Update app.py

app.py

@@ -4,7 +4,6 @@ import gc
 # --- 🛡️ SHIELDS ---
 os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
-os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
 
 # --- 🩹 Keras Monkey Patch (Fixes MTCNN Error) ---
 import tensorflow as tf
@@ -14,15 +13,6 @@ sys.modules['tensorflow.keras'] = keras
 sys.modules['tensorflow.keras.layers'] = keras.layers
 sys.modules['tensorflow.keras.models'] = keras.models
 
-# Compatibility Shim for Gradio 4.44 vs HF Hub 0.25+
-import huggingface_hub
-try: from huggingface_hub import HfFolder
-except ImportError:
-    class MockHfFolder:
-        @staticmethod
-        def get_token(): return None
-    huggingface_hub.HfFolder = MockHfFolder
-
 import gradio as gr
 import cv2
 import numpy as np
@@ -32,7 +22,7 @@ import pandas as pd
 import threading
 import time
 
-# --- Config: MediaPipe + TensorFlow Setup ---
+# --- Config ---
 DETECTOR = "mediapipe" 
 RESIZE_FACTOR = 0.5 
 COOL_DOWN_SEC = 5   
@@ -58,12 +48,10 @@ def get_startup_report():
     try:
         DeepFace.build_model("VGG-Face")
         report.append("🧠 AI Brain: TensorFlow (VGG) Ready")
-        gc.collect() # Clean RAM
-        
+        gc.collect() 
         db_files = [f for f in os.listdir("faces_db") if f.endswith(('.jpg', '.jpeg', '.png'))]
         report.append(f"📁 Database: {len(db_files)} Students")
         report.append(f"🔍 Detector: Google MediaPipe Active")
-        
         if not os.path.exists(LOG_FILE): pd.DataFrame(columns=["Name", "Time"]).to_csv(LOG_FILE, index=False)
         report.append("💾 Storage: Write Access OK")
     except Exception as e: report.append(f"⚠️ Startup Error: {e}")
@@ -120,20 +108,20 @@ def process_frame(frame):
     finally:
         with process_lock: is_processing = False
 
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="Attendance Pro") as demo:
     gr.Markdown("# 🏆 Pro Attendance AI (MediaPipe + TF)")
     with gr.Row():
         with gr.Column(scale=2):
-            webcam = gr.Image(sources=["webcam"], streaming=True, label="Live View")
+            # Gradio 3.x Syntax
+            webcam = gr.Image(source="webcam", streaming=True, label="Live View")
             status_terminal = gr.Textbox(label="💻 Logic Terminal", lines=8, interactive=False)
         with gr.Column(scale=1):
             gr.Markdown("### 📝 Present Today")
             attendance_sheet = gr.Textbox(label="", value="System Booting...", lines=18, interactive=False)
             status_log = gr.Textbox(value=get_startup_report(), label="System Status", lines=5, interactive=False)
 
-    webcam.stream(process_frame, inputs=[webcam], outputs=[webcam, attendance_sheet, status_terminal], concurrency_limit=1)
-
-demo.max_file_size = None 
+    webcam.stream(process_frame, inputs=[webcam], outputs=[webcam, attendance_sheet, status_terminal])
 
 if __name__ == "__main__":
-    demo.queue().launch(server_name="0.0.0.0", server_port=7860)
+    # The 'share=False' fixes the ValueError on Hugging Face
+    demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False)