Simplify H3 prompt curator component outputs

README.md

@@ -58,9 +58,10 @@
 
 - `Dumas H3 Prompt Curator`
   - 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`
+  - Outputs: `prompt`, `ref_image_1` through `ref_image_9`, `reference_count`, `debug`, `anchor`, `sounds`, `bgm`, `original_ref_1` through `original_ref_9`
   - 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.
+  - Extra component outputs expose the cleaned anchor, sounds, BGM, and each selected original reference image in compacted order.
   - 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`

dumas_image_nodes.py

@@ -1249,12 +1249,19 @@ def curate_h3_prompt(
     selected = _selected_prompt_refs(action_prompt, normalized_refs)
     picture_map = {slot_number: index for index, (slot_number, _ref) in enumerate(selected, 1)}
     action = _replace_reference_tags(action_prompt, picture_map)
+    anchor_text = _reference_text(anchor)
+    soundscape_text = _reference_text(soundscape)
+    bgm_text = _reference_text(bgm)
+    reference_description = ""
+    if selected:
+        reference_description = " ".join(
+            _reference_context(ref, picture_number)
+            for picture_number, (_slot, ref) in enumerate(selected, 1)
+        )
 
     prompt_parts = []
-    _append_prompt_section(prompt_parts, "Scene anchor", anchor)
+    _append_prompt_section(prompt_parts, "Scene anchor", anchor_text)
-    if selected:
+    _append_prompt_section(prompt_parts, "Reference context", reference_description)
-        contexts = [_reference_context(ref, picture_number) for picture_number, (_slot, ref) in enumerate(selected, 1)]
-        _append_prompt_section(prompt_parts, "Reference context", " ".join(contexts))
     _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)
@@ -1262,8 +1269,8 @@ def curate_h3_prompt(
         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, "overall_soundscape", soundscape_text)
-    _append_prompt_section(prompt_parts, "background_music", bgm)
+    _append_prompt_section(prompt_parts, "background_music", bgm_text)
 
     prompt = "\n\n".join(prompt_parts).strip()
     if len(prompt) > _H3_PROMPT_MAX_CHARS:
@@ -1279,7 +1286,16 @@ def curate_h3_prompt(
         if selected
         else "Selected 0 references."
     )
-    return (prompt, *images[:_H3_PROMPT_REF_SLOTS], len(selected), debug)
+    return (
+        prompt,
+        *images[:_H3_PROMPT_REF_SLOTS],
+        len(selected),
+        debug,
+        anchor_text,
+        soundscape_text,
+        bgm_text,
+        *images[:_H3_PROMPT_REF_SLOTS],
+    )
 
 
 def _parse_positive_int(value):
@@ -2666,7 +2682,12 @@ class DumasH3PromptCuratorNode:
         "compacted so only mentioned names, aliases, or explicit <Picture N>/<refN> "
         "tags are sent onward."
     )
-    RETURN_TYPES = ("STRING",) + ("IMAGE",) * _H3_PROMPT_REF_SLOTS + ("INT", "STRING")
+    RETURN_TYPES = (
+        ("STRING",)
+        + ("IMAGE",) * _H3_PROMPT_REF_SLOTS
+        + ("INT", "STRING", "STRING", "STRING", "STRING")
+        + ("IMAGE",) * _H3_PROMPT_REF_SLOTS
+    )
     RETURN_NAMES = (
         "prompt",
         "ref_image_1",
@@ -2680,6 +2701,18 @@ class DumasH3PromptCuratorNode:
         "ref_image_9",
         "reference_count",
         "debug",
+        "anchor",
+        "sounds",
+        "bgm",
+        "original_ref_1",
+        "original_ref_2",
+        "original_ref_3",
+        "original_ref_4",
+        "original_ref_5",
+        "original_ref_6",
+        "original_ref_7",
+        "original_ref_8",
+        "original_ref_9",
     )
     FUNCTION = "curate_prompt"
     CATEGORY = "Dumas/MiniMax"

tests/test_dumas_image_nodes.py

@@ -499,6 +499,12 @@ class DumasImageNodeTests(unittest.TestCase):
         self.assertIsNone(result[3])
         self.assertEqual(result[10], 2)
         self.assertIn("input 3-><Picture 2> Coffee Shop", result[11])
+        self.assertEqual(result[12], "grounded handheld thriller")
+        self.assertEqual(result[13], "steady rain")
+        self.assertEqual(result[14], "low suspense music")
+        self.assertIs(result[15], dave_image)
+        self.assertIs(result[16], cafe_image)
+        self.assertIsNone(result[17])
 
     def test_h3_prompt_curator_renumbers_explicit_reference_tags(self):
         node = self.image_nodes.DumasH3PromptCuratorNode()
@@ -636,8 +642,10 @@ class DumasImageNodeTests(unittest.TestCase):
 
     def test_h3_prompt_curator_uses_documented_reference_limits(self):
         node = self.image_nodes.DumasH3PromptCuratorNode()
-        self.assertEqual(len(node.RETURN_TYPES), 12)
+        self.assertEqual(len(node.RETURN_TYPES), 24)
         self.assertEqual(node.RETURN_NAMES[1:10], tuple(f"ref_image_{i}" for i in range(1, 10)))
+        self.assertEqual(node.RETURN_NAMES[12:15], ("anchor", "sounds", "bgm"))
+        self.assertEqual(node.RETURN_NAMES[15:24], tuple(f"original_ref_{i}" for i in range(1, 10)))
 
     def test_normalize_reference_upgrades_generic_summary_with_socket_picture_id(self):
         image = FakeTensorBatch()