Strip legacy anchor style note

README.md

@@ -91,8 +91,9 @@
 
 - `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`
@@ -262,7 +263,7 @@ 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, 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.
 

dumas_image_nodes.py

@@ -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)
@@ -420,6 +426,11 @@ 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:
@@ -2164,8 +2175,8 @@ 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"
 
@@ -2253,7 +2264,26 @@ 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:
@@ -2685,9 +2715,9 @@ 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,)
 
 

tests/test_dumas_image_nodes.py

@@ -421,7 +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()
@@ -560,6 +570,40 @@ class DumasImageNodeTests(unittest.TestCase):
         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"]
 
@@ -644,6 +688,19 @@ 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."