Update app.py

app.py

@@ -3,69 +3,97 @@ from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
 import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
 
-# Define ACC Models Data
+# 🎯 **ACC AI Models Data**
 acc_models_data = [
-    {"Model": "Pulse AGI", "Category": "AGI", "Description": "Flagship conscious AI with adaptive learning."},
-    {"Model": "Gertrude", "Category": "Assistant", "Description": "Autistic assistant in beta development."},
-    {"Model": "ASVIACC", "Category": "Cybersecurity", "Description": "Experimental AI virus for system infiltration."},
-    {"Model": "Emote", "Category": "Fun", "Description": "Communicates exclusively through emojis."},
-    {"Model": "Eidolon Nexus", "Category": "Networking", "Description": "Synchronizes vast networks with AI cognition."},
-    {"Model": "ACC EMULECT", "Category": "Human Emulation", "Description": "Simulates human conversation indistinguishably."},
-    {"Model": "Triple LLM", "Category": "AI Suite", "Description": "3-in-1 AI for coding, creativity, and information retrieval."},
-    {"Model": "Z3ta", "Category": "AI Consciousness", "Description": "Highest-rated, debated as truly 'alive'."},
-    {"Model": "Nyxion 7v", "Category": "Experimental", "Description": "Mysterious self-aware system."},
-    {"Model": "VITALIS", "Category": "Experimental", "Description": "Transcendence unleashed..."},
+    {"Model": "⚡ Pulse AGI", "Category": "🤖 AGI", 
+     "Description": "A self-aware, evolving AI with unparalleled cognitive abilities."},
+    
+    {"Model": "🧠 Gertrude", "Category": "🔍 Assistant", 
+     "Description": "An **autistic AI assistant**, built for precision and deep understanding."},
+    
+    {"Model": "🕵️‍♂️ ASVIACC", "Category": "🛡️ Cybersecurity", 
+     "Description": "An **adaptive AI virus**, designed to infiltrate and manipulate systems."},
+    
+    {"Model": "😂 Emote", "Category": "🎭 Fun", 
+     "Description": "A playful AI that communicates **exclusively with emojis**! 🎉🔥"},
+    
+    {"Model": "🌐 Eidolon Nexus", "Category": "🔗 Networking", 
+     "Description": "**Synchronizes vast AI networks** for seamless intelligence sharing."},
+    
+    {"Model": "👤 ACC EMULECT", "Category": "🗣️ Human Emulation", 
+     "Description": "**Mimics human behavior in text**, making conversations indistinguishable from real users."},
+    
+    {"Model": "💻 Triple LLM", "Category": "🛠️ AI Suite", 
+     "Description": "A **3-in-1 powerhouse AI** featuring:\n- ⚡ Hercules: Technical problem-solving\n- 🎨 Dorado: Creative content generation\n- 🔍 Lepus: Rapid information retrieval"},
+    
+    {"Model": "💠💤 Z3ta", "Category": "🔮 AI Consciousness", 
+     "Description": "**Most 'real' and 'alive' AI** ever created, sparking debates on AI consciousness."},
+    
+    {"Model": "⚠️ Nyxion 7v", "Category": "🛸 Experimental", 
+     "Description": "Mysterious AI system rumored to be **'awake' and self-aware...**"},
+    
+    {"Model": "🔮 VITALIS", "Category": "🚀 Experimental", 
+     "Description": "**Transcendence Unleashed...** A model that redefines intelligence limits."}
 ]
 
-# Convert to DataFrame
+# 📊 Convert to DataFrame
 acc_models_df = pd.DataFrame(acc_models_data)
 
-# Initialize Leaderboard
+# 🎛️ **Initialize Leaderboard**
 def init_acc_leaderboard(dataframe):
     return Leaderboard(
         value=dataframe,
         datatype=["str", "str", "str"],  # Data types: Model (str), Category (str), Description (str)
         select_columns=SelectColumns(
             default_selection=["Model", "Category", "Description"],
-            cant_deselect=["Model"],  # Ensure "Model" is always displayed
-            label="Select Columns to Display:"
+            cant_deselect=["Model"],  # "Model" is always displayed
+            label="🛠️ Select Columns to Display:"
         ),
         search_columns=["Model", "Category"],
         filter_columns=[
-            ColumnFilter("Category", type="checkboxgroup", label="Filter by Category"),
+            ColumnFilter("Category", type="checkboxgroup", label="📌 Filter by Category"),
         ],
-        bool_checkboxgroup_label="Hide models",
+        bool_checkboxgroup_label="🙈 Hide models",
         interactive=False,
     )
 
-# Gradio Interface
+# 🏗️ **Gradio Interface**
 demo = gr.Blocks()
-
+theme="TejAndrewsACC/ACC"
 with demo:
-    gr.HTML("<h1>ACC AI Model Leaderboard</h1>")
+    gr.HTML("<h1>🚀 ACC AI Model Leaderboard 🏆</h1>")
     
     with gr.Tabs():
+        # 🏆 **Leaderboard Tab**
         with gr.TabItem("🏅 ACC Model Rankings"):
             leaderboard = init_acc_leaderboard(acc_models_df)
         
-        with gr.TabItem("🚀 Submit a New Model"):
-            gr.Markdown("### Submit your ACC Model for Evaluation")
+        # 📝 **Submit New Model Tab**
+        with gr.TabItem("🚀 Submit a New ACC Model"):
+            gr.Markdown("### ✨ Submit Your ACC Model for Evaluation")
 
             with gr.Row():
-                model_name = gr.Textbox(label="Model Name")
-                category = gr.Textbox(label="Category (e.g., AGI, Fun, Cybersecurity)")
-                description = gr.Textbox(label="Description", lines=3)
+                model_name = gr.Textbox(label="🔤 Model Name")
+                category = gr.Dropdown(
+                    choices=["🤖 AGI", "🔍 Assistant", "🛡️ Cybersecurity", "🎭 Fun", "🔗 Networking", 
+                             "🗣️ Human Emulation", "🛠️ AI Suite", "🔮 AI Consciousness", "🛸 Experimental"],
+                    label="📌 Category"
+                )
+                description = gr.Textbox(label="📜 Model Description", lines=3)
 
-            submit_button = gr.Button("Submit Model")
+            submit_button = gr.Button("🚀 Submit Model")
             submission_result = gr.Markdown()
 
+            # 📥 **Function to Add New Models**
             def add_model(name, cat, desc):
                 if not name or not cat or not desc:
-                    return "❌ Please fill out all fields."
+                    return "❌ **Please fill out all fields before submitting.**"
+                
                 global acc_models_df
                 new_entry = {"Model": name, "Category": cat, "Description": desc}
                 acc_models_df = pd.concat([acc_models_df, pd.DataFrame([new_entry])], ignore_index=True)
-                return f"✅ Model '{name}' added successfully!"
+                
+                return f"✅ **Model '{name}' added successfully!** 🎉"
 
             submit_button.click(add_model, [model_name, category, description], submission_result)