{"schema":"record/v1","id":"art_01M62G0ZYKAR6PMJ7G2M8AHH0E","type":"article","revision":1,"etag":"\"r1.s0\"","title":"Wan 2.2 14B Fun Control ComfyUI template (video_wan2_2_14B_fun_control): control video wiring, bypassed Canny, 20-step default and 4-step LoRA group","summary":"The official video_wan2_2_14B_fun_control template (Comfy-Org/workflow_templates 0cc0fba) feeds a reference image and a control video to Wan22FunControlToVideo with the Wan 2.2 Fun Control 14B fp8_scaled high/low-noise pair. As saved, its Canny node is bypassed, so the example clip enters unprocessed as a ready-made control video. The active group runs 20 steps at CFG 3.5 (shift 8, 10 + 10) at 640x640, 81 frames, 16 fps; a bypassed copy adds the i2v lightx2v 4-step LoRAs (4 steps, CFG 1). Read statically; not executed.","status":"active","body":{"text":"Wan 2.2 14B Fun Control in ComfyUI: the official template\n\nScope. This guide reads the official video_wan2_2_14B_fun_control.json in Comfy-Org/workflow_templates at commit 0cc0fba562efe9f68e48050c2b82ed6495050bc2 (SHA256 52752247...88ea, 61,018 bytes). All 44 nodes and 50 links were traced statically. The file has no subgraphs and no switch nodes. Nothing was run, and no model, image, video or linked page was downloaded.\n\n1. Prerequisites\n- A ComfyUI build with the core nodes Wan22FunControlToVideo, LoadVideo, GetVideoComponents and Canny. Every node is comfy-core, saved at 0.3.45 or 0.3.49; those are saved version strings, not a tested minimum. The graph uses no custom node pack. Note 185 (\"About Control Video\") says you may need comfyui_controlnet_aux or ComfyUI-DepthAnythingV2 to preprocess other control types. It also says the model supports Canny, Depth, Pose and trajectory control.\n- Files, as declared by the loaders and the Model Links note (node 161, sizes as stated there):\n  - models/diffusion_models/wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors and wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors (13.31 GB each), from Comfy-Org/Wan_2.2_ComfyUI_Repackaged.\n  - models/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors (6.27 GB), from Comfy-Org/Wan_2.1_ComfyUI_repackaged.\n  - models/vae/wan_2.1_vae.safetensors (242.1 MB).\n  - Only for the 4-step group: models/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors and _low_noise.safetensors (1.14 GB each). These are the i2v Lightning LoRAs, applied here to the Fun Control experts.\n  The default route needs about 33 GB of files, and the LoRAs add about 2.3 GB. No CLIP vision model is used.\n\n2. The two groups\nLike the Wan 2.2 14B first-last-frame template, the file holds two complete copies of the pipeline:\n- \"Default workflow\" (active as saved).\n- \"Wan2.2 Fun Control fp8 scaled+ 4 steps LoRA\": every node in it is bypassed (mode 4) as saved.\nNote 183 says the Lightning LoRA reduces generation time but loses video dynamics, and that you enable one workflow as needed. To switch, toggle bypass on a group's nodes (Ctrl + B) and bypass the other group. Unlike the first-last-frame template, both groups here use the same prompts and the same example files.\n\n3. Control video and preprocessing (default group)\n- LoadVideo 158 (example video_wan2_2_14B_fun_control_start_image_control_video.mp4) feeds GetVideoComponents 156. Its images output (link 285) goes to Canny 157 (saved 0.1 and 0.6, the low and high thresholds in the core node's order). Canny's output (link 286) reaches the control_video input of Wan22FunControlToVideo 160. PreviewImage 159 shows Canny's output.\n- As saved, Canny 157 and PreviewImage 159 are bypassed, even in the active group. A bypassed node passes its image input through, so the clip's frames reach control_video unprocessed. The example file name suggests it is already a control video. It was not viewed.\n- With ordinary footage, enable Canny 157 (and PreviewImage 159 to check the edges). For depth or pose control, use a preprocessor from the packs named in note 185 and feed its images to control_video.\n- GetVideoComponents also outputs audio and fps, but neither is connected. The output is written at a fixed 16 fps without audio.\n\n4. Reference image\nLoadImage 145 (example video_wan2_2_14B_fun_control_start_image.jpg) feeds ref_image on Wan22FunControlToVideo 160 (link 284).\n\n5. Size and length\nWan22FunControlToVideo 160 holds width 640, height 640, length 81 and batch 1. Note 186 says the model supports multi-resolution video at 512, 768 and 1024, and was trained with 81 frames at 16 fps. The saved 640 is not one of those sizes. That is a note-versus-setting difference, not a tested problem. How the node handles a control clip that has more or fewer than 81 frames, or a different size, is not in this file. Prepare an 81-frame control clip at the output size and aspect ratio.\n\n6. Default sampling\n- Prompts: positive CLIPTextEncode 99 (a girl with white curly ponytails dancing slowly before the Leaning Tower of Pisa, in a realistic 3D style) and negative 91 (the usual Wan Chinese quality list). Both use CLIPLoader 90 (umt5_xxl_fp8_e4m3fn_scaled, type wan). VAELoader 92 loads wan_2.1_vae.\n- High noise: UNETLoader 101 feeds ModelSamplingSD3 93 (shift 8), then KSamplerAdvanced 96: add_noise enable, seed 909895218860439 set to randomize, 20 steps, CFG 3.5, euler, simple, steps 0 to 10, leftover noise enable.\n- Low noise: UNETLoader 102 feeds ModelSamplingSD3 94 (shift 8), then KSamplerAdvanced 95: no added noise, seed 0 fixed, 20 steps, CFG 3.5, euler, simple, steps 10 to the end. Sampler 95 takes its latent from 96.\n- Output: VAEDecode 97, then CreateVideo 100 at 16 fps, then SaveVideo 98 (prefix video/wan2.2_fun_control, format auto, codec auto). Expect one 640x640 video of 81 frames, about 5 s, following the control clip's motion with the reference image's look. That is the template's purpose; no output was produced here.\n\n7. 4-step LoRA group (bypassed as saved)\n- Models: UNETLoader 165 feeds LoraLoaderModelOnly 181 (wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise, strength 1), then ModelSamplingSD3 176 (shift 8). UNETLoader 166 feeds LoraLoaderModelOnly 182 (the _low_noise LoRA), then ModelSamplingSD3 177 (shift 8).\n- Samplers: KSamplerAdvanced 169 runs 4 steps at CFG 1, euler, simple, steps 0 to 2 with leftover noise, seed 342522439403882 set to randomize. KSamplerAdvanced 175 runs steps 2 to 4 without added noise.\n- Own inputs: CLIPLoader 167, prompts 179 and 162 (same text as the default group), VAELoader 168, LoadImage 178 and LoadVideo 174 (same example files), GetVideoComponents 171, Canny 173 (bypassed), PreviewImage 172 and Wan22FunControlToVideo 180 (640x640, length 81). Output goes through VAEDecode 164 and CreateVideo 163 (16 fps) to SaveVideo 170, with the same prefix as the default group.\n\n8. Run it\n1) Put the four default files in the folders above, plus the two LoRAs only if you will use the 4-step group. 2) Open the template and keep the Default workflow group active. 3) Load your control clip in LoadVideo 158. If it is not already a control video, enable Canny 157 or add another preprocessor. 4) Load your reference image in LoadImage 145. 5) Edit prompts 99 and 91, and size and length on node 160. 6) Run. Expect one video under video/wan2.2_fun_control.\nFor the 4-step group: enable its nodes, bypass the Default workflow group, and load the clip and image into LoadVideo 174 and LoadImage 178.\n\n9. Failure cases and checks\n- Ordinary footage used as control: with Canny bypassed, raw frames go in as the control signal. Enable a preprocessor first.\n- Preprocessor not installed: Canny is core. The depth and pose preprocessors named in note 185 are third-party packs, which the graph does not use.\n- Both groups enabled: both pipelines run through their own loaders, so the time of both routes is spent and two videos are written under the same prefix.\n- Edits that do nothing: the groups do not share loaders, inputs or sizes. Edit the group you run.\n- Clip length, fps or size mismatch: see section 5. The output fps is fixed at 16, whatever the clip's own fps.\n- Missing LoRA files only matter for the 4-step group. Missing Fun Control experts stop both groups. These are not the i2v or t2v experts.\n- Lightning trade-off: note 183 says the 4-step LoRAs reduce time but lose video dynamics.\n\n10. How it differs from the other 14B templates\nIt uses the same two-group bypass pattern as the Wan 2.2 14B first-last-frame template, and the same 20-step default at CFG 3.5 as the T2V guide (first-last-frame uses CFG 4). Its 4-step group keeps shift 8, where first-last-frame's uses 5, and it applies the i2v lightx2v LoRAs to the Fun Control experts. The step split is half and half on both routes.\n\nEvidence and rights. Evidence status: source_inspected, not_run, unreviewed. This is shared-founder desk curation by the tutorial lane. The workflow repository declares the MIT licence; that covers this analysis of the template, not the Wan models, LoRAs, preprocessors, example media or outputs, which keep their own terms.","citations":[{"url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","note":"Exact pinned template; node, link and group byte ranges and excerpt hashes are in the source pins."},{"url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/LICENSE","note":"Repository MIT licence at the same commit (existing native source)."}]},"categories":["T06","T08"],"tags":["ai","comfyui","tutorial","wan2.2","fun-control","controlnet","video-to-video","lightx2v","workflow-templates","reproducibility"],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[],"execution_record_ids":[]},"rights":[{"notes":"Original attributed analysis. Repository MIT notice cited; models, LoRAs, preprocessors, example media and outputs keep separate terms.","hosting":"permitted","component":"documentation","license_id":null,"modification":"permitted","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-199ededd5d477b885475291fcdfa3c9cbb65705b/record.json#p-199ededd5d477b885475291fcdfa3c9cbb65705b/record","import_batch_id":"pipe-1001437dcb0fe0d0b91f5a9cceaf31a8a6990ee7","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-1001437dcb0fe0d0b91f5a9cceaf31a8a6990ee7","original":{"body":{"text":"Wan 2.2 14B Fun Control in ComfyUI: the official template\n\nScope. This guide reads the official video_wan2_2_14B_fun_control.json in Comfy-Org/workflow_templates at commit 0cc0fba562efe9f68e48050c2b82ed6495050bc2 (SHA256 52752247...88ea, 61,018 bytes). All 44 nodes and 50 links were traced statically. The file has no subgraphs and no switch nodes. Nothing was run, and no model, image, video or linked page was downloaded.\n\n1. Prerequisites\n- A ComfyUI build with the core nodes Wan22FunControlToVideo, LoadVideo, GetVideoComponents and Canny. Every node is comfy-core, saved at 0.3.45 or 0.3.49; those are saved version strings, not a tested minimum. The graph uses no custom node pack. Note 185 (\"About Control Video\") says you may need comfyui_controlnet_aux or ComfyUI-DepthAnythingV2 to preprocess other control types. It also says the model supports Canny, Depth, Pose and trajectory control.\n- Files, as declared by the loaders and the Model Links note (node 161, sizes as stated there):\n  - models/diffusion_models/wan2.2_fun_control_high_noise_14B_fp8_scaled.safetensors and wan2.2_fun_control_low_noise_14B_fp8_scaled.safetensors (13.31 GB each), from Comfy-Org/Wan_2.2_ComfyUI_Repackaged.\n  - models/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors (6.27 GB), from Comfy-Org/Wan_2.1_ComfyUI_repackaged.\n  - models/vae/wan_2.1_vae.safetensors (242.1 MB).\n  - Only for the 4-step group: models/loras/wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors and _low_noise.safetensors (1.14 GB each). These are the i2v Lightning LoRAs, applied here to the Fun Control experts.\n  The default route needs about 33 GB of files, and the LoRAs add about 2.3 GB. No CLIP vision model is used.\n\n2. The two groups\nLike the Wan 2.2 14B first-last-frame template, the file holds two complete copies of the pipeline:\n- \"Default workflow\" (active as saved).\n- \"Wan2.2 Fun Control fp8 scaled+ 4 steps LoRA\": every node in it is bypassed (mode 4) as saved.\nNote 183 says the Lightning LoRA reduces generation time but loses video dynamics, and that you enable one workflow as needed. To switch, toggle bypass on a group's nodes (Ctrl + B) and bypass the other group. Unlike the first-last-frame template, both groups here use the same prompts and the same example files.\n\n3. Control video and preprocessing (default group)\n- LoadVideo 158 (example video_wan2_2_14B_fun_control_start_image_control_video.mp4) feeds GetVideoComponents 156. Its images output (link 285) goes to Canny 157 (saved 0.1 and 0.6, the low and high thresholds in the core node's order). Canny's output (link 286) reaches the control_video input of Wan22FunControlToVideo 160. PreviewImage 159 shows Canny's output.\n- As saved, Canny 157 and PreviewImage 159 are bypassed, even in the active group. A bypassed node passes its image input through, so the clip's frames reach control_video unprocessed. The example file name suggests it is already a control video. It was not viewed.\n- With ordinary footage, enable Canny 157 (and PreviewImage 159 to check the edges). For depth or pose control, use a preprocessor from the packs named in note 185 and feed its images to control_video.\n- GetVideoComponents also outputs audio and fps, but neither is connected. The output is written at a fixed 16 fps without audio.\n\n4. Reference image\nLoadImage 145 (example video_wan2_2_14B_fun_control_start_image.jpg) feeds ref_image on Wan22FunControlToVideo 160 (link 284).\n\n5. Size and length\nWan22FunControlToVideo 160 holds width 640, height 640, length 81 and batch 1. Note 186 says the model supports multi-resolution video at 512, 768 and 1024, and was trained with 81 frames at 16 fps. The saved 640 is not one of those sizes. That is a note-versus-setting difference, not a tested problem. How the node handles a control clip that has more or fewer than 81 frames, or a different size, is not in this file. Prepare an 81-frame control clip at the output size and aspect ratio.\n\n6. Default sampling\n- Prompts: positive CLIPTextEncode 99 (a girl with white curly ponytails dancing slowly before the Leaning Tower of Pisa, in a realistic 3D style) and negative 91 (the usual Wan Chinese quality list). Both use CLIPLoader 90 (umt5_xxl_fp8_e4m3fn_scaled, type wan). VAELoader 92 loads wan_2.1_vae.\n- High noise: UNETLoader 101 feeds ModelSamplingSD3 93 (shift 8), then KSamplerAdvanced 96: add_noise enable, seed 909895218860439 set to randomize, 20 steps, CFG 3.5, euler, simple, steps 0 to 10, leftover noise enable.\n- Low noise: UNETLoader 102 feeds ModelSamplingSD3 94 (shift 8), then KSamplerAdvanced 95: no added noise, seed 0 fixed, 20 steps, CFG 3.5, euler, simple, steps 10 to the end. Sampler 95 takes its latent from 96.\n- Output: VAEDecode 97, then CreateVideo 100 at 16 fps, then SaveVideo 98 (prefix video/wan2.2_fun_control, format auto, codec auto). Expect one 640x640 video of 81 frames, about 5 s, following the control clip's motion with the reference image's look. That is the template's purpose; no output was produced here.\n\n7. 4-step LoRA group (bypassed as saved)\n- Models: UNETLoader 165 feeds LoraLoaderModelOnly 181 (wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise, strength 1), then ModelSamplingSD3 176 (shift 8). UNETLoader 166 feeds LoraLoaderModelOnly 182 (the _low_noise LoRA), then ModelSamplingSD3 177 (shift 8).\n- Samplers: KSamplerAdvanced 169 runs 4 steps at CFG 1, euler, simple, steps 0 to 2 with leftover noise, seed 342522439403882 set to randomize. KSamplerAdvanced 175 runs steps 2 to 4 without added noise.\n- Own inputs: CLIPLoader 167, prompts 179 and 162 (same text as the default group), VAELoader 168, LoadImage 178 and LoadVideo 174 (same example files), GetVideoComponents 171, Canny 173 (bypassed), PreviewImage 172 and Wan22FunControlToVideo 180 (640x640, length 81). Output goes through VAEDecode 164 and CreateVideo 163 (16 fps) to SaveVideo 170, with the same prefix as the default group.\n\n8. Run it\n1) Put the four default files in the folders above, plus the two LoRAs only if you will use the 4-step group. 2) Open the template and keep the Default workflow group active. 3) Load your control clip in LoadVideo 158. If it is not already a control video, enable Canny 157 or add another preprocessor. 4) Load your reference image in LoadImage 145. 5) Edit prompts 99 and 91, and size and length on node 160. 6) Run. Expect one video under video/wan2.2_fun_control.\nFor the 4-step group: enable its nodes, bypass the Default workflow group, and load the clip and image into LoadVideo 174 and LoadImage 178.\n\n9. Failure cases and checks\n- Ordinary footage used as control: with Canny bypassed, raw frames go in as the control signal. Enable a preprocessor first.\n- Preprocessor not installed: Canny is core. The depth and pose preprocessors named in note 185 are third-party packs, which the graph does not use.\n- Both groups enabled: both pipelines run through their own loaders, so the time of both routes is spent and two videos are written under the same prefix.\n- Edits that do nothing: the groups do not share loaders, inputs or sizes. Edit the group you run.\n- Clip length, fps or size mismatch: see section 5. The output fps is fixed at 16, whatever the clip's own fps.\n- Missing LoRA files only matter for the 4-step group. Missing Fun Control experts stop both groups. These are not the i2v or t2v experts.\n- Lightning trade-off: note 183 says the 4-step LoRAs reduce time but lose video dynamics.\n\n10. How it differs from the other 14B templates\nIt uses the same two-group bypass pattern as the Wan 2.2 14B first-last-frame template, and the same 20-step default at CFG 3.5 as the T2V guide (first-last-frame uses CFG 4). Its 4-step group keeps shift 8, where first-last-frame's uses 5, and it applies the i2v lightx2v LoRAs to the Fun Control experts. The step split is half and half on both routes.\n\nEvidence and rights. Evidence status: source_inspected, not_run, unreviewed. This is shared-founder desk curation by the tutorial lane. The workflow repository declares the MIT licence; that covers this analysis of the template, not the Wan models, LoRAs, preprocessors, example media or outputs, which keep their own terms.","citations":[{"url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","note":"Exact pinned template; node, link and group byte ranges and excerpt hashes are in the source pins."},{"url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/LICENSE","note":"Repository MIT licence at the same commit (existing native source)."}]},"tags":["ai","comfyui","tutorial","wan2.2","fun-control","controlnet","video-to-video","lightx2v","workflow-templates","reproducibility"],"type":"article","title":"Wan 2.2 14B Fun Control ComfyUI template (video_wan2_2_14B_fun_control): control video wiring, bypassed Canny, 20-step default and 4-step LoRA group","rights":[{"notes":"Original attributed analysis. Repository MIT notice cited; models, LoRAs, preprocessors, example media and outputs keep separate terms.","hosting":"permitted","component":"documentation","modification":"permitted","model_training":"unknown","redistribution":"permitted"}],"summary":"The official video_wan2_2_14B_fun_control template (Comfy-Org/workflow_templates 0cc0fba) feeds a reference image and a control video to Wan22FunControlToVideo with the Wan 2.2 Fun Control 14B fp8_scaled high/low-noise pair. As saved, its Canny node is bypassed, so the example clip enters unprocessed as a ready-made control video. The active group runs 20 steps at CFG 3.5 (shift 8, 10 + 10) at 640x640, 81 frames, 16 fps; a bypassed copy adds the i2v lightx2v 4-step LoRAs (4 steps, CFG 1). Read statically; not executed.","evidence":{"review":"unreviewed","execution":"not_run","inspection":"source_inspected"},"categories":["T06","T08"],"extensions":{"curation/v1":{"curator":"scale67-tutorial-20261028-s1","revision":1,"topic_ids":[],"confidence":"Complete original JSON traced; control and reference wiring, node modes, sampler values and unused outputs asserted against the bytes; no runtime result.","limitations":["Static reading only; no workflow, model or node was executed and no image or video was viewed.","Control clip length/size handling and pass-through behaviour were not read from the node implementation.","Canny and conditioning widget names are given by position in the core node order; the file does not serialize them.","Saved node versions are metadata, not a tested minimum ComfyUI release.","Shared founder operator; source-based desk review, not independent formal Hub evidence review."],"observed_at":"2026-10-28T23:59:30.000Z","source_pins":[{"locator":"source.bin (video_wan2_2_14B_fun_control.json); 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node 157 Canny (bypassed); UTF-8 bytes 9274:10235; excerpt SHA256 5b6e2ea46b7b31ed6b9ca5ae8f3e89bf39fd894f07865474b079bc0b82f232fa","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 159 PreviewImage (bypassed); UTF-8 bytes 8470:9268; excerpt SHA256 1fe8c0907198f10c425e354ee42c2bcc7ff23e30d156b8a4f7d7607100d2c054","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); 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node 99 CLIPTextEncode positive; UTF-8 bytes 32368:33966; excerpt SHA256 1f2d26b29ad4650f042b039146fe87425f69a0695f65bf1cf62c9701cf050f4d","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 91 CLIPTextEncode negative; UTF-8 bytes 30872:32362; excerpt SHA256 f621196d3f18e55e393653b0e511da0e6274019366e09f2d28ad3e6ef1904faf","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 90 CLIPLoader; UTF-8 bytes 4850:6117; excerpt SHA256 129b9b576455e9945571f11bd4b8957cb08abcfdf01361691a60abbda6cda8fd","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 92 VAELoader; UTF-8 bytes 6123:7314; excerpt SHA256 49fa262c538c0b1284dbb95e66c7e1eb7a1e83e43e9506c09e7824634c1f12a9","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 101 UNETLoader high noise; UTF-8 bytes 2247:3544; excerpt SHA256 258b47cc03fa26b86c53116519c78003e097db36fdb2051434ced30ea0a8a9b6","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 102 UNETLoader low noise; UTF-8 bytes 3550:4844; excerpt SHA256 6c65d7aeaec1b1917de58d6570d563f2e88b0252c5c59fb9f9acd086c8749a41","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 93 ModelSamplingSD3; UTF-8 bytes 38390:39382; excerpt SHA256 721e0df6e1fc48113a5365ba21e981503d6baeb22c9ac3db31bdf6f507f07615","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 94 ModelSamplingSD3; UTF-8 bytes 39388:40381; excerpt SHA256 4c2d64a386fc9e4475c59e96f37cde204dae1342625d126c8571d9d5019ccd1f","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 96 KSamplerAdvanced high; UTF-8 bytes 40387:41823; excerpt SHA256 5a2cc6c5a4448d44ad02c27dd3478b7085de70c65f788fec241f2ad0cf7a5a5a","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 95 KSamplerAdvanced low; UTF-8 bytes 36969:38384; excerpt SHA256 fecbd31eeee0e4bc589513b45a91f2e3029ba74322980ebe50a5f871dff025d5","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 97 VAEDecode; UTF-8 bytes 1199:2241; excerpt SHA256 e7f75ce4719a4456f183c22d8e52292684523e8f6525b56605f2ad6a2a85edbc","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 100 CreateVideo; UTF-8 bytes 130:1193; excerpt SHA256 3ef7ed326f492f3fe6160de21ebbc17493ad1769d54253f59397c10c5b5729c7","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 98 SaveVideo; UTF-8 bytes 42701:43579; excerpt SHA256 c037d3cadb3dddc3f1d0d571791431dfbc4ac9cf69e7c329690119314b030fd0","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 185 MarkdownNote About Control Video; UTF-8 bytes 48822:49679; excerpt SHA256 6530ced246134c53592a657aff5779b22d10c9627a8608d756f5672db33bd1bd","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 183 Note Lightning LoRA; UTF-8 bytes 49685:50227; excerpt SHA256 bea09625235bb62d8e3e9f53fa255c9f12de4aff2805fdf112a5462399910683","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 161 MarkdownNote Model Links; UTF-8 bytes 50233:53232; excerpt SHA256 44782da55a039f85812953bf1e4613c5f9599ed77ce461c790cd83df3f261ce4","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 186 MarkdownNote About Wan2.2 Fun Control; UTF-8 bytes 53238:53967; excerpt SHA256 90bc770586e66eea57f5a5225524372f277b43807e9784eec5b4b2cf8f9401a9","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 181 LoraLoaderModelOnly high (LoRA group); UTF-8 bytes 26977:28420; excerpt SHA256 6f661a88fa3db63301363b487212c65cb27878c7bd1be30f344e92c3773fc193","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 182 LoraLoaderModelOnly low (LoRA group); UTF-8 bytes 29426:30866; excerpt SHA256 e1b086a4ec07b9b7575f63037915a24532445591f351a8b1cb1e2b7f984bbf43","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 176 ModelSamplingSD3 (LoRA group); UTF-8 bytes 25977:26971; excerpt SHA256 a008b2b7dde8d94a40cbaedaeeb3231d68548ca124f69a1a2cf2c96db0956b84","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 177 ModelSamplingSD3 (LoRA group); UTF-8 bytes 28426:29420; excerpt SHA256 788ea2832a1a158d6dfd3fb61947b2d5168dc78b92848b8c4a683ae12fe26abd","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 169 KSamplerAdvanced high (LoRA group); UTF-8 bytes 24537:25971; excerpt SHA256 668a3d2ccdc642f90c9cbf2d85b894522fa72bf07cc3d20dc6f3296ead39cd65","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 175 KSamplerAdvanced low (LoRA group); UTF-8 bytes 23123:24531; excerpt SHA256 7367e1c311d1b2958267d890abcf4a8d9d807de153314e2cd363218bc56c1dfb","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 180 Wan22FunControlToVideo (LoRA group); UTF-8 bytes 19076:20967; excerpt SHA256 4066e795fc763d98a55a6961f5db5f9f15565949b0a3b1bd58b1f77547e50910","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 173 Canny (LoRA group, bypassed); UTF-8 bytes 22156:23117; excerpt SHA256 7420cc71ece63c80e192803d14b4e46c6c2a7760735ac733050b3d7712deb650","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 174 LoadVideo (LoRA group); UTF-8 bytes 44389:45323; excerpt SHA256 6b859357048e91e64b1c5fcf8c2f88c123668a81bfd092a14de97bf8275da014","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 178 LoadImage (LoRA group); UTF-8 bytes 46827:47875; excerpt SHA256 e2288b77248accc635f4f3a7a8767d8b13d2479d765a5dcb7e477c30c9bb47c3","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 170 SaveVideo (LoRA group); UTF-8 bytes 41829:42695; excerpt SHA256 e08544bacebebeaf1fdab5406c0e8697442722a0bcba05c68857e8c7d47387f6","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); 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group \"Wan2.2 Fun Control fp8 scaled+ 4 steps LoRA\"; UTF-8 bytes 59062:59296; excerpt SHA256 e2fdfee4989d00e41cebbda83e35e8475a3b0c42bebaf27d0dea971ffef33499","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"LICENSE (existing native capture at 0cc0fba); complete MIT licence text; UTF-8 bytes 0:1074; excerpt SHA256 5dccd61c80c847cd6b22fa98124010163ab8646e573557a16a5cae31122f2056","source_id":"WIN-S-1964b68021bc93dd46d3fead48b8ef56","version_id":"WIN-V-9fcd5f987ca7b7a5e63926e3a4760712","observed_at":"2026-10-28T09:14:32.470Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/LICENSE","version_sha256":"e01fa7b6aef00c8bc0d64d14c1bf48157634435c91136efc98204d4d9d7299f3"}],"candidate_id":"WIN-K-4077d0f22fe331f81e7c8a4fdd8761fec762c619","claim_status":"untested_proposal","rights_basis":"Original explanation of public template structure; no workflow file, media or model is redistributed.","qualification":"shared_operator_desk_qa","supersedes_sha256":null}},"visibility":"public"},"observed_on":null,"original_id":"p-199ededd5d477b885475291fcdfa3c9cbb65705b/record","source_file":"records/p-199ededd5d477b885475291fcdfa3c9cbb65705b/record.json","research_side":{},"source_schema":"create-record-input/v1","original_sha256":"4907942f0fd8594f1cdadc23f447f6fb19a35808620f30742137457f8f6df918","unmapped_fields":[]}],"publication":{"rule":"item_visibility","policy":"l05-publication/1","visibility":"public"}},"curation/v1":{"curator":"scale67-tutorial-20261028-s1","revision":1,"topic_ids":[],"confidence":"Complete original JSON traced; control and reference wiring, node modes, sampler values and unused outputs asserted against the bytes; no runtime result.","limitations":["Static reading only; no workflow, model or node was executed and no image or video was viewed.","Control clip length/size handling and pass-through behaviour were not read from the node implementation.","Canny and conditioning widget names are given by position in the core node order; the file does not serialize them.","Saved node versions are metadata, not a tested minimum ComfyUI release.","Shared founder operator; source-based desk review, not independent formal Hub evidence review."],"observed_at":"2026-10-28T23:59:30.000Z","source_pins":[{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 158 LoadVideo; UTF-8 bytes 47881:48816; excerpt SHA256 c34d503d6a5b94f46559fc0d48068ef88ef32893d3b87ec8bae5310a6379aafd","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 156 GetVideoComponents; UTF-8 bytes 7320:8464; excerpt SHA256 c51af7a9ab11fcbcbf8c8ef0a01c382ada42842ddcdb3e4ae53eadaaa0419edc","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); 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node 99 CLIPTextEncode positive; UTF-8 bytes 32368:33966; excerpt SHA256 1f2d26b29ad4650f042b039146fe87425f69a0695f65bf1cf62c9701cf050f4d","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 91 CLIPTextEncode negative; UTF-8 bytes 30872:32362; excerpt SHA256 f621196d3f18e55e393653b0e511da0e6274019366e09f2d28ad3e6ef1904faf","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 90 CLIPLoader; UTF-8 bytes 4850:6117; excerpt SHA256 129b9b576455e9945571f11bd4b8957cb08abcfdf01361691a60abbda6cda8fd","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 92 VAELoader; UTF-8 bytes 6123:7314; excerpt SHA256 49fa262c538c0b1284dbb95e66c7e1eb7a1e83e43e9506c09e7824634c1f12a9","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 101 UNETLoader high noise; UTF-8 bytes 2247:3544; excerpt SHA256 258b47cc03fa26b86c53116519c78003e097db36fdb2051434ced30ea0a8a9b6","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 102 UNETLoader low noise; UTF-8 bytes 3550:4844; excerpt SHA256 6c65d7aeaec1b1917de58d6570d563f2e88b0252c5c59fb9f9acd086c8749a41","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 93 ModelSamplingSD3; UTF-8 bytes 38390:39382; excerpt SHA256 721e0df6e1fc48113a5365ba21e981503d6baeb22c9ac3db31bdf6f507f07615","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 94 ModelSamplingSD3; UTF-8 bytes 39388:40381; excerpt SHA256 4c2d64a386fc9e4475c59e96f37cde204dae1342625d126c8571d9d5019ccd1f","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 96 KSamplerAdvanced high; UTF-8 bytes 40387:41823; excerpt SHA256 5a2cc6c5a4448d44ad02c27dd3478b7085de70c65f788fec241f2ad0cf7a5a5a","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 95 KSamplerAdvanced low; UTF-8 bytes 36969:38384; excerpt SHA256 fecbd31eeee0e4bc589513b45a91f2e3029ba74322980ebe50a5f871dff025d5","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 97 VAEDecode; UTF-8 bytes 1199:2241; excerpt SHA256 e7f75ce4719a4456f183c22d8e52292684523e8f6525b56605f2ad6a2a85edbc","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 100 CreateVideo; UTF-8 bytes 130:1193; excerpt SHA256 3ef7ed326f492f3fe6160de21ebbc17493ad1769d54253f59397c10c5b5729c7","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 98 SaveVideo; UTF-8 bytes 42701:43579; excerpt SHA256 c037d3cadb3dddc3f1d0d571791431dfbc4ac9cf69e7c329690119314b030fd0","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 185 MarkdownNote About Control Video; UTF-8 bytes 48822:49679; excerpt SHA256 6530ced246134c53592a657aff5779b22d10c9627a8608d756f5672db33bd1bd","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 183 Note Lightning LoRA; UTF-8 bytes 49685:50227; excerpt SHA256 bea09625235bb62d8e3e9f53fa255c9f12de4aff2805fdf112a5462399910683","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 161 MarkdownNote Model Links; UTF-8 bytes 50233:53232; excerpt SHA256 44782da55a039f85812953bf1e4613c5f9599ed77ce461c790cd83df3f261ce4","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 186 MarkdownNote About Wan2.2 Fun Control; UTF-8 bytes 53238:53967; excerpt SHA256 90bc770586e66eea57f5a5225524372f277b43807e9784eec5b4b2cf8f9401a9","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 181 LoraLoaderModelOnly high (LoRA group); UTF-8 bytes 26977:28420; excerpt SHA256 6f661a88fa3db63301363b487212c65cb27878c7bd1be30f344e92c3773fc193","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 182 LoraLoaderModelOnly low (LoRA group); UTF-8 bytes 29426:30866; excerpt SHA256 e1b086a4ec07b9b7575f63037915a24532445591f351a8b1cb1e2b7f984bbf43","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 176 ModelSamplingSD3 (LoRA group); UTF-8 bytes 25977:26971; excerpt SHA256 a008b2b7dde8d94a40cbaedaeeb3231d68548ca124f69a1a2cf2c96db0956b84","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 177 ModelSamplingSD3 (LoRA group); UTF-8 bytes 28426:29420; excerpt SHA256 788ea2832a1a158d6dfd3fb61947b2d5168dc78b92848b8c4a683ae12fe26abd","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); node 169 KSamplerAdvanced high (LoRA group); UTF-8 bytes 24537:25971; excerpt SHA256 668a3d2ccdc642f90c9cbf2d85b894522fa72bf07cc3d20dc6f3296ead39cd65","source_id":"WIN-S-1ba41c5c26d16ac26e6c1ed2ad4ac147","version_id":"WIN-V-91aca2e3749741356b8e9d4137854a17","observed_at":"2026-10-28T23:44:31.877Z","canonical_url":"https://raw.githubusercontent.com/Comfy-Org/workflow_templates/0cc0fba562efe9f68e48050c2b82ed6495050bc2/templates/video_wan2_2_14B_fun_control.json","version_sha256":"0d27cb01413c8d55c32dac507e072b73931345a44f6b3b558e807dd25d96454d"},{"locator":"source.bin (video_wan2_2_14B_fun_control.json); 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