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olivv-cs-ComfyUI-FunPack/example_workflows/LTX23_FunPack_Node_Set_Example.json
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},
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}
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"title": "Image Processing",
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"name": "INT",
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"title": "number of frames",
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"This is an example workflow, finetuned for LTX2.3 video model, using FunPack nodes to enhance and correct the results, tweaking them according to user's preferences.\n\nVideo Refiner node learns from your ratings and feedback to provide the best result much more consistently than a base model does.\n\nThis workflow DOES NOT make model learn concepts it were never aware of. It only finetunes conditioning, sigmas and latents to match what YOU like as user, however it can't introduce knowledge that was never a part of a model.\n\nThis example workflow is actively using subgraphs to compact the space it takes, providing much more neat and clear workspace.\n\nIf you have any feedback or you found a bug or you have problems with using my nodes, feel free to file an issue on Github:\n\nhttps://github.com/digital-garbage/ComfyUI-FunPack\n\nPlease make sure you are reporting issues while using \"main\" branch of the repo. Issues with \"dev\" branch will not be reviewed unless they are critical bugs, breaking workflow fully."
],
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"link": 14069
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{
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},
{
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{
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},
{
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{
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"localized_name": "text",
"name": "text",
"type": "STRING",
"widget": {
"name": "text"
},
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}
],
"outputs": [
{
"localized_name": "positive",
"name": "positive",
"type": "CONDITIONING",
"links": [
14083
]
},
{
"localized_name": "negative",
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]
},
{
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],
"title": "Conditioning Processing",
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{
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{
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{
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{
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{
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{
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{
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{
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},
{
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},
{
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"type": "BOOLEAN",
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},
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},
{
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"shape": 7,
"type": "INT",
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},
{
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{
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"name": "feedback_rating",
"shape": 7,
"type": "INT",
"widget": {
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},
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}
],
"outputs": [
{
"localized_name": "modified_positive",
"name": "modified_positive",
"type": "CONDITIONING",
"links": [
14069,
14084
]
},
{
"localized_name": "status",
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},
{
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14090
]
},
{
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},
{
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"name": "loss_graph",
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},
{
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]
},
{
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]
}
],
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},
{
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"inputs": [
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],
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{
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"name": "video_latent",
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13884
]
},
{
"localized_name": "audio_latent",
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13455
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}
],
"title": "Separate Low Resolution AV Latent",
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},
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{
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{
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{
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],
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{
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"name": "latent",
"type": "LATENT",
"links": [
13885
]
},
{
"localized_name": "status",
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}
],
"title": "Save Refinement Latent",
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"### How to use Video Refiner\n\nVideo Refiner is the feedback part of this workflow. You run the workflow, look at the generated video, rate it, then run again with the same refinement key. The node uses your rating history to nudge the next generations toward what you personally prefer.\n\nIt does not train the model and it does not teach the model new concepts. It only adjusts things already present in the workflow: positive conditioning, sigma schedule, optional video latent refinement, and optional LoRA weight suggestions.\n\n## Rating\n\nYou are rating the previous generation made by this workflow. In this example, that means the video shown in the Result node.\n\nAvailable ratings:\n\n- \"I like it\" - use this when the result is good or near perfect. The refiner treats this as the direction to keep.\n- \"Missing details\" - use this when the main idea is there and the image quality is fine, but motion, small objects, camera behavior, timing, or details are not quite right.\n- \"Missing concept\" - use this when the video is visually acceptable, but it is not really doing what the prompt asked for.\n- \"Missing quality\" - use this when the result misses the prompt and also has visible quality problems.\n- \"I don't like it\" - use this for a bad result that should push the next generation away from this direction.\n- \"-Just forget it-\" - use this when the run should not be learned from at all. Good examples are wrong input image, wrong model, bad seed, broken generation, failed decode, wrong workflow connection, or any other technical mistake.\n\nDo not use \"I don't like it\" for technical failures. Use \"-Just forget it-\" instead, otherwise the refiner may learn from a result that was broken for reasons unrelated to the prompt.\n\n## Normal loop\n\n1. Run the workflow once.\n2. Check the Result video.\n3. Choose the rating that describes that result.\n4. Run again with the same refinement key.\n5. Repeat until the workflow starts giving results closer to what you want.\n\nThe first run may mostly pass things through, because the refiner has no useful history yet. It becomes more useful after it has a few rated generations for the same refinement key and prompt.\n\n## Refinement key\n\nThe refinement key is the session name. Keep it the same while you are teaching one set of preferences. Change it when you want to start a separate refinement history.\n\nThe same refinement key is used by:\n\n- FunPack Apply LoRA Weights\n- FunPack Video Refiner\n- FunPack Save Refinement Latent\n\nIf these keys do not match, the workflow will still run, but saved suggestions and latent references will not line up.\n\n## Prompt matching\n\nLoRA weight suggestions are prompt-specific. If you change the positive prompt, Apply LoRA Weights may not find previous suggestions for that exact prompt.\n\nThis is intentional. It prevents one prompt's LoRA corrections from accidentally affecting a different prompt.\n\n## LoRA stack\n\nConnect lora_stack from FunPack LoRA Loader into Video Refiner if you want the refiner to save suggested LoRA model weights.\n\nThe basic flow is:\n\nFunPack Apply LoRA Weights -> FunPack LoRA Loader -> FunPack Video Refiner\n\nApply LoRA Weights prepares the stack. LoRA Loader loads it into the model. Video Refiner reads the same stack and writes better prompt-specific suggestions after you rate the result.\n\n## Sigmas\n\nIf sigmas are connected, Video Refiner can output refined_sigmas. The sigma_strength setting controls how strongly it can alter them.\n\n- off: do not change sigmas\n- subtle: small, safer changes\n- medium / strong / max: stronger changes, useful when you want more noticeable behavior changes\n\nFor normal use, start with subtle or off. Increase only when you understand what the changes are doing.\n\n## Latent refinement\n\nUse only the separated video latent for Video Refiner's latent input. Do not connect the combined audio/video latent here.\n\nCorrect LTX audio/video path:\n\n1. Separate audio/video latent if needed.\n2. Send only the video latent into Video Refiner.\n3. Send refined_latent back into LTXVConcatAVLatent as video_latent.\n4. Keep the original audio latent connected as audio_latent.\n\nFunPack Save Refinement Latent saves a video latent reference under the same refinement key. This lets later runs compare against that reference. If the latent shape changes, the old reference may no longer apply and the workflow may pass the current latent through or replace the reference.\n\n## Feedback questions\n\nIf feedback is enabled, Video Refiner can ask a more specific question about the current prompt. Answer it with the feedback slider. This is optional, but it can help the refiner understand what kind of correction you meant.\n\nIf you do not want extra questions, leave feedback disabled and just use the main rating.\n\n## Reset session\n\nReset Session clears the saved history for the refinement key. Use it when the refiner has learned from bad ratings, when you changed the workflow too much, or when you simply want to start over.\n\nDo not leave Reset Session enabled by accident. 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