olivv-cs-ComfyUI-FunPack/docs/FunPackLoraWorkflow.md

FunPack LoRA Weight Workflow

This workflow lets FunPack Video Refiner save LoRA weight suggestions for an exact prompt. Loading stays predictable: the Apply node chooses the weights, the Loader loads them, and the Refiner updates suggestions after you rate the result.

Node Order

Use this pattern:

FunPack Apply LoRA Weights -> FunPack LoRA Loader -> FunPack Video Refiner

The loader does not learn from ratings. The refiner does that part.

FunPack Apply LoRA Weights

This node lists the LoRAs you want to use and their normal base weights.

Inputs:

• positive_prompt: Prompt text used for lookup.
• refinement_key: Same key used by FunPack Video Refiner.
• mode: Same tokenizer mode as the refiner.
• per_block: For supported ltx2 stacks, lets the loader analyze LoRA block deltas and balance competing block strengths behind the scenes.
• lora_N: LoRA file.
• lora_N_type: general, concept, style, quality, or character.
• lora_N_base_weight: Trainer-recommended model base weight.

Use + Add LoRA for more rows.

The first run uses base weights. Later runs can use saved suggestions for the same refinement_key, mode, and prompt.

Notes:

• Changing the prompt can start a new prompt record.
• Saved suggestions are ignored when the LoRA name, LoRA type, or saved base model weight no longer matches the current slot.
• lora_N_type is a hint for the refiner, not a loader category. A wrong type will not break loading, but it can make future suggestions less useful.
• 0.0 skips that LoRA for the current run.
• Negative weights are possible after repeated bad ratings.
• If refinement_key or mode differs from the refiner, the node falls back to base weights.

FunPack LoRA Loader

This node loads the LoRA stack using the weights prepared by FunPack Apply LoRA Weights, then passes the same stack forward so the refiner can read it. The clip input is optional and uses zero CLIP strength when omitted.

When per_block is enabled on an ltx2 stack, the loader keeps the visible global LoRA weight and derives block weights from the LoRA patches. With multiple supported LoRAs, it compares their block fingerprints before loading and gently boosts or dampens overlapping blocks according to each LoRA's type hint. If the model or LoRA layout is not supported, it just loads the LoRA normally.

Per-block notes:

• Per-block mode only applies to supported ltx2 image model configs.
• Wan and other non-LTX workflows fall back to normal global LoRA loading even if per_block is enabled.
• LoRAs without at least two detectable transformer blocks fall back to normal global loading.
• The per-block scales are not exposed as separate UI controls.
• Type hints affect conflict balancing: character and concept LoRAs get more protection in contested semantic blocks, quality LoRAs stay more supportive, and style or general LoRAs yield more readily when they overlap heavily.
• The loader status reports whether each LoRA used global, per-block, smart-per-block, or a fallback path.
• smart-per-block status includes the strongest detected blocks and the largest overlap score, which is useful for spotting LoRAs that are fighting over the same region.

Video Refiner Integration

Connect the lora_stack output from FunPack LoRA Loader into the optional lora_stack input on FunPack Video Refiner.

The refiner compares each LoRA's type and filename with the concepts it extracted from the prompt. After it processes your rating, it saves lora_weight_suggestions into the prompt history.

Examples:

• I like it gently reinforces matching LoRAs.
• Missing details nudges related concept, character, and general LoRAs upward.
• Missing concept favors the best concept or character match and can reduce weaker competing concept LoRAs.
• Missing quality can favor quality LoRAs and reduce unrelated concept LoRAs.
• I don't like it can mute or invert a LoRA if it keeps hurting the same prompt.
• -Just forget it- skips LoRA suggestion updates for that run.

If lora_stack is not connected, conditioning, sigma, and latent refinement still work, but LoRA suggestions are not updated.