Add H3 prompt curator
This commit is contained in:
@@ -56,6 +56,13 @@
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- Output: `prompt`
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- Builds one H3 prompt block per beat, with quick controls for per-shot timing, continuity, ref behavior, anchor additions, soundscape, and music while staying compatible with direct text editing.
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- `Dumas H3 Prompt Curator`
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- Inputs: `action_prompt`, `anatomy_guard`, optional `anchor`, optional `soundscape`, optional `ref_1` through `ref_9`
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- Outputs: `prompt`, `ref_image_1` through `ref_image_9`, `reference_count`, `debug`
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- Builds one standalone MiniMax H3 prompt from your final action text plus structured character/location references.
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- The action text can mention references by character/location name, alias, `<Picture N>`, or `<refN>`. Only mentioned references are emitted, and the output images are compacted/renumbered so skipped inputs do not leave gaps.
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- Adds curated reference context, optional anatomy guard text, anchor/style text, and `overall_soundscape:` text while respecting MiniMax H3's reference-generation shape: one prompt plus up to nine reference images.
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- `Dumas H3 Shot Length`
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- Inputs: `shot_seconds`, `fps`, optional `cap_to_h3_max`
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- Outputs: `seconds`, `frames`, `info`
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@@ -93,6 +100,11 @@
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- The preset wording is tuned for H3-safe persistent anchors: camera language, lighting, texture, production treatment, and tone, without naming characters or describing one-off actions.
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- Selecting a preset fills the editable description field, and the edited multiline description is the `STRING` value passed downstream into H3 anchor sockets such as `anchor_override`.
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- `Dumas Soundscape Helper`
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- Inputs: `soundscape`, `soundscape_description`
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- Output: `soundscape`
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- Matching soundscape helper for standalone H3 prompts. Pick a preset such as quiet interior, rainy street, cafe, city night, forest, industrial, or silent, then edit the text that flows into `Dumas H3 Prompt Curator`.
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- `Dumas JSON String to Object`
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- Input: `json_string`
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- Output: parsed `JSON`
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@@ -249,7 +261,7 @@ decr -> use index - 1
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`Dumas H3 Plan Attach Scene Images` and `Dumas H3 Plan Extract Scene Images` are a companion pair for `ComfyUI-MiniMaxH3-Contex-Loop` and the local `ref2v` lane. The upstream H3 plan node cannot dynamically grow nine new image sockets for every JSON-defined scene, so Dumas stores scene image bindings beside the plan using a lightweight token and an in-memory registry. That keeps `plan.json` archiving intact while still letting you wire up nine IMAGE sockets per scene through chained helper nodes.
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`Dumas Character Helper` is the restored two-image/text helper for general H3 workflows, and `Dumas Location Helper` mirrors it for scene/environment references. The structured `Dumas Character Reference` and `Dumas Location Reference` nodes remain available separately for workflows that still want a single `REFERENCE` socket.
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`Dumas Character Helper` is the restored two-image/text helper for general H3 workflows, and `Dumas Location Helper` mirrors it for scene/environment references. The structured `Dumas Character Reference` and `Dumas Location Reference` nodes remain available separately for workflows that want a single `REFERENCE` socket. `Dumas H3 Prompt Curator` consumes those structured references, assigns the final `<Picture N>` numbering, and outputs only the compacted images the prompt actually mentions.
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`Dumas Strip Iteration Suffix` keeps the part before the first underscore and drops the rest. Names like `char123_pose_final.png` become `char123.png`, while names with no underscore such as `char123.png` are left untouched.
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@@ -27,6 +27,15 @@ _H3_PLAN_IMAGE_BINDINGS_CAP = 128
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_H3_PLAN_IMAGE_SLOTS = 9
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_FOLDER_IMAGE_EXTS = (".png", ".jpg", ".jpeg", ".webp", ".bmp", ".gif", ".tiff", ".tif")
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_ANCHOR_STYLE_H3_NOTE = ""
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_H3_PROMPT_REF_SLOTS = 9
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_H3_PROMPT_MAX_CHARS = 7000
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_PICTURE_TAG_RE = re.compile(r"<\s*picture[\s_\-]*(\d+)\s*>", re.I)
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_REF_TAG_RE = re.compile(r"<\s*ref[\s_\-]*(\d+)\s*>", re.I)
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_ANATOMY_GUARD_TEXT = (
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"Each person has one head, two arms, two hands with five fingers on each hand, "
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"and two legs with two feet. Limbs stay attached to the correct body and move "
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"only with the person they belong to."
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)
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_ANCHOR_STYLE_PRESETS = OrderedDict(
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[
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(
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@@ -346,6 +355,47 @@ _ANCHOR_STYLE_PRESETS = OrderedDict(
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),
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]
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)
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_SOUNDSCAPE_PRESETS = OrderedDict(
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[
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(
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"quiet interior",
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"quiet indoor room tone, faint ventilation and distant household ambience",
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),
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(
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"rainy street",
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"steady rain, wet pavement, distant traffic hum",
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),
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(
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"cafe",
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"low room tone, faint glassware, cutlery, and muted conversation",
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),
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(
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"city night",
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"distant traffic hum, occasional horn, night air",
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),
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(
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"forest",
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"wind in leaves, distant birds, soft natural ambience",
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),
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(
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"industrial",
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"large interior reverb, distant metal ticks, low machine hum",
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),
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(
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"silent",
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"no dialogue, no vocals, only the natural ambient bed of the scene",
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),
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("custom", ""),
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]
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)
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def _soundscape_options():
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return list(_SOUNDSCAPE_PRESETS.keys())
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def _soundscape_description(soundscape_name):
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return _SOUNDSCAPE_PRESETS.get(soundscape_name, "")
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_LOAD_IMAGES_FOLDER_DEFAULT_STATE = {
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"version": 1,
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"folder": "",
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@@ -920,6 +970,206 @@ def normalize_reference(value, picture_id=None, allow_image_fallback=True):
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)
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def _reference_text(value):
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return " ".join(str(value or "").split()).strip()
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def _reference_sentence(value):
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text = _reference_text(value)
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if text and text[-1] not in ".!?":
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text += "."
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return text
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def _reference_name_keys(ref):
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names = []
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for key in ("name", "id"):
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value = _reference_text(ref.get(key))
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if value:
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names.append(value)
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for alias in ref.get("aliases") or []:
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value = _reference_text(alias)
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if value:
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names.append(value)
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seen = set()
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out = []
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for name in names:
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key = name.lower()
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if key in seen:
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continue
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seen.add(key)
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out.append(name)
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return out
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def _reference_image(ref):
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if not isinstance(ref, dict):
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return None
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return ref.get("image")
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def _normalize_prompt_refs(raw_refs):
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refs = []
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for slot_number, raw in enumerate(raw_refs or (), 1):
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if raw is None:
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refs.append(None)
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continue
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try:
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ref = normalize_reference(raw, picture_id=slot_number, allow_image_fallback=False)
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except Exception:
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refs.append(None)
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continue
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if _reference_image(ref) is None:
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refs.append(None)
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else:
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refs.append(ref)
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return refs
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def _explicit_reference_tags(text):
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return sorted(
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{
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int(match.group(1))
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for pattern in (_PICTURE_TAG_RE, _REF_TAG_RE)
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for match in pattern.finditer(text or "")
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}
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)
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def _name_matches_reference(text, ref):
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haystack = str(text or "")
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for name in _reference_name_keys(ref):
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if re.search(r"\b" + re.escape(name) + r"\b", haystack, re.I):
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return True
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return False
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def _selected_prompt_refs(action_prompt, refs):
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selected = []
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seen_slots = set()
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for slot_number in _explicit_reference_tags(action_prompt):
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if not (1 <= slot_number <= len(refs)):
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continue
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ref = refs[slot_number - 1]
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if ref is None:
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continue
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selected.append((slot_number, ref))
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seen_slots.add(slot_number)
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for slot_number, ref in enumerate(refs, 1):
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if slot_number in seen_slots or ref is None:
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continue
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if _name_matches_reference(action_prompt, ref):
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selected.append((slot_number, ref))
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seen_slots.add(slot_number)
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return selected
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def _replace_reference_tags(text, picture_map):
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def repl(match):
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original = int(match.group(1))
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compacted = picture_map.get(original)
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if compacted is None:
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return ""
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return f"<Picture {compacted}>"
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rewritten = _PICTURE_TAG_RE.sub(repl, str(text or ""))
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rewritten = _REF_TAG_RE.sub(repl, rewritten)
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return re.sub(r"[ \t]{2,}", " ", rewritten).strip()
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def _reference_fact_sentence(ref, label):
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if ref.get("kind") != "character":
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return ""
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facts = dict(ref.get("facts") or {})
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bits = []
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aliases = [_reference_text(alias) for alias in (ref.get("aliases") or []) if _reference_text(alias)]
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if aliases:
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bits.append(f"also known as {aliases[0]}")
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for key in ("gender", "nationality", "occupation"):
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value = _reference_text(facts.get(key))
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if value:
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bits.append(value if key != "occupation" else f"works as {value}")
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age = _parse_positive_int(facts.get("age"))
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if age is not None:
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bits.append(f"{age} years old")
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feet = _reference_text(facts.get("height_feet"))
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inches = _reference_text(facts.get("height_inches"))
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if feet and inches:
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bits.append(f"{feet} foot {inches} tall")
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elif feet:
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bits.append(f"{feet} foot tall")
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accent = _reference_text(facts.get("accent"))
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if accent:
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bits.append(f"speaks with a {accent} accent")
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if not bits:
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return ""
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return f"Character facts for {label}: " + ", ".join(bits) + "."
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def _reference_context(ref, compact_picture_number):
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label_name = _reference_text(ref.get("name")) or _reference_text(ref.get("id")) or "this reference"
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label = f"<Picture {compact_picture_number}> {label_name}"
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parts = [_reference_sentence(_reference_summary(ref.get("kind"), label_name, compact_picture_number))]
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description = _reference_sentence(ref.get("description"))
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wardrobe = _reference_sentence(ref.get("wardrobe"))
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general = _reference_sentence(ref.get("general"))
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facts = _reference_fact_sentence(ref, label)
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if ref.get("kind") == "location":
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if description:
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parts.append(f"Location context for {label}: {description}")
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if general:
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parts.append(f"Location notes for {label}: {general}")
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else:
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if facts:
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parts.append(facts)
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if description:
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parts.append(f"Persistent appearance for {label}: {description}")
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if wardrobe:
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parts.append(f"Persistent wardrobe/style for {label}: {wardrobe}")
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if general:
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parts.append(f"Character notes for {label}: {general}")
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return " ".join(part for part in parts if part).strip()
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def _append_prompt_section(parts, label, text):
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clean = _reference_text(text)
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if clean:
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parts.append(f"{label}: {clean}")
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def curate_h3_prompt(action_prompt, anchor="", soundscape="", refs=(), anatomy_guard="auto"):
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normalized_refs = _normalize_prompt_refs(refs)
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selected = _selected_prompt_refs(action_prompt, normalized_refs)
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picture_map = {slot_number: index for index, (slot_number, _ref) in enumerate(selected, 1)}
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action = _replace_reference_tags(action_prompt, picture_map)
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prompt_parts = []
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_append_prompt_section(prompt_parts, "Scene anchor", anchor)
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if selected:
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contexts = [_reference_context(ref, picture_number) for picture_number, (_slot, ref) in enumerate(selected, 1)]
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_append_prompt_section(prompt_parts, "Reference context", " ".join(contexts))
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_append_prompt_section(prompt_parts, "Action", action)
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if anatomy_guard == "on" or (anatomy_guard == "auto" and any(ref.get("kind") == "character" for _slot, ref in selected)):
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_append_prompt_section(prompt_parts, "Anatomy guard", _ANATOMY_GUARD_TEXT)
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_append_prompt_section(prompt_parts, "overall_soundscape", soundscape)
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prompt = "\n\n".join(prompt_parts).strip()
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if len(prompt) > _H3_PROMPT_MAX_CHARS:
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prompt = prompt[: _H3_PROMPT_MAX_CHARS - 3].rstrip() + "..."
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images = [_reference_image(ref) for _slot, ref in selected]
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images.extend([None] * (_H3_PROMPT_REF_SLOTS - len(images)))
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debug = (
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f"Selected {len(selected)} reference(s): "
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+ ", ".join(
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f"input {slot}-><Picture {index}> {_reference_text(ref.get('name')) or ref.get('id')}"
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for index, (slot, ref) in enumerate(selected, 1)
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)
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if selected
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else "Selected 0 references."
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)
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return (prompt, *images[:_H3_PROMPT_REF_SLOTS], len(selected), debug)
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def _parse_positive_int(value):
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text = str(value or "").strip()
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if not text:
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@@ -2163,6 +2413,154 @@ class DumasLocationReferenceNode:
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)
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class DumasSoundscapeHelperNode:
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DESCRIPTION = (
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"Choose a soundscape preset, auto-fill its editable description, and pass "
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"the final soundscape text downstream for MiniMax H3 prompts."
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)
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("soundscape",)
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FUNCTION = "build_soundscape"
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CATEGORY = "Dumas/MiniMax"
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@classmethod
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def INPUT_TYPES(cls):
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default_soundscape = "quiet interior"
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return {
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"required": {
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"soundscape": (
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_soundscape_options(),
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{
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"default": default_soundscape,
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"tooltip": "Preset title used to seed the editable soundscape description.",
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},
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),
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"soundscape_description": (
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"STRING",
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{
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"default": _soundscape_description(default_soundscape),
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"multiline": True,
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"tooltip": (
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"Editable environmental audio description. Whatever text is here "
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"is what the node outputs to the soundscape socket."
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),
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},
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),
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}
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}
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def build_soundscape(self, soundscape, soundscape_description):
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text = str(soundscape_description or "").strip()
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if not text:
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text = _soundscape_description(soundscape)
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return (text,)
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class DumasH3PromptCuratorNode:
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DESCRIPTION = (
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"Curate one MiniMax H3 prompt from an action textbox, anchor text, "
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"soundscape text, and up to nine structured references. References are "
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"compacted so only mentioned names, aliases, or explicit <Picture N>/<refN> "
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"tags are sent onward."
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)
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RETURN_TYPES = ("STRING",) + ("IMAGE",) * _H3_PROMPT_REF_SLOTS + ("INT", "STRING")
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RETURN_NAMES = (
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"prompt",
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"ref_image_1",
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"ref_image_2",
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"ref_image_3",
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"ref_image_4",
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"ref_image_5",
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"ref_image_6",
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"ref_image_7",
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"ref_image_8",
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"ref_image_9",
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"reference_count",
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"debug",
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)
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FUNCTION = "curate_prompt"
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CATEGORY = "Dumas/MiniMax"
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@classmethod
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def INPUT_TYPES(cls):
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optional = {
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"anchor": (
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"STRING",
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{
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"forceInput": True,
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"tooltip": "Optional anchor/style text, usually from Dumas Anchor Style.",
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},
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),
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"soundscape": (
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"STRING",
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{
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"forceInput": True,
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"tooltip": "Optional soundscape text, usually from Dumas Soundscape Helper.",
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},
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),
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}
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for slot in range(1, _H3_PROMPT_REF_SLOTS + 1):
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optional[f"ref_{slot}"] = (
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_REFERENCE_TYPE,
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{
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"tooltip": (
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f"Optional structured reference {slot}. The curator only outputs "
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"it if the action prompt mentions its name/alias or an explicit "
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f"<Picture {slot}>/<ref{slot}> tag."
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)
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},
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)
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return {
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"required": {
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"action_prompt": (
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"STRING",
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{
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"default": "",
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"multiline": True,
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"tooltip": (
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"Write the final shot action here using character/location names. "
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"Mention a reference by name, alias, <Picture N>, or <refN> to use it."
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),
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},
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),
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"anatomy_guard": (
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["auto", "on", "off"],
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{
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"default": "auto",
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"tooltip": (
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"Add the anatomy guard. Auto adds it when a character reference is used."
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),
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},
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),
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},
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"optional": optional,
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}
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def curate_prompt(
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self,
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action_prompt,
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anatomy_guard,
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anchor="",
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||||
soundscape="",
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||||
ref_1=None,
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||||
ref_2=None,
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ref_3=None,
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ref_4=None,
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ref_5=None,
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||||
ref_6=None,
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ref_7=None,
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||||
ref_8=None,
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||||
ref_9=None,
|
||||
):
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return curate_h3_prompt(
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action_prompt,
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||||
anchor=anchor,
|
||||
soundscape=soundscape,
|
||||
refs=(ref_1, ref_2, ref_3, ref_4, ref_5, ref_6, ref_7, ref_8, ref_9),
|
||||
anatomy_guard=anatomy_guard,
|
||||
)
|
||||
|
||||
|
||||
class DumasAnchorStyleNode:
|
||||
DESCRIPTION = (
|
||||
"Choose an anchor-style preset, auto-fill its full description, and pass "
|
||||
@@ -2214,6 +2612,8 @@ NODE_CLASS_MAPPINGS = {
|
||||
"DumasH3PlanExtractSceneImages": DumasH3PlanExtractSceneImagesNode,
|
||||
"DumasCharacterReference": DumasCharacterReferenceNode,
|
||||
"DumasLocationReference": DumasLocationReferenceNode,
|
||||
"DumasSoundscapeHelper": DumasSoundscapeHelperNode,
|
||||
"DumasH3PromptCurator": DumasH3PromptCuratorNode,
|
||||
"DumasAnchorStyle": DumasAnchorStyleNode,
|
||||
"DumasCharacterHelper": DumasCharacterHelperNode,
|
||||
"DumasLocationHelper": DumasLocationHelperNode,
|
||||
@@ -2228,6 +2628,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"DumasH3PlanExtractSceneImages": "Dumas H3 Plan Extract Scene Images",
|
||||
"DumasCharacterReference": "Dumas Character Reference",
|
||||
"DumasLocationReference": "Dumas Location Reference",
|
||||
"DumasSoundscapeHelper": "Dumas Soundscape Helper",
|
||||
"DumasH3PromptCurator": "Dumas H3 Prompt Curator",
|
||||
"DumasAnchorStyle": "Dumas Anchor Style",
|
||||
"DumasCharacterHelper": "Dumas Character Helper",
|
||||
"DumasLocationHelper": "Dumas Location Helper",
|
||||
|
||||
@@ -412,14 +412,102 @@ class DumasImageNodeTests(unittest.TestCase):
|
||||
self.assertIn("Evening ambience, cramped but cozy.", result[2])
|
||||
self.assertEqual(len(result), 3)
|
||||
|
||||
def test_soundscape_helper_defaults_to_selected_preset_description(self):
|
||||
node = self.image_nodes.DumasSoundscapeHelperNode()
|
||||
|
||||
result = node.build_soundscape("rainy street", "")
|
||||
|
||||
self.assertEqual(result[0], "steady rain, wet pavement, distant traffic hum")
|
||||
|
||||
def test_h3_prompt_curator_compacts_named_references(self):
|
||||
node = self.image_nodes.DumasH3PromptCuratorNode()
|
||||
dave_image = FakeTensorBatch()
|
||||
cafe_image = FakeTensorBatch()
|
||||
van_image = FakeTensorBatch()
|
||||
dave = self.image_nodes.make_reference(
|
||||
kind="character",
|
||||
image=dave_image,
|
||||
name="Dave",
|
||||
aliases="The Locksmith",
|
||||
description="tired eyes, cropped brown hair",
|
||||
wardrobe="red flight jacket",
|
||||
)
|
||||
cafe = self.image_nodes.make_reference(
|
||||
kind="location",
|
||||
image=cafe_image,
|
||||
name="Coffee Shop",
|
||||
description="warm tungsten lighting and rainy windows",
|
||||
)
|
||||
van = self.image_nodes.make_reference(
|
||||
kind="location",
|
||||
image=van_image,
|
||||
name="Blue Van",
|
||||
description="scuffed blue delivery van",
|
||||
)
|
||||
|
||||
result = node.curate_prompt(
|
||||
action_prompt="Dave runs from the Coffee Shop into the rain.",
|
||||
anatomy_guard="auto",
|
||||
anchor="grounded handheld thriller",
|
||||
soundscape="steady rain",
|
||||
ref_1=dave,
|
||||
ref_2=van,
|
||||
ref_3=cafe,
|
||||
)
|
||||
|
||||
prompt = result[0]
|
||||
self.assertIn("<Picture 1> Dave", prompt)
|
||||
self.assertIn("<Picture 2> Coffee Shop", prompt)
|
||||
self.assertIn("Action: Dave runs from the Coffee Shop into the rain.", prompt)
|
||||
self.assertIn("Anatomy guard:", prompt)
|
||||
self.assertIs(result[1], dave_image)
|
||||
self.assertIs(result[2], cafe_image)
|
||||
self.assertIsNone(result[3])
|
||||
self.assertEqual(result[10], 2)
|
||||
self.assertIn("input 3-><Picture 2> Coffee Shop", result[11])
|
||||
|
||||
def test_h3_prompt_curator_renumbers_explicit_reference_tags(self):
|
||||
node = self.image_nodes.DumasH3PromptCuratorNode()
|
||||
image1 = FakeTensorBatch()
|
||||
image3 = FakeTensorBatch()
|
||||
unused = FakeTensorBatch()
|
||||
first = self.image_nodes.make_reference(kind="character", image=image1, name="Maya")
|
||||
second = self.image_nodes.make_reference(kind="location", image=unused, name="Lobby")
|
||||
third = self.image_nodes.make_reference(kind="location", image=image3, name="Rooftop")
|
||||
|
||||
result = node.curate_prompt(
|
||||
action_prompt="<Picture 1> Maya crosses to <ref3> as the wind rises.",
|
||||
anatomy_guard="off",
|
||||
ref_1=first,
|
||||
ref_2=second,
|
||||
ref_3=third,
|
||||
)
|
||||
|
||||
prompt = result[0]
|
||||
self.assertIn("<Picture 1> Maya crosses to <Picture 2>", prompt)
|
||||
self.assertNotIn("<Picture 3>", prompt)
|
||||
self.assertIs(result[1], image1)
|
||||
self.assertIs(result[2], image3)
|
||||
self.assertIsNone(result[3])
|
||||
self.assertEqual(result[10], 2)
|
||||
|
||||
def test_helper_node_mappings_use_general_purpose_helpers(self):
|
||||
mappings = self.image_nodes.NODE_CLASS_MAPPINGS
|
||||
display = self.image_nodes.NODE_DISPLAY_NAME_MAPPINGS
|
||||
|
||||
self.assertIs(mappings["DumasCharacterHelper"], self.image_nodes.DumasCharacterHelperNode)
|
||||
self.assertIs(mappings["DumasLocationHelper"], self.image_nodes.DumasLocationHelperNode)
|
||||
self.assertIs(mappings["DumasSoundscapeHelper"], self.image_nodes.DumasSoundscapeHelperNode)
|
||||
self.assertIs(mappings["DumasH3PromptCurator"], self.image_nodes.DumasH3PromptCuratorNode)
|
||||
self.assertEqual(display["DumasCharacterHelper"], "Dumas Character Helper")
|
||||
self.assertEqual(display["DumasLocationHelper"], "Dumas Location Helper")
|
||||
self.assertEqual(display["DumasSoundscapeHelper"], "Dumas Soundscape Helper")
|
||||
self.assertEqual(display["DumasH3PromptCurator"], "Dumas H3 Prompt Curator")
|
||||
|
||||
def test_h3_prompt_curator_uses_documented_reference_limits(self):
|
||||
node = self.image_nodes.DumasH3PromptCuratorNode()
|
||||
self.assertEqual(len(node.RETURN_TYPES), 12)
|
||||
self.assertEqual(node.RETURN_NAMES[1:10], tuple(f"ref_image_{i}" for i in range(1, 10)))
|
||||
|
||||
def test_normalize_reference_upgrades_generic_summary_with_socket_picture_id(self):
|
||||
image = FakeTensorBatch()
|
||||
|
||||
Reference in New Issue
Block a user