still initial commit

app.py

@@ -3,35 +3,34 @@ import gradio as gr
 import cv2
 import numpy as np
 import modal
-
 # ── Authentication & Modal Connection ───────────────────────────────────────
-# Modal automatically authenticates using MODAL_TOKEN_ID and MODAL_TOKEN_SECRET 
-# from the environment. We check them here to ensure your HF Secrets are loaded.
-
 token_id = os.environ.get("MODAL_TOKEN_ID")
 token_secret = os.environ.get("MODAL_TOKEN_SECRET")
+has_tokens = bool(token_id and token_secret)
 
-if not token_id or not token_secret:
+status_text = "🟢 Ready" if has_tokens else "🔴 Offline (Missing Tokens)"
+if not has_tokens:
     print("⚠️ [AUTH ERROR] Modal tokens missing! Check your Hugging Face Secrets.")
-    voxel_backend = None
-    status_text = "🔴 Offline (Missing Tokens)"
-else:
-    try:
-        print("🔑 Tokens found. Connecting to Modal...")
-        # Hook directly into your remote Modal class
+
+# Cache to prevent Python 3.13 cross-thread loop crashes
+_voxel_backend = None
+
+def get_modal_backend():
+    """Lazy-loads the Modal client inside the execution thread to protect the event loop."""
+    global _voxel_backend
+    if _voxel_backend is None and has_tokens:
+        print("🔑 Connecting to Modal...")
         VoxelModelCls = modal.Cls.from_name("flux-klein-voxel-backend", "VoxelModel")
-        voxel_backend = VoxelModelCls().process_frame
-        status_text = "🟢 Connected"
+        _voxel_backend = VoxelModelCls().process_frame
         print("✅ Successfully connected to Modal backend.")
-    except Exception as e:
-        print(f"❌ Failed to connect to Modal: {e}")
-        voxel_backend = None
-        status_text = "🔴 Offline (Connection Error)"
+    return _voxel_backend
+
 
 # ── Core Backend Execution ──────────────────────────────────────────────────
-async def run_modal_backend(frame: np.ndarray) -> np.ndarray:
+def run_modal_backend(frame: np.ndarray) -> np.ndarray:
     """Compresses the frame, sends it to Modal, and decodes the returned bytes."""
-    if voxel_backend is None:
+    backend = get_modal_backend()
+    if backend is None:
         return frame
 
     # Compress to JPEG to save network bandwidth
@@ -40,8 +39,8 @@ async def run_modal_backend(frame: np.ndarray) -> np.ndarray:
         return frame
 
     try:
-        # Fire bytes to Modal serverless container ASYNCHRONOUSLY
-        processed_bytes = await voxel_backend.remote.aio(encoded.tobytes())
+        # Fire bytes to Modal serverless container
+        processed_bytes = backend.remote(encoded.tobytes())
         # Decode the returning bytes back into an OpenCV image
         result = cv2.imdecode(np.frombuffer(processed_bytes, dtype=np.uint8), cv2.IMREAD_COLOR)
         return result if result is not None else frame
@@ -55,18 +54,19 @@ async def run_modal_backend(frame: np.ndarray) -> np.ndarray:
 
 
 # ── Activation & Pre-Warming Logic ──────────────────────────────────────────
-async def start_and_warmup_container():
+def start_and_warmup_container():
     """Forces the Modal container to start up before enabling the webcam stream."""
     print("🚀 [START CLICKED] Waking up Modal container to prevent cold-start lag...")
     
-    if voxel_backend is not None:
+    backend = get_modal_backend()
+    if backend is not None:
         try:
             # Create a tiny 1x1 blank image payload
             dummy_frame = np.zeros((1, 1, 3), dtype=np.uint8)
             success, encoded = cv2.imencode(".jpg", dummy_frame)
             if success:
-                # Trigger a remote execution to force container ignition ASYNCHRONOUSLY
-                await voxel_backend.remote.aio(encoded.tobytes())
+                # Trigger a remote execution to force container ignition
+                backend.remote(encoded.tobytes())
                 print("✅ [CONTAINER READY] Modal container is hot and ready for frames.")
         except Exception as e:
             print(f"ℹ️ [CONTAINER NOTIFICATION] Warmup call dispatched: {e}")
@@ -75,7 +75,7 @@ async def start_and_warmup_container():
 
 
 # ── Streaming Logic ─────────────────────────────────────────────────────────
-async def process_video_stream(frame: np.ndarray, mode: str, is_running: bool) -> np.ndarray:
+def process_video_stream(frame: np.ndarray, mode: str, is_running: bool) -> np.ndarray:
     """Handles the webcam feed and respects the Start/Stop toggle."""
     if frame is None:
         return None
@@ -85,8 +85,8 @@ async def process_video_stream(frame: np.ndarray, mode: str, is_running: bool) -
     if not is_running:
         return frame
 
-    # 1. Process the frame through the Modal network (AWAIT IT)
-    processed = await run_modal_backend(frame)
+    # 1. Process the frame through the Modal network
+    processed = run_modal_backend(frame)
 
     # 2. Format the output based on the selected UI mode
     if mode == "Minecraft Filter":