Duplicate from jmpplbp/VideoKarma1-rebuild-20260927

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
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+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
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+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
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+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

APP_FILES.json

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+[
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+    "sha256": "a3b26856b061ec10fff08145a8f24d168f185bc823e23aa3e2d16585ecc65d0c"
+  }
+]

ATTRIBUTION.md

@@ -0,0 +1,15 @@
+# Licenses and attribution
+
+- [SquishedSquirrel/Wan2.2EV](https://huggingface.co/SquishedSquirrel/Wan2.2EV/tree/46c390c08b58861a20effc0425d0284de2d665f9): apache-2.0
+- [SquishedSquirrel/Wan2.2EV](https://huggingface.co/SquishedSquirrel/Wan2.2EV/tree/46c390c08b58861a20effc0425d0284de2d665f9): apache-2.0
+- [Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/c4f60d30c55a624e35427060fdd217579a6c1d77): apache-2.0
+- [Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/c4f60d30c55a624e35427060fdd217579a6c1d77): apache-2.0
+- [Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/c4f60d30c55a624e35427060fdd217579a6c1d77): apache-2.0
+- [Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/c4f60d30c55a624e35427060fdd217579a6c1d77): apache-2.0
+- [Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/c4f60d30c55a624e35427060fdd217579a6c1d77): apache-2.0
+- [Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/c4f60d30c55a624e35427060fdd217579a6c1d77): apache-2.0
+- [Comfy-Org/Wan_2.1_ComfyUI_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/617a7633e636506f850e043bc4605f290a466a8e): apache-2.0
+- [Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/tree/c4f60d30c55a624e35427060fdd217579a6c1d77): apache-2.0
+
+
+Original source revisions and checksums are recorded in MODEL_SOURCES.json where present. Runtime component notices are in RUNTIME_SOURCES.json and bundled LICENSE files.

MODEL_SOURCES.json

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+[
+  {
+    "slot": "wan.high",
+    "source_repo": "SquishedSquirrel/Wan2.2EV",
+    "source_revision": "46c390c08b58861a20effc0425d0284de2d665f9",
+    "source_path": "Wan2.2_ev_high.safetensors",
+    "target_path": "models/diffusion_models/Wan2.2_ev_high.safetensors",
+    "size": 14293828968,
+    "sha256": "f6a29c51486a2ec073d155ce85e90cc3bf9ee6c726aa87bf3835c0aa63b05de4",
+    "license": "apache-2.0",
+    "required_when": "Wan i2v; high/low pair and corresponding default 4-step acceleration LoRA."
+  },
+  {
+    "slot": "wan.low",
+    "source_repo": "SquishedSquirrel/Wan2.2EV",
+    "source_revision": "46c390c08b58861a20effc0425d0284de2d665f9",
+    "source_path": "Wan2.2_ev_low.safetensors",
+    "target_path": "models/diffusion_models/Wan2.2_ev_low.safetensors",
+    "size": 14293828968,
+    "sha256": "82a642cde3b39eb0c45115d6d89c39d2cbae9ec3309bc9fbd8aab8e5e72b9c8c",
+    "license": "apache-2.0",
+    "required_when": "Wan i2v; high/low pair and corresponding default 4-step acceleration LoRA."
+  },
+  {
+    "slot": "wan.high-lora",
+    "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+    "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+    "source_path": "split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors",
+    "target_path": "models/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors",
+    "size": 1226977424,
+    "sha256": "d176c808d6fc461999b68e321efcb7501b20b8c3797523ed0df14f7d1deff11e",
+    "license": "apache-2.0",
+    "required_when": "Wan i2v; high/low pair and corresponding default 4-step acceleration LoRA."
+  },
+  {
+    "slot": "wan.low-lora",
+    "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+    "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+    "source_path": "split_files/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors",
+    "target_path": "models/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors",
+    "size": 1226977424,
+    "sha256": "024f21de095bc8fad9809ded3e9e49a2e170dcf27075da8145ba7d60d8aab7f9",
+    "license": "apache-2.0",
+    "required_when": "Wan i2v; high/low pair and corresponding default 4-step acceleration LoRA."
+  },
+  {
+    "slot": "wan.t2v-high",
+    "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+    "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+    "source_path": "split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors",
+    "target_path": "models/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors",
+    "size": 14293923632,
+    "sha256": "cad711ae211c8b23455ec68cd6a190a33a3d874234a77eb57266d73f8f0e6c9f",
+    "license": "apache-2.0",
+    "required_when": "Wan t2v only; not needed for i2v."
+  },
+  {
+    "slot": "wan.t2v-low",
+    "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+    "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+    "source_path": "split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors",
+    "target_path": "models/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors",
+    "size": 14293923632,
+    "sha256": "e71b96d7c82e638694c5e7fb98fac4bfb0e4ddc5fbbb4b1df40da8f0f1278a97",
+    "license": "apache-2.0",
+    "required_when": "Wan t2v only; not needed for i2v."
+  },
+  {
+    "slot": "wan.t2v-high-lora",
+    "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+    "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+    "source_path": "split_files/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors",
+    "target_path": "models/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors",
+    "size": 1226977424,
+    "sha256": "698321cb86bd30c4af06c9b84e656a1048c8cb54e06d50694536fb5de37fde41",
+    "license": "apache-2.0",
+    "required_when": "Wan t2v only; not needed for i2v."
+  },
+  {
+    "slot": "wan.t2v-low-lora",
+    "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+    "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+    "source_path": "split_files/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_low_noise.safetensors",
+    "target_path": "models/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_low_noise.safetensors",
+    "size": 1226977424,
+    "sha256": "ec95216e614b3c132c11bfb387b11feedf62163150ccc9068bca8a189771e75a",
+    "license": "apache-2.0",
+    "required_when": "Wan t2v only; not needed for i2v."
+  },
+  {
+    "slot": "wan.text-encoder",
+    "source_repo": "Comfy-Org/Wan_2.1_ComfyUI_repackaged",
+    "source_revision": "617a7633e636506f850e043bc4605f290a466a8e",
+    "source_path": "split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors",
+    "target_path": "models/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors",
+    "size": 6735906897,
+    "sha256": "c3355d30191f1f066b26d93fba017ae9809dce6c627dda5f6a66eaa651204f68",
+    "license": "apache-2.0",
+    "required_when": "All i2v, t2v modes using this default slot."
+  },
+  {
+    "slot": "wan.vae",
+    "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+    "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+    "source_path": "split_files/vae/wan_2.1_vae.safetensors",
+    "target_path": "models/vae/wan_2.1_vae.safetensors",
+    "size": 253815318,
+    "sha256": "2fc39d31359a4b0a64f55876d8ff7fa8d780956ae2cb13463b0223e15148976b",
+    "license": "apache-2.0",
+    "required_when": "All i2v, t2v modes using this default slot."
+  }
+]

README.md

@@ -0,0 +1,12 @@
+---
+tags:
+- runtime
+---
+# Video Karma
+
+画像・テキストから動画。
+
+Runtime assets use neutral filenames. This is an application package; underlying components retain their original licenses and authorship.
+
+[Licenses and attribution](ATTRIBUTION.md)
+

RUNTIME_RELEASE.json

@@ -0,0 +1,5 @@
+{
+  "created_at": "2026-09-25T08:07:46.715516+00:00",
+  "base_revision": "895a58aeafc117510eca41e4484ea75450e74a40",
+  "purpose": "Fresh deployment of Seisui release using verified WAN endpoint configuration"
+}

RUNTIME_SOURCES.json

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+{
+  "base_image_digest": "sha256:38e06c231c5dd608058db20fb3d8d6755ca4e23a6cced6fc5211a22dbfc575c2",
+  "custom_nodes": {
+    "hf_bernini": {
+      "source": "custom_nodes/hf_bernini/__init__.py",
+      "purpose": "Bundled color and first-frame blend nodes"
+    },
+    "hf_ltx_extensions": {
+      "source": "https://github.com/TenStrip/10S-Comfy-nodes",
+      "local_source": "msr_v4_inspect/custom_nodes/10S-Comfy-nodes",
+      "version": "1.9.2",
+      "license": "MIT as declared by upstream pyproject.toml",
+      "selection": [
+        "stg_guider.py",
+        "lora_stack_av.py",
+        "ltx_reference_enable.py",
+        "ltx_reference_conditioning.py"
+      ]
+    },
+    "hf_mx": {
+      "source": "https://github.com/Smirnov75/ComfyUI-mxToolkit",
+      "version": "0.9.92",
+      "license": "GPL-3.0; original LICENSE included",
+      "selection": [
+        "mxtoolkit.py"
+      ],
+      "export": "mxSlider"
+    },
+    "hf_failsafe_translate": {
+      "source": "https://github.com/ah-kun/ComfyUI-FailSafe-Translate-Node",
+      "revision": "b0b901a926f561176776c29ac8bfe0b4d3acaf03"
+    },
+    "hf_nvidia_rtx": {
+      "source": "https://github.com/Comfy-Org/Nvidia_RTX_Nodes_ComfyUI",
+      "revision": "892515e3eb9a4920a131a502a047e47adca9eb0d"
+    }
+  },
+  "runtime_wheels": [
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+      "filename": "deep_translator-1.11.4-py3-none-any.whl",
+      "size": 42285,
+      "sha256": "d635df037e23fa35d12fd42dab72a0b55c9dd19e6292009ee7207e3f30b9e60a"
+    },
+    {
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+      "size": 597321055,
+      "sha256": "e51d9e6faa68466e45b83be7928321af4b0c561c7c5536a8cb2b7e6aba25f905"
+    }
+  ],
+  "code_sha256": {
+    "custom_nodes/hf_bernini/__init__.py": "645d6b38a275782e9cf770d1f1978ae261bc46317ed562171686440a858f9c82",
+    "custom_nodes/hf_failsafe_translate/failsafe_translate_node.py": "b2aa0e3dde7d8e1ecdf13caedadbdffafa8381bc4d543b4937548198ffc75a20",
+    "custom_nodes/hf_failsafe_translate/test_node.py": "a2ac4002ce078a6495aa247527703f0c76f616da6ca5275d5be6b86fdfebd6d6",
+    "custom_nodes/hf_failsafe_translate/__init__.py": "9d216c7f27fdcd2855eef2161afcb24731321fa020f4bed60c9536c3bbdfecf7",
+    "custom_nodes/hf_ltx_extensions/lora_stack_av.py": "401e93c32665b6057e2318a7920a4cea0e4bad381a254f8b4483867fcede965b",
+    "custom_nodes/hf_ltx_extensions/ltx_reference_conditioning.py": "81e5c61f6854da1857ff28ff884fd1d1714a587e138a6abac95fae583e0e8143",
+    "custom_nodes/hf_ltx_extensions/ltx_reference_enable.py": "ce40f0abe51fae12ed21800a777141b1550f81f3de4c094d4d7d6205204e27f1",
+    "custom_nodes/hf_ltx_extensions/stg_guider.py": "475ff841c3d6e139e6dc5483333b549a8f3b1578b53f157fb4c8e9bb340342ff",
+    "custom_nodes/hf_ltx_extensions/__init__.py": "1fa32bdde6d5a9704688a9e0c7838cdcbe2ea7d259d6a72a55c6e98468d7b620",
+    "custom_nodes/hf_mx/mxtoolkit.py": "4167ce23fed719f651618965e0d2af094b2b7c0b7efef77bf1168a5d55c2deb2",
+    "custom_nodes/hf_mx/__init__.py": "976b2b972fe79ee1464504a3509108f0e9f289d119d10d70b1327bd704e41f1d",
+    "custom_nodes/hf_nvidia_rtx/__init__.py": "185aa7648151904a1741237f54a186bd19647172d78cdfe4e598aef726314252"
+  }
+}

SUPPORT_SOURCES.json

@@ -0,0 +1,31 @@
+{
+  "repo": "jmpplbp/VideoKarma1",
+  "files": [],
+  "upstream_documents": [
+    {
+      "source_repo": "Comfy-Org/Wan_2.1_ComfyUI_repackaged",
+      "source_revision": "617a7633e636506f850e043bc4605f290a466a8e",
+      "source_path": "README.md",
+      "target_path": "upstream/Comfy-Org--Wan_2.1_ComfyUI_repackaged/617a7633e636506f850e043bc4605f290a466a8e/README.md",
+      "sha256": "56072c73cfd706f1160a400aac8820ab95ff3976e4ded03ffc3a5481fcb214bc",
+      "size": 3724
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+    {
+      "source_repo": "Comfy-Org/Wan_2.2_ComfyUI_Repackaged",
+      "source_revision": "c4f60d30c55a624e35427060fdd217579a6c1d77",
+      "source_path": "README.md",
+      "target_path": "upstream/Comfy-Org--Wan_2.2_ComfyUI_Repackaged/c4f60d30c55a624e35427060fdd217579a6c1d77/README.md",
+      "sha256": "65f2895855c8906a2dc6e73489282a174aacf4fbc1780b7bf01f6d5df95d5c6f",
+      "size": 4546
+    },
+    {
+      "source_repo": "SquishedSquirrel/Wan2.2EV",
+      "source_revision": "46c390c08b58861a20effc0425d0284de2d665f9",
+      "source_path": "README.md",
+      "target_path": "upstream/SquishedSquirrel--Wan2.2EV/46c390c08b58861a20effc0425d0284de2d665f9/README.md",
+      "sha256": "4e36442f45d0442052b8b92d8790265fe55e941b38d047f623b256d09a107a0d",
+      "size": 64
+    }
+  ],
+  "existing_models_preserved": true
+}

app-runtime.json

@@ -0,0 +1,45 @@
+{
+  "runtime": "hf-html-v1",
+  "backend": "python",
+  "engine": "comfyui",
+  "models": {
+    "diffusion_models": [
+      "models/diffusion_models/denoiser-01.safetensors",
+      "models/diffusion_models/denoiser-02.safetensors",
+      "models/diffusion_models/denoiser-03.safetensors",
+      "models/diffusion_models/denoiser-04.safetensors"
+    ],
+    "loras": [
+      "models/loras/adapter-01.safetensors",
+      "models/loras/adapter-02.safetensors",
+      "models/loras/adapter-03.safetensors",
+      "models/loras/adapter-04.safetensors",
+      "models/loras/a-high.safetensors",
+      "models/loras/a-low.safetensors",
+      "models/loras/b-high.safetensors",
+      "models/loras/b-low.safetensors",
+      "models/loras/c-high.safetensors",
+      "models/loras/c-low.safetensors",
+      "models/loras/d-high.safetensors",
+      "models/loras/d-low.safetensors",
+      "models/loras/e-high.safetensors",
+      "models/loras/e-low.safetensors",
+      "models/loras/f-high.safetensors",
+      "models/loras/f-low.safetensors",
+      "models/loras/g-high.safetensors",
+      "models/loras/g-low.safetensors",
+      "models/loras/h-high.safetensors",
+      "models/loras/h-low.safetensors",
+      "models/loras/i-high.safetensors",
+      "models/loras/i-low.safetensors",
+      "models/loras/j-high.safetensors",
+      "models/loras/j-low.safetensors"
+    ],
+    "text_encoders": [
+      "models/text_encoders/encoder-01.safetensors"
+    ],
+    "vae": [
+      "models/vae/decoder-01.safetensors"
+    ]
+  }
+}

app.js

@@ -0,0 +1,4 @@
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\u30C8\u30FC\u30AF\u30F3",d()):(T("#token-usage").textContent="\u6D88\u8CBB\u30C8\u30FC\u30AF\u30F3\u3092\u7CBE\u7B97\u4E2D\u2026",t.getUsage&&f<20&&(l=setTimeout(()=>{t.getUsage(r.jobId).then(y=>_(y,f+1)).catch(()=>{T("#token-usage").textContent="\u7CBE\u7B97\u7D50\u679C\u3092\u78BA\u8A8D\u3067\u304D\u307E\u305B\u3093\u3002\u518D\u8868\u793A\u3057\u3066\u78BA\u8A8D\u3057\u3066\u304F\u3060\u3055\u3044\u3002"})},3e3)))};t.onUsage?.(r=>_(r)),d(),t.onGenerate(Nt),t.onResult(Ot),t.onStatus(r=>{le(["collecting","preparing_input","uploading","starting","queued","running"].includes(r.phase)),T("#app-execute").disabled=!r.canRun,a.disabled=!r.canRun,!r.canRun&&e.open&&e.close(),W(r.message,r.phase==="failed");let f=T("#transfer-progress");f.hidden=!r.progress,r.progress&&(f.max=r.progress.totalBytes||1,f.value=r.progress.bytes||0)}),T("#app-execute").onclick=()=>{e.open||e.showModal()},a.onclick=()=>{a.disabled||!e.open||(e.close(),le(!0),T("#token-usage").textContent="",t.run().catch(r=>W(r.message,!0)).finally(()=>{le(!1),d()}))}}else W("\u3053\u306Eindex.html\u306FGPU App\u304B\u3089\u958B\u304F\u3068\u5B9F\u884C\u3067\u304D\u307E\u3059\u3002");})();
+
+;/* media selection removal */
+(()=>{var c=new WeakMap;function u(e){if(c.has(e))return;let n=document.createElement("div");n.className="media-clear-actions",e.insertAdjacentElement("afterend",n);let t=()=>{n.replaceChildren();let r=Array.from(e.files||[]);n.hidden=r.length===0,r.forEach((s,b)=>{let d=document.createElement("div");d.className="media-clear-row";let l=document.createElement("span");l.textContent=s.name;let a=document.createElement("button");a.type="button",a.className="media-clear-button",a.textContent="\xD7",a.title="\u7D20\u6750\u3092\u89E3\u9664",a.setAttribute("aria-label",s.name+"\u3092\u89E3\u9664"),a.disabled=e.disabled,a.addEventListener("click",()=>{if(e.disabled)return;let m=Array.from(e.files||[]).filter((i,o)=>o!==b);if(m.length){let i=new DataTransfer;m.forEach(o=>i.items.add(o)),e.files=i.files}else e.value="";e.setCustomValidity(""),e.dispatchEvent(new Event("change",{bubbles:!0})),t(),(n.querySelector("button")||e).focus()}),d.append(l,a),n.append(d)})};c.set(e,t),e.addEventListener("change",()=>queueMicrotask(t)),t()}function f(){if(document.getElementById("media-clear-style"))return;let e=document.createElement("style");e.id="media-clear-style",e.textContent=".media-clear-actions{display:grid;gap:6px;min-width:0;margin-top:6px}.media-clear-actions[hidden]{display:none!important}.media-clear-row{display:flex;align-items:center;gap:8px;min-width:0}.media-clear-row>span{flex:1;min-width:0;overflow-wrap:anywhere;font-size:12px;color:var(--muted,#63776a)}button.media-clear-button{flex:none;width:36px;min-width:36px;height:36px;min-height:36px;margin:0;padding:0;display:inline-flex;align-items:center;justify-content:center;border:1px solid #bed0c4;border-radius:8px;background:#fff;color:#245b43;font:24px/1 system-ui;cursor:pointer}button.media-clear-button:hover{background:#edf4ef}button.media-clear-button:disabled{opacity:.45;cursor:default}",document.head.append(e);let n=t=>{(t instanceof Element||t instanceof Document)&&(t instanceof HTMLInputElement&&t.type==="file"&&u(t),t.querySelectorAll('input[type="file"]').forEach(u))};n(document),new MutationObserver(t=>{for(let r of t)r.type==="attributes"?c.get(r.target)?.():r.addedNodes.forEach(n)}).observe(document.body,{childList:!0,subtree:!0,attributes:!0,attributeFilter:["disabled"]})}document.readyState==="loading"?document.addEventListener("DOMContentLoaded",f,{once:!0}):f();})();

bernini_continuation.py

@@ -0,0 +1,143 @@
+from __future__ import annotations
+
+import base64
+import re
+import subprocess
+import tempfile
+from pathlib import Path
+from typing import Any
+
+
+_DEADLINE = None
+
+VIDEO_SUFFIXES = {'.mp4', '.mov', '.mkv', '.webm', '.avi', '.m4v'}
+
+
+def _safe_name(value: object, fallback: str) -> str:
+    name = str(value or fallback).replace('\\', '/').split('/')[-1]
+    name = re.sub(r'[^A-Za-z0-9._-]+', '_', name).strip('._')
+    return (name or fallback)[:160]
+
+
+def _decode(value: object, label: str) -> bytes:
+    encoded = str(value or '').strip()
+    if encoded.startswith('data:') and ',' in encoded:
+        encoded = encoded.split(',', 1)[1]
+    encoded = re.sub(r'\s+', '', encoded).replace('-', '+').replace('_', '/')
+    encoded += '=' * ((4 - len(encoded) % 4) % 4)
+    try:
+        data = base64.b64decode(encoded, validate=True)
+    except Exception as exc:
+        raise ValueError(f'{label} is not valid base64') from exc
+    if not data:
+        raise ValueError(f'{label} is empty')
+    return data
+
+
+def _run(command: list[str], label: str, timeout: int) -> None:
+    if _DEADLINE is not None: timeout = _DEADLINE.remaining(timeout)
+    completed = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, timeout=timeout, check=False)
+    if completed.returncode:
+        detail = (completed.stderr or completed.stdout or '').strip()[-2000:]
+        raise RuntimeError(f'{label} failed: {detail}')
+
+
+def validate_continuation(value: object) -> dict[str, Any] | None:
+    if value is None or value is False:
+        return None
+    if not isinstance(value, dict):
+        raise ValueError('continuation must be an object')
+    if value.get('enabled') is False:
+        return None
+    source_name = _safe_name(value.get('source_video_name'), 'bernini_source_video.mp4')
+    frame_name = _safe_name(value.get('last_frame_name'), 'bernini_continuation_last_frame.png')
+    if Path(source_name).suffix.lower() not in VIDEO_SUFFIXES:
+        raise ValueError('continuation source must be a video file')
+    if Path(frame_name).suffix.lower() != '.png':
+        raise ValueError('continuation last frame must be a PNG file')
+    try:
+        width = int(value.get('width'))
+        height = int(value.get('height'))
+        fps = int(value.get('fps', 20))
+        drop = int(value.get('drop_generated_frames', 2))
+        target_value = value.get('target_duration_seconds')
+        target_duration = float(target_value) if target_value is not None else None
+    except (TypeError, ValueError) as exc:
+        raise ValueError('invalid continuation settings') from exc
+    if not 256 <= width <= 2048 or not 256 <= height <= 2048 or width % 2 or height % 2:
+        raise ValueError('invalid continuation dimensions')
+    if not 1 <= fps <= 60 or not 1 <= drop <= 10:
+        raise ValueError('invalid continuation frame settings')
+    if target_duration is not None and not 1 <= target_duration <= 3600:
+        raise ValueError('invalid continuation target duration')
+    return {'source_video_name': source_name, 'last_frame_name': frame_name, 'width': width, 'height': height, 'fps': fps, 'drop_generated_frames': drop, 'target_duration_seconds': target_duration}
+
+
+def prepare_continuation_assets(payload: dict[str, Any]) -> dict[str, Any] | None:
+    config = validate_continuation(payload.get('continuation'))
+    if config is None:
+        return None
+    assets = payload.get('assets')
+    if not isinstance(assets, list):
+        raise ValueError('continuation assets are missing')
+    source = next((item for item in assets if isinstance(item, dict) and item.get('name') == config['source_video_name']), None)
+    if source is None:
+        raise ValueError('continuation source video was not supplied')
+    source_bytes = _decode(source.get('data'), config['source_video_name'])
+    suffix = Path(config['source_video_name']).suffix.lower()
+    with tempfile.TemporaryDirectory(prefix='video-continuation-frame-') as temp_dir:
+        root = Path(temp_dir)
+        source_path = root / ('source' + suffix)
+        output_path = root / config['last_frame_name']
+        source_path.write_bytes(source_bytes)
+        resize = f"scale={config['width']}:{config['height']}:force_original_aspect_ratio=decrease,pad={config['width']}:{config['height']}:(ow-iw)/2:(oh-ih)/2:color=black,setsar=1"
+        errors = []
+        for offset in ('-0.1', '-0.5', '-1.0'):
+            output_path.unlink(missing_ok=True)
+            try:
+                _run(
+                    ['ffmpeg', '-hide_banner', '-loglevel', 'error', '-y', '-sseof', offset,
+                     '-i', str(source_path), '-map', '0:v:0', '-an', '-frames:v', '1',
+                     '-vf', resize, str(output_path)],
+                    'continuation last-frame extraction', 300,
+                )
+            except (RuntimeError, subprocess.TimeoutExpired) as exc:
+                errors.append(str(exc))
+            if output_path.is_file() and output_path.stat().st_size > 0:
+                break
+        else:
+            output_path.unlink(missing_ok=True)
+            try:
+                _run(
+                    ['ffmpeg', '-hide_banner', '-loglevel', 'error', '-y', '-i', str(source_path),
+                     '-map', '0:v:0', '-an', '-vf', resize, '-fps_mode', 'passthrough',
+                     '-update', '1', str(output_path)],
+                    'continuation full-decode fallback', 3600,
+                )
+            except (RuntimeError, subprocess.TimeoutExpired) as exc:
+                errors.append(str(exc))
+        if not output_path.is_file() or output_path.stat().st_size <= 0:
+            raise RuntimeError('continuation last-frame extraction produced no image: ' + '; '.join(errors)[-2000:])
+        assets.append({'name': config['last_frame_name'], 'data': base64.b64encode(output_path.read_bytes()).decode('ascii')})
+    return config
+
+
+def merge_continuation_output(source_path: Path, generated_path: Path, output_path: Path, config: dict[str, Any]) -> None:
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    resize = f"scale={config['width']}:{config['height']}:force_original_aspect_ratio=decrease,pad={config['width']}:{config['height']}:(ow-iw)/2:(oh-ih)/2:color=black,setsar=1,format=yuv420p"
+    filters = (
+        f"[0:v]fps={config['fps']},{resize},setpts=PTS-STARTPTS[source];"
+        f"[1:v]fps={config['fps']},{resize},trim=start_frame={config['drop_generated_frames']},setpts=PTS-STARTPTS[generated];"
+        '[source][generated]concat=n=2:v=1:a=0[video]'
+    )
+    partial = output_path.with_suffix(output_path.suffix + '.part.mp4')
+    _run([
+        'ffmpeg', '-hide_banner', '-loglevel', 'error', '-y', '-i', str(source_path), '-i', str(generated_path),
+        '-filter_complex', filters, '-map', '[video]', '-map', '0:a?', '-c:v', 'libx264', '-preset', 'fast',
+        '-crf', '16', '-pix_fmt', 'yuv420p', '-c:a', 'aac', '-b:a', '192k',
+        *(['-t', str(config['target_duration_seconds'])] if config['target_duration_seconds'] is not None else []),
+        '-movflags', '+faststart', str(partial),
+    ], 'continuation video merge', 3600)
+    if not partial.is_file() or partial.stat().st_size <= 0:
+        raise RuntimeError('continuation merge produced no video')
+    partial.replace(output_path)

catalog_boot.py

@@ -0,0 +1,76 @@
+"""Start Comfy with HF-provided custom nodes while leaving the image unchanged."""
+import atexit,json,os,subprocess,sys,time,urllib.request
+from pathlib import Path
+PROCESS=None
+
+def stop():
+    global PROCESS
+    if PROCESS and PROCESS.poll() is None:
+        PROCESS.terminate()
+        try:PROCESS.wait(timeout=3)
+        except subprocess.TimeoutExpired:PROCESS.kill()
+    PROCESS=None
+
+def extra_paths(root):
+    paths={'base_path':str(root),'is_default':True}
+    if (root/'custom_nodes').is_dir():paths['custom_nodes']='custom_nodes'
+    if (root/'models').is_dir():
+        for folder in (root/'models').iterdir():
+            if folder.is_dir() and folder.name.replace('_','').isalnum():paths[folder.name]='models/'+folder.name
+    return paths
+
+def initialize():
+    global PROCESS
+    value=os.environ.get('HF_APP_ROOT')
+    if not value:return
+    startup_deadline=time.monotonic()+220
+    root=Path(value);config=json.loads((root/'app-runtime.json').read_text(encoding='utf-8-sig'))
+    if config.get('engine')!='comfyui':return
+    if config.get('backend')!='python':raise ValueError('HF custom-node startup requires backend python / engine comfyui')
+    work=Path('/workspace/hf-app');user=work/'comfy-user';user.mkdir(parents=True,exist_ok=True)
+    extra=work/'hf-extra-paths.yaml'
+    wheels=sorted((root/'runtime_wheels').glob('*.whl'))
+    packages=work/'python-deps'
+    if wheels:
+        stamp=json.dumps([(wheel.name,wheel.stat().st_size) for wheel in wheels])
+        marker=packages/'.installed-wheels.json'
+        if not marker.is_file() or marker.read_text()!=stamp:
+            subprocess.run(['/opt/venv/bin/python','-m','pip','install','--disable-pip-version-check','--no-deps','--no-index','--no-compile','--target',str(packages),*[str(wheel) for wheel in wheels]],check=True,timeout=120)
+            marker.write_text(stamp)
+        sys.path.insert(0,str(packages))
+        os.environ['PYTHONPATH']=str(packages)+os.pathsep+os.environ.get('PYTHONPATH','')
+    # JSON is a valid YAML document and avoids path quoting ambiguities.
+    paths=extra_paths(root)
+    mappings={'hf_app':paths}
+    if (root/'auxiliary'/'pose').is_dir():
+        os.environ['AUX_ANNOTATOR_CKPTS_PATH']=str(root/'auxiliary'/'pose')
+        os.environ['AUX_USE_SYMLINKS']='False'
+        os.environ['AUX_TEMP_DIR']=str(work/'aux-temp')
+
+    extra.write_text(json.dumps(mappings))
+    entrypoints=[p for p in Path('/opt').glob('*/comfy_main_with_shared_models.py') if p.is_file()]
+    if len(entrypoints)!=1:raise RuntimeError('Expected one installed runtime entrypoint')
+    arguments=['/opt/venv/bin/python','-u',str(entrypoints[0]),
+        '--listen','127.0.0.1','--port','8188','--disable-auto-launch','--disable-metadata',
+        '--disable-api-nodes','--log-stdout','--enable-dynamic-vram','--reserve-vram','1',
+        '--use-sage-attention','--async-offload','2','--preview-method','none',
+        '--enable-triton-backend','--fast','fp16_accumulation',
+        '--input-directory','/comfyui/input','--output-directory','/comfyui/output',
+        '--temp-directory','/comfyui/temp','--user-directory',str(user),
+        '--database-url','sqlite:////workspace/hf-app/comfy-user/comfyui.db','--extra-model-paths-config',str(extra)]
+    PROCESS=subprocess.Popen(arguments,cwd='/comfyui')
+    # Keep the enclosing v53 child ready/cleanup checks pointed at the real Comfy process.
+    main=sys.modules.get('__main__')
+    if main and hasattr(main,'COMFY'):main.COMFY=PROCESS
+    deadline=min(startup_deadline,time.monotonic()+180)
+    while time.monotonic()<deadline:
+        if PROCESS.poll() is not None:raise RuntimeError('ComfyUI exited while loading HF runtime extensions')
+        try:
+            with urllib.request.urlopen('http://127.0.0.1:8188/system_stats',timeout=2) as response:
+                if response.status==200:
+                    print('HF_CATALOG_COMFY_READY',flush=True);return
+        except Exception:pass
+        time.sleep(.5)
+    stop();raise TimeoutError('HF Comfy runtime did not become ready within180seconds')
+
+atexit.register(stop)

catalog_runtime.py

@@ -0,0 +1,575 @@
+"""Generic ComfyUI/Irodori app backend supplied by the HF repository.
+
+The fixed v53 image executes this code as uid10001. HTML is hosted separately.
+Only a job-scoped Cloudflare capability is received; no provider keys are needed.
+"""
+from __future__ import annotations
+import base64,hashlib,json,math,mimetypes,os,re,shutil,subprocess,sys,time,urllib.error,urllib.parse,urllib.request,uuid
+from pathlib import Path
+
+TRUSTED_ORIGIN=os.environ['APP_SERVICE_ORIGIN']
+USER_AGENT='app-HF/1.0'
+INPUT_ROOT=Path('/comfyui/input')
+OUTPUT_ROOT=Path('/comfyui/output')
+TEMP_ROOT=Path('/comfyui/temp')
+CHUNK_BYTES=8*1024*1024
+MAX_ARTIFACT=512*1024*1024
+MAX_TOTAL=2*1024*1024*1024
+MAX_FILES=16
+MEDIA_MARKERS=('loadimage','loadvideo','loadaudio')
+MEDIA_KEYS={'image','images','imagefile','imagepath','video','videos','videofile','videopath','audio','audiofile','audiopath','file','filename','path','filepath','directory','folder','url','uri'}
+MODEL_KEYS={'ckpt_name','unet_name','lora_name','vae_name','clip_name','clip_name1','clip_name2','clip_name3','clip_name4','control_net_name','model_name','text_encoder','text_encoder_name','tiny_vae','mmaudio_model','clip_model','vae_model','synchformer_model'}
+DENIED_MARKERS={'python','shell','terminal','subprocess','executecommand','systemcommand','commandline','comfyinstall','comfymanager'}
+MIMES={'.mp4':'video/mp4','.webm':'video/webm','.mov':'video/quicktime','.mkv':'video/x-matroska','.avi':'video/x-msvideo','.m4v':'video/mp4','.wav':'audio/wav','.flac':'audio/flac','.mp3':'audio/mpeg','.ogg':'audio/ogg','.opus':'audio/ogg','.m4a':'audio/mp4','.png':'image/png','.jpg':'image/jpeg','.jpeg':'image/jpeg','.webp':'image/webp','.gif':'image/gif','.avif':'image/avif'}
+
+class Deadline:
+    def __init__(self,seconds=280):self.end=time.monotonic()+seconds
+    def remaining(self,limit=None):
+        remaining=self.end-time.monotonic()
+        if remaining<=0:raise TimeoutError('Generation and artifact transfer exceeded the 280-second app limit')
+        return min(remaining,limit) if limit is not None else remaining
+
+class NoRedirect(urllib.request.HTTPRedirectHandler):
+    def redirect_request(self,*args,**kwargs):raise ValueError('Media service redirects are not accepted')
+
+def trusted_url(value):
+    if not isinstance(value,str) or len(value)>4096:raise ValueError('Invalid media service URL')
+    parsed=urllib.parse.urlsplit(value)
+    if parsed.scheme!='https' or parsed.netloc!=urllib.parse.urlsplit(TRUSTED_ORIGIN).netloc or parsed.username or parsed.password or parsed.fragment:
+        raise ValueError('Media URL must use the trusted Cloudflare service origin')
+    return value
+
+def set_read_timeout(response,deadline):
+    remaining=deadline.remaining(25)
+    # urllib's read timeout is otherwise reset per read, allowing a slow peer to
+    # retain the original timeout after the overall job budget has elapsed.
+    sock=getattr(getattr(getattr(response,'fp',None),'raw',None),'_sock',None)
+    if sock is not None:sock.settimeout(remaining)
+
+def service_error(label,error,deadline):
+    details=['HTTP '+str(error.code)]
+    # Never reflect capability URLs, HTML, echoed request data, or credentials.
+    try:
+        set_read_timeout(error,deadline)
+        snippet=error.read(8192).decode('utf-8',errors='replace')
+        match=re.search(r'(?:error[ _-]*code|cloudflare[ _-]*error)\s*[:=]\s*["\']?(1[0-9]{3})\b',snippet,re.I)
+        if match:details.append('Cloudflare '+match.group(1))
+        if error.headers.get('cf-mitigated')=='challenge':details.append('Cloudflare challenge')
+        ray=error.headers.get('cf-ray','')
+        if re.fullmatch(r'[0-9a-fA-F]{8,32}-[A-Z]{3}',ray):details.append('Ray '+ray)
+    except Exception:pass
+    return RuntimeError(label+' ('+', '.join(details)+')')
+
+def trusted_network_test(url,deadline):
+    trusted_url(url)
+    request=urllib.request.Request(url,headers={'User-Agent':USER_AGENT,'Range':'bytes=0-0','Accept':'application/octet-stream'})
+    try:
+        with urllib.request.build_opener(NoRedirect()).open(request,timeout=deadline.remaining(25)) as response:
+            set_read_timeout(response,deadline);received=len(response.read(1))
+            return {'status':response.status,'sample_bytes':received,'content_type':response.headers.get('Content-Type'),'content_length':response.headers.get('Content-Length'),'cache_status':response.headers.get('CF-Cache-Status')}
+    except urllib.error.HTTPError as error:raise service_error('Network diagnostic failed',error,deadline) from None
+    except urllib.error.URLError:raise RuntimeError('Network diagnostic connection failed') from None
+
+def request_json(url,method,body,deadline,headers=None):
+    trusted_url(url)
+    raw=body if isinstance(body,bytes) else json.dumps(body,separators=(',',':'),allow_nan=False).encode()
+    actual={'User-Agent':USER_AGENT,'Content-Type':'application/octet-stream' if isinstance(body,bytes) else 'application/json',**(headers or {})}
+    req=urllib.request.Request(url,data=raw,method=method,headers=actual)
+    try:
+        with urllib.request.build_opener(NoRedirect()).open(req,timeout=deadline.remaining(25)) as response:
+            set_read_timeout(response,deadline)
+            encoded=response.read(65537)
+            if len(encoded)>65536:raise ValueError('Media service JSON response is too large')
+            result=json.loads(encoded)
+            if not isinstance(result,dict):raise ValueError('Invalid media service response')
+            return result
+    except urllib.error.HTTPError as error:
+        # Capability URLs must never appear in error messages returned to the user.
+        raise service_error('Media service request failed',error,deadline) from None
+    except urllib.error.URLError as error:
+        raise RuntimeError('Media service connection failed: '+str(type(error.reason).__name__)) from None
+
+def relative_name(value):
+    return isinstance(value,str) and bool(value) and len(value)<=512 and not value.startswith('/') and '\\' not in value and ':' not in value and not any(part in ('','..','.') for part in value.split('/')) and '\x00' not in value
+
+def reference_name(value):
+    if not isinstance(value,str):return None
+    if value.startswith('input/'):value=value[6:]
+    if value.endswith(' [input]'):value=value[:-8]
+    return value if relative_name(value) else None
+
+def safe_cache_path(root,value,directory=False):
+    if not relative_name(value):raise ValueError('Invalid cached model path')
+    source=Path(root)/value
+    # Native HF snapshot files are symlinks into this repository's blob directory.
+    resolved=source.resolve();repo=Path(root).parent.parent.resolve()
+    if not (resolved.is_relative_to(Path(root).resolve()) or resolved.is_relative_to(repo)):
+        raise ValueError('Cached model escaped its repository')
+    if not (source.is_dir() if directory else source.is_file()):raise ValueError('Required file is missing from the native HF cache: '+value)
+    return source
+
+def prepare_files(files,job,deadline):
+    if files is None:files=[]
+    if not isinstance(files,list) or len(files)>20:raise ValueError('files must contain at most20 items')
+    directory=INPUT_ROOT/'hf-jobs'/job
+    directory.mkdir(parents=True,exist_ok=False)
+    references={};total=0
+    try:
+        for item in files:
+            deadline.remaining()
+            if not isinstance(item,dict):raise ValueError('Invalid input file')
+            name=item.get('name')
+            if not isinstance(name,str) or not re.fullmatch(r'[A-Za-z0-9][A-Za-z0-9._-]{0,159}',name) or name in references:
+                raise ValueError('Input file names must be unique safe basenames')
+            if Path(name).suffix.lower() not in MIMES:raise ValueError('Unsupported input media extension: '+name)
+            expected=item.get('size');expected_hash=item.get('sha256')
+            if expected is not None and (isinstance(expected,bool) or not isinstance(expected,int) or expected<1 or expected>MAX_ARTIFACT):
+                raise ValueError('Input file size is invalid or exceeds512MiB')
+            if expected_hash is not None and not re.fullmatch(r'[a-f0-9]{64}',str(expected_hash)):
+                raise ValueError('Input SHA256 must be lowercase hexadecimal')
+            target=directory/(uuid.uuid4().hex+Path(name).suffix.lower())
+            digest=hashlib.sha256();size=0
+            with target.open('xb') as out:
+                if item.get('url'):
+                    trusted_url(item['url'])
+                    if expected is None or expected_hash is None:raise ValueError('Staged inputs require size and sha256')
+                    try:
+                        request=urllib.request.Request(item['url'],headers={'User-Agent':USER_AGENT,'Accept':'application/octet-stream'})
+                        response=urllib.request.build_opener(NoRedirect()).open(request,timeout=deadline.remaining(25))
+                    except urllib.error.HTTPError as error:raise service_error('Input media download failed',error,deadline) from None
+                    except urllib.error.URLError as error:raise RuntimeError('Input media download connection failed') from None
+                    with response:
+                        while True:
+                            deadline.remaining()
+                            set_read_timeout(response,deadline)
+                            chunk=response.read(256*1024)
+                            if not chunk:break
+                            size+=len(chunk);total+=len(chunk)
+                            if size>expected or size>MAX_ARTIFACT or total>MAX_TOTAL:raise ValueError('Input media size exceeds declared or job limits')
+                            digest.update(chunk);out.write(chunk)
+                elif isinstance(item.get('data'),str):
+                    encoded=item['data'].split(',',1)[-1]
+                    if len(encoded)>768*1024:raise ValueError('Inline media is too large; stage it through Cloudflare first')
+                    try:raw=base64.b64decode(encoded,validate=True)
+                    except ValueError:raise ValueError('Invalid input base64') from None
+                    size=len(raw);total+=size;digest.update(raw);out.write(raw)
+                else:raise ValueError('Input media requires a staged URL')
+            if not size or (expected is not None and size!=expected):raise ValueError('Input media size does not match its manifest')
+            if expected_hash is not None and digest.hexdigest()!=expected_hash:raise ValueError('Input media SHA256 does not match its manifest')
+            references[name]=target.relative_to(INPUT_ROOT).as_posix()
+        return references,directory
+    except BaseException:
+        shutil.rmtree(directory,ignore_errors=True)
+        raise
+
+def normalize_and_validate(workflow,object_info,references,job):
+    if not isinstance(workflow,dict) or not workflow or len(workflow)>512:raise ValueError('workflow must be a non-empty API graph with at most512 nodes')
+    workflow=json.loads(json.dumps(workflow,allow_nan=False))
+    for node_id,node in workflow.items():
+        if not isinstance(node_id,str) or not re.fullmatch(r'[A-Za-z0-9_-]{1,80}',node_id):raise ValueError('Invalid workflow node ID')
+        if not isinstance(node,dict) or not isinstance(node.get('inputs'),dict):raise ValueError('Invalid workflow node: '+node_id)
+        node_type=node.get('class_type')
+        if not isinstance(node_type,str) or node_type not in object_info:raise ValueError('Node type is not installed: '+str(node_type))
+        normalized=re.sub('[^a-z0-9]','',node_type.lower())
+        if any(marker in normalized for marker in DENIED_MARKERS):raise ValueError('This node cannot run in the shared runtime: '+node_type)
+        definitions=object_info[node_type].get('input',{})
+        definitions={**definitions.get('required',{}),**definitions.get('optional',{})}
+        if object_info[node_type].get('output_node') and 'filename_prefix' in definitions and 'filename_prefix' not in node['inputs']:
+            node['inputs']['filename_prefix']='output'
+        for key,value in list(node['inputs'].items()):
+            lower=str(key).lower()
+            if isinstance(value,str) and len(value)>20000:raise ValueError('Workflow text is too long')
+            if isinstance(value,list) and len(value)==2 and isinstance(value[0],str) and isinstance(value[1],int):
+                if value[0] not in workflow or not 0<=value[1]<=128:raise ValueError('Broken workflow link in node '+node_id)
+            if isinstance(value,(int,float)) and not isinstance(value,bool):
+                if not math.isfinite(value):raise ValueError('Workflow numbers must be finite')
+                limits={'width':8192,'height':8192,'target_width':8192,'target_height':8192,'output_width':8192,'output_height':8192,
+                        'length':2000,'num_frames':2000,'frames':2000,'video_frames':2000,'frame_count':2000,
+                        'fps':240,'frame_rate':240,'steps':120,'batch':8,'batch_size':8,'batch_count':8,'duration':300,'duration_seconds':300}
+                if lower in limits and not 0<=value<=limits[lower]:raise ValueError('Workflow exceeds '+lower+' limit')
+            if (lower in MODEL_KEYS or re.fullmatch(r'lora_\d+',lower)) and isinstance(value,str) and value.lower() not in ('none','disabled'):
+                if not relative_name(value):raise ValueError('Unsafe model path in '+node_id)
+                definition=definitions.get(key)
+                options=definition[0] if isinstance(definition,list) and definition and isinstance(definition[0],list) else None
+                if options and value not in options:
+                    basename=Path(value).name
+                    matches=[option for option in options if isinstance(option,str) and Path(option).name==basename]
+                    if len(matches)==1:node['inputs'][key]=matches[0]
+                    else:raise ValueError('Model is missing from the native HF cache mapping: '+value)
+            if lower in ('filename_prefix','subfolder') and isinstance(value,str):
+                if value and not relative_name(value):raise ValueError('Unsafe output path')
+                node['inputs'][key]='hf-jobs/'+job+'/'+(value or 'output')
+            media_key=re.sub('[^a-z0-9]','',lower)
+            if any(marker in normalized for marker in MEDIA_MARKERS) and media_key in MEDIA_KEYS and isinstance(value,str):
+                source=reference_name(value)
+                if source not in references:raise ValueError('Workflow input media was not supplied by this job: '+str(source))
+                node['inputs'][key]=references[source]
+    return workflow
+
+def snapshot_outputs():
+    state={}
+    for root in (OUTPUT_ROOT,TEMP_ROOT):
+        if not root.exists():continue
+        for path in root.rglob('*'):
+            try:
+                resolved=path.resolve()
+                if path.is_file() and resolved.is_relative_to(root.resolve()):
+                    stat=path.stat();state[resolved]=(stat.st_size,stat.st_mtime_ns)
+            except OSError:pass
+    return state
+
+def output_files(history,before):
+    paths=[];owned=[];seen=set()
+    def visit(value,depth=0):
+        if depth>8:return
+        if isinstance(value,list):
+            for child in value:visit(child,depth+1)
+        elif isinstance(value,dict):
+            if isinstance(value.get('filename'),str):
+                name=value['filename'];subfolder=value.get('subfolder','');kind=value.get('type','output')
+                roots={'output':OUTPUT_ROOT,'temp':TEMP_ROOT}
+                if kind not in roots or not relative_name(name) or (subfolder and not relative_name(subfolder)):return
+                root=roots[kind].resolve();path=(root/subfolder/name).resolve()
+                if not path.is_relative_to(root) or not path.is_file() or path in seen:return
+                seen.add(path);paths.append(path)
+                stat=path.stat()
+                if before.get(path)!=(stat.st_size,stat.st_mtime_ns):owned.append(path)
+            else:
+                for child in value.values():visit(child,depth+1)
+    visit(history.get('outputs',{}))
+    if not paths:raise RuntimeError('ComfyUI completed without an image, video or audio artifact')
+    if len(paths)>MAX_FILES:raise ValueError('Workflow produced more than16 output artifacts')
+    return paths,owned
+
+def comfy_execution_ms(history):
+    """Use ComfyUI execution lifecycle timestamps; exclude input/output transfer."""
+    events={}
+    for item in (history.get('status') or {}).get('messages',[]):
+        if not isinstance(item,(list,tuple)) or len(item)!=2:continue
+        name,data=item
+        if name not in ('execution_start','execution_success') or not isinstance(data,dict):continue
+        stamp=data.get('timestamp')
+        if isinstance(stamp,(int,float)) and not isinstance(stamp,bool) and math.isfinite(stamp):events[name]=(data.get('prompt_id'),stamp)
+    start=events.get('execution_start');end=events.get('execution_success')
+    if not start or not end or not start[0] or start[0]!=end[0] or end[1]<start[1]:return None
+    return math.ceil(end[1]-start[1])
+
+
+def run_comfy(workflow,context,deadline):
+    identifier=None
+    with context.lock:
+        execution_started=time.monotonic()
+        try:
+            result=context.comfy('/prompt',{'prompt':workflow,'client_id':'hf-'+uuid.uuid4().hex})
+            identifier=result.get('prompt_id')
+            if not isinstance(identifier,str):raise RuntimeError('ComfyUI rejected the workflow: '+json.dumps(result)[:1800])
+            while True:
+                deadline.remaining(10)
+                history=context.comfy('/history/'+identifier).get(identifier)
+                if isinstance(history,dict):
+                    status=history.get('status') or {}
+                    if status.get('status_str')=='error':raise RuntimeError('ComfyUI execution failed: '+json.dumps(status.get('messages',[]))[:1800])
+                    if status.get('completed') or status.get('status_str')=='success':
+                        # Fallback measured inside the lock, before cleanup/transfer.
+                        return {**history,'_execution_ms':elapsed_ms(execution_started)}
+                time.sleep(min(.25,deadline.remaining()))
+        except (TimeoutError,KeyboardInterrupt):
+            try:context.comfy('/interrupt',{})
+            except Exception:pass
+            raise
+        except urllib.error.HTTPError as error:
+            try:message=error.read(16384).decode(errors='replace')
+            except Exception:message=''
+            raise RuntimeError('ComfyUI rejected the workflow (HTTP '+str(error.code)+'): '+message[:1800]) from None
+        finally:
+            if identifier:
+                try:context.comfy('/history',{'delete':[identifier]})
+                except Exception:pass
+
+def file_metadata(path,deadline):
+    size=path.stat().st_size
+    if not 0<size<=MAX_ARTIFACT:raise ValueError('Output artifact must be1byte..512MiB')
+    digest=hashlib.sha256()
+    with path.open('rb') as source:
+        while True:
+            deadline.remaining();chunk=source.read(CHUNK_BYTES)
+            if not chunk:break
+            digest.update(chunk)
+    return {'filename':path.name,'mime_type':MIMES.get(path.suffix.lower()) or mimetypes.guess_type(path.name)[0] or 'application/octet-stream',
+            'size':size,'sha256':digest.hexdigest()}
+
+def upload_outputs(paths,capability,deadline):
+    if len(paths)>MAX_FILES or sum(path.stat().st_size for path in paths)>MAX_TOTAL:raise ValueError('Output artifacts exceed the per-job limit')
+    if capability:
+        trusted_url(capability)
+        parsed=urllib.parse.urlsplit(capability)
+        if parsed.query or not re.fullmatch(r'/a/[A-Za-z0-9_-]{43}',parsed.path):raise ValueError('Invalid job-scoped artifact capability')
+    elif sum(path.stat().st_size for path in paths)>7*1024*1024:
+        raise ValueError('A Cloudflare artifact upload capability is required for output larger than7MiB')
+    outputs=[]
+    for path in paths:
+        metadata=file_metadata(path,deadline)
+        if not capability:
+            outputs.append({**metadata,'data':base64.b64encode(path.read_bytes()).decode()});continue
+        response=request_json(capability+'/begin','POST',metadata,deadline)
+        identifier=response.get('id')
+        if not isinstance(identifier,str) or not re.fullmatch(r'[A-Za-z0-9_-]{8,100}',identifier):raise RuntimeError('Invalid artifact upload ID')
+        parts=[]
+        with path.open('rb') as source:
+            index=0
+            while True:
+                deadline.remaining();chunk=source.read(CHUNK_BYTES)
+                if not chunk:break
+                digest=hashlib.sha256(chunk).hexdigest()
+                response=request_json(capability+'/'+identifier+'/parts/'+str(index),'PUT',chunk,deadline,{'X-Part-SHA256':digest})
+                if response.get('sha256') and response['sha256']!=digest:raise RuntimeError('Artifact part checksum mismatch')
+                parts.append({'index':index,'sha256':digest,'size':len(chunk)});index+=1
+        completed=request_json(capability+'/'+identifier+'/complete','POST',{'parts':parts,'sha256':metadata['sha256'],'size':metadata['size']},deadline)
+        url=completed.get('url');trusted_url(url)
+        if completed.get('sha256') and completed['sha256']!=metadata['sha256']:raise RuntimeError('Uploaded artifact checksum mismatch')
+        if completed.get('size') is not None and completed['size']!=metadata['size']:raise RuntimeError('Uploaded artifact size mismatch')
+        outputs.append({**metadata,'url':url,'expires_at':completed.get('expires_at')})
+    return outputs
+
+def finite_number(body,key,default,minimum,maximum,integer=False):
+    raw=body.get(key,default)
+    if isinstance(raw,bool):raise ValueError(key+' must be numeric')
+    try:value=float(raw)
+    except (TypeError,ValueError):raise ValueError(key+' must be numeric') from None
+    if not math.isfinite(value) or not minimum<=value<=maximum or (integer and value!=int(value)):
+        raise ValueError(key+' must be between'+str(minimum)+' and'+str(maximum))
+    return int(value) if integer else value
+
+def run_irodori(payload,context,references,job,deadline):
+    config=json.loads((context.root/'app-runtime.json').read_text(encoding='utf-8-sig')).get('irodori')
+    if not isinstance(config,dict):raise ValueError('HF app is missing its irodori model configuration')
+    text=payload.get('text');caption=payload.get('caption','')
+    if not isinstance(text,str) or not text.strip() or len(text)>1000:raise ValueError('Irodori text must contain1..1000 characters')
+    if not isinstance(caption,str) or len(caption)>2000:raise ValueError('Irodori caption exceeds2000 characters')
+    checkpoint=safe_cache_path(context.root,config.get('checkpoint'))
+    codec=safe_cache_path(context.root,config.get('codec'))
+    tokenizer=safe_cache_path(context.root,config.get('tokenizer','tokenizer'),directory=True)
+    if not (tokenizer/'tokenizer_config.json').is_file():raise ValueError('Irodori tokenizer_config.json is missing')
+    directory=OUTPUT_ROOT/'hf-jobs'/job;directory.mkdir(parents=True,exist_ok=True)
+    output=directory/'irodori.wav'
+    reference=payload.get('reference_audio')
+    many=payload.get('reference_audios')
+    if reference is not None and many is not None:raise ValueError('Use one reference representation')
+    selected=many if many is not None else ([reference] if reference else [])
+    if not isinstance(selected,list) or len(selected)>20 or any(name not in references for name in selected):raise ValueError('Irodori reference audio was not supplied by this job')
+    if sum((INPUT_ROOT/references[name]).stat().st_size for name in selected)>20*1024*1024:raise ValueError('Irodori reference audio exceeds20MiB combined')
+    request={'checkpoint':str(checkpoint),'codec':str(codec),'tokenizer':str(tokenizer),'output':str(output),
+        'text':text.strip(),'caption':caption.strip(),'reference_wav':str(INPUT_ROOT/references[reference]) if reference else None,
+        'reference_wavs':[str(INPUT_ROOT/references[name]) for name in many] if many is not None else None,
+        'num_steps':finite_number(payload,'num_steps',60,4,80,True),'duration_scale':finite_number(payload,'duration_scale',1,.5,2),
+        'cfg_scale_text':finite_number(payload,'cfg_scale_text',3,0,20),'cfg_scale_caption':finite_number(payload,'cfg_scale_caption',3,0,20),
+        'cfg_scale_speaker':finite_number(payload,'cfg_scale_speaker',10,0,20),
+        'seed':None if payload.get('seed') is None else finite_number(payload,'seed',0,0,2**53-1,True),
+        'seconds':None if payload.get('seconds') is None else finite_number(payload,'seconds',5,.5,45)}
+    runner=context.root/'irodori_runner.py'
+    if not runner.is_file():raise ValueError('irodori_runner.py is missing from the HF app')
+    log=directory/'irodori.stderr'
+    with log.open('wb') as error_log:
+        try:
+            result=subprocess.run(['/opt/irodori-venv/bin/python',str(runner)],input=json.dumps(request),text=True,
+                stdout=subprocess.PIPE,stderr=error_log,timeout=deadline.remaining(),check=False,
+                env={**os.environ,'HF_HUB_OFFLINE':'1','TRANSFORMERS_OFFLINE':'1'})
+        except subprocess.TimeoutExpired:raise TimeoutError('Irodori exceeded the remaining280-second app budget') from None
+    if result.returncode:
+        with log.open('rb') as error_log:error_log.seek(max(0,log.stat().st_size-1600));detail=error_log.read().decode(errors='replace')
+        raise RuntimeError('Irodori generation failed: '+detail)
+    try:summary=json.loads(result.stdout)
+    except ValueError:raise RuntimeError('Irodori returned invalid metadata') from None
+    if summary.get('error'):raise RuntimeError(str(summary['error'])[:1600])
+    if not output.is_file():raise RuntimeError('Irodori returned no WAV file')
+    return [output],summary
+
+def cleanup_job(directory,roots):
+    if directory is None:return
+    resolved=directory.resolve()
+    if any(resolved.is_relative_to((root/'hf-jobs').resolve()) and resolved!=(root/'hf-jobs').resolve() for root in roots):
+        shutil.rmtree(directory,ignore_errors=True)
+
+def elapsed_ms(started):
+    return max(0,math.ceil((time.monotonic()-started)*1000))
+
+def generate(payload,context):
+    if not isinstance(payload,dict):raise ValueError('Generation payload must be an object')
+    deadline=Deadline(280);started=time.monotonic();job=uuid.uuid4().hex
+    metadata=payload.get('_app') or {}
+    if not isinstance(metadata,dict):raise ValueError('Invalid artifact metadata')
+    capability=metadata.get('artifact_upload_url')
+    if capability:trusted_url(capability)
+    references={};input_directory=None;owned=[];additional=[]
+    try:
+        references,input_directory=prepare_files(payload.get('files'),job,deadline)
+        if payload.get('task')=='diagnostics':
+            execution_started=time.monotonic()
+            result=diagnostics(payload,context)
+            result['summary']={'backend':'diagnostics','executed_ms':elapsed_ms(execution_started)}
+            return result
+        if payload.get('task')=='chat':
+            execution_started=time.monotonic()
+            result=run_chat(payload,context,deadline)
+            result['summary']['executed_ms']=elapsed_ms(execution_started)
+            result['summary']['elapsed_seconds']=round(time.monotonic()-started,3)
+            return result
+        if payload.get('task')=='irodori':
+            execution_started=time.monotonic()
+            paths,summary=run_irodori(payload,context,references,job,deadline);owned=paths
+            summary['executed_ms']=elapsed_ms(execution_started)
+        else:
+            additional_ms=0
+            if payload.get('task')=='dialogue':
+                settings=payload.get('irodori')
+                if not isinstance(settings,dict):raise ValueError('Dialogue requires Irodori synthesis settings')
+                execution_started=time.monotonic()
+                audio,tts_summary=run_irodori(settings,context,references,job,deadline)
+                additional_ms=elapsed_ms(execution_started)
+                tts_summary['executed_ms']=additional_ms
+                reference=input_directory/'dialogue-generated.wav'
+                shutil.copyfile(audio[0],reference)
+                references['dialogue-generated.wav']=reference.relative_to(INPUT_ROOT).as_posix()
+                additional.extend(audio);owned.extend(audio)
+            continuation=prepare_continuation(payload.get('continuation'),references,input_directory,deadline)
+            workflow=payload.get('workflow')
+            if workflow is None:
+                default=context.root/'workflow.json'
+                if not default.is_file():raise ValueError('Provide an API workflow or include workflow.json in the HF app')
+                workflow=json.loads(default.read_text(encoding='utf-8-sig'))
+            if payload.get('task')=='dialogue':workflow=dialogue_timing(workflow,tts_summary)
+            info=context.comfy('/object_info')
+            workflow=normalize_and_validate(workflow,info,references,job)
+            before=snapshot_outputs();history=run_comfy(workflow,context,deadline)
+            paths,new_outputs=output_files(history,before);owned.extend(new_outputs)
+            paths,merged=finish_continuation(paths,continuation,job,deadline);owned.extend(merged)
+            executed_ms=comfy_execution_ms(history)
+            if executed_ms is None:executed_ms=history['_execution_ms']
+            paths.extend(additional);summary={'backend':'comfyui','nodes':len(workflow),'executed_ms':executed_ms+additional_ms}
+            if additional:summary['irodori']=tts_summary
+            if continuation:summary['continuation']=True
+        outputs=upload_outputs(paths,capability,deadline)
+        return {'files':outputs,'summary':{**summary,'elapsed_seconds':round(time.monotonic()-started,3)}}
+    finally:
+        cleanup_job(input_directory,(INPUT_ROOT,))
+        for path in owned:
+            try:
+                resolved=path.resolve()
+                if any(resolved.is_relative_to(root.resolve()) for root in (OUTPUT_ROOT,TEMP_ROOT)):path.unlink(missing_ok=True)
+            except OSError:pass
+        for root in (OUTPUT_ROOT,TEMP_ROOT):cleanup_job(root/'hf-jobs'/job,(root,))
+
+def run_chat(payload,context,deadline):
+    config=json.loads((context.root/'app-runtime.json').read_text(encoding='utf-8-sig')).get('chat') or {}
+    model_path=context.root if config.get('model_path','.')=='.' else safe_cache_path(context.root,config['model_path'],directory=True)
+    if not (model_path/'config.json').is_file():raise ValueError('Chat model config.json is missing from the native HF cache')
+    messages=payload.get('messages')
+    if messages is None:
+        messages=[]
+        if payload.get('system_prompt'):messages.append({'role':'system','content':payload['system_prompt']})
+        if isinstance(payload.get('history'),list):messages.extend(payload['history'])
+        messages.append({'role':'user','content':payload.get('message','')})
+    if not isinstance(messages,list) or not 1<=len(messages)<=64:raise ValueError('Chat requires1..64 messages')
+    for message in messages:
+        if not isinstance(message,dict) or message.get('role') not in ('system','user','assistant') or not isinstance(message.get('content'),str) or not message['content'].strip() or len(message['content'])>20000:
+            raise ValueError('Chat messages require role and nonempty text content')
+    request={'model_path':str(model_path),'messages':messages,'max_tokens':finite_number(payload,'max_tokens',512,1,2048,True),
+             'temperature':finite_number(payload,'temperature',.78,0,2),'top_p':finite_number(payload,'top_p',.9,.01,1),
+             'repetition_penalty':finite_number(payload,'repetition_penalty',1.08,1,2),
+             'seed':None if payload.get('seed') is None else finite_number(payload,'seed',0,0,2**53-1,True),
+             'generation_seconds':deadline.remaining()}
+    directory=Path('/workspace/hf-app');directory.mkdir(parents=True,exist_ok=True)
+    log=directory/('chat-'+uuid.uuid4().hex+'.stderr')
+    try:
+        with log.open('wb') as error_log:
+            try:result=subprocess.run(['/opt/venv/bin/python',str(context.root/'chat_runner.py')],input=json.dumps(request),text=True,
+                stdout=subprocess.PIPE,stderr=error_log,timeout=deadline.remaining(),check=False,
+                env={**os.environ,'HF_HUB_OFFLINE':'1','TRANSFORMERS_OFFLINE':'1'})
+            except subprocess.TimeoutExpired:raise TimeoutError('Chat exceeded the remaining280-second app budget') from None
+        try:output=json.loads(result.stdout)
+        except ValueError:raise RuntimeError('Chat returned invalid JSON') from None
+        if result.returncode or output.get('error'):raise RuntimeError('Chat failed: '+str(output.get('error','runtime exited'))[:1600])
+        return output
+    finally:log.unlink(missing_ok=True)
+
+def prepare_continuation(value,references,directory,deadline):
+    import bernini_continuation as module
+    config=module.validate_continuation(value)
+    if config is None:return None
+    name=config['source_video_name']
+    if name not in references:raise ValueError('Continuation source video was not supplied')
+    source=INPUT_ROOT/references[name]
+    frame=directory/(uuid.uuid4().hex+'.png')
+    resize=f"scale={config['width']}:{config['height']}:force_original_aspect_ratio=decrease,pad={config['width']}:{config['height']}:(ow-iw)/2:(oh-ih)/2:color=black,setsar=1"
+    module._DEADLINE=deadline
+    errors=[]
+    for offset in ('-0.1','-0.5','-1.0'):
+        frame.unlink(missing_ok=True)
+        try:module._run(['ffmpeg','-hide_banner','-loglevel','error','-y','-sseof',offset,'-i',str(source),'-map','0:v:0','-an','-frames:v','1','-vf',resize,str(frame)],'continuation frame extraction',30)
+        except (RuntimeError,subprocess.TimeoutExpired) as error:errors.append(str(error))
+        if frame.is_file() and frame.stat().st_size:break
+    else:
+        frame.unlink(missing_ok=True)
+        module._run(['ffmpeg','-hide_banner','-loglevel','error','-y','-i',str(source),'-map','0:v:0','-an','-vf',resize,'-fps_mode','passthrough','-update','1',str(frame)],'continuation full-decode frame extraction',deadline.remaining())
+    if not frame.is_file() or not frame.stat().st_size:raise RuntimeError('Continuation produced no reference frame')
+    references[config['last_frame_name']]=frame.relative_to(INPUT_ROOT).as_posix()
+    return {**config,'source_path':source}
+
+def finish_continuation(paths,config,job,deadline):
+    if config is None:return paths,[]
+    import bernini_continuation as module
+    module._DEADLINE=deadline
+    outputs=[];created=[]
+    for path in paths:
+        if path.suffix.lower() not in module.VIDEO_SUFFIXES:outputs.append(path);continue
+        target=OUTPUT_ROOT/'hf-jobs'/job/('continued-'+str(len(created))+'.mp4')
+        module.merge_continuation_output(config['source_path'],path,target,config)
+        outputs.append(target);created.append(target)
+    if not created:raise RuntimeError('Continuation workflow produced no video')
+    return outputs,created
+
+
+def diagnostics(payload,context):
+    """Bounded, read-only inspection for version/mapping and workflow smoke checks."""
+    network=trusted_network_test(payload['network_url'],Deadline(25)) if payload.get('network_url') else None
+    if payload.get('network_only'):
+        if network is None:raise ValueError('network_only requires a trusted network_url')
+        return {'network':network}
+    requested=payload.get('requested_class_types',[])
+    if not isinstance(requested,list) or len(requested)>128 or any(not isinstance(name,str) or len(name)>160 for name in requested):
+        raise ValueError('requested_class_types must contain at most128 node names')
+    info=context.comfy('/object_info')
+    result={'network':network,'available_node_count':len(info),'missing':[name for name in requested if name not in info], 'nodes':{}}
+    for name in requested:
+        if name not in info:continue
+        node=info[name]
+        result['nodes'][name]={'input':node.get('input',{}),'output':node.get('output',[]),'output_node':bool(node.get('output_node'))}
+    stats=context.comfy('/system_stats')
+    system=stats.get('system',{})
+    result['versions']={key:system.get(key) for key in ('comfyui_version','python_version','pytorch_version','embedded_python') if key in system}
+    workflow=payload.get('workflow')
+    if workflow is not None:
+        references={}
+        for item in payload.get('files',[]):
+            if isinstance(item,dict) and isinstance(item.get('name'),str):references[item['name']]='hf-jobs/diagnostics/'+item['name']
+        normalized=normalize_and_validate(workflow,info,references,'diagnostics')
+        result['workflow']={'valid':True,'nodes':len(normalized),'model_inputs':{node_id:{key:value for key,value in node['inputs'].items() if key.lower() in MODEL_KEYS or re.fullmatch(r'lora_\d+',key.lower())} for node_id,node in normalized.items()}}
+    if len(json.dumps(result,separators=(',',':')).encode())>512*1024:raise ValueError('Requested diagnostic schema exceeds512KiB; request fewer nodes')
+    return result
+
+
+def dialogue_timing(workflow,summary):
+    """Preserve the host dialogue graph's speech-duration dependent frame count."""
+    if not isinstance(workflow,dict):raise ValueError('Dialogue workflow must be an object')
+    workflow=json.loads(json.dumps(workflow,allow_nan=False))
+    expected={'796':'mxSlider','535':'LTXVEmptyLatentAudio','542':'PrimitiveFloat','549':'VHS_VideoCombine'}
+    if any(workflow.get(key,{}).get('class_type')!=kind for key,kind in expected.items()):
+        raise ValueError('Dialogue workflow is missing its duration/frame-rate controls')
+    fps=finite_number(workflow['542']['inputs'],'value',24,1,120)
+    duration=finite_number(summary,'duration_seconds',0,.001,45)
+    seconds=max(3,math.ceil(duration+.25));frames=int(seconds*fps)
+    workflow['796']['inputs'].update(Xi=frames,Xf=frames)
+    workflow['535']['inputs'].update(frames_number=frames+1,frame_rate=fps)
+    workflow['542']['inputs']['value']=fps
+    workflow['549']['inputs']['frame_rate']=fps
+    return workflow

chat_runner.py

@@ -0,0 +1,32 @@
+"""Local-HF chat adapter matching the original host defaults."""
+from contextlib import redirect_stdout
+import json,sys,time
+
+def chat(data):
+    import torch
+    from transformers import AutoModelForCausalLM,AutoTokenizer,StoppingCriteria,StoppingCriteriaList
+    tokenizer=AutoTokenizer.from_pretrained(data['model_path'],local_files_only=True,trust_remote_code=False)
+    model=AutoModelForCausalLM.from_pretrained(data['model_path'],torch_dtype='auto',device_map={'':'cuda:0'},low_cpu_mem_usage=True,local_files_only=True,trust_remote_code=False)
+    model.eval()
+    if data.get('seed') is not None:torch.manual_seed(data['seed'])
+    prompt=tokenizer.apply_chat_template(data['messages'],tokenize=False,add_generation_prompt=True)
+    encoded=tokenizer(prompt,return_tensors='pt',truncation=True,max_length=4096).to(model.device)
+    count=encoded['input_ids'].shape[-1]
+    deadline=time.monotonic()+max(1,data.get('generation_seconds',250))
+    class StopAtDeadline(StoppingCriteria):
+        def __call__(self,input_ids,scores,**kwargs):return time.monotonic()>=deadline
+    kwargs={'max_new_tokens':data['max_tokens'],'do_sample':data['temperature']>0,'repetition_penalty':data['repetition_penalty'],
+            'stopping_criteria':StoppingCriteriaList([StopAtDeadline()]),'pad_token_id':tokenizer.pad_token_id or tokenizer.eos_token_id}
+    if kwargs['do_sample']:kwargs.update(temperature=data['temperature'],top_p=data['top_p'])
+    with torch.inference_mode():tokens=model.generate(**encoded,**kwargs)
+    generated=tokens[0,count:]
+    return {'text':tokenizer.decode(generated,skip_special_tokens=True),'usage':{'prompt_tokens':count,'completion_tokens':len(generated)},
+            'summary':{'backend':'transformers','finish_reason':'time_limit' if time.monotonic()>=deadline else 'completed'},'files':[]}
+
+if __name__=='__main__':
+    try:
+        with redirect_stdout(sys.stderr):result=chat(json.load(sys.stdin))
+        json.dump(result,sys.stdout,ensure_ascii=False)
+    except Exception as error:
+        json.dump({'error':str(error)[:1600]},sys.stdout,ensure_ascii=False)
+        raise SystemExit(1)

generate.py

@@ -0,0 +1,4 @@
+"""HF app entry point; shared GPU image remains unchanged."""
+from catalog_runtime import generate
+from catalog_boot import initialize
+initialize()

index.html

@@ -0,0 +1,12 @@
+<!doctype html>
+<html lang="ja">
+<head><meta charset="utf-8"><meta name="viewport" content="width=device-width,initial-scale=1"><meta name="color-scheme" content="light dark"><title>VideoKarma1</title><link rel="stylesheet" href="./style.css"></head>
+<body><main class="shell">
+<header class="hero"><h1 id="title">Workflow Studio</h1><p id="description"></p></header>
+<div class="workspace"><section class="editor">
+<form id="app-form"><div class="top-panel"><label class="field" id="mode-field"><span>モード</span><select id="mode"></select></label></div>
+<div id="quick-controls"></div><div id="upload-list" class="media-list"></div><div id="workflow-form"></div>
+</form><div class="app-execution"><div class="token-summary" aria-live="polite"><p id="token-balance">トークン残高を確認しています…</p><p id="token-usage"></p></div><button id="app-execute" type="button" disabled>実行する</button><p id="ui-status" class="status" role="status" aria-live="polite">接続を確認しています…</p><progress id="transfer-progress" max="1" value="0" hidden></progress><small>起動・読み込み・実行・停止待ちはGPUの稼働時間に含まれます。タブを閉じても処理はキャンセルされません。</small></div></section>
+<aside class="output"><div class="output-heading"><h2>プレビュー</h2></div><div class="preview-stage"><div id="preview-loading" class="preview-loading" role="status" aria-live="polite" hidden><span class="light-ring" aria-hidden="true"></span><span>生成中…</span></div><div id="results"><div class="empty-state"><span>✧</span><p>実行結果がここに表示されます。</p></div></div></div></aside></div>
+
+</main><script id="app-config" type="application/json">{"id":"video-karma","title":"VideoKarma1","description":"画像・テキストから動画","modes":[{"id":"i2v","label":"画像から","workflow":{"84":{"class_type":"CLIPLoader","inputs":{"clip_name":"encoder-01.safetensors","type":"wan","device":"default"},"_meta":{"title":"処理 Text Encoder"}},"85":{"class_type":"KSamplerAdvanced","inputs":{"model":["103",0],"positive":["98",0],"negative":["98",1],"latent_image":["86",0],"add_noise":"disable","noise_seed":0,"steps":4,"cfg":1,"sampler_name":"euler","scheduler":"simple","start_at_step":2,"end_at_step":4,"return_with_leftover_noise":"disable"}},"86":{"class_type":"KSamplerAdvanced","inputs":{"model":["104",0],"positive":["98",0],"negative":["98",1],"latent_image":["98",2],"add_noise":"enable","noise_seed":1,"steps":4,"cfg":1,"sampler_name":"euler","scheduler":"simple","start_at_step":0,"end_at_step":2,"return_with_leftover_noise":"enable"}},"87":{"class_type":"VAEDecode","inputs":{"samples":["85",0],"vae":["90",0]}},"89":{"class_type":"CLIPTextEncode","inputs":{"clip":["84",0],"text":"low quality, blurry, artifacts, watermark, text, zoom in, close-up, crop, face distortion, identity change"},"_meta":{"title":"ネガティブプロンプト"}},"90":{"class_type":"VAELoader","inputs":{"vae_name":"decoder-01.safetensors"},"_meta":{"title":"処理 VAE"}},"93":{"class_type":"CLIPTextEncode","inputs":{"clip":["84",0],"text":"女性が笑顔で笑う"},"_meta":{"title":"ポジティブプロンプト"}},"94":{"class_type":"CreateVideo","inputs":{"images":["87",0],"fps":16}},"95":{"class_type":"UNETLoader","inputs":{"unet_name":"denoiser-01.safetensors","weight_dtype":"default"},"_meta":{"title":"High Noise Model"}},"96":{"class_type":"UNETLoader","inputs":{"unet_name":"denoiser-02.safetensors","weight_dtype":"default"},"_meta":{"title":"Low Noise 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Text Encoder"}},"85":{"class_type":"KSamplerAdvanced","inputs":{"model":["103",0],"positive":["93",0],"negative":["89",0],"latent_image":["86",0],"add_noise":"disable","noise_seed":0,"steps":4,"cfg":1,"sampler_name":"euler","scheduler":"simple","start_at_step":2,"end_at_step":4,"return_with_leftover_noise":"disable"}},"86":{"class_type":"KSamplerAdvanced","inputs":{"model":["104",0],"positive":["93",0],"negative":["89",0],"latent_image":["wan_t2v_latent",0],"add_noise":"enable","noise_seed":1,"steps":4,"cfg":1,"sampler_name":"euler","scheduler":"simple","start_at_step":0,"end_at_step":2,"return_with_leftover_noise":"enable"}},"87":{"class_type":"VAEDecode","inputs":{"samples":["85",0],"vae":["90",0]}},"89":{"class_type":"CLIPTextEncode","inputs":{"clip":["84",0],"text":"low quality, blurry, artifacts, watermark, text, zoom in, close-up, crop, face distortion, identity 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Model"}},"101":{"class_type":"LoraLoaderModelOnly","inputs":{"model":["95",0],"lora_name":"adapter-03.safetensors","strength_model":1}},"102":{"class_type":"LoraLoaderModelOnly","inputs":{"model":["96",0],"lora_name":"adapter-04.safetensors","strength_model":1}},"103":{"class_type":"ModelSamplingSD3","inputs":{"model":["102",0],"shift":5}},"104":{"class_type":"ModelSamplingSD3","inputs":{"model":["101",0],"shift":5}},"108":{"class_type":"SaveVideo","inputs":{"video":["94",0],"filename_prefix":"video/VideoKarma_t2v","format":"auto","codec":"auto"}},"wan_t2v_latent":{"class_type":"EmptyHunyuanLatentVideo","inputs":{"width":704,"height":704,"length":81,"batch_size":1}}},"missingNodes":[]}],"source":"host-current-r2v-deploy"}</script><script src="./app.js" defer></script></body></html>

irodori_runner.py

@@ -0,0 +1,104 @@
+from __future__ import annotations
+
+import base64
+from contextlib import redirect_stdout
+import io
+import json
+import math
+from pathlib import Path
+import sys
+
+
+def load_reference_audio(path):
+    # torchaudio.load on the base requires TorchCodec. Decode this local input
+    # with libsndfile instead; torchaudio functional resampling remains intact.
+    import soundfile as sf
+    import torch
+    info = sf.info(str(path))
+    if not 0 < info.duration <= 120 or not 1 <= info.channels <= 2 or not 8000 <= info.samplerate <= 192000:
+        raise ValueError('Reference audio must be 0-120 seconds, mono/stereo, 8-192 kHz')
+    audio, rate = sf.read(str(path), dtype='float32', always_2d=True)
+    if not len(audio) or not rate or not torch.isfinite(torch.from_numpy(audio)).all():
+        raise ValueError('Reference audio is empty or invalid')
+    return torch.from_numpy(audio.T.copy()), int(rate)
+
+
+def synthesize(data):
+    import soundfile as sf
+    import torch
+    sys.path.insert(0, '/opt/irodori-tts')
+    from irodori_tts import inference_runtime as runtime_module
+    runtime_module._load_audio = load_reference_audio
+    runtime_module._resolve_tokenizer_source = lambda checkpoint, fallback: (data['tokenizer'], True)
+    checkpoint = Path(data['checkpoint'])
+    if not checkpoint.is_file():
+        raise ValueError('Irodori checkpoint does not exist')
+    reference = data.get('reference_wav')
+    references = data.get('reference_wavs')
+    if reference and references:
+        raise ValueError('Use one reference representation')
+    paths = references if references is not None else ([reference] if reference else [])
+    if not isinstance(paths, list) or len(paths) > 20 or any(not isinstance(path, str) or not path for path in paths):
+        raise ValueError('Invalid reference audio paths')
+    total_seconds = 0
+    for path in paths:
+        info = sf.info(path)
+        if not 0 < info.duration <= 120 or not 1 <= info.channels <= 2 or not 8000 <= info.samplerate <= 192000:
+            raise ValueError('Reference audio must be 0-120 seconds, mono/stereo, 8-192 kHz')
+        total_seconds += info.duration
+    if total_seconds > 120:
+        raise ValueError('Reference audio must be at most 120 seconds combined')
+    decoded = {str(path): load_reference_audio(path) for path in paths}
+    if decoded:
+        runtime_module._load_audio = lambda path: decoded[str(path)] if str(path) in decoded else load_reference_audio(path)
+    has_reference = bool(paths)
+    caption = data.get('caption') or None
+    runtime, reloaded = runtime_module.get_cached_runtime(runtime_module.RuntimeKey(
+        checkpoint=str(checkpoint), model_device='cuda', model_precision='bf16',
+        codec_repo=data['codec'], codec_device='cuda',
+        codec_precision='fp32', codec_deterministic_encode=True,
+        codec_deterministic_decode=True, compile_model=False, compile_dynamic=False,
+    ))
+    if caption and not runtime.model_cfg.use_caption_condition:
+        raise ValueError('Selected model does not support voice descriptions')
+    if has_reference and not runtime.model_cfg.use_speaker_condition_resolved:
+        raise ValueError('Selected model does not support reference audio')
+    text_cfg, caption_cfg, speaker_cfg, messages = runtime_module.resolve_cfg_scales(
+        cfg_guidance_mode='independent', cfg_scale_text=data['cfg_scale_text'],
+        cfg_scale_caption=data['cfg_scale_caption'] if caption else 0,
+        cfg_scale_speaker=data['cfg_scale_speaker'] if has_reference else 0,
+        cfg_scale=None, use_caption_condition=bool(caption), use_speaker_condition=has_reference,
+    )
+    request = runtime_module.SamplingRequest(
+        text=data['text'], caption=caption, ref_wav=reference, ref_wavs=references, no_ref=not has_reference,
+        seconds=data.get('seconds'), duration_scale=data['duration_scale'],
+        min_seconds=0.5, max_seconds=45, max_ref_seconds=120,
+        num_candidates=1, decode_mode='sequential', num_steps=data['num_steps'],
+        seed=data['seed'], cfg_guidance_mode='independent', cfg_scale_text=text_cfg,
+        cfg_scale_caption=caption_cfg, cfg_scale_speaker=speaker_cfg,
+        context_kv_cache=True, trim_tail=True,
+    )
+    result = runtime.synthesize(request)
+    audio = result.audio.detach().float().cpu().squeeze()
+    if audio.ndim != 1 or not audio.numel() or not torch.isfinite(audio).all():
+        raise ValueError('Irodori generated invalid audio')
+    buffer = io.BytesIO()
+    sf.write(buffer, audio.numpy(), int(result.sample_rate), format='WAV', subtype='PCM_16')
+    Path(data['output']).write_bytes(buffer.getvalue())
+    return {
+        'backend': 'irodori',
+        'audio_mime': 'audio/wav', 'sample_rate': int(result.sample_rate),
+        'duration_seconds': audio.numel() / int(result.sample_rate),
+        'seed': int(result.used_seed), 'num_steps': data['num_steps'],
+        'model': checkpoint.name, 'runtime_reloaded': bool(reloaded),
+        'messages': [*messages, *result.messages],
+    }
+
+
+if __name__ == '__main__':
+    try:
+        with redirect_stdout(sys.stderr):
+            result = synthesize(json.load(sys.stdin))
+    except Exception as exc:
+        result = {'error': str(exc)}
+    json.dump(result, sys.stdout, ensure_ascii=False)

models/diffusion_models/denoiser-01.safetensors

@@ -0,0 +1,3 @@
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models/diffusion_models/denoiser-02.safetensors

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ui-monospace,monospace}.error{color:#ffa7a7!important}.status{font-size:12px;padding:10px 4px;white-space:pre-wrap}.output .error{padding:16px}.chat-history{margin:14px 0;padding:12px;border:1px solid var(--line);border-radius:8px;font-size:13px}.chat-history:empty{display:none}footer{font-size:11px;color:#7f8595;margin:24px 0 0}#quick-controls>.panel{display:grid;grid-template-columns:repeat(3,minmax(0,1fr));gap:12px}#workflow-form>.field{margin:12px 0}[hidden]{display:none!important}@media(max-width:850px){.shell{padding:22px 16px}.workspace{grid-template-columns:minmax(0,1fr)}.output{position:static}.output-heading{padding:18px 18px 0}.empty-state{padding:26px 10px 40px}}@media(max-width:480px){.shell{padding:18px 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+
+.basic-controls{grid-template-columns:minmax(0,1fr)}.basic-prompts{display:grid;gap:14px}.basic-prompts:empty,.basic-controls>.fields:empty{display:none}
+
+/* This layout belongs to this example repository, not the GPU service. */
+html{background:#f4f6f4;color-scheme:light}body{max-width:none;margin:0;padding:24px;background:#f4f6f4;color:#223a30;font-family:system-ui,sans-serif;--surface:#fff;--line:#d8e3db;--muted:#63776a;--accent:#286645}
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+
+.token-summary{padding:10px 13px;border:1px solid #47556955;border-radius:8px;margin-bottom:12px;font-size:13px}.token-summary p{margin:4px 0}
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+
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+
+
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+.video-lora-control input{min-width:0;width:100%;box-sizing:border-box}
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upstream/Comfy-Org--Wan_2.1_ComfyUI_repackaged/617a7633e636506f850e043bc4605f290a466a8e/README.md

@@ -0,0 +1,92 @@
+---
+license: apache-2.0
+tags:
+- comfyui
+- diffusion-single-file
+base_model:
+- Wan-AI/Wan2.1-FLF2V-14B-720P
+- alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control-Camera
+- alibaba-pai/Wan2.1-Fun-V1.1-14B-Control-Camera
+- alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control
+- alibaba-pai/Wan2.1-Fun-V1.1-1.3B-InP
+- Wan-AI/Wan2.1-I2V-14B-480P
+- Wan-AI/Wan2.1-I2V-14B-720P
+- MAGREF-Video/MAGREF
+- Wan-AI/Wan2.1-T2V-1.3B
+- Wan-AI/Wan2.1-T2V-14B
+- Wan-AI/Wan2.1-VACE-1.3B
+- Wan-AI/Wan2.1-VACE-14B
+- htdong/Wan-Alpha
+- MeiGen-AI/InfiniteTalk
+---
+
+# Wan 2.1
+
+Repackaged model files for ComfyUI.
+
+Original model repository:
+
+- https://huggingface.co/Wan-AI/Wan2.1-FLF2V-14B-720P
+- https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control-Camera
+- https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-14B-Control-Camera
+- https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control
+- https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-1.3B-InP
+- https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-480P
+- https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-720P
+- https://huggingface.co/MAGREF-Video/MAGREF
+- https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B
+- https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
+- https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B
+- https://huggingface.co/Wan-AI/Wan2.1-VACE-14B
+- https://huggingface.co/htdong/Wan-Alpha
+- https://huggingface.co/MeiGen-AI/InfiniteTalk
+
+Place the files in the following folders:
+
+```
+📂 ComfyUI/
+├── 📂 models/
+│   ├── 📂 clip_vision/
+│   │   └── clip_vision_h.safetensors
+│   ├── 📂 diffusion_models/
+│   │   ├── wan2.1_flf2v_720p_14B_fp16.safetensors
+│   │   ├── wan2.1_flf2v_720p_14B_fp8_e4m3fn.safetensors
+│   │   ├── wan2.1_fun_camera_v1.1_1.3B_bf16.safetensors
+│   │   ├── wan2.1_fun_camera_v1.1_14B_bf16.safetensors
+│   │   ├── wan2.1_fun_control_1.3B_bf16.safetensors
+│   │   ├── wan2.1_fun_inp_1.3B_bf16.safetensors
+│   │   ├── wan2.1_i2v_480p_14B_bf16.safetensors
+│   │   ├── wan2.1_i2v_480p_14B_fp16.safetensors
+│   │   ├── wan2.1_i2v_480p_14B_fp8_e4m3fn.safetensors
+│   │   ├── wan2.1_i2v_480p_14B_fp8_scaled.safetensors
+│   │   ├── wan2.1_i2v_720p_14B_bf16.safetensors
+│   │   ├── wan2.1_i2v_720p_14B_fp16.safetensors
+│   │   ├── wan2.1_i2v_720p_14B_fp8_e4m3fn.safetensors
+│   │   ├── wan2.1_i2v_720p_14B_fp8_scaled.safetensors
+│   │   ├── wan2.1_magref_14B_fp16.safetensors
+│   │   ├── wan2.1_t2v_1.3B_bf16.safetensors
+│   │   ├── wan2.1_t2v_1.3B_fp16.safetensors
+│   │   ├── wan2.1_t2v_14B_bf16.safetensors
+│   │   ├── wan2.1_t2v_14B_fp16.safetensors
+│   │   ├── wan2.1_t2v_14B_fp8_e4m3fn.safetensors
+│   │   ├── wan2.1_t2v_14B_fp8_scaled.safetensors
+│   │   ├── wan2.1_vace_1.3B_fp16.safetensors
+│   │   ├── wan2.1_vace_1.3B_preview_fp16.safetensors
+│   │   └── wan2.1_vace_14B_fp16.safetensors
+│   ├── 📂 loras/
+│   │   └── wan_alpha_2.1_rgba_lora.safetensors
+│   ├── 📂 model_patches/
+│   │   ├── wan2.1_infiniteTalk_multi_fp16.safetensors
+│   │   └── wan2.1_infiniteTalk_single_fp16.safetensors
+│   ├── 📂 text_encoders/
+│   │   ├── umt5_xxl_fp16.safetensors
+│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
+│   ├── 📂 vae/
+│   │   ├── wan_2.1_vae.safetensors
+│   │   ├── wan_alpha_2.1_vae_alpha_channel.safetensors
+│   │   └── wan_alpha_2.1_vae_rgb_channel.safetensors
+```
+
+---
+
+Wan 2.1 repackaged for ComfyUI use. For examples see: https://comfyanonymous.github.io/ComfyUI_examples/wan

upstream/Comfy-Org--Wan_2.2_ComfyUI_Repackaged/c4f60d30c55a624e35427060fdd217579a6c1d77/README.md

@@ -0,0 +1,98 @@
+---
+license: apache-2.0
+tags:
+- comfyui
+- diffusion-single-file
+base_model:
+- nvidia/ChronoEdit-14B-Diffusers
+- Wan-AI/Wan2.2-Animate-14B
+- alibaba-pai/Wan2.2-Fun-A14B-Control-Camera
+- alibaba-pai/Wan2.2-Fun-A14B-Control
+- alibaba-pai/Wan2.2-Fun-5B-Control
+- alibaba-pai/Wan2.2-Fun-5B-InP
+- alibaba-pai/Wan2.2-Fun-A14B-InP
+- alibaba-pai/Wan2.2-VACE-Fun-A14B
+- Wan-AI/Wan2.2-I2V-A14B
+- Wan-AI/Wan2.2-S2V-14B
+- Wan-AI/Wan2.2-T2V-A14B
+- Wan-AI/Wan2.2-TI2V-5B
+- lightx2v/Wan2.2-Distill-Loras
+pipeline_tag: image-to-video
+---
+
+# Wan 2.2
+
+Repackaged model files for ComfyUI.
+
+Original model repository:
+
+- https://huggingface.co/nvidia/ChronoEdit-14B-Diffusers
+- https://huggingface.co/Wan-AI/Wan2.2-Animate-14B
+- https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control-Camera
+- https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control
+- https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-Control
+- https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-InP
+- https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-InP
+- https://huggingface.co/alibaba-pai/Wan2.2-VACE-Fun-A14B
+- https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B
+- https://huggingface.co/Wan-AI/Wan2.2-S2V-14B
+- https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B
+- https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B
+- https://huggingface.co/lightx2v/Wan2.2-Distill-Loras
+
+Place the files in the following folders:
+
+```
+📂 ComfyUI/
+├── 📂 models/
+│   ├── 📂 audio_encoders/
+│   │   └── wav2vec2_large_english_fp16.safetensors
+│   ├── 📂 diffusion_models/
+│   │   ├── chrono_edit_14B_fp16.safetensors
+│   │   ├── wan2.2_animate_14B_bf16.safetensors
+│   │   ├── wan2.2_animate_14B_int8_convrot.safetensors
+│   │   ├── wan2.2_fun_camera_high_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_camera_high_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_fun_camera_low_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_camera_low_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_fun_control_5B_bf16.safetensors
+│   │   ├── wan2.2_fun_control_high_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_fun_control_low_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_fun_inpaint_5B_bf16.safetensors
+│   │   ├── wan2.2_fun_inpaint_high_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_inpaint_high_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_fun_inpaint_low_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_inpaint_low_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_fun_vace_high_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_vace_high_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_fun_vace_low_noise_14B_bf16.safetensors
+│   │   ├── wan2.2_fun_vace_low_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_i2v_high_noise_14B_fp16.safetensors
+│   │   ├── wan2.2_i2v_high_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_i2v_low_noise_14B_fp16.safetensors
+│   │   ├── wan2.2_i2v_low_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_s2v_14B_bf16.safetensors
+│   │   ├── wan2.2_s2v_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_t2v_high_noise_14B_fp16.safetensors
+│   │   ├── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors
+│   │   ├── wan2.2_t2v_low_noise_14B_fp16.safetensors
+│   │   ├── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors
+│   │   └── wan2.2_ti2v_5B_fp16.safetensors
+│   ├── 📂 loras/
+│   │   ├── chronoedit_distill_lora.safetensors
+│   │   ├── wan2.2_animate_14B_relight_lora_bf16.safetensors
+│   │   ├── wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors
+│   │   ├── wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors
+│   │   ├── wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors
+│   │   └── wan2.2_t2v_lightx2v_4steps_lora_v1.1_low_noise.safetensors
+│   ├── 📂 text_encoders/
+│   │   ├── umt5_xxl_fp16.safetensors
+│   │   └── umt5_xxl_fp8_e4m3fn_scaled.safetensors
+│   ├── 📂 vae/
+│   │   ├── wan2.2_vae.safetensors
+│   │   └── wan_2.1_vae.safetensors
+```
+
+Examples: https://comfyanonymous.github.io/ComfyUI_examples/wan22/