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3 changed files with 395 additions and 19 deletions
+14 -7
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@@ -57,11 +57,11 @@
- 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.
- `Dumas H3 Prompt Curator`
- Inputs: `action_prompt`, `anatomy_guard`, optional `anchor`, optional `soundscape`, optional `ref_1` through `ref_9`
- Inputs: `action_prompt`, `anatomy_guard`, `subject_count_guard`, optional `anchor`, optional `soundscape`, optional `bgm`, optional `ref_1` through `ref_9`
- Outputs: `prompt`, `ref_image_1` through `ref_image_9`, `reference_count`, `debug`
- Builds one standalone MiniMax H3 prompt from your final action text plus structured character/location references.
- 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.
- 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.
- Adds curated reference context, anatomy guard text, optional subject-count guard text, anchor/style text, `overall_soundscape:` text, and `background_music:` text while respecting MiniMax H3's reference-generation shape: one prompt plus up to nine reference images.
- `Dumas H3 Shot Length`
- Inputs: `shot_seconds`, `fps`, optional `cap_to_h3_max`
@@ -85,13 +85,15 @@
- `Dumas Character Helper`
- Inputs: `image1`, `image2`, picture IDs, character identity fields, `general`, `wardrobe`
- Outputs: `image1`, `image2`, `reference_prompt`, `wardrobe`
- Restores the original general-purpose helper shape: pass two images through unchanged and emit prompt text/wardrobe text for manual wiring.
- Outputs: `image1`, `image2`, `reference_prompt`, `wardrobe`, `reference1`, `reference2`
- Restores the original general-purpose helper shape while also emitting two structured `REFERENCE` objects for the prompt curator.
- The structured references carry the same character name, alias, age, height, gender, nationality, occupation, accent, wardrobe, and notes, so mentioning the character name in `Dumas H3 Prompt Curator` can include both helper images and the character facts automatically.
- `Dumas Location Helper`
- Inputs: `image1`, `image2`, picture IDs, `location_id`, `name`, `alias`, `description`, `general`
- Outputs: `image1`, `image2`, `reference_prompt`
- Matching general-purpose helper for environments/locations: pass two images through unchanged and emit location reference prompt text.
- Outputs: `image1`, `image2`, `reference_prompt`, `reference1`, `reference2`
- Matching general-purpose helper for environments/locations: pass two images through unchanged, emit location reference prompt text, and provide two structured `REFERENCE` objects for the prompt curator.
- The structured references carry the same location name, alias, description, and notes, so mentioning the location name in `Dumas H3 Prompt Curator` can include both helper images and the location context automatically.
- `Dumas Anchor Style`
- Inputs: `anchor_style`, `style_description`
@@ -105,6 +107,11 @@
- Output: `soundscape`
- 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`.
- `Dumas Background Music Helper`
- Inputs: `bgm`, `bgm_description`
- Output: `bgm`
- Matching BGM helper for standalone H3 prompts. Pick a preset such as subtle tension, cinematic suspense, emotional piano, dark ambient, hopeful orchestral, retro synth, action pulse, lo-fi, or no vocals, then edit the text that flows into `Dumas H3 Prompt Curator`.
- `Dumas JSON String to Object`
- Input: `json_string`
- Output: parsed `JSON`
@@ -261,7 +268,7 @@ decr -> use index - 1
`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.
`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.
`Dumas Character Helper` is the restored two-image/text helper for general H3 workflows, and `Dumas Location Helper` mirrors it for scene/environment references. Both helpers also emit structured `REFERENCE` sockets for the curator. 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 plus optional anchor, soundscape, and BGM strings, assigns the final `<Picture N>` numbering, and outputs only the compacted images the prompt actually mentions.
`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.
+237 -11
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@@ -27,6 +27,12 @@ _H3_PLAN_IMAGE_BINDINGS_CAP = 128
_H3_PLAN_IMAGE_SLOTS = 9
_FOLDER_IMAGE_EXTS = (".png", ".jpg", ".jpeg", ".webp", ".bmp", ".gif", ".tiff", ".tif")
_ANCHOR_STYLE_H3_NOTE = ""
_ANCHOR_STYLE_LEGACY_NOTE_RE = re.compile(
r"\s*Keep this anchor focused on persistent camera language, lighting, "
r"texture, environment treatment, and tone; do not name characters or "
r"describe one-off actions\.?",
re.I,
)
_H3_PROMPT_REF_SLOTS = 9
_H3_PROMPT_MAX_CHARS = 7000
_PICTURE_TAG_RE = re.compile(r"<\s*picture[\s_\-]*(\d+)\s*>", re.I)
@@ -36,6 +42,10 @@ _ANATOMY_GUARD_TEXT = (
"and two legs with two feet. Limbs stay attached to the correct body and move "
"only with the person they belong to."
)
_SUBJECT_COUNT_FALLBACK_TEXT = (
"Only include the people explicitly described in the action. Do not invent "
"extra people, doubles, duplicate bodies, background performers, or extra faces."
)
_ANCHOR_STYLE_PRESETS = OrderedDict(
[
(
@@ -388,6 +398,51 @@ _SOUNDSCAPE_PRESETS = OrderedDict(
("custom", ""),
]
)
_BGM_PRESETS = OrderedDict(
[
(
"none",
"",
),
(
"subtle tension",
"low, restrained tension bed with sparse pulses and no vocals",
),
(
"cinematic suspense",
"cinematic suspense score with muted strings, low drones, and controlled rising pressure",
),
(
"emotional piano",
"soft emotional piano underscoring with gentle space and no vocals",
),
(
"dark ambient",
"dark ambient music bed with deep drones, distant texture, and slow unease",
),
(
"hopeful orchestral",
"hopeful orchestral underscore with warm strings, gentle brass, and restrained lift",
),
(
"retro synth",
"retro synth score with analog pulses, warm pads, and steady momentum",
),
(
"action pulse",
"driving action pulse with percussion, rhythmic bass, and urgent forward motion",
),
(
"lo-fi",
"soft lo-fi instrumental bed with mellow rhythm and warm tape texture",
),
(
"no vocals",
"instrumental background music only, no singing, no lyrics, no vocal hooks",
),
("custom", ""),
]
)
def _soundscape_options():
@@ -396,6 +451,14 @@ def _soundscape_options():
def _soundscape_description(soundscape_name):
return _SOUNDSCAPE_PRESETS.get(soundscape_name, "")
def _bgm_options():
return list(_BGM_PRESETS.keys())
def _bgm_description(bgm_name):
return _BGM_PRESETS.get(bgm_name, "")
_LOAD_IMAGES_FOLDER_DEFAULT_STATE = {
"version": 1,
"folder": "",
@@ -416,6 +479,11 @@ def _anchor_style_description(style_name):
return _ANCHOR_STYLE_PRESETS.get(str(style_name or "").strip().lower(), "")
def _clean_anchor_style_text(text):
cleaned = _ANCHOR_STYLE_LEGACY_NOTE_RE.sub("", str(text or ""))
return re.sub(r"[ \t]{2,}", " ", cleaned).strip()
def _clean_input_token_value(value):
cleaned = ""
if value is not None:
@@ -1131,13 +1199,52 @@ def _reference_context(ref, compact_picture_number):
return " ".join(part for part in parts if part).strip()
def _subject_count_guard_text(selected_refs):
character_labels = []
seen_characters = set()
for picture_number, (_slot, ref) in enumerate(selected_refs or (), 1):
if ref.get("kind") != "character":
continue
name = _reference_text(ref.get("name")) or _reference_text(ref.get("id"))
key = (_reference_text(ref.get("id")) or name or f"picture-{picture_number}").lower()
if key in seen_characters:
continue
seen_characters.add(key)
label = f"<Picture {picture_number}>"
if name:
label = f"{label} {name}"
character_labels.append(label)
if not character_labels:
return _SUBJECT_COUNT_FALLBACK_TEXT
if len(character_labels) == 1:
return (
f"The shot contains exactly one named character: {character_labels[0]}. "
"Do not create any extra people, doubles, duplicate bodies, background "
"performers, or extra faces."
)
return (
f"The shot contains exactly {len(character_labels)} named characters: "
+ ", ".join(character_labels)
+ ". Do not create any extra people, doubles, duplicate bodies, background "
"performers, or extra faces."
)
def _append_prompt_section(parts, label, text):
clean = _reference_text(text)
if clean:
parts.append(f"{label}: {clean}")
def curate_h3_prompt(action_prompt, anchor="", soundscape="", refs=(), anatomy_guard="auto"):
def curate_h3_prompt(
action_prompt,
anchor="",
soundscape="",
bgm="",
refs=(),
anatomy_guard="auto",
subject_count_guard="auto",
):
normalized_refs = _normalize_prompt_refs(refs)
selected = _selected_prompt_refs(action_prompt, normalized_refs)
picture_map = {slot_number: index for index, (slot_number, _ref) in enumerate(selected, 1)}
@@ -1151,7 +1258,12 @@ def curate_h3_prompt(action_prompt, anchor="", soundscape="", refs=(), anatomy_g
_append_prompt_section(prompt_parts, "Action", action)
if anatomy_guard == "on" or (anatomy_guard == "auto" and any(ref.get("kind") == "character" for _slot, ref in selected)):
_append_prompt_section(prompt_parts, "Anatomy guard", _ANATOMY_GUARD_TEXT)
if subject_count_guard == "on" or (
subject_count_guard == "auto" and any(ref.get("kind") == "character" for _slot, ref in selected)
):
_append_prompt_section(prompt_parts, "Subject count guard", _subject_count_guard_text(selected))
_append_prompt_section(prompt_parts, "overall_soundscape", soundscape)
_append_prompt_section(prompt_parts, "background_music", bgm)
prompt = "\n\n".join(prompt_parts).strip()
if len(prompt) > _H3_PROMPT_MAX_CHARS:
@@ -1919,8 +2031,8 @@ class DumasCharacterHelperNode:
"IMAGE sockets plus simple identity fields, while passing both images "
"through unchanged."
)
RETURN_TYPES = ("IMAGE", "IMAGE", "STRING", "STRING")
RETURN_NAMES = ("image1", "image2", "reference_prompt", "wardrobe")
RETURN_TYPES = ("IMAGE", "IMAGE", "STRING", "STRING", _REFERENCE_TYPE, _REFERENCE_TYPE)
RETURN_NAMES = ("image1", "image2", "reference_prompt", "wardrobe", "reference1", "reference2")
FUNCTION = "build_character_text"
CATEGORY = "Dumas/MiniMax"
@@ -2081,7 +2193,36 @@ class DumasCharacterHelperNode:
name,
alias,
)
return (image1, image2, text, wardrobe_text)
facts = {
"gender": _normalize_free_text(gender),
"age": str(_parse_positive_int(age) or ""),
"nationality": _normalize_free_text(nationality),
"occupation": _normalize_free_text(occupation),
"height_feet": str(height_feet or "").strip(),
"height_inches": str(height_inches or "").strip(),
"accent": _normalize_free_text(accent),
}
common = {
"kind": "character",
"explicit_id": character_id,
"name": name,
"aliases": alias,
"description": general,
"wardrobe": wardrobe,
"general": general,
"facts": facts,
}
reference1 = make_reference(
image=image1,
summary="Primary full-body character reference.",
**common,
)
reference2 = make_reference(
image=image2,
summary="Secondary facial character reference.",
**common,
)
return (image1, image2, text, wardrobe_text, reference1, reference2)
class DumasLocationHelperNode:
@@ -2089,8 +2230,8 @@ class DumasLocationHelperNode:
"Build a general location reference prompt from two IMAGE sockets plus "
"simple environment fields, while passing both images through unchanged."
)
RETURN_TYPES = ("IMAGE", "IMAGE", "STRING")
RETURN_NAMES = ("image1", "image2", "reference_prompt")
RETURN_TYPES = ("IMAGE", "IMAGE", "STRING", _REFERENCE_TYPE, _REFERENCE_TYPE)
RETURN_NAMES = ("image1", "image2", "reference_prompt", "reference1", "reference2")
FUNCTION = "build_location_text"
CATEGORY = "Dumas/MiniMax"
@@ -2178,7 +2319,26 @@ class DumasLocationHelperNode:
description,
general,
)
return (image1, image2, text)
common = {
"kind": "location",
"explicit_id": location_id,
"name": name,
"aliases": alias,
"description": description,
"general": general,
"facts": {},
}
reference1 = make_reference(
image=image1,
summary="Primary location reference.",
**common,
)
reference2 = make_reference(
image=image2,
summary="Secondary location reference.",
**common,
)
return (image1, image2, text, reference1, reference2)
class DumasCharacterReferenceNode:
@@ -2456,10 +2616,53 @@ class DumasSoundscapeHelperNode:
return (text,)
class DumasBackgroundMusicHelperNode:
DESCRIPTION = (
"Choose a background music preset, auto-fill its editable description, "
"and pass the final BGM text downstream for MiniMax H3 prompts."
)
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("bgm",)
FUNCTION = "build_bgm"
CATEGORY = "Dumas/MiniMax"
@classmethod
def INPUT_TYPES(cls):
default_bgm = "none"
return {
"required": {
"bgm": (
_bgm_options(),
{
"default": default_bgm,
"tooltip": "Preset title used to seed the editable background music description.",
},
),
"bgm_description": (
"STRING",
{
"default": _bgm_description(default_bgm),
"multiline": True,
"tooltip": (
"Editable background music description. Whatever text is here "
"is what the node outputs to the bgm socket."
),
},
),
}
}
def build_bgm(self, bgm, bgm_description):
text = str(bgm_description or "").strip()
if not text:
text = _bgm_description(bgm)
return (text,)
class DumasH3PromptCuratorNode:
DESCRIPTION = (
"Curate one MiniMax H3 prompt from an action textbox, anchor text, "
"soundscape text, and up to nine structured references. References are "
"soundscape/BGM text, and up to nine structured references. References are "
"compacted so only mentioned names, aliases, or explicit <Picture N>/<refN> "
"tags are sent onward."
)
@@ -2498,6 +2701,13 @@ class DumasH3PromptCuratorNode:
"tooltip": "Optional soundscape text, usually from Dumas Soundscape Helper.",
},
),
"bgm": (
"STRING",
{
"forceInput": True,
"tooltip": "Optional background music text, usually from Dumas Background Music Helper.",
},
),
}
for slot in range(1, _H3_PROMPT_REF_SLOTS + 1):
optional[f"ref_{slot}"] = (
@@ -2526,12 +2736,22 @@ class DumasH3PromptCuratorNode:
"anatomy_guard": (
["auto", "on", "off"],
{
"default": "auto",
"default": "on",
"tooltip": (
"Add the anatomy guard. Auto adds it when a character reference is used."
),
},
),
"subject_count_guard": (
["auto", "on", "off"],
{
"default": "auto",
"tooltip": (
"Add a guard against extra people, duplicate bodies, or extra faces. "
"Auto adds it when a character reference is used."
),
},
),
},
"optional": optional,
}
@@ -2540,8 +2760,10 @@ class DumasH3PromptCuratorNode:
self,
action_prompt,
anatomy_guard,
subject_count_guard,
anchor="",
soundscape="",
bgm="",
ref_1=None,
ref_2=None,
ref_3=None,
@@ -2556,8 +2778,10 @@ class DumasH3PromptCuratorNode:
action_prompt,
anchor=anchor,
soundscape=soundscape,
bgm=bgm,
refs=(ref_1, ref_2, ref_3, ref_4, ref_5, ref_6, ref_7, ref_8, ref_9),
anatomy_guard=anatomy_guard,
subject_count_guard=subject_count_guard,
)
@@ -2598,9 +2822,9 @@ class DumasAnchorStyleNode:
}
def build_anchor(self, anchor_style, style_description):
text = str(style_description or "").strip()
text = _clean_anchor_style_text(style_description)
if not text:
text = _anchor_style_description(anchor_style)
text = _clean_anchor_style_text(_anchor_style_description(anchor_style))
return (text,)
@@ -2613,6 +2837,7 @@ NODE_CLASS_MAPPINGS = {
"DumasCharacterReference": DumasCharacterReferenceNode,
"DumasLocationReference": DumasLocationReferenceNode,
"DumasSoundscapeHelper": DumasSoundscapeHelperNode,
"DumasBackgroundMusicHelper": DumasBackgroundMusicHelperNode,
"DumasH3PromptCurator": DumasH3PromptCuratorNode,
"DumasAnchorStyle": DumasAnchorStyleNode,
"DumasCharacterHelper": DumasCharacterHelperNode,
@@ -2629,6 +2854,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"DumasCharacterReference": "Dumas Character Reference",
"DumasLocationReference": "Dumas Location Reference",
"DumasSoundscapeHelper": "Dumas Soundscape Helper",
"DumasBackgroundMusicHelper": "Dumas Background Music Helper",
"DumasH3PromptCurator": "Dumas H3 Prompt Curator",
"DumasAnchorStyle": "Dumas Anchor Style",
"DumasCharacterHelper": "Dumas Character Helper",
+144 -1
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@@ -386,6 +386,17 @@ class DumasImageNodeTests(unittest.TestCase):
self.assertIn("Dave is also known as The Locksmith", result[2])
self.assertIn("is 41 years old", result[2])
self.assertEqual(result[3], "Dave = weathered red flight jacket, grey cargo shorts, black boots")
self.assertIs(result[4]["image"], image1)
self.assertIs(result[5]["image"], image2)
self.assertEqual(result[4]["id"], "char-dave")
self.assertEqual(result[5]["id"], "char-dave")
self.assertEqual(result[4]["name"], "Dave")
self.assertEqual(result[4]["aliases"], ["The Locksmith"])
self.assertEqual(result[4]["facts"]["age"], "41")
self.assertEqual(result[4]["facts"]["height_feet"], "6")
self.assertEqual(result[4]["facts"]["height_inches"], "2")
self.assertEqual(result[4]["wardrobe"], "weathered red flight jacket, grey cargo shorts, black boots")
self.assertEqual(len(result), 6)
def test_location_helper_matches_character_helper_shape_without_wardrobe(self):
node = self.image_nodes.DumasLocationHelperNode()
@@ -410,7 +421,17 @@ class DumasImageNodeTests(unittest.TestCase):
self.assertIn("Coffee Shop is also known as Cafe Interior", result[2])
self.assertIn("Warm tungsten lighting, narrow counter, rainy front window.", result[2])
self.assertIn("Evening ambience, cramped but cozy.", result[2])
self.assertEqual(len(result), 3)
self.assertIs(result[3]["image"], image1)
self.assertIs(result[4]["image"], image2)
self.assertEqual(result[3]["kind"], "location")
self.assertEqual(result[4]["kind"], "location")
self.assertEqual(result[3]["id"], "coffee-shop-01")
self.assertEqual(result[4]["id"], "coffee-shop-01")
self.assertEqual(result[3]["name"], "Coffee Shop")
self.assertEqual(result[3]["aliases"], ["Cafe Interior"])
self.assertEqual(result[3]["description"], "Warm tungsten lighting, narrow counter, rainy front window")
self.assertEqual(result[3]["general"], "Evening ambience, cramped but cozy")
self.assertEqual(len(result), 5)
def test_soundscape_helper_defaults_to_selected_preset_description(self):
node = self.image_nodes.DumasSoundscapeHelperNode()
@@ -419,6 +440,13 @@ class DumasImageNodeTests(unittest.TestCase):
self.assertEqual(result[0], "steady rain, wet pavement, distant traffic hum")
def test_background_music_helper_defaults_to_selected_preset_description(self):
node = self.image_nodes.DumasBackgroundMusicHelperNode()
result = node.build_bgm("subtle tension", "")
self.assertEqual(result[0], "low, restrained tension bed with sparse pulses and no vocals")
def test_h3_prompt_curator_compacts_named_references(self):
node = self.image_nodes.DumasH3PromptCuratorNode()
dave_image = FakeTensorBatch()
@@ -448,8 +476,10 @@ class DumasImageNodeTests(unittest.TestCase):
result = node.curate_prompt(
action_prompt="Dave runs from the Coffee Shop into the rain.",
anatomy_guard="auto",
subject_count_guard="auto",
anchor="grounded handheld thriller",
soundscape="steady rain",
bgm="low suspense music",
ref_1=dave,
ref_2=van,
ref_3=cafe,
@@ -460,6 +490,10 @@ class DumasImageNodeTests(unittest.TestCase):
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.assertIn("Subject count guard:", prompt)
self.assertIn("overall_soundscape: steady rain", prompt)
self.assertIn("background_music: low suspense music", prompt)
self.assertIn("exactly one named character: <Picture 1> Dave", prompt)
self.assertIs(result[1], dave_image)
self.assertIs(result[2], cafe_image)
self.assertIsNone(result[3])
@@ -478,6 +512,7 @@ class DumasImageNodeTests(unittest.TestCase):
result = node.curate_prompt(
action_prompt="<Picture 1> Maya crosses to <ref3> as the wind rises.",
anatomy_guard="off",
subject_count_guard="off",
ref_1=first,
ref_2=second,
ref_3=third,
@@ -491,6 +526,99 @@ class DumasImageNodeTests(unittest.TestCase):
self.assertIsNone(result[3])
self.assertEqual(result[10], 2)
def test_h3_prompt_curator_can_force_subject_count_without_character_refs(self):
node = self.image_nodes.DumasH3PromptCuratorNode()
result = node.curate_prompt(
action_prompt="A locked-off shot of the empty corridor.",
anatomy_guard="off",
subject_count_guard="on",
)
self.assertIn("Subject count guard:", result[0])
self.assertIn("Only include the people explicitly described", result[0])
self.assertEqual(result[10], 0)
def test_h3_prompt_curator_treats_helper_image_pair_as_one_character(self):
helper = self.image_nodes.DumasCharacterHelperNode()
curator = self.image_nodes.DumasH3PromptCuratorNode()
image1 = FakeTensorBatch()
image2 = FakeTensorBatch()
helper_result = helper.build_character_text(
image1=image1,
image2=image2,
image1_picture_id="1",
image2_picture_id="2",
character_id="char_dave",
name="Dave",
alias="The Locksmith",
gender="male",
age="41",
nationality="English",
occupation="detective",
height_feet="6",
height_inches="2",
accent="English",
general="Tired eyes, cropped brown hair",
wardrobe="weathered red flight jacket",
)
result = curator.curate_prompt(
action_prompt="Dave checks the locked door.",
anatomy_guard="on",
subject_count_guard="auto",
ref_1=helper_result[4],
ref_2=helper_result[5],
)
self.assertIs(result[1], image1)
self.assertIs(result[2], image2)
self.assertEqual(result[10], 2)
self.assertIn("Character facts for <Picture 1> Dave", result[0])
self.assertIn("41 years old", result[0])
self.assertIn("6 foot 2 tall", result[0])
self.assertIn("exactly one named character: <Picture 1> Dave", result[0])
self.assertNotIn("exactly 2 named characters", result[0])
def test_h3_prompt_curator_uses_location_helper_references_by_name(self):
helper = self.image_nodes.DumasLocationHelperNode()
curator = self.image_nodes.DumasH3PromptCuratorNode()
image1 = FakeTensorBatch()
image2 = FakeTensorBatch()
helper_result = helper.build_location_text(
image1=image1,
image2=image2,
image1_picture_id="1",
image2_picture_id="2",
location_id="coffee_shop",
name="Coffee Shop",
alias="Cafe Interior",
description="Warm tungsten lighting, narrow counter, rainy front window",
general="Evening ambience, cramped but cozy",
)
result = curator.curate_prompt(
action_prompt="A slow push through the Coffee Shop as rain streaks the windows.",
anatomy_guard="on",
subject_count_guard="auto",
ref_1=helper_result[3],
ref_2=helper_result[4],
)
self.assertIs(result[1], image1)
self.assertIs(result[2], image2)
self.assertEqual(result[10], 2)
self.assertIn("<Picture 1> Coffee Shop", result[0])
self.assertIn("<Picture 2> Coffee Shop", result[0])
self.assertIn("Location context for <Picture 1> Coffee Shop", result[0])
self.assertIn("Warm tungsten lighting", result[0])
self.assertNotIn("Subject count guard:", result[0])
def test_h3_prompt_curator_defaults_anatomy_guard_to_on(self):
required = self.image_nodes.DumasH3PromptCuratorNode.INPUT_TYPES()["required"]
self.assertEqual(required["anatomy_guard"][1]["default"], "on")
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
@@ -498,10 +626,12 @@ class DumasImageNodeTests(unittest.TestCase):
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["DumasBackgroundMusicHelper"], self.image_nodes.DumasBackgroundMusicHelperNode)
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["DumasBackgroundMusicHelper"], "Dumas Background Music Helper")
self.assertEqual(display["DumasH3PromptCurator"], "Dumas H3 Prompt Curator")
def test_h3_prompt_curator_uses_documented_reference_limits(self):
@@ -570,6 +700,19 @@ class DumasImageNodeTests(unittest.TestCase):
self.assertIn("real time", result[0])
self.assertNotIn("persistent camera language", result[0])
def test_anchor_style_node_strips_legacy_persistent_anchor_note(self):
node = self.image_nodes.DumasAnchorStyleNode()
legacy = (
"Gritty handheld realism. Keep this anchor focused on persistent camera "
"language, lighting, texture, environment treatment, and tone; do not "
"name characters or describe one-off actions."
)
result = node.build_anchor("cinematic action movie", legacy)
self.assertEqual(result[0], "Gritty handheld realism.")
self.assertNotIn("persistent camera language", result[0])
def test_anchor_style_node_prefers_manual_description_edits(self):
node = self.image_nodes.DumasAnchorStyleNode()
custom = "Lo-fi pirate broadcast with smeared highlights and anxious zoom corrections."