Update app.py

app.py

@@ -447,6 +447,7 @@ print("=" * 80)
 print("Downloading LoRA adapters from dagloop5/LoRA...")
 print("=" * 80)
 pose_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2_3_NSFW_furry_concat_v2.safetensors")
+twod_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2.3_2d_NSFW_motion_enhancer.safetensors") # 2d style animation
 general_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2.3_reasoning_I2V_V3.safetensors")
 motion_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="motion_helper.safetensors")
 dreamlay_lora_path = hf_hub_download(repo_id="lynaNSFW/DR34ML4Y_AIO_NSFW_LTX23", filename="DR34ML4Y_LTXXX_V2.safetensors") # m15510n4ry, bl0wj0b, d0ubl3_bj, d0gg1e, c0wg1rl
@@ -463,6 +464,7 @@ reasoning_lora_path = hf_hub_download(repo_id="LiconStudio/Ltx2.3-VBVR-lora-I2V"
 twostep_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2.3_Multi_step_video_reasoning_V0.1.safetensors")
 
 print(f"Pose LoRA: {pose_lora_path}")
+print(f"twod LoRA: {twod_lora_path}")
 print(f"General LoRA: {general_lora_path}")
 print(f"Motion LoRA: {motion_lora_path}")
 print(f"Dreamlay LoRA: {dreamlay_lora_path}")
@@ -490,8 +492,9 @@ pipeline = LTX23DistilledA2VPipeline(
     quantization=QuantizationPolicy.fp8_cast(),
 )
 
-def _make_lora_key(pose_strength: float, general_strength: float, motion_strength: float, dreamlay_strength: float, mself_strength: float, dramatic_strength: float, fluid_strength: float, liquid_strength: float, demopose_strength: float, voice_strength: float, realism_strength: float, transition_strength: float, physics_strength: float, reasoning_strength: float, twostep_strength: float) -> tuple[str, str]:
+def _make_lora_key(pose_strength: float, twod_strength: float, general_strength: float, motion_strength: float, dreamlay_strength: float, mself_strength: float, dramatic_strength: float, fluid_strength: float, liquid_strength: float, demopose_strength: float, voice_strength: float, realism_strength: float, transition_strength: float, physics_strength: float, reasoning_strength: float, twostep_strength: float) -> tuple[str, str]:
     rp = round(float(pose_strength), 2)
+    ra = round(float(twod_strength), 2)
     rg = round(float(general_strength), 2)
     rm = round(float(motion_strength), 2)
     rd = round(float(dreamlay_strength), 2)
@@ -506,13 +509,14 @@ def _make_lora_key(pose_strength: float, general_strength: float, motion_strengt
     ry = round(float(physics_strength), 2)
     ri = round(float(reasoning_strength), 2)
     rw = round(float(twostep_strength), 2)
-    key_str = f"{pose_lora_path}:{rp}|{general_lora_path}:{rg}|{motion_lora_path}:{rm}|{dreamlay_lora_path}:{rd}|{mself_lora_path}:{rs}|{dramatic_lora_path}:{rr}|{fluid_lora_path}:{rf}|{liquid_lora_path}:{rl}|{demopose_lora_path}:{ro}|{voice_lora_path}:{rv}|{realism_lora_path}:{re}|{transition_lora_path}:{rt}|{physics_lora_path}:{ry}|{reasoning_lora_path}:{ri}|{twostep_lora_path}:{rw}"
+    key_str = f"{pose_lora_path}:{rp}|{twod_lora_path}:{ra}|{general_lora_path}:{rg}|{motion_lora_path}:{rm}|{dreamlay_lora_path}:{rd}|{mself_lora_path}:{rs}|{dramatic_lora_path}:{rr}|{fluid_lora_path}:{rf}|{liquid_lora_path}:{rl}|{demopose_lora_path}:{ro}|{voice_lora_path}:{rv}|{realism_lora_path}:{re}|{transition_lora_path}:{rt}|{physics_lora_path}:{ry}|{reasoning_lora_path}:{ri}|{twostep_lora_path}:{rw}"
     key = hashlib.sha256(key_str.encode("utf-8")).hexdigest()
     return key, key_str
 
 
 def prepare_lora_cache(
     pose_strength: float,
+    twod_strength: float,
     general_strength: float,
     motion_strength: float,
     dreamlay_strength: float,
@@ -539,7 +543,7 @@ def prepare_lora_cache(
     global PENDING_LORA_KEY, PENDING_LORA_STATE, PENDING_LORA_STATUS
 
     ledger = pipeline.model_ledger
-    key, _ = _make_lora_key(pose_strength, general_strength, motion_strength, dreamlay_strength, mself_strength, dramatic_strength, fluid_strength, liquid_strength, demopose_strength, voice_strength, realism_strength, transition_strength, physics_strength, reasoning_strength, twostep_strength)
+    key, _ = _make_lora_key(pose_strength, twod_strength, general_strength, motion_strength, dreamlay_strength, mself_strength, dramatic_strength, fluid_strength, liquid_strength, demopose_strength, voice_strength, realism_strength, transition_strength, physics_strength, reasoning_strength, twostep_strength)
     cache_path = LORA_CACHE_DIR / f"{key}.safetensors"
 
     progress(0.05, desc="Preparing LoRA state")
@@ -556,6 +560,7 @@ def prepare_lora_cache(
 
     entries = [
         (pose_lora_path, round(float(pose_strength), 2)),
+        (twod_lora_path, round(float(twod_strength), 2)),
         (general_lora_path, round(float(general_strength), 2)),
         (motion_lora_path, round(float(motion_strength), 2)),
         (dreamlay_lora_path, round(float(dreamlay_strength), 2)),
@@ -761,6 +766,7 @@ def get_gpu_duration(
     audio_rescale_scale: float = 1.0,
     audio_v2a_scale: float = 3.0,
     pose_strength: float = 0.0,
+    twod_strength: float = 0.0,
     general_strength: float = 0.0,
     motion_strength: float = 0.0,
     dreamlay_strength: float = 0.0,
@@ -804,6 +810,7 @@ def generate_video(
     audio_rescale_scale: float = 1.0,
     audio_v2a_scale: float = 3.0,
     pose_strength: float = 0.0,
+    twod_strength: float = 0.0,
     general_strength: float = 0.0,
     motion_strength: float = 0.0,
     dreamlay_strength: float = 0.0,
@@ -1031,7 +1038,7 @@ with gr.Blocks(title="LTX-2.3 Distilled with LoRAs, Negative Prompting, and Adva
             
             with gr.Row():
                 pose_strength = gr.Slider(label="Anthro Enhancer", minimum=0.0, maximum=2.0, value=0.0, step=0.01)
-                gr.Markdown("")  # Spacer for alignment
+                twod_strength = gr.Slider(label="2D Enhancer", minimum=0.0, maximum=2.0, value=0.0, step=0.01)
             
             with gr.Row():
                 general_strength = gr.Slider(label="Reasoning Enhancer", minimum=0.0, maximum=2.0, value=0.0, step=0.01)
@@ -1074,7 +1081,7 @@ with gr.Blocks(title="LTX-2.3 Distilled with LoRAs, Negative Prompting, and Adva
 
     prepare_lora_btn.click(
         fn=prepare_lora_cache,
-        inputs=[pose_strength, general_strength, motion_strength, dreamlay_strength,
+        inputs=[pose_strength, twod_strength, general_strength, motion_strength, dreamlay_strength,
                 mself_strength, dramatic_strength, fluid_strength, liquid_strength,
                 demopose_strength, voice_strength, realism_strength, transition_strength, physics_strength, reasoning_strength, twostep_strength],
         outputs=[lora_status],
@@ -1087,7 +1094,7 @@ with gr.Blocks(title="LTX-2.3 Distilled with LoRAs, Negative Prompting, and Adva
             enhance_prompt, seed, randomize_seed, height, width,
             video_cfg_scale, video_stg_scale, video_rescale_scale, video_a2v_scale,
             audio_cfg_scale, audio_stg_scale, audio_rescale_scale, audio_v2a_scale,
-            pose_strength, general_strength, motion_strength,
+            pose_strength, twod_strength, general_strength, motion_strength,
             dreamlay_strength, mself_strength, dramatic_strength, fluid_strength,
             liquid_strength, demopose_strength, voice_strength, realism_strength,
             transition_strength, physics_strength, reasoning_strength, twostep_strength, num_inference_steps,