Update api/ltx_server.py

api/ltx_server.py

@@ -579,17 +579,13 @@ class VideoService:
             i=0
             while i < n_chunks:
                 start = (num_latente_por_chunk*i)
-                end = (start+num_latente_por_chunk+overlap)
+                end = (start+num_latente_por_chunk+(overlap+1))
                 if i+1 < n_chunks:
-                    if i > 0:
-                        chunk = latents_brutos[:, :, start-overlap:end, :, :].clone().detach()
-                        print(f"[DEBUG] chunk{i+1}[:, :, {start}:{end}, :, :] = {chunk.shape[2]}")
-                    else:
-                        chunk = latents_brutos[:, :, start:end, :, :].clone().detach()
-                        print(f"[DEBUG] chunk{i+1}[:, :, {start}:{end}, :, :] = {chunk.shape[2]}")
+                    chunk = latents_brutos[:, :, start:end, :, :].clone().detach()
+                    print(f"[DEBUG] chunk{i+1}[:, :, {start}:{end}, :, :] = {chunk.shape[2]}")
                 else:
-                    chunk = latents_brutos[:, :, start-overlap:, :, :].clone().detach()
-                    print(f"[DEBUG] chunk{i+1}[:, :, {start-overlap}:, :, :] = {chunk.shape[2]}")
+                    chunk = latents_brutos[:, :, start:, :, :].clone().detach()
+                    print(f"[DEBUG] chunk{i+1}[:, :, {start}:, :, :] = {chunk.shape[2]}")
                 chunks.append(chunk)
                 i+=1
         else:
@@ -873,7 +869,7 @@ class VideoService:
                     except Exception:
                          pass
                 
-                    latents_parts_up = self._dividir_latentes_por_tamanho(latents_cpu_up,4,1)
+                    latents_parts_up = self._dividir_latentes_por_tamanho(latents_cpu_up,40,1)
 
                     print("\n\n--- INICIANDO ETAPA 3: REFINAMENTO DE TEXTURA (SECOND PASS) ---")
 
@@ -923,21 +919,33 @@ class VideoService:
                         print("#########################################")
                       
                     print("\n\n--- FIM ETAPA 3: REFINAMENTO DE TEXTURA (SECOND PASS) ---")
-                    
+
                 else: # Geração de etapa única
                     print("\n--- INICIANDO GERAÇÃO DE ETAPA ÚNICA ---")
                     t_single = time.perf_counter()
-                    single_pass_kwargs = call_kwargs.copy()
-                    single_pass_kwargs.update(self.config.get("first_pass", {}))
-                    single_pass_kwargs["guidance_scale"] = float(guidance_scale)
+                    
                     single_pass_kwargs["output_type"] = "latent"
+                    single_pass_call_kwargs = call_kwargs.copy()
+                    first_pass_config_from_yaml = PIPELINE_CONFIG_YAML.get("first_pass", {})
+            
+                    single_pass_call_kwargs["timesteps"] = first_pass_config_from_yaml.get("timesteps")
+                    single_pass_call_kwargs["guidance_scale"] = float(guidance_scale)
+                    single_pass_call_kwargs["stg_scale"] = first_pass_config_from_yaml.get("stg_scale")
+                    single_pass_call_kwargs["rescaling_scale"] = first_pass_config_from_yaml.get("rescaling_scale")
+                    single_pass_call_kwargs["skip_block_list"] = first_pass_config_from_yaml.get("skip_block_list")
                     
-                    latents = self.pipeline(**single_pass_kwargs).images
+                    # Remove keys that might conflict or are not used in single pass / handled by above
+                    single_pass_call_kwargs.pop("num_inference_steps", None) 
+                    single_pass_call_kwargs.pop("first_pass", None) 
+                    single_pass_call_kwargs.pop("second_pass", None)
+                    single_pass_call_kwargs.pop("downscale_factor", None)
+                    
+                    latents = self.pipeline(**single_pass_call_kwargs).images
                     log_tensor_info(latents, "Latentes Finais (Etapa Única)")
                     print(f"[DEBUG] Etapa única concluída em {time.perf_counter() - t_single:.2f}s")
 
                     latents_list.append(latents)
-
+            
             # --- ETAPA FINAL: DECODIFICAÇÃO E CODIFICAÇÃO MP4 ---
             print("\n--- INICIANDO ETAPA FINAL: DECODIFICAÇÃO E MONTAGEM ---")