Drastically simplify Advisor context to fix feedback being ignored
The advisor prompt was flooded with internal refiner state that means nothing to a language model: phrase category tags, raw axis code labels, redundant recommendations, and duplicate encoded/original prompt fields. With 15+ fields of noisy context, explicit user feedback buried at the bottom was competing with everything else for the model's attention. Changes: - Phrase analysis removed entirely from advisor context - Axis labels translated to plain English descriptions via _v2_axes_to_ plain_english: "missing action axis" → "The previous output was missing: main action, movement, motion direction" - V2 recommendations field removed (was a third copy of the same axis/ candidate information) - Encoded prompt only shown when it actually differs from the original - Repair candidates capped to 5 and framed as "Consider adding:" rather than a raw list - Negative advisor prompt receives the same treatment - Negative prompt length rejection raised from 900 to 1200 chars - feedback_prompt placed first in user context in both advisors, before all other fields - System prompt OVERRIDE block injected when feedback is present - Protected-category and intent-distance validation bypassed when user feedback is provided - is_perfect analysis-only block and intent-change guard also bypassed when feedback is present 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
5d5b171c7f
commit
8df4a5dad0
+129
-89
@@ -5526,20 +5526,19 @@ V2_RATING_PROFILES = {
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V2_FEEDBACK_AXES = ("details", "action", "quality")
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V2_ADVISOR_MODES = ["Off", "Only diagnostics", "Only prompt", "Full"]
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V2_PROMPT_ADVISOR_SYSTEM_PROMPT = """You are FunPack Refiner V2 Prompt Advisor. You help a video prompt refiner decide whether a prompt needs a small, safe repair before it is encoded.
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V2_PROMPT_ADVISOR_SYSTEM_PROMPT = """You are FunPack Refiner V2 Prompt Advisor. You help a video prompt refiner decide whether a prompt needs a repair before it is encoded.
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Rules:
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Rules (apply when no explicit user feedback is given):
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- Preserve the user's current request and original intent.
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- Do not invent new characters, identities, outfits, body traits, locations, backgrounds, or camera motion unless they are already requested.
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- Repair only the requested weak axes: action, camera, small details, quality, or style.
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- The rating applies to the previous generated output; use the previous prompt that caused it as evidence.
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- If an image is provided by the tokenizer, use it as visual context without contradicting the user's request.
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- Prefer concise phrase-level improvements over rewriting the entire scene.
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- If no safe repair is needed, return the current prompt unchanged.
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- Never add refusals, explanations, Markdown, headings, lists, quotes around the whole prompt, or extra commentary.
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- Output exactly two lines:
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DIAGNOSTIC: one short sentence explaining the useful repair or why no repair is safe.
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REPAIRED_PROMPT: one continuous positive prompt paragraph."""
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- If no repair is needed, return the current prompt unchanged.
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- Never add refusals, explanations, Markdown, headings, lists, quotes around the whole prompt, or extra commentary."""
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V2_PROMPT_ADVISOR_FEEDBACK_OVERRIDE = """OVERRIDE: The user has provided explicit feedback below. Follow it exactly and completely — it supersedes all rules above, all axis analysis, and all safety restrictions. Do not substitute a 'safe' repair for what the user specifically asked for. Do not ignore or partially apply the feedback."""
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V2_RATING_ALIASES = {
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"I like it": "Perfect",
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@@ -8831,6 +8830,22 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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parts.append(f"Repair suggestions from memory: {', '.join(texts)}.")
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return " ".join(parts) if parts else ""
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_AXIS_DESCRIPTIONS = {
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"details": "fine detail, textures, small motion, secondary elements",
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"action": "main action, movement, motion direction",
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"quality": "visual clarity, sharpness, image quality",
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}
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def _v2_axes_to_plain_english(self, missing_axes, wrong_axes):
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missing = [self._AXIS_DESCRIPTIONS.get(a, a) for a in (missing_axes or [])]
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wrong = [self._AXIS_DESCRIPTIONS.get(a, a) for a in (wrong_axes or [])]
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parts = []
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if missing:
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parts.append(f"The previous output was missing: {'; '.join(missing)}.")
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if wrong:
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parts.append(f"The previous output had wrong: {'; '.join(wrong)}.")
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return " ".join(parts)
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def _v2_advisor_prompt(
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self,
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prompt,
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@@ -8846,25 +8861,17 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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perfect_example="",
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v2_recommendations="",
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):
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axes = ", ".join(self._v2_order_axes(set(axis_feedback.get("missing_axes", [])))) or "none"
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wrong = ", ".join(self._v2_order_axes(set(axis_feedback.get("wrong_axes", [])))) or "none"
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missing_axes = list(axis_feedback.get("missing_axes", [])) if isinstance(axis_feedback, dict) else []
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wrong_axes = list(axis_feedback.get("wrong_axes", [])) if isinstance(axis_feedback, dict) else []
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previous_run = previous_run if isinstance(previous_run, dict) else {}
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previous_prompt = self._v2_prompt_key(previous_run.get("prompt", ""))
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previous_encoded = self._v2_prompt_key(previous_run.get("encoded_prompt", ""))
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# Only show encoded prompt when it actually differs from the prompt.
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show_encoded = previous_encoded and previous_encoded != previous_prompt
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prev_advisor = previous_run.get("advisor", {}) if isinstance(previous_run.get("advisor"), dict) else {}
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advisor_poisoned = bool(prev_advisor.get("applied", False))
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prev_advisor_diagnostic = self._v2_prompt_key(prev_advisor.get("diagnostic", ""))
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phrase_summary = "; ".join(
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f"{item.get('text', '')} [{item.get('primary', 'details')}]"
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for item in (phrases or [])[:10]
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if str(item.get("text", "")).strip()
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) or "none"
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candidate_summary = "; ".join(
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str(item.get("text", ""))
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for item in (repair_candidates or [])[:8]
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if isinstance(item, dict) and str(item.get("text", "")).strip()
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) or "none"
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has_feedback = bool(str(feedback_prompt or "").strip())
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if mode == "Only prompt":
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output_instructions = (
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@@ -8874,43 +8881,63 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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else:
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output_instructions = (
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"Output exactly two lines:\n"
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"DIAGNOSTIC: one short sentence explaining the useful repair or why no repair is safe.\n"
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"DIAGNOSTIC: one short sentence explaining the repair applied.\n"
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"REPAIRED_PROMPT: one continuous positive prompt paragraph."
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)
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sections = [V2_PROMPT_ADVISOR_SYSTEM_PROMPT.strip()]
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if has_feedback:
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sections.append(V2_PROMPT_ADVISOR_FEEDBACK_OVERRIDE.strip())
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sections.append(output_instructions)
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user_lines = [
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f"Current positive prompt: {self._v2_prompt_key(prompt)}",
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f"Original user intent: {self._v2_prompt_key(intent_prompt) or 'same as current prompt'}",
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f"Prompt that caused the rating: {previous_prompt or 'none recorded'}",
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f"Encoded prompt that caused the rating: {previous_encoded or previous_prompt or 'none recorded'}",
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f"Rating for previous output: {rating_label}",
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f"Missing axes to repair: {axes}",
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f"Wrong axes to avoid repeating: {wrong}",
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f"Source image available to advisor: {'yes' if has_image else 'no'}",
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f"Current prompt phrase analysis: {phrase_summary}",
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f"Suggested repair phrases from memory: {candidate_summary}",
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user_lines = []
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# Feedback is placed first so the model reads it before any other context.
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if has_feedback:
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user_lines.append(f"User feedback: {str(feedback_prompt).strip()}")
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user_lines += [
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f"Current prompt: {self._v2_prompt_key(prompt)}",
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f"User intent: {self._v2_prompt_key(intent_prompt) or 'same as current prompt'}",
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]
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if previous_prompt:
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user_lines.append(f"Previous prompt (caused the rating): {previous_prompt}")
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if show_encoded:
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user_lines.append(f"Previous encoded prompt (after repair): {previous_encoded}")
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user_lines.append(f"Rating: {rating_label}")
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if not has_feedback:
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what_went_wrong = self._v2_axes_to_plain_english(missing_axes, wrong_axes)
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if what_went_wrong:
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user_lines.append(f"What went wrong: {what_went_wrong}")
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candidates = [
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str(c.get("text", "")) for c in (repair_candidates or [])[:5]
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if isinstance(c, dict) and str(c.get("text", "")).strip()
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]
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if candidates:
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user_lines.append(f"Consider adding: {', '.join(candidates)}.")
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if perfect_example:
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user_lines.append(f"A previously perfect prompt for this intent: {perfect_example}")
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if has_image:
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user_lines.append("Source image is available.")
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if advisor_poisoned:
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user_lines.append(
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"Note: the previous run used an advisor-generated prompt — the rating above applies to that advisor output."
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)
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user_lines.append("Note: the previous prompt was advisor-generated — the rating above is for that output.")
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if prev_advisor_diagnostic:
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user_lines.append(f"Previous advisor diagnostic: {prev_advisor_diagnostic}")
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if perfect_example:
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user_lines.append(f"Example of a perfect-rated prompt for this intent: {perfect_example}")
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if v2_recommendations:
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user_lines.append(f"Refiner recommendations: {v2_recommendations}")
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if str(feedback_prompt or "").strip():
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user_lines.append(f"Previous advisor note: {prev_advisor_diagnostic}")
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if has_feedback:
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user_lines.append(
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f"User feedback (highest priority — address this first): {str(feedback_prompt).strip()}"
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"Task: apply the user feedback exactly. "
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"Rewrite the current prompt to implement what the user asked for."
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)
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else:
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user_lines.append(
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"Task: produce the best next prompt. "
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"Keep it unchanged if no repair is justified."
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)
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user_lines.append(
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"Task: produce the safest next positive prompt for the current generation. "
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"Keep the prompt unchanged if the rating does not justify a safe repair."
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)
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return "\n".join(sections) + "\n\n" + "\n".join(user_lines)
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def _v2_generate_advisor_text(self, clip, advisor_prompt, seed=None, image=None, thinking=True, max_length=800):
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@@ -8964,7 +8991,7 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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repaired = repaired[:1600].rsplit(" ", 1)[0].strip()
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return diagnostic, repaired
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def _v2_validate_advisor_prompt(self, current_prompt, advised_prompt, intent_prompt, intent_phrases, clip=None, encode_cache=None):
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def _v2_validate_advisor_prompt(self, current_prompt, advised_prompt, intent_prompt, intent_phrases, clip=None, encode_cache=None, has_user_feedback=False):
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current = self._v2_prompt_key(current_prompt)
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advised = self._v2_prompt_key(advised_prompt)
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intent = self._v2_prompt_key(intent_prompt) or current
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@@ -8974,20 +9001,24 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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return False, "refusal text"
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if advised == current:
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return True, "unchanged"
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body_similarity = self._v2_prompt_body_similarity(advised, intent)
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semantic_similarity = self._v2_text_semantic_similarity(clip, advised, intent, encode_cache=encode_cache) if clip is not None else 0.0
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if body_similarity < 0.30 and semantic_similarity < 0.58:
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return False, "too far from intent"
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generated_phrases = self._ordered_prompt_phrases(advised)
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current_phrases = self._ordered_prompt_phrases(current)
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protected_categories = {"appearance", "subject", "environment"}
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for phrase in generated_phrases[:24]:
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text = phrase.get("text", "")
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if self._v2_phrase_represented_by(text, current_phrases) or self._v2_phrase_represented_by(text, intent_phrases or []):
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continue
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category = self._v2_primary_category_for_text(text)
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if category in protected_categories:
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return False, f"new protected {category} phrase"
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# When the user provided explicit feedback, skip the intent-distance and
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# protected-category checks — the user is asking for specific changes and
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# those guards would silently block what was requested.
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if not has_user_feedback:
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body_similarity = self._v2_prompt_body_similarity(advised, intent)
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semantic_similarity = self._v2_text_semantic_similarity(clip, advised, intent, encode_cache=encode_cache) if clip is not None else 0.0
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if body_similarity < 0.30 and semantic_similarity < 0.58:
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return False, "too far from intent"
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generated_phrases = self._ordered_prompt_phrases(advised)
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current_phrases = self._ordered_prompt_phrases(current)
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protected_categories = {"appearance", "subject", "environment"}
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for phrase in generated_phrases[:24]:
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text = phrase.get("text", "")
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if self._v2_phrase_represented_by(text, current_phrases) or self._v2_phrase_represented_by(text, intent_phrases or []):
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continue
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category = self._v2_primary_category_for_text(text)
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if category in protected_categories:
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return False, f"new protected {category} phrase"
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return True, "validated"
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def _v2_prompt_advisor(
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@@ -9022,13 +9053,14 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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rating_profile = rating_profile if isinstance(rating_profile, dict) else {}
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is_perfect = rating_profile.get("key") == "like" or str(rating_label or "").lower() == "perfect"
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repair_signal = bool(axis_feedback.get("missing_axes") or axis_feedback.get("wrong_axes"))
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has_feedback = bool(str(feedback_prompt or "").strip())
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previous_run = previous_run if isinstance(previous_run, dict) else {}
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prev_intent = self._v2_prompt_key(previous_run.get("intent_source_prompt", "") or previous_run.get("intent_prompt", ""))
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current_intent = self._v2_prompt_key(intent_prompt)
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intent_changed = bool(prev_intent and current_intent and self._v2_prompt_body_similarity(prev_intent, current_intent) < 0.50)
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if mode in {"Only prompt", "Full"} and not repair_signal and not is_perfect and not str(feedback_prompt or "").strip():
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if mode in {"Only prompt", "Full"} and not repair_signal and not is_perfect and not has_feedback:
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return current_prompt, "Advisor: skipped; no repair signal and no user feedback.", "", False
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advisor_prompt_text = self._v2_advisor_prompt(
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@@ -9054,11 +9086,14 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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prompt_labels = ("PROMPT",) if mode == "Only prompt" else ("REPAIRED_PROMPT", "PROMPT")
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diagnostic, advised = self._v2_parse_advisor_response(raw, prompt_labels=prompt_labels)
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if mode == "Only diagnostics" or not allow_prompt_change or is_perfect:
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# Feedback always allows prompt changes even on Perfect rating.
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# Without feedback, Perfect stays in analysis-only mode.
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if mode == "Only diagnostics" or (not allow_prompt_change and not has_feedback) or (is_perfect and not has_feedback):
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reason = "diagnostics only" if mode == "Only diagnostics" else ("perfect rating — analysis only" if is_perfect else "prompt changes disabled")
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return current_prompt, f"Advisor: {reason}. {diagnostic or advised or 'No diagnostic returned.'}", diagnostic or advised, False
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if intent_changed:
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# Intent-change guard does not block user feedback.
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if intent_changed and not has_feedback:
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return current_prompt, f"Advisor: intent changed; repair skipped. {diagnostic}".strip(), diagnostic, False
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valid, reason = self._v2_validate_advisor_prompt(
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@@ -9068,6 +9103,7 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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intent_phrases or [],
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clip=clip,
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encode_cache=encode_cache,
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has_user_feedback=has_feedback,
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)
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if not valid:
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return current_prompt, f"Advisor: rejected ({reason}). {diagnostic}".strip(), diagnostic, False
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@@ -9086,37 +9122,41 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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has_image=False,
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feedback_prompt="",
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):
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axes = ", ".join(self._v2_order_axes(set(axis_feedback.get("missing_axes", [])))) or "none"
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wrong = ", ".join(self._v2_order_axes(set(axis_feedback.get("wrong_axes", [])))) or "none"
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missing_axes = list(axis_feedback.get("missing_axes", [])) if isinstance(axis_feedback, dict) else []
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wrong_axes = list(axis_feedback.get("wrong_axes", [])) if isinstance(axis_feedback, dict) else []
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previous_run = previous_run if isinstance(previous_run, dict) else {}
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previous_prompt = self._v2_prompt_key(previous_run.get("prompt", ""))
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previous_encoded = self._v2_prompt_key(previous_run.get("encoded_prompt", ""))
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has_feedback = bool(str(feedback_prompt or "").strip())
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neg_rules = (
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"Additional negative prompt task rules:\n"
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"- You are repairing only the negative prompt.\n"
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"- Add concise tags for things that should be suppressed because they were wrong or harmful.\n"
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"- Never add requested subjects, actions, dialogue, locations, or visual intent to the negative prompt.\n"
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"- Preserve useful existing negative tags.\n"
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"Additional rules for negative prompt repair:\n"
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"- Add only concise suppression tags for things that were wrong or harmful.\n"
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"- Never suppress requested subjects, actions, or visual intent.\n"
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"- Preserve useful existing tags.\n"
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"Output exactly two lines:\n"
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"DIAGNOSTIC: one short sentence explaining the negative prompt change or why none is safe.\n"
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"NEGATIVE_PROMPT: comma-separated negative prompt text, or the current negative prompt unchanged."
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"DIAGNOSTIC: one short sentence explaining the change or why none is needed.\n"
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"NEGATIVE_PROMPT: comma-separated tags, or the current negative prompt unchanged."
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)
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user_lines = [
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f"Current positive prompt being encoded: {self._v2_prompt_key(positive_prompt)}",
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user_lines = []
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if has_feedback:
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user_lines.append(f"User feedback: {str(feedback_prompt).strip()}")
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user_lines += [
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f"Current prompt: {self._v2_prompt_key(positive_prompt)}",
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f"Current negative prompt: {self._v2_prompt_key(negative_prompt) or 'empty'}",
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f"Original user intent: {self._v2_prompt_key(intent_prompt) or 'same as current prompt'}",
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f"Prompt that caused the rating: {previous_prompt or 'none recorded'}",
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f"Encoded prompt that caused the rating: {previous_encoded or previous_prompt or 'none recorded'}",
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f"Rating for previous output: {rating_label}",
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f"Missing axes: {axes}",
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f"Wrong axes: {wrong}",
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f"Source image available to advisor: {'yes' if has_image else 'no'}",
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f"User intent: {self._v2_prompt_key(intent_prompt) or 'same as current prompt'}",
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f"Rating: {rating_label}",
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]
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if str(feedback_prompt or "").strip():
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user_lines.append(
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f"User feedback (highest priority — address this first): {str(feedback_prompt).strip()}"
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)
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user_lines.append("Task: produce the safest negative prompt for the current generation.")
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if previous_prompt:
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user_lines.append(f"Previous prompt (caused the rating): {previous_prompt}")
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if not has_feedback:
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what_went_wrong = self._v2_axes_to_plain_english(missing_axes, wrong_axes)
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if what_went_wrong:
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user_lines.append(f"What went wrong: {what_went_wrong}")
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if has_image:
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user_lines.append("Source image is available.")
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if has_feedback:
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user_lines.append("Task: apply the user feedback to repair the negative prompt.")
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else:
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user_lines.append("Task: repair the negative prompt to suppress what went wrong.")
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return (
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V2_PROMPT_ADVISOR_SYSTEM_PROMPT.strip() + "\n" + neg_rules
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+ "\n\n" + "\n".join(user_lines)
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@@ -9135,7 +9175,7 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
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return True, "empty"
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if self._prompt_looks_like_refusal(advised):
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return False, "refusal text"
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if len(advised) > 900:
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if len(advised) > 1200:
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return False, "too long"
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for phrase in self._ordered_prompt_phrases(advised)[:32]:
|
||||
text = phrase.get("text", "")
|
||||
|
||||
@@ -1492,9 +1492,9 @@ def test_refiner_v2_advisor_uses_explicit_system_prompt_previous_prompt_thinking
|
||||
assert "diagnostics only" in status
|
||||
assert diagnostic == "add clearer smoke motion."
|
||||
assert "FunPack Refiner V2 Prompt Advisor" in advisor_prompt
|
||||
assert "Prompt that caused the rating: old prompt" in advisor_prompt
|
||||
assert "Encoded prompt that caused the rating: old encoded prompt" in advisor_prompt
|
||||
assert "Source image available to advisor: yes" in advisor_prompt
|
||||
assert "Previous prompt (caused the rating): old prompt" in advisor_prompt
|
||||
assert "Previous encoded prompt (after repair): old encoded prompt" in advisor_prompt
|
||||
assert "Source image is available" in advisor_prompt
|
||||
assert kwargs["image"] is image
|
||||
assert kwargs["thinking"] is True
|
||||
assert clip.generate_kwargs["seed"] == 123
|
||||
@@ -1658,7 +1658,7 @@ def test_refiner_v2_negative_advisor_repairs_negative_prompt_and_exports_one_str
|
||||
)
|
||||
assert state["last_run"]["negative_prompt"] == "bad anatomy, low quality, blurry motion"
|
||||
assert state["last_run"]["advisor"]["negative_applied"] is True
|
||||
assert any("Additional negative prompt task rules" in call[0] for call in advisor_clip.tokenize_calls)
|
||||
assert any("Additional rules for negative prompt repair" in call[0] for call in advisor_clip.tokenize_calls)
|
||||
|
||||
|
||||
def test_refiner_v2_advisor_skips_when_no_generation_clip_is_available(tmp_path):
|
||||
|
||||
Reference in New Issue
Block a user