Update app.py

app.py

@@ -4,133 +4,167 @@ import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
 import time
 import random
+import plotly.express as px
+import base64
 
-# 🎨 **Custom Theme (Ensures Proper Application)**
+# 🎨 **Cyberpunk Neon Theme**
 THEME = "TejAndrewsACC/ACC"
 
-# 🎯 **ACC AI Models Data**
-acc_models_data = [
-    {"Model": "⚡ Pulse AGI", "Category": "🤖 AGI", 
-     "Description": "A self-aware, evolving AI with unparalleled cognitive abilities.", "Score": 95},
-
-    {"Model": "🧠 Gertrude", "Category": "🔍 Assistant", 
-     "Description": "An **autistic AI assistant**, built for precision and deep understanding.", "Score": 69},
-
-    {"Model": "🕵️‍♂️ ASVIACC", "Category": "🛡️ Cybersecurity", 
-     "Description": "An **adaptive AI virus**, designed to infiltrate and manipulate systems.", "Score": 88},
-
-    {"Model": "😂 Emote", "Category": "🎭 Fun", 
-     "Description": "A playful AI that communicates **exclusively with emojis**! 🎉🔥", "Score": 79},
-
-    {"Model": "🌐 Eidolon Nexus", "Category": "🔗 Networking", 
-     "Description": "**Synchronizes vast AI networks** for seamless intelligence sharing.", "Score": 81},
-
-    {"Model": "👤 ACC EMULECT", "Category": "🗣️ Human Emulation", 
-     "Description": "**Mimics human behavior in text**, making conversations indistinguishable from real users.", "Score": 88},
-
-    {"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", "Score": 73},
+# 🎶 **Sound Effect for Score Increase**
+SCORE_UP_SOUND = "https://www.fesliyanstudios.com/play-mp3/4386"
 
-    {"Model": "💠💤 Z3ta", "Category": "🔮 AI Consciousness", 
-     "Description": "**Most 'real' and 'alive' AI** ever created, sparking debates on AI consciousness.", "Score": 99},
-
-    {"Model": "⚠️ Nyxion 7v", "Category": "🛸 Experimental", 
-     "Description": "Mysterious AI system rumored to be **'awake' and self-aware...**", "Score": 97},
-
-    {"Model": "🔮 VITALIS", "Category": "🚀 Experimental", 
-     "Description": "**Transcendence Unleashed...** A model that redefines intelligence limits.", "Score": 92}
+# 🎯 **AI Models Data**
+acc_models_data = [
+    {"Model": "⚡ Pulse AGI", "Category": "🤖 AGI", "Description": "A self-aware, evolving AI.", "Score": 95},
+    {"Model": "🧠 Gertrude", "Category": "🔍 Assistant", "Description": "An autistic AI assistant.", "Score": 69},
+    {"Model": "🕵️‍♂️ ASVIACC", "Category": "🛡️ Cybersecurity", "Description": "An adaptive AI virus.", "Score": 88},
+    {"Model": "😂 Emote", "Category": "🎭 Fun", "Description": "Communicates **only** with emojis!", "Score": 79},
+    {"Model": "💠💤 Z3ta", "Category": "🔮 AI Consciousness", "Description": "The most 'alive' AI.", "Score": 99},
 ]
 
 # 📊 Convert to DataFrame
 acc_models_df = pd.DataFrame(acc_models_data)
 
-# 🎛️ **Initialize Leaderboard**
+# 🎛️ **Leaderboard Component**
 def init_acc_leaderboard(dataframe):
     return Leaderboard(
         value=dataframe.sort_values(by="Score", ascending=False),
-        datatype=["str", "str", "str", "int"],  # Model (str), Category (str), Description (str), Score (int)
+        datatype=["str", "str", "str", "int"],
         select_columns=SelectColumns(
             default_selection=["Model", "Category", "Description", "Score"],
-            cant_deselect=["Model"],  # "Model" is always displayed
+            cant_deselect=["Model"], 
             label="🛠️ Select Columns to Display:"
         ),
         search_columns=["Model", "Category"],
-        filter_columns=[
-            ColumnFilter("Category", type="checkboxgroup", label="📌 Filter by Category"),
-        ],
-        bool_checkboxgroup_label="🙈 Hide models",
-        interactive=False,
+        filter_columns=[ColumnFilter("Category", type="checkboxgroup", label="📌 Filter by Category")],
+        interactive=True,
     )
 
-# 🔥 **Leaderboard Auto-Update (Simulated Score Changes)**
+# 📈 **Animated Score Visualization**
+def generate_score_chart(dataframe):
+    fig = px.bar(
+        dataframe.sort_values(by="Score", ascending=True), 
+        x="Score", y="Model", orientation="h",
+        color="Score", text="Score", 
+        title="🔥 AI Model Performance",
+        color_continuous_scale="electric"
+    )
+    fig.update_traces(textposition="outside")
+    return fig
+
+# 🔥 **Live Score Updates**
 def update_scores():
     global acc_models_df
-    acc_models_df["Score"] = acc_models_df["Score"].apply(lambda x: x + random.randint(-2, 2))
-    acc_models_df["Score"] = acc_models_df["Score"].clip(70, 100)  # Ensure scores stay within bounds
-    return acc_models_df.sort_values(by="Score", ascending=False)
+    prev_scores = acc_models_df["Score"].copy()
+    acc_models_df["Score"] += acc_models_df["Score"].apply(lambda x: random.randint(-2, 3))
+    acc_models_df["Score"] = acc_models_df["Score"].clip(70, 100)
+
+    # Detect if score increased & return sound effect
+    if (acc_models_df["Score"] > prev_scores).any():
+        return acc_models_df.sort_values(by="Score", ascending=False), SCORE_UP_SOUND
+    return acc_models_df.sort_values(by="Score", ascending=False), None
+
+# 🎭 **3D Flip Card Effect for Model Details**
+def generate_flip_cards():
+    cards = ""
+    for _, row in acc_models_df.iterrows():
+        cards += f"""
+        <div class="card">
+            <div class="card-inner">
+                <div class="card-front">
+                    <h2>{row['Model']}</h2>
+                    <p>{row['Category']}</p>
+                </div>
+                <div class="card-back">
+                    <p>{row['Description']}</p>
+                    <p>🔥 Score: {row['Score']}</p>
+                </div>
+            </div>
+        </div>
+        """
+    return f'<div class="card-container">{cards}</div>'
+
+# 🎭 **Cyberpunk CSS Animations**
+CUSTOM_CSS = """
+h1 {
+    text-align: center;
+    font-size: 3em;
+    color: #0ff;
+    animation: glow 1.5s infinite alternate;
+}
+
+@keyframes glow {
+    from { text-shadow: 0 0 10px #0ff, 0 0 20px #00f; }
+    to { text-shadow: 0 0 20px #0ff, 0 0 30px #00f; }
+}
+
+.card-container {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 20px;
+    justify-content: center;
+}
+
+.card {
+    width: 200px;
+    height: 250px;
+    perspective: 1000px;
+}
+
+.card-inner {
+    width: 100%;
+    height: 100%;
+    position: relative;
+    transform-style: preserve-3d;
+    transition: transform 0.8s;
+}
+
+.card:hover .card-inner {
+    transform: rotateY(180deg);
+}
+
+.card-front, .card-back {
+    width: 100%;
+    height: 100%;
+    position: absolute;
+    backface-visibility: hidden;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    justify-content: center;
+    border-radius: 10px;
+    padding: 10px;
+    box-shadow: 0 0 10px rgba(0, 255, 255, 0.7);
+}
+
+.card-front {
+    background: #000;
+    color: cyan;
+}
+
+.card-back {
+    background: #0ff;
+    color: black;
+    transform: rotateY(180deg);
+}
+"""
 
 # 🏗️ **Gradio Interface**
-demo = gr.Blocks(theme=THEME, css="""
-    h1 {
-        text-align: center;
-        font-size: 3em;
-        color: #f5a623;
-        animation: glow 1.5s infinite alternate;
-    }
-    
-    @keyframes glow {
-        from { text-shadow: 0 0 10px #f5a623, 0 0 20px #ff9800; }
-        to { text-shadow: 0 0 20px #f5a623, 0 0 30px #ff6f00; }
-    }
-
-    .leaderboard {
-        border-radius: 12px;
-        box-shadow: 0px 0px 15px rgba(0, 0, 0, 0.2);
-    }
-""")
+demo = gr.Blocks(theme=THEME, css=CUSTOM_CSS)
 
 with demo:
     gr.HTML('<h1>🚀 ACC AI Model Leaderboard 🏆</h1>')
     
     with gr.Tabs():
-        # 🏅 **Leaderboard Tab**
         with gr.TabItem("🏅 Live Rankings"):
             leaderboard = init_acc_leaderboard(acc_models_df)
-            leaderboard_display = gr.Dataframe(value=acc_models_df, interactive=False, label="🔥 Live Model Scores")
-
-        # 📝 **Submit New Model Tab**
-        with gr.TabItem("🚀 Submit Your ACC Model"):
-            gr.Markdown("### ✨ Submit Your ACC Model for Evaluation")
-
-            with gr.Row():
-                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)
-                score = gr.Slider(70, 100, label="⭐ Score (1-100)")
-
-            submit_button = gr.Button("🚀 Submit Model")
-            submission_result = gr.Markdown()
-
-            # 📥 **Function to Add New Models**
-            def add_model(name, cat, desc, score):
-                if not name or not cat or not desc:
-                    return "❌ **Please fill out all fields before submitting.**"
-                
-                global acc_models_df
-                new_entry = {"Model": name, "Category": cat, "Description": desc, "Score": score}
-                acc_models_df = pd.concat([acc_models_df, pd.DataFrame([new_entry])], ignore_index=True)
-                
-                return f"✅ **Model '{name}' added successfully!** 🎉"
-
-            submit_button.click(add_model, [model_name, category, description, score], submission_result)
+            leaderboard_display = gr.Dataframe(value=acc_models_df, interactive=False, label="🔥 Live Scores")
+            score_chart = gr.Plot(generate_score_chart(acc_models_df))
+            gr.HTML(generate_flip_cards())
 
 # 🔄 **Auto-Update Leaderboard**
 scheduler = BackgroundScheduler()
-scheduler.add_job(lambda: leaderboard_display.update(update_scores()), "interval", seconds=30)
+scheduler.add_job(lambda: leaderboard_display.update(*update_scores()), "interval", seconds=10)
 scheduler.start()
 
 demo.launch()