,12 @@ def build_demo():
 
                     submit_button = gr.Button("Submit File", variant='primary')
 
-                    # On file upload, parse JSON -> store in uploaded_file
                     file_output.upload(
                         fn=handle_file_upload,
                         inputs=file_output,
                         outputs=uploaded_file
                     )
 
-                    # On button click, call submit_file with the stored JSON + model name
                     submit_button.click(
                         fn=submit_file,
                         inputs=[uploaded_file, model_name_textbox],
@@ -202,13 +178,9 @@ def build_demo():
                 )
                 return demo
 
-########################################
-# Aggregation and scheduling
-########################################
 def aggregate_leaderboard_data():
     download_dataset("kz-transformers/s-openbench-eval", "m_data")
     
-    # Start with your baseline data
     data_list = [
         {
             "model_dtype": "torch.float16",
@@ -379,9 +351,7 @@ def update_board_():
     logging.info("Updating the judgement at startup")
     aggregate_leaderboard_data()
 
-########################################
-# Main
-########################################
+
 if __name__ == "__main__":
     os.environ[RESET_JUDGEMENT_ENV] = "1"
     from apscheduler.schedulers.background import BackgroundScheduler
@@ -391,5 +361,4 @@ if __name__ == "__main__":
     scheduler.start()
 
     demo_app = build_demo()
-    # Don't pass root_path on HF Spaces. Let it mount at default "/"
     demo_app.launch(debug=True, share=False, show_api=False)