Update api/ltx_server.py

api/ltx_server.py

@@ -14,13 +14,9 @@ logging.set_verbosity_error()
 logging.set_verbosity_warning()
 logging.set_verbosity_info()
 logging.set_verbosity_debug()
-
-
 LTXV_DEBUG=1
 LTXV_FRAME_LOG_EVERY=8
 
-
-
 # --- 1. IMPORTAÇÕES ---
 import os, subprocess, shlex, tempfile
 import torch
@@ -108,8 +104,6 @@ def _query_gpu_processes_via_nvidiasmi(device_index: int) -> List[Dict]:
                 continue
     return results
 
-
-
 def calculate_new_dimensions(orig_w, orig_h, divisor=8):
     """
     Calcula novas dimensões mantendo a proporção, garantindo que ambos os
@@ -144,7 +138,6 @@ def calculate_new_dimensions(orig_w, orig_h, divisor=8):
     print(f"[Dimension Calc] Original: {orig_w}x{orig_h} -> Calculado: {new_w:.0f}x{new_h:.0f} -> Final (divisível por {divisor}): {final_w}x{final_h}")
     return final_h, final_w # Retorna (altura, largura)
 
-
 def handle_media_upload_for_dims(filepath, current_h, current_w):
     """
     Esta função agora usará o novo cálculo robusto.
@@ -218,7 +211,6 @@ def add_deps_to_path():
 add_deps_to_path()
 
 # --- 3. IMPORTAÇÕES ESPECÍFICAS DO MODELO ---
-
 from ltx_video.pipelines.pipeline_ltx_video import ConditioningItem, LTXMultiScalePipeline
 from ltx_video.utils.skip_layer_strategy import SkipLayerStrategy
 from ltx_video.models.autoencoders.vae_encode import un_normalize_latents, normalize_latents
@@ -241,10 +233,6 @@ def log_tensor_info(tensor, name="Tensor"):
             pass
     print("------------------------------------------\n")
 
-
-
-
-
 # --- 5. CLASSE PRINCIPAL DO SERVIÇO ---
 class VideoService:
     def __init__(self):
@@ -367,28 +355,28 @@ class VideoService:
 
     def _load_models(self):
         t0 = time.perf_counter()
-        LTX_REPO = "Lightricks/LTX-Video"
-        print("[DEBUG] Baixando checkpoint principal...")
-        distilled_model_path = hf_hub_download(
-            repo_id=LTX_REPO,
-            filename=self.config["checkpoint_path"],
-            local_dir=os.getenv("HF_HOME"),
-            cache_dir=os.getenv("HF_HOME_CACHE"),
-            token=os.getenv("HF_TOKEN"),
-        )
-        self.config["checkpoint_path"] = distilled_model_path
-        print(f"[DEBUG] Checkpoint em: {distilled_model_path}")
-
-        print("[DEBUG] Baixando upscaler espacial...")
-        spatial_upscaler_path = hf_hub_download(
-            repo_id=LTX_REPO,
-            filename=self.config["spatial_upscaler_model_path"],
-            local_dir=os.getenv("HF_HOME"),
-            cache_dir=os.getenv("HF_HOME_CACHE"),
-            token=os.getenv("HF_TOKEN")
+        #LTX_REPO = "Lightricks/LTX-Video"
+        #print("[DEBUG] Baixando checkpoint principal...")
+        #distilled_model_path = hf_hub_download(
+        #    repo_id=LTX_REPO,
+        #    filename=self.config["checkpoint_path"],
+        #    local_dir=os.getenv("HF_HOME"),
+        #    cache_dir=os.getenv("HF_HOME_CACHE"),
+        #    token=os.getenv("HF_TOKEN"),
+        #)
+        #self.config["checkpoint_path"] = distilled_model_path
+        #print(f"[DEBUG] Checkpoint em: {distilled_model_path}")
+
+        #print("[DEBUG] Baixando upscaler espacial...")
+        #spatial_upscaler_path = hf_hub_download(
+        #    repo_id=LTX_REPO,
+        #    filename=self.config["spatial_upscaler_model_path"],
+        #    local_dir=os.getenv("HF_HOME"),
+        #    cache_dir=os.getenv("HF_HOME_CACHE"),
+        #    token=os.getenv("HF_TOKEN")
         )
-        self.config["spatial_upscaler_model_path"] = spatial_upscaler_path
-        print(f"[DEBUG] Upscaler em: {spatial_upscaler_path}")
+        #self.config["spatial_upscaler_model_path"] = spatial_upscaler_path
+        #print(f"[DEBUG] Upscaler em: {spatial_upscaler_path}")
 
         print("[DEBUG] Construindo pipeline...")
         pipeline = create_ltx_video_pipeline(