Restore LoRA strength to 0.8

app.py

@@ -78,6 +78,8 @@ from ltx_pipelines.utils.helpers import (
 )
 from ltx_pipelines.utils.media_io import decode_audio_from_file, encode_video
 from ltx_pipelines.utils.types import PipelineComponents
+from ltx_core.loader.primitives import LoraPathStrengthAndSDOps
+from ltx_core.loader.sd_ops import LTXV_LORA_COMFY_RENAMING_MAP
 
 # --- Attention backend patch (same as Element-16) ---
 import torch.nn.functional as F
@@ -303,14 +305,22 @@ def download_upsampler():
 def download_gemma():
     return snapshot_download(repo_id=GEMMA_REPO)
 
-with ThreadPoolExecutor(max_workers=3) as executor:
+def download_talking_head_lora():
+    return hf_hub_download(
+        repo_id="elix3r/LTX-2.3-22b-AV-LoRA-talking-head",
+        filename="LTX-2.3-22b-AV-LoRA-talking-head-v1.safetensors"
+    )
+
+with ThreadPoolExecutor(max_workers=4) as executor:
     f_ckpt      = executor.submit(download_checkpoint)
     f_upsampler = executor.submit(download_upsampler)
     f_gemma     = executor.submit(download_gemma)
+    f_lora      = executor.submit(download_talking_head_lora)
 
-    checkpoint_path = f_ckpt.result()
-    upsampler_path  = f_upsampler.result()
-    gemma_root      = f_gemma.result()
+    checkpoint_path   = f_ckpt.result()
+    upsampler_path    = f_upsampler.result()
+    gemma_root        = f_gemma.result()
+    talking_head_lora = f_lora.result()
 
 print(f"Checkpoint:        {checkpoint_path}")
 print(f"Spatial upsampler: {upsampler_path}")
@@ -320,7 +330,11 @@ pipeline = DistilledAudioGuidancePipeline(
     distilled_checkpoint_path=checkpoint_path,
     spatial_upsampler_path=upsampler_path,
     gemma_root=gemma_root,
-    loras=(),
+    loras=(LoraPathStrengthAndSDOps(
+        path=talking_head_lora,
+        strength=0.8,
+        sd_ops=LTXV_LORA_COMFY_RENAMING_MAP
+    ),),
 )
 
 # Preload all models for ZeroGPU tensor packing