still initial commit

app.py

@@ -61,14 +61,14 @@ def _offline_frame(frame: np.ndarray, message: str) -> np.ndarray:
     return out
 
 
-def _run_voxel_backend(frame: np.ndarray, prompt: str, strength: float) -> np.ndarray:
-    """Encodes and ships raw image bytes along with UI parameters to the Modal worker."""
+def _run_voxel_backend(frame: np.ndarray) -> np.ndarray:
+    """Encodes and ships ONLY raw image bytes to the Modal worker."""
     success, encoded = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 85])
     if not success:
         return frame
     try:
-        # Match the 3 required arguments expected by the VoxelModel class on Modal
-        processed_bytes = voxel_backend.remote(encoded.tobytes(), prompt, strength)
+        # Pushing ONLY the camera feed byte data across the network
+        processed_bytes = voxel_backend.remote(encoded.tobytes())
         result = cv2.imdecode(np.frombuffer(processed_bytes, dtype=np.uint8), cv2.IMREAD_COLOR)
         return result if result is not None else frame
     except Exception as err:
@@ -81,9 +81,9 @@ def _run_voxel_backend(frame: np.ndarray, prompt: str, strength: float) -> np.nd
 # ── Core Stream Handler ─────────────────────────────────────────────────────
 frame_counter = 0
 
-def process_video_stream(frame: np.ndarray, mode: str, is_running: bool, prompt: str, strength: float) -> np.ndarray:
+def process_video_stream(frame: np.ndarray, mode: str, is_running: bool) -> np.ndarray:
     """
-    Accepts incoming frame from the webcam, pipeline settings, execution state, and prompt config.
+    Accepts incoming frame from the webcam, pipeline settings, and execution state.
     """
     global frame_counter
     if frame is None:
@@ -104,8 +104,8 @@ def process_video_stream(frame: np.ndarray, mode: str, is_running: bool, prompt:
     if frame_counter % 15 == 0:
         print(f"🚀 [LIVE PIPELINE] Transmitting frames. Dispatched {frame_counter} payloads to Modal.")
 
-    # Process via the single-image pipeline, passing down prompt strings and context values
-    processed = _run_voxel_backend(frame, prompt, strength)
+    # Process via the single-image pipeline
+    processed = _run_voxel_backend(frame)
 
     # Mode A: Full view rendering
     if mode == "Minecraft Filter":
@@ -154,23 +154,6 @@ with gr.Blocks(title="⛏️ Minecraft Spatial Voxel Filter") as demo:
                 label="🎯 Pipeline Mode",
                 interactive=True,
             )
-
-            # Added controls to dynamically configure the FLUX diffusion backend
-            prompt_input = gr.Textbox(
-                value="isometric 3d minecraft block voxel style, high resolution, volumetric lighting",
-                label="✨ Generation Prompt",
-                lines=2,
-                interactive=True
-            )
-            
-            strength_slider = gr.Slider(
-                minimum=0.1,
-                maximum=1.0,
-                value=0.45,
-                step=0.05,
-                label="🎛️ Image Transformation Strength",
-                interactive=True
-            )
             
             with gr.Row():
                 start_btn = gr.Button("🚀 Start Processing", variant="primary")
@@ -185,10 +168,10 @@ with gr.Blocks(title="⛏️ Minecraft Spatial Voxel Filter") as demo:
     start_btn.click(fn=lambda: True, inputs=None, outputs=is_running)
     stop_btn.click(fn=lambda: False, inputs=None, outputs=is_running)
 
-    # Core engine transmission loop linked up with the new UI input arguments
+    # Core engine transmission loop linked up with ONLY the stream, mode, and run-state
     input_stream.stream(
         fn=process_video_stream,
-        inputs=[input_stream, mode_dropdown, is_running, prompt_input, strength_slider],
+        inputs=[input_stream, mode_dropdown, is_running],
         outputs=[output_stream],
         trigger_mode="always_last", # Drops intermediate backlog frames when backend is busy
         concurrency_limit=1         # Ensures only one frame flies over the network at a time

backend/backend.py

@@ -30,7 +30,7 @@ app = modal.App("flux-klein-voxel-backend", image=image)
 # 🏎️ 1. THE DEMO PIPELINE (FALLBACK ROUTE)
 # ==============================================================================
 @app.function()
-def demo_stream_frame(img_bytes: bytes, prompt: str, strength: float) -> bytes:
+def demo_stream_frame(img_bytes: bytes) -> bytes:
     """Fallback route structurally aligned to match the frontend signature."""
     from PIL import Image, ImageDraw
     
@@ -102,10 +102,14 @@ class VoxelModel:
         print("Warmup complete. Ready for real-time requests!")
 
     @modal.method()
-    def process_frame(self, img_bytes: bytes, prompt: str, strength: float) -> bytes:
+    def process_frame(self, img_bytes: bytes) -> bytes:
         from PIL import Image
         import torch
         
+        # Hardcoded parameters that were previously passed from the UI
+        prompt = "isometric 3d minecraft block voxel style, high resolution, volumetric lighting"
+        strength = 0.45
+        
         input_image = Image.open(io.BytesIO(img_bytes)).convert("RGB")
         input_image = input_image.resize((512, 512))