Update app.py

app.py

@@ -330,7 +330,6 @@ else:
 checkpoint_path = EROS_FIXED
 spatial_upsampler_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename="ltx-2.3-spatial-upscaler-x2-1.0.safetensors")
 gemma_root = snapshot_download(repo_id=GEMMA_REPO)
-distilled_lora_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename=DISTILLED_LORA_FILE)
 
 # ---- Insert block (LoRA downloads) between lines 268 and 269 ----
 # LoRA repo + download the requested LoRA adapters
@@ -347,7 +346,7 @@ mself_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="Furry Hyper Mastu
 dramatic_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX-2.3 - Orgasm.safetensors") # "[He | She] is having am orgasm." (am or an?)
 fluid_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="cr3ampi3_animation_i2v_ltx2_v1.0.safetensors") # cr3ampi3 animation., missionary animation, doggystyle bouncy animation, double penetration animation
 liquid_lora_path = hf_hub_download(repo_id="valiantcat/LTX-2.3-Transition-LORA", filename="ltx2.3-transition.safetensors") # wet dr1pp
-demopose_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="hentai_voice_ltx23.safetensors")
+demopose_lora_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename=DISTILLED_LORA_FILE)
 
 print(f"Pose LoRA: {pose_lora_path}")
 print(f"General LoRA: {general_lora_path}")
@@ -367,12 +366,6 @@ print(f"Distilled LoRA: {distilled_lora_path}")
 
 # Initialize pipeline WITH text encoder and optional audio support
 # ---- Replace block (pipeline init) lines 275-281 ----
-print("Creating TI2VidTwoStagesPipeline...")
-distilled_lora = [LoraPathStrengthAndSDOps(
-    path=distilled_lora_path,
-    strength=0.9,
-    sd_ops=SDOps(name="distilled_lora", mapping=()),
-)]
 pipeline = LTX23DistilledA2VPipeline(
     distilled_checkpoint_path=checkpoint_path,
     spatial_upsampler_path=spatial_upsampler_path,
@@ -805,7 +798,7 @@ with gr.Blocks(title="LTX-2.3 Distilled") as demo:
                         minimum=0.0, maximum=2.0, value=0.0, step=0.01
                     )
                     demopose_strength = gr.Slider(
-                        label="Audio Helper strength",
+                        label="Distilled strength",
                         minimum=0.0, maximum=2.0, value=0.0, step=0.01
                     )
                 prepare_lora_btn = gr.Button("Prepare / Load LoRA Cache", variant="secondary")