3.0 KiB
FunPack Gemma Embedding Refiner
This node analyzes the positive conditioning produced by your text encoder, tracks your feedback over time, and nudges the conditioning toward directions that should score higher in future generations.
Parameters
positive_conditioning: Conditioning to refine. Place this node after your text encoder and before the downstream video conditioning node.
mode: Tokenizer mode used for prompt analysis. Use ltx2 for LTX-style workflows and wan for Wan workflows.
rating: Rating for the previously generated result, from 1 to 10, where 1 means "awful" and 10 means "masterpiece".
refinement_key: Name of the refinement session. The node stores its learned refinement data under this key so you can continue training the same style later.
scheduler_mode: Learning behavior preset. original keeps the legacy behavior, while accurate and aggressive adjust how strongly the node updates the refinement.
positive_prompt: Optional prompt text used for token analysis and concept-level feedback.
sigmas: Optional input sigma schedule to co-refine alongside the conditioning. When connected, the node preserves the first and last sigma exactly and only adjusts the middle values.
sigma_strength: Preset strength for sigma refinement. off disables sigma changes, while subtle, medium, strong, and max allow progressively larger movement of the middle sigma values.
reset_session: If enabled, clears the saved training history for the selected refinement key and starts a fresh session.
unlimited_history: If enabled, disables history pruning.
seed: Seed used for exploration behavior during refinement.
feedback_enabled: If enabled, the node can return a concept-focused feedback question alongside the refined conditioning.
feedback_rating: Answer to the feedback question on its own 1 to 6 scale. This is only useful when concept feedback is enabled.
Outputs
modified_positive: Refined conditioning. Connect this output to the next conditioning stage in your workflow.
status: Human-readable training status, including iteration and refinement diagnostics.
feedback_question: Optional concept feedback prompt generated by the node when feedback mode is active.
training_info: Additional training details for the current refinement step.
loss_graph: Graph image showing learning loss over total session iterations for the current refinement key.
refined_sigmas: Refined sigma schedule. If no sigmas input is connected, this output is empty.
Purpose
Use this node when you want to iteratively tune prompt conditioning based on your own ratings instead of manually rewriting prompts every time. Over multiple runs, it builds a refinement profile for the selected refinement_key.
Warning
Sigma refinement currently breaks audio generation in workflows that also produce audio streams. If you need audio to generate and save correctly, do not connect sigmas to this node. Use the refiner only for conditioning in those workflows.