Update api/ltx_server_refactored.py

api/ltx_server_refactored.py

@@ -246,7 +246,8 @@ class VideoService:
         first_pass_kwargs = {
             "prompt": prompt, "negative_prompt": negative_prompt, "height": downscaled_height, "width": downscaled_width,
             "num_frames": actual_num_frames, "frame_rate": int(FPS), "generator": torch.Generator(device=self.device).manual_seed(used_seed),
-            "output_type": "latent", "conditioning_items": conditioning_items, "guidance_scale": float(guidance_scale),
+            "output_type": "latent", "conditioning_items": conditioning_items, 
+            #"guidance_scale": float(guidance_scale),
             **(self.config.get("first_pass", {}))
         }
         try: 
@@ -295,10 +296,10 @@ class VideoService:
             print("[DEBUG] Sobrepondo configurações do LTX com valores da UI...")
             if "first_pass_num_inference_steps" in ltx_configs_override:
                 first_pass_config["num_inference_steps"] = ltx_configs_override["first_pass_num_inference_steps"]
-            if "first_pass_guidance_scale" in ltx_configs_override:
-                max_val = max(first_pass_config.get("guidance_scale", [1]))
-                new_max_val = ltx_configs_override["first_pass_guidance_scale"]
-                first_pass_config["guidance_scale"] = [new_max_val if x==max_val else x for x in first_pass_config["guidance_scale"]]
+            #if "first_pass_guidance_scale" in ltx_configs_override:
+            #    max_val = max(first_pass_config.get("guidance_scale", [1]))
+            #    new_max_val = ltx_configs_override["first_pass_guidance_scale"]
+            #    first_pass_config["guidance_scale"] = [new_max_val if x==max_val else x for x in first_pass_config["guidance_scale"]]
         
         first_pass_kwargs = {
             "prompt": prompt, "negative_prompt": negative_prompt, "height": downscaled_height, "width": downscaled_width,
@@ -307,8 +308,8 @@ class VideoService:
             **first_pass_config
         }
         # Removido guidance_scale daqui pois agora está dentro do first_pass_config
-        if "guidance_scale" in first_pass_kwargs:
-            del first_pass_kwargs['guidance_scale']
+        #if "guidance_scale" in first_pass_kwargs:
+        #    del first_pass_kwargs['guidance_scale']
 
         with torch.autocast(device_type="cuda", dtype=self.runtime_autocast_dtype, enabled=self.device.type == 'cuda'):
             latents_bruto = self.pipeline(**first_pass_kwargs).images
@@ -376,7 +377,9 @@ class VideoService:
             
             latentes_bruto = self._generate_single_chunk_low(
                 prompt=chunk_prompt, negative_prompt=negative_prompt, height=height, width=width,
-                num_frames=num_frames_para_gerar, guidance_scale=guidance_scale, seed=used_seed + i,
+                num_frames=num_frames_para_gerar, 
+                #guidance_scale=guidance_scale, 
+                seed=used_seed + i,
                 initial_latent_condition=condition_item_latent_overlap, image_conditions=current_image_conditions,
                 ltx_configs_override=ltx_configs_override
             )
@@ -431,7 +434,7 @@ class VideoService:
             negative_prompt=negative_prompt,
             height=height, width=width,
             num_frames=total_actual_frames,
-            guidance_scale=guidance_scale,
+            #guidance_scale=guidance_scale,
             seed=used_seed,
             image_conditions=initial_image_conditions,
             ltx_configs_override=ltx_configs_override
@@ -476,7 +479,8 @@ class VideoService:
                     second_pass_width = chunk.shape[4] * self.pipeline.vae_scale_factor
                     second_pass_kwargs = {
                         "prompt": prompt, "negative_prompt": negative_prompt, "height": second_pass_height, "width": second_pass_width,
-                        "num_frames": chunk.shape[2], "latents": chunk, "guidance_scale": float(guidance_scale),
+                        "num_frames": chunk.shape[2], "latents": chunk, 
+                        #"guidance_scale": float(guidance_scale),
                         "output_type": "latent", "generator": torch.Generator(device=self.device).manual_seed(used_seed),
                         **(self.config.get("second_pass", {}))
                     }