Rename app(currentwithcustomcheckpointand1stage).py to app.py

app(currentwithcustomcheckpointand1stage).py → app.py

@@ -6,9 +6,6 @@ import sys
 os.environ["TORCH_COMPILE_DISABLE"] = "1"
 os.environ["TORCHDYNAMO_DISABLE"] = "1"
 
-# Install xformers for memory-efficient attention
-subprocess.run([sys.executable, "-m", "pip", "install", "xformers==0.0.32.post2", "--no-build-isolation"], check=False)
-
 # Clone LTX-2 repo and install packages
 LTX_REPO_URL = "https://github.com/Lightricks/LTX-2.git"
 LTX_REPO_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "LTX-2")
@@ -79,16 +76,6 @@ from ltx_core.loader.sd_ops import LTXV_LORA_COMFY_RENAMING_MAP
 
 from ltx_pipelines.utils.types import PipelineComponents
 
-# Force-patch xformers attention into the LTX attention module.
-from ltx_core.model.transformer import attention as _attn_mod
-print(f"[ATTN] Before patch: memory_efficient_attention={_attn_mod.memory_efficient_attention}")
-try:
-    from xformers.ops import memory_efficient_attention as _mea
-    _attn_mod.memory_efficient_attention = _mea
-    print(f"[ATTN] After patch: memory_efficient_attention={_attn_mod.memory_efficient_attention}")
-except Exception as e:
-    print(f"[ATTN] xformers patch FAILED: {type(e).__name__}: {e}")
-
 logging.getLogger().setLevel(logging.INFO)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -245,8 +232,8 @@ PENDING_LORA_STATUS: str = "No LoRA state prepared yet."
 weights_dir = Path("weights")
 weights_dir.mkdir(exist_ok=True)
 checkpoint_path = hf_hub_download(
-    repo_id="SulphurAI/Sulphur-2-base",
-    filename="sulphur_distil_bf16.safetensors",
+    repo_id="TenStrip/LTX2.3-10Eros",
+    filename="10Eros_v1_bf16.safetensors",
     local_dir=str(weights_dir),
     local_dir_use_symlinks=False,
 )
@@ -261,22 +248,27 @@ LORA_REPO = "dagloop5/LoRA"
 print("=" * 80)
 print("Downloading LoRA adapters from dagloop5/LoRA...")
 print("=" * 80)
+distilled_lora_path = hf_hub_download(repo_id="TenStrip/LTX2.3_Distilled_Lora_1.1_Experiments", filename="ltx-2.3-22b-distilled-lora-1.1_fro90_ceil72_condsafe.safetensors")
 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=LORA_REPO, filename="DR34ML4Y_LTXXX_PREVIEW_RC1.safetensors") # m15510n4ry, bl0wj0b, d0ubl3_bj, d0gg1e, c0wg1rl
+dreamlay_lora_path = hf_hub_download(repo_id="lynaNSFW/DR34ML4Y_AIO_NSFW_LTX23", filename="DR34ML4Y_LTXXX_V2.safetensors") # m15510n4ry, bl0wj0b, d0ubl3_bj, d0gg1e, c0wg1rl
 mself_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="Furry Hyper Masturbation - LTX-2 I2V v1.safetensors") # Hyperfap
 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="LTX2.3_CREAMPIE_ANIMATION-V0.1.safetensors") # cum
+fluid_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="Cr3ampi3_animation_sulphur-2_i2v_v1.0.safetensors") # cr3ampi3 animation
 liquid_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="liquid_wet_dr1pp_ltx2_v1.0_scaled.safetensors") # wet dr1pp
 demopose_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="clapping-cheeks-audio-v001-alpha.safetensors")
 voice_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="hentai_voice_ltx23.safetensors")
-realism_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="FurryenhancerLTX2.3V1.215.safetensors")
+realism_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="FurryenhancerLTX2.3V4.094fused.safetensors")
 transition_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX-2_takerpov_lora_v1.2.safetensors") # takerpov1, taker pov
-physics_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2.3_Better_Physics_PhysLTX.safetensors")
-reasoning_lora_path = hf_hub_download(repo_id="TenStrip/LTX2.3_Distilled_Lora_1.1_Experiments", filename="ltx-2.3-22b-distilled-lora-1.1_fro90_ceil72_condsafe.safetensors")
+physics_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2.3_Physics_V2_000002000.safetensors")
+reasoning_lora_path = hf_hub_download(repo_id="LiconStudio/Ltx2.3-VBVR-lora-I2V", filename="Ltx2.3-Licon-VBVR-I2V-390K-R32.safetensors")
+twostep_lora_path = hf_hub_download(repo_id=LORA_REPO, filename="LTX2.3_Multi_step_video_reasoning_V0.1.safetensors")
 
+print(f"Distilled LoRA: {distilled_lora_path}")
 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}")
@@ -290,7 +282,7 @@ print(f"Realism LoRA: {realism_lora_path}")
 print(f"Transition LoRA: {transition_lora_path}")
 print(f"Physics LoRA: {physics_lora_path}")
 print(f"Reasoning LoRA: {reasoning_lora_path}")
-# ----------------------------------------------------------------
+print(f"Twostep LoRA: {twostep_lora_path}")
 
 print(f"Checkpoint: {checkpoint_path}")
 print(f"Spatial upsampler: {spatial_upsampler_path}")
@@ -307,8 +299,10 @@ pipeline = LTX23DistilledA2VPipeline(
 )
 # ----------------------------------------------------------------
 
-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) -> tuple[str, str]:
+def _make_lora_key(distilled_strength: float, 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]:
+    rx = round(float(distilled_strength), 2)
     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)
@@ -322,13 +316,16 @@ def _make_lora_key(pose_strength: float, general_strength: float, motion_strengt
     rt = round(float(transition_strength), 2)
     ry = round(float(physics_strength), 2)
     ri = round(float(reasoning_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}"
+    rw = round(float(twostep_strength), 2)
+    key_str = f"{distilled_lora_path}:{rx}|{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(
+    distilled_strength: float,
     pose_strength: float,
+    twod_strength: float,
     general_strength: float,
     motion_strength: float,
     dreamlay_strength: float,
@@ -342,6 +339,7 @@ def prepare_lora_cache(
     transition_strength: float,
     physics_strength: float,
     reasoning_strength: float,
+    twostep_strength: float,
     progress=gr.Progress(track_tqdm=True),
 ):
     """
@@ -354,7 +352,7 @@ 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)
+    key, _ = _make_lora_key(distilled_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)
     cache_path = LORA_CACHE_DIR / f"{key}.safetensors"
 
     progress(0.05, desc="Preparing LoRA state")
@@ -370,7 +368,9 @@ def prepare_lora_cache(
             print(f"[LoRA] Cache load failed: {type(e).__name__}: {e}")
 
     entries = [
+        (distilled_lora_path, round(float(distilled_strength), 2)),
         (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)),
@@ -384,6 +384,7 @@ def prepare_lora_cache(
         (transition_lora_path, round(float(transition_strength), 2)),
         (physics_lora_path, round(float(physics_strength), 2)),
         (reasoning_lora_path, round(float(reasoning_strength), 2)),
+        (twostep_lora_path, round(float(twostep_strength), 2)),
     ]
     loras_for_builder = [
         LoraPathStrengthAndSDOps(path, strength, LTXV_LORA_COMFY_RENAMING_MAP)
@@ -567,7 +568,9 @@ def get_gpu_duration(
     randomize_seed: bool = True,
     height: int = 1024,
     width: int = 1536,
+    distilled_strength: float = 0.0,
     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,
@@ -581,6 +584,7 @@ def get_gpu_duration(
     transition_strength: float = 0.0,
     physics_strength: float = 0.0,
     reasoning_strength: float = 0.0,
+    twostep_strength: float = 0.0,
     progress=None,
 ):
     return int(gpu_duration)
@@ -598,7 +602,9 @@ def generate_video(
     randomize_seed: bool = True,
     height: int = 1024,
     width: int = 1536,
+    distilled_strength: float = 0.0,
     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,
@@ -612,6 +618,7 @@ def generate_video(
     transition_strength: float = 0.0,
     physics_strength: float = 0.0,
     reasoning_strength: float = 0.0,
+    twostep_strength: float = 0.0,
     progress=gr.Progress(track_tqdm=True),
 ):
     try:
@@ -718,6 +725,10 @@ with gr.Blocks(title="LTX-2.3 Distilled") as demo:
                     high_res = gr.Checkbox(label="High Resolution", value=True)
                 with gr.Column():
                     gr.Markdown("### LoRA adapter strengths (set to 0 to disable; slow and WIP)")
+                    distilled_strength = gr.Slider(
+                        label="Distilled LoRA strength",
+                        minimum=0.0, maximum=2.0, value=0.0, step=0.01
+                    )
                     pose_strength = gr.Slider(
                         label="Anthro Enhancer strength",
                         minimum=0.0, maximum=2.0, value=0.0, step=0.01
@@ -771,7 +782,11 @@ with gr.Blocks(title="LTX-2.3 Distilled") as demo:
                         minimum=0.0, maximum=2.0, value=0.0, step=0.01
                     )
                     reasoning_strength = gr.Slider(
-                        label="Distilled strength",
+                        label="Official Reasoning strength",
+                        minimum=0.0, maximum=2.0, value=0.0, step=0.01
+                    )
+                    twostep_strength = gr.Slider(
+                        label="Multistep Reasoning strength",
                         minimum=0.0, maximum=2.0, value=0.0, step=0.01
                     )
                 prepare_lora_btn = gr.Button("Prepare / Load LoRA Cache", variant="secondary")
@@ -791,47 +806,6 @@ with gr.Blocks(title="LTX-2.3 Distilled") as demo:
                 step=1.0,
             )
 
-    gr.Examples(
-        examples=[
-            [
-                None,
-                "pinkknit.jpg",
-                "The camera falls downward through darkness as if dropped into a tunnel. "
-                "As it slows, five friends wearing pink knitted hats and sunglasses lean "
-                "over and look down toward the camera with curious expressions. The lens "
-                "has a strong fisheye effect, creating a circular frame around them. They "
-                "crowd together closely, forming a symmetrical cluster while staring "
-                "directly into the lens.",
-                3.0,
-                80.0,
-                False,
-                42,
-                True,
-                1024,
-                1024,
-                0.0,  # pose_strength (example)
-                0.0,  # general_strength (example)
-                0.0,  # motion_strength (example)
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-                0.0,
-            ],
-        ],
-        inputs=[
-            first_image, last_image, prompt, duration, gpu_duration,
-            enhance_prompt, seed, randomize_seed, height, width,
-            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,
-        ],
-    )
-
     first_image.change(
         fn=on_image_upload,
         inputs=[first_image, last_image, high_res],
@@ -852,7 +826,7 @@ with gr.Blocks(title="LTX-2.3 Distilled") as demo:
 
     prepare_lora_btn.click(
         fn=prepare_lora_cache,
-        inputs=[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],
+        inputs=[distilled_strength, 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],
         outputs=[lora_status],
     )
     
@@ -861,7 +835,7 @@ with gr.Blocks(title="LTX-2.3 Distilled") as demo:
         inputs=[
             first_image, last_image, prompt, duration, gpu_duration, enhance_prompt,
             seed, randomize_seed, height, width,
-            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,
+            distilled_strength, 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,
         ],
         outputs=[output_video, seed],
     )