olivv-cs-ComfyUI-FunPack/CHANGELOG.md

Changelog

Unreleased

Added

Added an optional CLIP text-generation advisor to FunPack Video Refiner V2. The advisor uses an explicit Refiner system prompt, can run Gemma thinking mode, passes source images to compatible CLIP tokenizers, sees the prompt that caused the current rating, and can either report diagnostics or apply a validated prompt repair before encoding.

Added an optional advisor_clip input to FunPack Video Refiner V2 so the advisor can use a separate generative CLIP/Gemma model while the main clip continues handling normal prompt encoding.

[2.4.2] - 2026-05-15

Added

Added Learning mode to FunPack Video Refiner V2. It still observes prompts, conditioning, ratings, phrase memory, and diagnostics, but passes positive and negative prompt conditioning through without prompt repair, Lucky composition, wildcard cleanup, or conditioning-vector adaptation.

Fixed

Fixed FunPack Scene Builder mode handling so the live Mode widget stays independent from the selected saved scene, including queue-time Learning and Auto behavior.

Fixed FunPack Scene Builder rich prompt editing so the caret can move past a final inline phrase chip with the mouse or right arrow key.

[2.4.1] - 2026-05-14

Fixed

Improved FunPack Scene Builder database rows so long words and phrases show their full text as a hover hint, and double-click editing opens a wider multiline field with explicit OK/Cancel buttons.

[2.4.0] - 2026-05-14

Added

Added FunPack Scene Builder, a scene preset node that replaces FunPack Template Manager. It collects universal prompt phrase memory, lets users manually assign positive/negative scene phrases, passes the current LoRA stack through unchanged, and can auto-apply a saved scene from an intent prompt match.

Simplified FunPack Scene Builder so prompt and intent text are connection-only inputs, removed model-mode and per-block controls, and outputs only scene prompt data plus the pass-through FunPack LoRA stack instead of conditioning.

Added Learning mode to FunPack Scene Builder; it records connected prompt phrases into the selected refinement key's scene memory while passing positive prompt, negative prompt, and LoRA stack through unchanged. Refiner reset clears conditioning-delta learning while preserving the refinement key's Scene Builder memory.

Redesigned FunPack Scene Builder as a compact button-driven node with centered editor menus for scene name, mode, aliases, Positive Prompt, Negative Prompt, and Database controls. First use asks for a scene name before editing, connected prompts now teach useful words as well as phrase chunks, the editor refreshes the selected refinement-key database before opening, prompt editors highlight already-used chips, database words can be double-clicked for inline editing, and wildcard random choice is now a checkbox for adjacent entries instead of a text group.

Added searchable LoRA picking to FunPack Apply LoRA Weights. The compact row UI remains the primary workflow, and saved workflows still serialize through the existing lora_list JSON value.

Added optional clip_vision_output, source_image, and negative_prompt inputs to FunPack Video Refiner V2.

Added a final modified_negative conditioning output to FunPack Video Refiner V2. When negative repair has prompt text to encode and CLIP is connected, the node returns repaired negative conditioning; otherwise it returns an empty conditioning list.

Added advisory V2 vision context storage for source image dimensions, aspect ratio bucket, image fingerprint, CLIP Vision tensor summaries, and changed-image detection. Vision context is diagnostic only and is not blended into positive conditioning.

Added experimental early velocity bias capture/application controls to FunPack Hybrid Euler 2S Sampler, defaulting off.

Changed

Removed public registration for FunPack Template Manager. Use FunPack Scene Builder for new scene/preset workflows.

Updated V2 prompt repair so repaired phrases preserve stopwords and phrase text while still using filtered semantic tokens for matching and categorization.

Reduced repeated Refiner V2 CLIP model calls by caching category and phrase encodes within each run.

Updated negative repair to persist poorly rated or wrong-context tags and append them to future negative prompts before encoding negative conditioning.

[2.3.3] - 2026-05-08

Fixed

Fixed Refiner V2 so CLIP and pre-encoded positive_conditioning can both be optional inputs. When CLIP is connected, V2 keeps owning prompt encoding as before. When CLIP is not connected but positive_conditioning is connected, V2 accepts the finished Gemma3/LTX2 conditioning, uses the prompt for analysis, and loads only the Gemma3 tokenizer.

[2.3.2] - 2026-05-08

Added

Added Refiner V2 original-intent alignment memory. When user_intent_prompt stays the same but an enhancer produces different positive_prompt variants, the refiner now remembers intent-enhance pairs, which variants rated well, which original-intent phrases were omitted, and which enhancer-only phrases were rejected.

Fixed

Fixed Refiner V2 so learned original-intent omissions can be restored on later runs, while repeatedly rejected enhancer-only additions can be removed before encoding. Rejected enhancer-only full words and adjacent word pairs are stored as omit evidence for that original intent.

[2.3.1] - 2026-05-08

Fixed

Fixed Refiner V2 Prompt Repair so missing/wrong ratings only repair from the current prompt or explicit user intent, instead of pulling unrelated learned favorite actions, details, quality cues, camera moves, or styles from memory.

Fixed Prompt Repair memory matching so the same word with different neighboring prompt context is treated as different evidence.

Fixed vague raw user intent handling so prompts like Figure it out let the enhanced positive_prompt drive repair matching when available.

[2.3.0] - 2026-05-08

Added

Added Wrong appearance rating to FunPack Video Refiner V2 for outputs contaminated by remembered clothing, character, subject, or background concepts.

Added FunPack Refinement Key Loader, with a selectable key dropdown, create-on-load behavior, and browser-side JSON import/export buttons.

Added a Discord-friendly Refiner V2 quick guide for new users.

Changed

Updated Refiner V2 Prompt Repair so it only auto-adds safe repair concepts such as action, camera, details, quality, and style. Appearance, subject/character, and environment/background concepts are now blocked from Prompt Repair.

Updated I'm Feeling Lucky in Refiner V2 so appearance, subject/character, and environment/background memory is not auto-injected unless the user explicitly includes that phrase in the current prompt.

Updated legacy Void/Lucky token-bank selection to skip appearance, subject/character, and environment/background tokens.

Updated Refiner V2 and FunPack Apply LoRA Weights so both can accept a linked refinement key from FunPack Refinement Key Loader.

Fixed

Fixed appearance bleed-over where highly liked clothing or character tags could reappear in unrelated image-to-video prompts.

[2.2.1] - 2026-05-07

Fixed

Fixed FunPack Video Refiner V2 prompt phrase categorization so environment and appearance descriptions are not pulled into action learning by generic -ing or -ed words.

Updated Refiner V2 category similarity blending so CLIP category comparisons only help uncertain phrases instead of overriding strong local action, camera, appearance, environment, quality, or detail anchors.

Fixed FunPack Video Refiner V2 so prompt-enhancer refusal text like "I'm sorry, I cannot help..." is passed through without being saved into prompt history, phrase memory, or future learning targets.

Improved FunPack Video Refiner V2 training data output with clearer sections and extra line breaks for run state, learning, prompt analysis, adaptation, guidance, and LoRA diagnostics.

Updated FunPack Video Refiner V2 to remember liked action/detail phrase clusters with their neighbors and use those ordered clusters before weaker ngram or token memory when repairing missing axes.

Added Wrong details, Wrong action, and Wrong details + action ratings for good-looking videos that do not match the requested intent; these preserve satisfied quality/composition signals while marking the mismatched action/detail context for repair.

[2.2.0] - 2026-05-07

Added

Added FunPack Video Refiner V2, a simplified prompt-owned refiner that accepts positive_prompt and a connected CLIP, owns prompt encoding internally, learns from ratings, and returns refined positive conditioning plus diagnostics.

Added FunPack Template Manager, a preset node for storing prompts, activation words, refinement keys, sigma schedules, and FunPack LoRA stacks with import/export support.

Added I'm Feeling Lucky mode to FunPack Video Refiner V2. It works as a preference composer that can inject learned user-preferred actions, camera moves, details, and styles even when the current prompt is vague.

Changed

Updated LTX per-block LoRA loading so supported stacks now compare LoRA block fingerprints across the whole stack and apply type-aware conflict balancing before patches are loaded.

Fixed FunPack Hybrid Euler 2S Sampler restart timing so restart_trigger_pct is respected across the full sigma schedule instead of being clamped to the Euler-to-2S quality transition.

Improved FunPack LoRA Loader rerun performance by caching recently used raw LoRA files, model-mapped LoRA patches, and per-block fingerprint analysis.

Reworked FunPack Video Refiner V2 ratings around explicit missing-axis signals: Perfect, single missing axes, paired missing axes, and Awful.

Removed the Refiner V2 mode input. V2 now accepts whatever connected CLIP the workflow provides and stores state in a CLIP-owned namespace.

Renamed visible Refiner and LoRA intent from concept to action. Old Missing concept ratings and old concept LoRA rows are still accepted as compatibility aliases, but V2 stores and displays action.

Updated I'm Feeling Lucky in Refiner V2 so Lucky only composes prompt text when enabled. When disabled, it may train memory from rated runs but does not compose or alter output.

Fixed

Fixed I'm Feeling Lucky token-bank learning for changing prompt/conditioning workflows by falling back to prompt-order token placement when exact tokenizer position matching cannot find enough words.

Fixed I'm Feeling Lucky rating attribution for changing prompts so ratings update the previous prompt's learned tokens while the current prompt seeds new neutral discovery tokens.

Updated I'm Feeling Lucky filtering to learn poor adjacent token pairs instead of refusing individual tokens outright.

Updated I'm Feeling Lucky with uncapped token, pair, and context memory so it can learn which concepts belong together and call strong missing neighbors when prompt anchors are present.

Fixed I'm Feeling Lucky composition order so the current generation uses already-learned memory first, then seeds current prompt tokens for future runs.

Fixed I'm Feeling Lucky memory-first output so vague or empty incoming conditioning can use the longest compatible learned conditioning canvas instead of being limited to the current prompt's shape/content.

Added an optional clip input to FunPack Video Refiner so I'm Feeling Lucky can compose a learned prompt, re-encode it through the connected CLIP/Gemma text encoder, and refine from that freshly tokenized conditioning.

Improved I'm Feeling Lucky runtime by selecting learned conditioning canvases from saved tensor metadata before decoding, capping CLIP/Gemma Lucky prompts to a practical per-run concept count, and decoding only the token vectors selected for the current generation.

Reduced redundant I'm Feeling Lucky work by keeping Lucky runs in one stable memory history, skipping normal prompt-variant conditioning scans while Lucky is active, validating large Lucky memories once per loaded session, and updating context relationships locally instead of writing all-to-all token graphs every run.

Fixed I'm Feeling Lucky CLIP/Gemma re-encode crashes when the encoded Lucky prompt has a different sequence length than the incoming conditioning by resizing the refinement delta before applying it.

Updated I'm Feeling Lucky CLIP/Gemma prompt composition to preserve learned comma/semicolon-separated concept phrases instead of emitting loose word lists when phrase memory is available.

Added Lucky phrase placement memory so learned prompt phrases remember their rated order positions and CLIP/Gemma Lucky prompts can reassemble phrases into a more coherent prompt order instead of sentence salad.

Fixed I'm Feeling Lucky bootstrap learning so sessions that start with Lucky enabled now create a real discovery history entry, seed prompt tokens/phrases, and can learn from ratings without first running the classic refinement loop.

Updated Lucky memory so normal non-Lucky runs still seed reusable token, phrase, context, and placement memory for later Lucky runs.

Updated all missing-axis ratings so Missing details, Missing concept, Missing quality, and paired missing ratings now mark prompt tokens as wanted-but-underrepresented instead of weak neutral feedback; repeated missing feedback reserves Lucky composition room for those tokens and their compatible neighbours.

Fixed Lucky diagnostics so the collapsed Lucky memory stream reports real Lucky update counts and learned memory size instead of implying the session is still prompt 1 out of 1.

Removed

Removed the old public FunPack Video Refiner node, the FunPackGemmaEmbeddingRefiner compatibility alias, and FunPack Save Refinement Latent from the registered node list.

Removed sigma refinement, latent refinement, manual scheduler controls, and feedback-question inputs from the active Refiner workflow. These systems are not part of Refiner V2.

[2.1.3] - 2026-04-24

Changed

FunPack Apply LoRA Weights now has more user-friendly, compact UI.

FunPack Video Refiner now has updated logic to work more stable when provided different prompts and conditioning with each new generation.

[2.1.1] - 2026-04-24

Added

Added -Just forget it- as a Video Refiner rating. Use it when a generation failed for reasons that should not be learned from, such as a broken reference, bad seed, or workflow mistake.

Added category feedback questions for prompt phrases that the refiner cannot confidently classify. The answer scale is general, concept, style, quality, character, and details.

Added a CLIP Vision output combiner node for workflows that need one combined CLIP Vision output from multiple inputs.

Changed

Updated the Video Refiner rating categories so feedback can separate missing details, missing concept, missing quality, and fully failed output instead of treating all bad results the same way.

Reduced repeated category feedback prompts after the user has already answered enough about the same concept.

Refreshed README and refiner docs for 2.1.1.

Fixed

Fixed LoRA weight row restore order when workflows are loaded.

[2.1.0] - 2026-04-23

Added

Added FunPack Apply LoRA Weights and FunPack LoRA Loader, a prompt-exact LoRA weight workflow designed to work with FunPack Video Refiner.

Added FunPack Save Refinement Latent, which stores latent tensor bundles by refinement key for optional latent refinement in FunPack Video Refiner.

Added hidden LTX per-block LoRA redistribution for supported ltx2 model stacks. The UI still exposes normal LoRA weights, while the loader derives per-block strengths from the LoRA patch magnitudes when the model and LoRA layout support it.

The new workflow uses base LoRA weights on the first run for a prompt, then lets the refiner save prompt-specific suggested LoRA weights into its existing JSON state for later runs.

Changed

Renamed the visible refiner title from FunPack Gemma Embedding Refiner to FunPack Video Refiner. The old node key is still available as a compatibility alias.

Split the old single funpack.py implementation into focused modules:

• conditioning.py
• samplers.py
• image_processing.py
• model_management.py

funpack.py remains as a compatibility re-export for older imports.

Updated FunPack Video Refiner so it can accept a FunPack LoRA stack and save next-run model LoRA weight suggestions based on prompt concepts, LoRA type hints, and user ratings.

Updated FunPack Video Refiner with optional latent input/output refinement. If no matching saved latent exists and both latent input and output are connected, the input latent is saved as the first reference and passed through unchanged.

Updated prompt analysis so quoted speech and backslash-wrapped phrases can be protected as whole prompt units.

Documentation

Documented unintended and edge-case usage for the new refiner workflow, including disconnected latent paths, saved-latent-only runs, wrong LTX audio/AV latent connections, exact-prompt LoRA lookup behavior, base-weight mismatch behavior, zero-weight LoRA skipping, and unsupported per-block fallback behavior.

[1.3.3] - 2026-04-22

Changed

Expanded /docs so every node in funpack.py now has matching documentation, and refreshed the existing node docs to match the current inputs and outputs.

[1.3.2] - 2026-04-19

Changed

Changed the core logic of Self-Refiner. Removed obsolete nodes.

[1.3.0 & 1.3.1] - 2026-04-18

Changed

Added new nodes - User Rating and Gemma Self-Refinement for LTX2.3 video workflows.

Fixed

Device type mismatch in new nodes.

[1.2.3] - 2026-01-30

Fixed

Fixed Transformers library error when running Prompt Enhancer and Story Writer nodes.

[1.2.2] - 2026-01-26

Changed

Changed the logic of processing sequences in Story Writer node. Now doesn't append full instructions and previous context to previous messages with each loop iteration, now fully replaces messages with a system prompt and sequence history without appending.

[1.2.1] - 2026-01-24

Added

Added experimental LoRA recommendation feature and Sanity Check features to Story Writer node.

[1.2.0] - 2026-01-23

Added

Added new Story Writer node, based on existing Prompt Enhancer. It generates up to 5 prompts one after another, based on either user's prompt directly, or on the story generated from the user's prompt.

[1.1.0] - 2026-01-02

Added

Added Creative Template and Lorebook Enhancer nodes. The Creative Template is a wildcard-based node that replaces given keywords in the template with ones provided by user. Lorebook Enhancer is a node that takes SillyTavern format .json lorebooks and enhances your prompt by adding required knowledge.

[1.0.0] - 2026-01-01

Initial release on Comfy Registry.