Remove negative conditioning output and input from Refiner V2
- Drop CONDITIONING 5th return slot (modified_negative) and the negative_prompt optional input entirely. - Remove all negative encoding, repair, and advisor call sites from the processing path. - Strip negative_* fields from saved prompt_history and last_run state. - Update status strings and _v2_encoded_prompts_output (positive only). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
digital-garbage
co-authored by
Claude Sonnet 4.6
Claude Sonnet 4.6
parent
d4ef898299
commit
e47b92a5ad
+7
-51
@@ -5606,8 +5606,8 @@ def normalize_refiner_v2_rating(value):
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class FunPackVideoRefinerV2(FunPackVideoRefiner):
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CATEGORY = "FunPack/Refinement"
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RETURN_TYPES = ("CONDITIONING", "STRING", "STRING", "IMAGE", "CONDITIONING", "STRING")
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RETURN_NAMES = ("modified_positive", "status", "training_info", "loss_graph", "modified_negative", "encoded_prompts")
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RETURN_TYPES = ("CONDITIONING", "STRING", "STRING", "IMAGE", "STRING")
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RETURN_NAMES = ("modified_positive", "status", "training_info", "loss_graph", "encoded_prompts")
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FUNCTION = "refine_v2"
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DESCRIPTION = "Prompt-owned Video Refiner V2. Encodes through the connected CLIP, learns from ratings, and writes LoRA suggestions without sigma/latent/feedback systems."
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@@ -5747,11 +5747,6 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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"source_image": ("IMAGE", {
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"tooltip": "Optional original/source image or frame batch. V2 stores size, aspect ratio, and a simple fingerprint to notice changed inputs.",
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}),
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"negative_prompt": ("STRING", {
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"multiline": True,
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"default": "",
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"tooltip": "Optional negative prompt. V2 can persistently add poorly rated tags and return repaired negative conditioning.",
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}),
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"refinement_key_input": ("STRING", {
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"default": "",
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"multiline": False,
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@@ -9255,11 +9250,8 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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return negative_prompt, f"Negative advisor: no change. {diagnostic}".strip(), diagnostic, False
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return advised, f"Negative advisor: applied. {diagnostic}".strip(), diagnostic, True
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def _v2_encoded_prompts_output(self, positive_prompt, negative_prompt):
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return (
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f"Positive prompt: {str(positive_prompt or '').strip()}\n\n"
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f"Negative prompt: {str(negative_prompt or '').strip()}"
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)
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def _v2_encoded_prompts_output(self, positive_prompt):
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return f"Positive prompt: {str(positive_prompt or '').strip()}"
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def _v2_scene_builder_category_for_entry(self, entry):
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category = str(entry.get("primary", "") if isinstance(entry, dict) else "").lower()
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@@ -9884,7 +9876,7 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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def refine_v2(self, positive_prompt, clip=None, rating="Missing action", refinement_key="",
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seed=0, reset_session=False, lora_stack=None, im_feeling_lucky=False, user_intent_prompt="",
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refinement_key_input="", positive_conditioning=None, clip_vision_output=None,
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source_image=None, negative_prompt="", mode="Refine", advisor_mode="Off", advisor_thinking=True,
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source_image=None, mode="Refine", advisor_mode="Off", advisor_thinking=True,
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advisor_clip=None, feedback_prompt="", prompt_repair=True):
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if seed != 0:
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torch.manual_seed(seed)
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@@ -10030,9 +10022,6 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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advisor_status = "Advisor: off."
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advisor_diagnostic = ""
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advisor_applied = False
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negative_advisor_status = "Negative advisor: off."
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negative_advisor_diagnostic = ""
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negative_advisor_applied = False
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feedback_history = ""
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advisor_rating_label = rating_label
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if current_prompt_refusal:
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@@ -10162,20 +10151,15 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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status,
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training_info,
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fallback_graph,
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[],
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self._v2_encoded_prompts_output(prompt_to_encode, negative_prompt),
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self._v2_encoded_prompts_output(prompt_to_encode),
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)
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if learning_mode:
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refined = cond
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adaptation_status = "Adaptation: Learning mode; conditioning vectors passed through unchanged."
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repaired_negative_prompt = str(negative_prompt or "")
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negative_repair_status = "Negative repair: skipped in Learning mode."
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elif prompt_only_mode:
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refined = cond
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adaptation_status = "Adaptation: Prompt only mode; conditioning vectors passed through unchanged."
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repaired_negative_prompt = str(negative_prompt or "")
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negative_repair_status = "Negative repair: skipped."
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else:
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refined, adaptation_status = self._v2_apply_conditioning_memory(
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cond,
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@@ -10184,20 +10168,6 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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repair_feedback,
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intent_family_slot=current_family_slot,
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)
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repaired_negative_prompt = str(negative_prompt or "")
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negative_repair_status = "Negative repair: skipped."
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negative_conditioning = []
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negative_encode_status = "negative prompt empty"
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if repaired_negative_prompt and clip is not None:
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negative_cond, negative_meta, negative_encode_status = self._v2_encode_prompt(
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clip,
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repaired_negative_prompt,
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encode_cache=encode_cache,
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)
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if isinstance(negative_cond, torch.Tensor):
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negative_conditioning = [(negative_cond, negative_meta)]
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elif repaired_negative_prompt:
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negative_encode_status = "negative prompt available but CLIP missing"
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prompt_key = self._v2_prompt_key(analysis_prompt)
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prompt_history = None
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if current_prompt_refusal:
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@@ -10277,7 +10247,6 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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"rating_label": rating_label if has_previous_run else "Unrated",
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"encoded_role": encoded_role,
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"prompt": prompt_to_encode,
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"negative_prompt": repaired_negative_prompt,
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"phrases": phrases,
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"repair_candidates": state_repair_candidates,
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"vision_context": vision_context,
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@@ -10287,9 +10256,6 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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"status": advisor_status,
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"diagnostic": advisor_diagnostic,
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"applied": bool(advisor_applied),
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"negative_status": negative_advisor_status,
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"negative_diagnostic": negative_advisor_diagnostic,
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"negative_applied": bool(negative_advisor_applied),
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},
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})
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@@ -10314,12 +10280,8 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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"status": advisor_status,
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"diagnostic": advisor_diagnostic,
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"applied": bool(advisor_applied),
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"negative_status": negative_advisor_status,
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"negative_diagnostic": negative_advisor_diagnostic,
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"negative_applied": bool(negative_advisor_applied),
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},
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"repair_candidates": state_repair_candidates,
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"negative_prompt": repaired_negative_prompt,
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"vision_context": vision_context,
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"encoded_role": encoded_role,
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"auto_injected_prompt_additions": [
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@@ -10357,8 +10319,6 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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f"\n{repair_status}"
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f"\n{advisor_status}"
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f"\n{wildcard_status}"
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f"\n{negative_repair_status}"
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f"\n{negative_advisor_status}"
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f"\n{vision_status}"
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f"{refusal_status_line}"
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)
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@@ -10406,9 +10366,6 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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f"{repair_status}\n"
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f"{advisor_status}\n"
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f"{wildcard_status}\n"
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f"{negative_repair_status}\n"
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f"{negative_advisor_status}\n"
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f"Negative encode: {negative_encode_status}\n"
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f"{vision_status}"
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f"{refusal_status_line}"
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),
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@@ -10426,8 +10383,7 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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status,
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training_info,
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loss_graph,
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negative_conditioning,
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self._v2_encoded_prompts_output(prompt_to_encode, repaired_negative_prompt),
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self._v2_encoded_prompts_output(prompt_to_encode),
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)
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