Lightricks have updated their pipeline

Applying same changes as: https://github.com/Lightricks/LTX-Video/commit/93af6864b942e931908fcf1a3f04feebf97dbb36#diff-e4522277a659ca45d158c90142b86a4518428bda49b31d8027e7f5482039a74f

handler.py

@@ -89,10 +89,9 @@ class GenerationConfig:
     quality: int = 18
 
     # STG (Spatiotemporal Guidance) settings
-    stg_scale: float = 1.0
-    stg_rescale: float = 0.7
+    stg_scale: float = 0.0
+    stg_rescale: float = 1.0
     stg_mode: str = "attention_values"  # Can be "attention_values", "attention_skip", "residual", or "transformer_block"
-    stg_skip_layers: str = "19"  # Comma-separated list of layers to block for spatiotemporal guidance
 
     # VAE noise augmentation
     decode_timestep: float = 0.05
@@ -147,10 +146,6 @@ class GenerationConfig:
         elif self.stg_mode.lower() == "stg_t" or self.stg_mode.lower() == "transformer_block":
             self.stg_mode = "transformer_block"
         
-        # Convert STG skip layers from string to list of integers
-        if isinstance(self.stg_skip_layers, str):
-            self.stg_skip_layers = [int(x.strip()) for x in self.stg_skip_layers.split(",")]
-
         # Check if we should enhance the prompt
         if self.enhance_prompt and self.prompt:
             prompt_word_count = len(self.prompt.split())
@@ -407,7 +402,7 @@ class EndpointHandler:
                 width=768,  # Using smaller resolution for faster warm-up
                 height=416,
                 num_frames=33,  # Just enough frames for a valid video
-                guidance_scale=3.0,
+                guidance_scale=1.0,
                 num_inference_steps=4,  # Fewer steps for faster warm-up
                 seed=42,  # Fixed seed for consistent warm-up
                 fps=16,  # Lower FPS for faster processing
@@ -505,7 +500,6 @@ class EndpointHandler:
             stg_scale=params.get("stg_scale", GenerationConfig.stg_scale),
             stg_rescale=params.get("stg_rescale", GenerationConfig.stg_rescale),
             stg_mode=params.get("stg_mode", GenerationConfig.stg_mode),
-            stg_skip_layers=params.get("stg_skip_layers", GenerationConfig.stg_skip_layers),
             
             # VAE noise settings
             decode_timestep=params.get("decode_timestep", GenerationConfig.decode_timestep),
@@ -589,7 +583,6 @@ class EndpointHandler:
                     generator=generator,
                     output_type="pt",  # Return as PyTorch tensor
                     skip_layer_strategy=skip_layer_strategy,
-                    skip_block_list=config.stg_skip_layers,
                     stg_scale=config.stg_scale,
                     do_rescaling=config.stg_rescale != 1.0,
                     rescaling_scale=config.stg_rescale,