Update api/ltx_server_refactored.py

api/ltx_server_refactored.py

@@ -233,10 +233,18 @@ class VideoService:
             tensor = self._prepare_conditioning_tensor(media, height, width, padding_values) if isinstance(media, str) else media.to(self.device, dtype=self.runtime_autocast_dtype)
             safe_frame = max(0, min(int(frame), num_frames - 1))
             conditioning_items.append(ConditioningItem(tensor, safe_frame, float(weight)))
-        
-        
         return conditioning_items
 
+    def prepare_condition_items_latent(self, items_list: List, height: int, width: int, num_frames: int):
+        if not items_list: return []
+        conditioning_items = []
+        for tensor_patch, frame, weight in items_list:
+            tensor = torch.load(tensor_patch).to(self.device)
+            safe_frame = max(0, min(int(frame), num_frames - 1))
+            conditioning_items.append(ConditioningItem(tensor, safe_frame, float(weight)))
+        return conditioning_items
+        
+
     def generate_low(self, prompt, negative_prompt, height, width, duration, guidance_scale, seed, conditioning_items=None):
         used_seed = random.randint(0, 2**32 - 1) if seed is None else int(seed)
         seed_everething(used_seed)
@@ -409,8 +417,10 @@ class VideoService:
         frames_per_chunk_last = max(9, frames_per_chunk_last)
         
         poda_latents_num = overlap_frames // self.pipeline.video_scale_factor if self.pipeline.video_scale_factor > 0 else 0
-        
+
+        initial_conditions= []
         latentes_chunk_video = []
+        overlap_condition = []
         lista_patch_latentes_chunk = []
         condition_item_latent_overlap = None
         temp_dir = tempfile.mkdtemp(prefix="ltxv_narrative_"); self._register_tmp_dir(temp_dir)
@@ -443,10 +453,22 @@ class VideoService:
 
             frames_per_chunk = ((frames_per_chunk - 1)//8)*8 + 1
 
+
+            if i== 0:
+                initial_conditions = initial_conditions
+            else:
+                initial_conditions = None
+
+            if overlap_latents!=None:
+                items_list = [[overlap_latents, 0, 1.0]]
+                overlap_condition = prepare_condition_items_latent(items_list)
+                
+            itens_conditions_itens = latentes_chunk_video + overlap_condition
+
             latentes_bruto_r = self._generate_single_chunk_low(
                 prompt=chunk_prompt, negative_prompt=negative_prompt, height=height, width=width,
                 num_frames=frames_per_chunk, guidance_scale=guidance_scale, seed=used_seed + i,
-                itens_conditions_itens=None, 
+                itens_conditions_itens=itens_conditions_itens, 
                 ltx_configs_override=ltx_configs_override
             )
 
@@ -458,12 +480,9 @@ class VideoService:
             #final_latents = torch.cat(lista_tensores, dim=2).to(self.device)
 
 
-            if i== 0:
-                initial_conditions = None
-            else:
-                initial_conditions = initial_conditions
-                
-                
+            
+            
+            
             
             
             #poda inicio overlap