Release 2.5.1 - docs, changelog, version bump

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

CHANGELOG.md

@@ -1,5 +1,35 @@
 # Changelog
 
+## [2.5.1] - 2026-05-16
+
+### Added
+
+Added `FunPackAdvisorLLM` node. Loads any HuggingFace CausalLM (including sharded checkpoints) as an advisor for Refiner V2. Connect the output to `advisor_clip`. Model is cached after first load so subsequent runs do not reload. Also fully compatible with the built-in `TextGenerate` and `TextGenerateLTX2Prompt` nodes - supports `skip_template`, `min_p`, `presence_penalty`, and progressive fallback for unsupported generation parameters.
+
+Added `_v2_direction_readout` to training_info Adaptation section. Shows each direction memory slot in plain language: run count, magnitude, whether it is in direction mode or lerp fallback, and the role each axis is playing this run.
+
+### Changed
+
+Advisor prompt format rewritten to natural language. Both the repair and analysis user messages now read as plain enhancement requests rather than structured field-value pairs. Works with enhancement-type models (Sulphur, Qwen prompt enhancers) as well as instruction-following models. System prompt reduced to one sentence.
+
+Direction-based conditioning now uses `max_new_tokens` instead of `max_length` in the `FunPackAdvisorLLM` wrapper so prompt length does not eat into the generation budget.
+
+Model patch status expanded to show which direction slots are active with run counts and which phrase texts are being emphasized in cross-attention.
+
+Adaptation status block rewritten to multi-line readable format showing strength, reward trend, streak, per-slot mode (direction vs lerp fallback), and axis adjustments applied this run.
+
+### Fixed
+
+Fixed `_v2_generate_advisor_text` returning `None` when layer 1 tokenization succeeded - `generate`/`decode`/`return` were inside the `except TypeError` block so they only ran when layer 1 failed.
+
+Fixed session reset not clearing `intent_expansion_memory`, `session_source_mean_count`, `liked_dir`, and `bad_dir` - these fields were missing from `_v2_empty_state` and survived reset via `setdefault`.
+
+Fixed advisor repetition loops: `repetition_penalty` raised from 1.05 to 1.3, added `no_repeat_ngram_size=5`, temperature raised from 0.5 to 0.7.
+
+Fixed system prompt bleeding into advisor output by splitting prompts into `(system, user)` tuples and applying the model's native chat template. Three-layer fallback: native `system_prompt` kwarg, manual `apply_chat_template` via BFS, flat string with completion anchor.
+
+Added persistent cross-run encode cache (`_V2_PERSISTENT_ENCODE_CACHE`, 4096 entry cap) so phrase encodings are not recomputed every run when CLIP and text are unchanged.
+
 ## [2.5.0] - 2026-05-15
 
 ### Added

README.md

@@ -2,6 +2,18 @@
 
 A set of ComfyUI nodes for experimenting with video generation workflows based on WAN, HunyuanVideo, LTX, and similar models.
 
+## Updates in 2.5.1
+
+Added `FunPack Advisor LLM` node - loads any HuggingFace CausalLM (sharded or single-file) as an advisor for Refiner V2 or as a drop-in replacement for the built-in `TextGenerate` node. Set a HuggingFace repo ID or local path, pick dtype, connect the output to `advisor_clip`. Model is cached after first load. Compatible with `skip_template`, `min_p`, `presence_penalty`, and any model architecture that `AutoModelForCausalLM.from_pretrained` supports.
+
+Advisor prompt format rewritten to plain natural language so enhancement-type models (Sulphur, Qwen prompt enhancers) produce useful output rather than ignoring structured field-value instructions. System prompt reduced to one sentence.
+
+Training info Adaptation section now shows direction memory in plain language: run count per slot, magnitude, whether each axis is in direction mode or lerp fallback, and what was applied this run. Model patch status shows which directions were injected into cross-attention and which phrase texts are being emphasized.
+
+Fixed several bugs: advisor returning None when tokenization succeeded (generate was inside the wrong branch), session reset not clearing newer memory fields, system prompt bleeding into advisor output, and repetition loops from the 1.05 penalty being too weak for 8B+ models.
+
+Added persistent cross-run encode cache so phrase encodings are not recomputed every run.
+
 ## Updates in 2.5.0
 
 Added a two-pass CLIP text-generation advisor to `FunPack Video Refiner V2`. Pass 1 analyses what specifically needs to change in the suggested prompt. Pass 2 applies those findings. The advisor uses a structured input format — `ORIGINAL_USER_INTENT`, `LAST_PROMPT`, `RATING`, and `OPTIONAL_NOTE` — so the model knows exactly what failed and what to fix. Token budget: 1200 tokens for analysis, 1600 for repair.

pyproject.toml

@@ -2,7 +2,7 @@
 [project]
 name = "ComfyUI-FunPack" # Unique identifier for your node. Immutable after creation.
 description = "A set of nodes for experiments with video generation models, including prompt refinement, adaptive LoRA weight workflows, story tools, video stitching, lorebook enhancement and more."
-version = "2.4.2" # Custom Node version. Must be semantically versioned.
+version = "2.5.1" # Custom Node version. Must be semantically versioned.
 license = { text = "GNU GPL v3" }
 dependencies  = [] # Filled in from requirements.txt