Add check when VectorSearchIndex has no vector field

Author: WaVEV

django_mongodb_backend/indexes.py

@@ -241,6 +241,18 @@ def check(self, model, connection):
                     id=f"{self._error_id_prefix}.E005",
                 )
             )
+        # There isn't any vector.
+        if expected_similarities == 0:
+            errors.append(
+                Error(
+                    "VectorSearchIndex requires at least one field containing vector data "
+                    "(e.g., an ArrayField(FloatField, size=10)). "
+                    "If you're aiming to perform search operations on other data types, "
+                    "consider using SearchIndex instead.",
+                    obj=model,
+                    id=f"{self._error_id_prefix}.E006",
+                )
+            )
         return errors
 
     def deconstruct(self):

tests/indexes_/test_checks.py

@@ -41,9 +41,10 @@ class Meta:
     def test_vector_search_requires_atlas_search_support(self):
         class Article(models.Model):
             title = models.CharField(max_length=10)
+            vector_float = ArrayField(models.FloatField(), size=10)
 
             class Meta:
-                indexes = [VectorSearchIndex(fields=["title"])]
+                indexes = [VectorSearchIndex(fields=["title", "vector_float"])]
 
         errors = checks.run_checks(app_configs=self.apps.get_app_configs(), databases={"default"})
         self.assertEqual(
@@ -108,9 +109,10 @@ class Meta:
     def test_unsupported_type(self):
         class Article(models.Model):
             data = models.JSONField()
+            vector_float = ArrayField(models.FloatField(), size=10)
 
             class Meta:
-                indexes = [VectorSearchIndex(fields=["data"])]
+                indexes = [VectorSearchIndex(fields=["data", "vector_float"])]
 
         errors = checks.run_checks(app_configs=self.apps.get_app_configs(), databases={"default"})
         self.assertEqual(
@@ -219,3 +221,24 @@ class Meta:
 
         errors = checks.run_checks(app_configs=self.apps.get_app_configs(), databases={"default"})
         self.assertEqual(errors, [])
+
+    def test_requires_vector_field(self):
+        class NoSearchVectorModel(models.Model):
+            text = models.CharField(max_length=100)
+
+            class Meta:
+                indexes = [VectorSearchIndex(name="recent_test_idx", fields=["text"])]
+
+        errors = checks.run_checks(app_configs=self.apps.get_app_configs(), databases={"default"})
+        self.assertEqual(
+            errors,
+            [
+                checks.Error(
+                    "VectorSearchIndex requires at least one field containing vector data "
+                    "(e.g., an ArrayField(FloatField, size=10)). If you're aiming to perform "
+                    "search operations on other data types, consider using SearchIndex instead.",
+                    id="django_mongodb_backend.indexes.VectorSearchIndex.E006",
+                    obj=NoSearchVectorModel,
+                ),
+            ],
+        )