From 2ace4dc4d7239f8a0ccf2601ff2ddb5ccbc4bfb8 Mon Sep 17 00:00:00 2001 From: digital-garbage <133010426+digital-garbage@users.noreply.github.com> Date: Sat, 1 Aug 2026 18:14:07 +0300 Subject: [PATCH] maint: remove dead refiner-state template cluster conditioning_from_refiner + its four exclusive helpers (load_refiner_state, choose_prompt_history, best_history_conditioning, prompt_key_for_refiner). Closed cluster: the only references to any of them were from each other. Checked: 1 occurrence each repo-wide (grep -a, incl. NUL-byte frontend files), not a route handler, not in NODE_CLASS_MAPPINGS, not an INPUT_TYPES widget, no getattr/setattr or monkey-patch use, 0 refs in ComfyUI core and FunUI. Tests: 22 failed / 460 passed, identical to baseline. Co-Authored-By: Claude Opus 5 --- templates.py | 94 ---------------------------------------------------- 1 file changed, 94 deletions(-) diff --git a/templates.py b/templates.py index 6641d69c..b0cdafa5 100644 --- a/templates.py +++ b/templates.py @@ -1073,108 +1073,14 @@ def resolve_wildcards(text, seed=0): return current -def prompt_key_for_refiner(prompt, mode): - del mode - return re.sub(r"\s+", " ", str(prompt or "").strip()) -def load_refiner_state(refinement_key, mode): - if not refinement_key: - return None, "No refinement key stored." - candidates = ( - (refinement_state_path(refinement_key, "clip", prefix="refine_v2"), "V2 refiner state"), - (refinement_state_path(refinement_key, mode), "legacy refiner state"), - ) - for path, label in candidates: - if not os.path.exists(path): - continue - try: - with open(path, "r", encoding="utf-8") as file: - data = json.load(file) - if isinstance(data, dict): - data["_funpack_state_label"] = label - return data, f"{label} loaded for key '{refinement_key}'." - except (json.JSONDecodeError, OSError, ValueError): - return None, f"{label} for key '{refinement_key}' is unreadable." - return None, f"No refiner state found for key '{refinement_key}'." -def choose_prompt_history(data, prompt, mode): - prompt_histories = data.get("prompt_histories", {}) if isinstance(data, dict) else {} - if not isinstance(prompt_histories, dict) or not prompt_histories: - return None, "", "No prompt histories in refiner state." - - prompt_key = prompt_key_for_refiner(prompt, mode) - if prompt_key in prompt_histories and isinstance(prompt_histories[prompt_key], dict): - return prompt_histories[prompt_key], prompt_key, "Matched exact prompt history." - - last_key = data.get("last_prompt_key") if isinstance(data, dict) else None - if isinstance(last_key, str) and isinstance(prompt_histories.get(last_key), dict): - return prompt_histories[last_key], last_key, "Used latest prompt history." - - for key, history in prompt_histories.items(): - if isinstance(history, dict): - return history, key, "Used first available prompt history." - - return None, "", "No usable prompt history found." -def best_history_conditioning(history): - if not isinstance(history, dict): - return None, "No prompt history selected." - - liked = history.get("liked_reference_embeds") - if liked is not None and int(history.get("liked_reference_count", 0) or 0) > 0: - return liked, "Loaded liked-average conditioning." - - best_entry = None - best_score = None - for entry in history.get("history", []): - if not isinstance(entry, dict) or entry.get("modified_embeds") is None: - continue - profile = normalize_refiner_rating(entry.get("rating_label", entry.get("rating", 0))) - score = ( - int(profile.get("level", 0)), - float(profile.get("reward", 0.0)), - int(entry.get("iteration", 0)), - ) - if best_score is None or score > best_score: - best_entry = entry - best_score = score - if best_entry is not None: - return best_entry.get("modified_embeds"), "Loaded best-rated history conditioning." - - reference = history.get("reference_embeds") or history.get("source_conditioning_embeds") - if reference is not None: - return reference, "Loaded stored reference conditioning." - - return None, "No conditioning data found in selected history." -def conditioning_from_refiner(refinement_key, mode, prompt): - data, state_status = load_refiner_state(refinement_key, mode) - if data is None: - return None, state_status - - history, _, history_status = choose_prompt_history(data, prompt, mode) - serialized, conditioning_status = best_history_conditioning(history) - if serialized is None and isinstance(data, dict): - global_state = data.get("global") if isinstance(data.get("global"), dict) else {} - if isinstance(global_state.get("liked_conditioning"), dict): - serialized = global_state.get("liked_conditioning") - conditioning_status = "Loaded V2 liked-average conditioning." - elif isinstance(data.get("last_run"), dict) and isinstance(data["last_run"].get("conditioning"), dict): - serialized = data["last_run"].get("conditioning") - conditioning_status = "Loaded V2 latest-run conditioning." - if serialized is None: - return None, f"{state_status} {history_status} {conditioning_status}" - - try: - tensor = serializable_to_tensor(serialized) - except Exception as error: - return None, f"{state_status} {history_status} Failed to restore conditioning: {error}" - - return [(tensor, {"pooled_output": None})], f"{state_status} {history_status} {conditioning_status}" def template_field_summary(template):