Update app.py

app.py

@@ -53,69 +53,6 @@ request_log = []
 clip_model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32", cache_dir=model_path)
 clip_processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32", cache_dir=model_path)
 
-if not os.path.exists(LOG_FILE_PATH):
-    with open(LOG_FILE_PATH, "w", newline="") as f:
-        writer = csv.writer(f)
-        writer.writerow(
-            [
-                "timestamp",
-                "request_type",
-                "prompt",
-                "negative_prompt",
-                "height",
-                "width",
-                "num_frames",
-                "frame_rate",
-                "seed",
-                "num_inference_steps",
-                "guidance_scale",
-                "is_enhanced",
-                "clip_embedding",
-                "original_resolution",
-            ]
-        )
-
-@lru_cache(maxsize=128)
-def log_request(
-    request_type,
-    prompt,
-    negative_prompt,
-    height,
-    width,
-    num_frames,
-    frame_rate,
-    seed,
-    num_inference_steps,
-    guidance_scale,
-    is_enhanced,
-    clip_embedding=None,
-    original_resolution=None,
-):
-    """Log the user's request to a CSV file."""
-    timestamp = datetime.now().isoformat()
-    with open(LOG_FILE_PATH, "a", newline="") as f:
-        try:
-            writer = csv.writer(f)
-            writer.writerow(
-                [
-                    timestamp,
-                    request_type,
-                    prompt,
-                    negative_prompt,
-                    height,
-                    width,
-                    num_frames,
-                    frame_rate,
-                    seed,
-                    num_inference_steps,
-                    guidance_scale,
-                    is_enhanced,
-                    clip_embedding,
-                    original_resolution,
-                ]
-            )
-        except Exception as e:
-            print(f"Error logging request: {e}")
 
 def compute_clip_embedding(text=None, image=None):
     """
@@ -400,21 +337,6 @@ def generate_video_from_image(
             original_resolution = f"{img.width}x{img.height}"  # Format as "widthxheight"
             clip_embedding = compute_clip_embedding(image=img)
 
-        log_request(
-            "img2vid",
-            prompt,
-            negative_prompt,
-            height,
-            width,
-            num_frames,
-            frame_rate,
-            seed,
-            num_inference_steps,
-            guidance_scale,
-            enhance_prompt_toggle,
-            json.dumps(clip_embedding),
-            original_resolution,
-        )
 
     media_items = load_image_to_tensor_with_resize(image_path, height, width).to(device).detach()