Add compiled prompt reference output pairs

tests/test_dumas_image_nodes.py

@@ -515,6 +515,14 @@ class DumasImageNodeTests(unittest.TestCase):
         self.assertIn("<Picture 2> Coffee Shop", result[26])
         self.assertIn("Location context for <Picture 2> Coffee Shop", result[26])
         self.assertEqual(result[27], "")
+        self.assertIs(result[34], dave_image)
+        self.assertIs(result[35], cafe_image)
+        self.assertIsNone(result[36])
+        self.assertIn("<Picture 1> Dave", result[43])
+        self.assertNotIn("<Picture 2> Coffee Shop", result[43])
+        self.assertIn("<Picture 2> Coffee Shop", result[44])
+        self.assertIn("Location context for <Picture 2> Coffee Shop", result[44])
+        self.assertEqual(result[45], "")
 
     def test_h3_prompt_curator_renumbers_explicit_reference_tags(self):
         node = self.image_nodes.DumasH3PromptCuratorNode()
@@ -652,7 +660,7 @@ 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), 34)
+        self.assertEqual(len(node.RETURN_TYPES), 52)
         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)))
@@ -661,6 +669,11 @@ class DumasImageNodeTests(unittest.TestCase):
             node.RETURN_NAMES[25:34],
             tuple(f"original_ref_description_{i}" for i in range(1, 10)),
         )
+        self.assertEqual(node.RETURN_NAMES[34:43], tuple(f"compiled_ref_image_{i}" for i in range(1, 10)))
+        self.assertEqual(
+            node.RETURN_NAMES[43:52],
+            tuple(f"compiled_ref_description_{i}" for i in range(1, 10)),
+        )
 
     def test_normalize_reference_upgrades_generic_summary_with_socket_picture_id(self):
         image = FakeTensorBatch()