Update app.py

app.py

@@ -1,38 +1,143 @@
-from pathlib import Path
 import gradio as gr
+import json
+import os
+import random
 
-demo = gr.Interface("file", "json")
+# Nombre del archivo JSON para almacenar la información de la leaderboard
+JSON_FILE = "dipromats2024-t2_leaderboard-data.json"
 
-'''
-def upload_file(filepath):
-    name = Path(filepath).name
-    return [gr.UploadButton(visible=False), gr.DownloadButton(label=f"Download {name}", value=filepath, visible=True)]
+# 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)
 
-def download_file():
-    return [gr.UploadButton(visible=True), gr.DownloadButton(visible=False)]
+# 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 []
 
-with gr.Blocks() as demo:
-    gr.Markdown("First upload a file and and then you'll be able download it (but only once!)")
-    with gr.Row():
-        u = gr.UploadButton("Upload a file", file_count="single")
-        d = gr.DownloadButton("Download the file", visible=False)
+# Función para convertir el json del leaderboard en tabla
+def update_table():
+    data = load_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
 
-    u.upload(upload_file, u, [u, d])
-    d.click(download_file, None, [u, d])
-'''
+# 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
+    return lenient_f1, strict_f1, average_f1
 
-demo.launch()
+# Función para procesar el archivo de resultados
+def process_file(file_path, team_input, run_id, description, email):
+    warn=False
+    if not file_path:
+        gr.Warning("File cannot be blank")
+        warn=True
+    if not team_input:
+        gr.Warning("Team name cannot be blank")
+        warn=True
+    if not run_id:
+        gr.Warning("Run ID cannot be blank")
+        warn=True
+    if not file_path:
+        gr.Warning("File cannot be blank")
+        warn=True
+    if not description:
+        gr.Warning("Description cannot be blank")
+        warn=True
+    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
 
+    lenient_f1, strict_f1, average_f1 = evaluate_results(file_path)
 
-'''
-def greet(name, intensity):
-    return "Hello, " + name + "!" * int(intensity)
+    return gr.Button(visible=False), gr.Button(visible=True), lenient_f1, strict_f1, average_f1
 
-demo = gr.Interface(
-    fn=greet,
-    inputs=["text", "slider"],
-    outputs=["text"],
-)
 
-demo.launch()
-'''
+# 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
+        # Automatic Detection of Narratives from Diplomats of Major Powers
+        This is...
+        You can...
+        """)
+    with gr.Tabs() as tabs:
+
+        # Tab 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(),
+                        interactive=False)
+            
+        # Tab Evaluate
+        with gr.TabItem("Evaluate your results", id=1):
+            gr.Markdown(
+                """
+                # Upload your results and get evaluated
+                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():
+                    with gr.Row():
+                        team_input = gr.Textbox(label="Team Name")
+                        run_id = gr.Textbox(label="Run ID")
+                    email_input = gr.Textbox(label="Email (only for submission verification, it won't be shown)")
+                description_input = gr.Textbox(label="System description", lines=6)
+            file_input = gr.File(label="Upload a JSON file", file_types=[".json"], type="filepath", file_count="single")
+            evaluate_button = gr.Button("Evaluate")
+
+            # System results table
+            with gr.Row(visible=True):
+                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], 
+                        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], 
+                        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()