Update app.py

app.py

@@ -1,45 +1,60 @@
+# prompt: instead of using JSON_FILE in local drive, use the HuggingFace dataset "NLP-UNED/dipromats2024-t2_leaderboard-data"
 import gradio as gr
 import json
 import os
 import random
+import datasets #load_dataset, save_to_disk, load_from_disk
 
-# Nombre del archivo JSON para almacenar la información de la leaderboard
-JSON_FILE = "dipromats2024-t2_leaderboard-data.json"
-
-# Función para guardar los datos en el json leaderboard
-def save_data(data):
-    with open(JSON_FILE, "w") as f:
-        json.dump(data, f, indent=4)
-
-# Función para cargar los datos del json del leaderboard
-def load_data():
-    if os.path.exists(JSON_FILE):
-        with open(JSON_FILE, "r") as f:
-            try:
-                return json.load(f)
-            except json.JSONDecodeError:
-                return []
-    return []
-
-# Función para convertir el json del leaderboard en tabla
-def update_table():
-    data = load_data()
+# Use the Hugging Face dataset
+DATASET_NAME = "NLP-UNED/dipromats2024-t2_leaderboard-data"
+
+try:
+    #dataset = datasets.load_dataset(DATASET_NAME)
+    #data = dataset['train']
+    data = datasets.load_from_disk(DATASET_NAME)
+
+except Exception as e:
+    print(f"Error loading dataset: {e}")
+    data = []
+
+# Función para convertir el dataset en tabla
+def data_to_table():
+    global data
     table_data = []
     for item in data:
         table_data.append([item.get("team_name", ""), item.get("run_id", ""),
                            item.get("lenient_f1", ""), item.get("strict_f1", ""), item.get("average_f1", "")])
     return table_data
 
+
+# Función para subir los resultados al leaderboard
+def update_leaderboard(email, team_input, run_id, description, lenient_f1, strict_f1, average_f1):
+    global data
+    data.add_item({
+        "email": email,
+        "team_name": team_input,
+        "run_id": run_id,
+        "description": description,
+        "lenient_f1": lenient_f1,
+        "strict_f1": strict_f1,
+        "average_f1": average_f1
+    })
+    #data.save_to_disk(DATASET_NAME)
+    data.save_to_disk(DATASET_NAME+"/prueba")
+    return data_to_table(), gr.Tabs(selected=0), gr.Button(visible=True), gr.Button(visible=False), "", "", "", "", None, None, None, None
+
+
 # Función para evaluar los resultados
 def evaluate_results(file_path):
-    lenient_f1=random.random()
-    strict_f1=random.random()
-    average_f1=(lenient_f1+strict_f1)/2
+    lenient_f1 = random.random()
+    strict_f1 = random.random()
+    average_f1 = (lenient_f1 + strict_f1) / 2
     return lenient_f1, strict_f1, average_f1
 
+
 # Función para procesar el archivo de resultados
 def process_file(file_path, team_input, run_id, description, email):
-    warn=False
+    warn = False
     if not file_path:
         gr.Warning("File cannot be blank")
         warn=True
@@ -58,7 +73,7 @@ def process_file(file_path, team_input, run_id, description, email):
     if not email:
         gr.Warning("Email cannot be blank")
         warn=True
-    
+
     if warn:
         return gr.Button(visible=True), gr.Button(visible=False), None, None, None
 
@@ -67,25 +82,10 @@ def process_file(file_path, team_input, run_id, description, email):
     return gr.Button(visible=False), gr.Button(visible=True), lenient_f1, strict_f1, average_f1
 
 
-# Función para subir los resultados al leaderboard
-def update_leaderboard(email, team_input, run_id, description, lenient_f1, strict_f1, average_f1):
-    data = load_data()
-    data.append({
-        "email": email,
-        "team_name": team_input,
-        "run_id": run_id,
-        "description": description,
-        "lenient_f1": lenient_f1,
-        "strict_f1": strict_f1,
-        "average_f1": average_f1
-    })
-    save_data(data)
-    return update_table(), gr.Tabs(selected=0), gr.Button(visible=True), gr.Button(visible=False), "", "", "", "", None, None, None, None # Clear inputs
-
 # Main
-    
+
 with gr.Blocks() as leaderboard:
-    
+
     gr.Markdown(
         """
         # Dipromats 2024 Task 2 Leaderboard
@@ -99,13 +99,13 @@ with gr.Blocks() as leaderboard:
         with gr.TabItem("Leaderboard", id=0):
             gr.Markdown(
                 """
-                # 
+                #
                 # Leaderboard
                 """)
             leaderboard_table = gr.Dataframe(headers=["Team", "Run ID", "Lenient F1", "Strict F1", "Average F1"],
-                        value=update_table(),
+                        value=data_to_table(),
                         interactive=False)
-            
+
         # Tab Evaluate
         with gr.TabItem("Evaluate your results", id=1):
             gr.Markdown(
@@ -114,7 +114,7 @@ with gr.Blocks() as leaderboard:
                 Then you can decide to submit your results to the leaderboard or not.
                 Make sure that you upload a file with the json format described in...
                 """)
-            
+
             # Submission Form
             with gr.Row():
                 with gr.Column():
@@ -128,17 +128,17 @@ with gr.Blocks() as leaderboard:
 
             # System results table
             with gr.Row(visible=True):
-                lenient_f1 = gr.Number(label="Lenient F1", interactive=False)  
+                lenient_f1 = gr.Number(label="Lenient F1", interactive=False)
                 strict_f1 = gr.Number(label="Strict F1", interactive=False)
                 average_f1 = gr.Number(label="Average F1", interactive=False)
 
             # Submit to leaderboard
             submit_button = gr.Button("Submit to leaderboard", visible=False)
 
-    evaluate_button.click(process_file, 
-                        inputs=[file_input, team_input, run_id, description_input, email_input], 
+    evaluate_button.click(process_file,
+                        inputs=[file_input, team_input, run_id, description_input, email_input],
                         outputs=[evaluate_button,submit_button,lenient_f1, strict_f1, average_f1])
-    submit_button.click(update_leaderboard, 
-                        inputs=[email_input, team_input, run_id, description_input, lenient_f1, strict_f1, average_f1], 
+    submit_button.click(update_leaderboard,
+                        inputs=[email_input, team_input, run_id, description_input, lenient_f1, strict_f1, average_f1],
                         outputs=[leaderboard_table, tabs, evaluate_button, submit_button, team_input, run_id, description_input, email_input, file_input,lenient_f1, strict_f1, average_f1])
 leaderboard.launch()