add tests

Author: nirinchev

src/tools/mongodb/create/createIndex.ts

@@ -21,41 +21,51 @@ export class CreateIndexTool extends MongoDBToolBase {
                         type: z.literal("vectorSearch"),
                         fields: z
                             .array(
-                                z.object({
-                                    type: z
-                                        .enum(["vector", "filter"])
-                                        .describe(
-                                            "Field type to use to index fields for vector search. You must specify `vector` for fields that contain vector embeddings and `filter` for additional fields to filter on."
-                                        ),
-                                    path: z
-                                        .string()
-                                        .describe(
-                                            "Name of the field to index. For nested fields, use dot notation to specify path to embedded fields"
-                                        ),
-                                    numDimensions: z
-                                        .number()
-                                        .min(1)
-                                        .max(8192)
-                                        .describe(
-                                            "Number of vector dimensions that MongoDB Vector Search enforces at index-time and query-time"
-                                        ),
-                                    similarity: z
-                                        .enum(["cosine", "euclidean", "dotProduct"])
-                                        .default("cosine")
-                                        .describe(
-                                            "Vector similarity function to use to search for top K-nearest neighbors. You can set this field only for vector-type fields."
-                                        ),
-                                    quantization: z
-                                        .enum(["none", "scalar", "binary"])
-                                        .optional()
-                                        .default("none")
-                                        .describe(
-                                            "Type of automatic vector quantization for your vectors. Use this setting only if your embeddings are float or double vectors."
-                                        ),
-                                })
+                                z.discriminatedUnion("type", [
+                                    z.object({
+                                        type: z.literal("filter"),
+                                        path: z
+                                            .string()
+                                            .describe(
+                                                "Name of the field to index. For nested fields, use dot notation to specify path to embedded fields"
+                                            ),
+                                    }),
+                                    z.object({
+                                        type: z.literal("vector"),
+                                        path: z
+                                            .string()
+                                            .describe(
+                                                "Name of the field to index. For nested fields, use dot notation to specify path to embedded fields"
+                                            ),
+                                        numDimensions: z
+                                            .number()
+                                            .min(1)
+                                            .max(8192)
+                                            .describe(
+                                                "Number of vector dimensions that MongoDB Vector Search enforces at index-time and query-time"
+                                            ),
+                                        similarity: z
+                                            .enum(["cosine", "euclidean", "dotProduct"])
+                                            .default("cosine")
+                                            .describe(
+                                                "Vector similarity function to use to search for top K-nearest neighbors. You can set this field only for vector-type fields."
+                                            ),
+                                        quantization: z
+                                            .enum(["none", "scalar", "binary"])
+                                            .optional()
+                                            .default("none")
+                                            .describe(
+                                                "Type of automatic vector quantization for your vectors. Use this setting only if your embeddings are float or double vectors."
+                                            ),
+                                    }),
+                                ])
                             )
+                            .nonempty()
+                            .refine((fields) => fields.some((f) => f.type === "vector"), {
+                                message: "At least one vector field must be defined",
+                            })
                             .describe(
-                                "Definitions for the vector and filter fields to index, one definition per document. The fields array must contain at least one vector-type field definition."
+                                "Definitions for the vector and filter fields to index, one definition per document. You must specify `vector` for fields that contain vector embeddings and `filter` for additional fields to filter on. At least one vector-type field definition is required."
                             ),
                     }),
                 ])