address PR comments

nirinchev · nirinchev · commit afde1138c49a · 2025-10-15T13:10:02.000+02:00
diff --git a/src/common/config.ts b/src/common/config.ts
@@ -183,6 +183,8 @@ export interface UserConfig extends CliOptions {
     maxBytesPerQuery: number;
     atlasTemporaryDatabaseUserLifetimeMs: number;
     voyageApiKey: string;
+    vectorSearchDimensions: number;
+    vectorSearchSimilarityFunction: "cosine" | "euclidean" | "dotProduct";
 }
 
 export const defaultUserConfig: UserConfig = {
@@ -214,6 +216,8 @@ export const defaultUserConfig: UserConfig = {
     maxBytesPerQuery: 16 * 1024 * 1024, // By default, we only return ~16 mb of data per query / aggregation
     atlasTemporaryDatabaseUserLifetimeMs: 4 * 60 * 60 * 1000, // 4 hours
     voyageApiKey: "",
+    vectorSearchDimensions: 1024,
+    vectorSearchSimilarityFunction: "euclidean",
 };
 
 export const config = setupUserConfig({
diff --git a/src/common/connectionManager.ts b/src/common/connectionManager.ts
@@ -46,8 +46,8 @@ export class ConnectionStateConnected implements ConnectionState {
     public async isSearchSupported(): Promise<boolean> {
         if (this._isSearchSupported === undefined) {
             try {
-                const dummyDatabase = `search-index-test-db-${Date.now()}`;
-                const dummyCollection = `search-index-test-coll-${Date.now()}`;
+                const dummyDatabase = "test";
+                const dummyCollection = "test";
                 // If a cluster supports search indexes, the call below will succeed
                 // with a cursor otherwise will throw an Error
                 await this.serviceProvider.getSearchIndexes(dummyDatabase, dummyCollection);
diff --git a/src/common/session.ts b/src/common/session.ts
@@ -141,7 +141,7 @@ export class Session extends EventEmitter<SessionEvents> {
         return this.connectionManager.currentConnectionState.tag === "connected";
     }
 
-    get isConnectedToMongot(): Promise<boolean> {
+    isSearchSupported(): Promise<boolean> {
         const state = this.connectionManager.currentConnectionState;
         if (state.tag === "connected") {
             return state.isSearchSupported();
diff --git a/src/resources/common/debug.ts b/src/resources/common/debug.ts
@@ -61,7 +61,7 @@ export class DebugResource extends ReactiveResource<
 
         switch (this.current.tag) {
             case "connected": {
-                const searchIndexesSupported = await this.session.isConnectedToMongot;
+                const searchIndexesSupported = await this.session.isSearchSupported();
                 result += `The user is connected to the MongoDB cluster${searchIndexesSupported ? " with support for search indexes" : " without any support for search indexes"}.`;
                 break;
             }
diff --git a/src/tools/mongodb/create/createIndex.ts b/src/tools/mongodb/create/createIndex.ts
@@ -5,65 +5,66 @@ import type { ToolCategory } from "../../tool.js";
 import { type ToolArgs, type OperationType, FeatureFlags } from "../../tool.js";
 import type { IndexDirection } from "mongodb";
 
-const vectorSearchIndexDefinition = z.object({
-    type: z.literal("vectorSearch"),
-    fields: z
-        .array(
-            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"
-                            ),
-                    })
-                    .strict()
-                    .describe("Definition for a field that will be used for pre-filtering results."),
-                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."
-                            ),
-                    })
-                    .strict()
-                    .describe("Definition for a field that contains vector embeddings."),
-            ])
-        )
-        .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. 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."
-        ),
-});
-
 export class CreateIndexTool extends MongoDBToolBase {
+    private vectorSearchIndexDefinition = z.object({
+        type: z.literal("vectorSearch"),
+        fields: z
+            .array(
+                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"
+                                ),
+                        })
+                        .strict()
+                        .describe("Definition for a field that will be used for pre-filtering results."),
+                    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)
+                                .default(this.config.vectorSearchDimensions)
+                                .describe(
+                                    "Number of vector dimensions that MongoDB Vector Search enforces at index-time and query-time"
+                                ),
+                            similarity: z
+                                .enum(["cosine", "euclidean", "dotProduct"])
+                                .default(this.config.vectorSearchSimilarityFunction)
+                                .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."
+                                ),
+                        })
+                        .strict()
+                        .describe("Definition for a field that contains vector embeddings."),
+                ])
+            )
+            .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. 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."
+            ),
+    });
+
     public name = "create-index";
     protected description = "Create an index for a collection";
     protected argsShape = {
@@ -76,7 +77,7 @@ export class CreateIndexTool extends MongoDBToolBase {
                         type: z.literal("classic"),
                         keys: z.object({}).catchall(z.custom<IndexDirection>()).describe("The index definition"),
                     }),
-                    ...(this.isFeatureFlagEnabled(FeatureFlags.VectorSearch) ? [vectorSearchIndexDefinition] : []),
+                    ...(this.isFeatureFlagEnabled(FeatureFlags.VectorSearch) ? [this.vectorSearchIndexDefinition] : []),
                 ])
             )
             .describe(
@@ -110,7 +111,7 @@ export class CreateIndexTool extends MongoDBToolBase {
                 break;
             case "vectorSearch":
                 {
-                    const isVectorSearchSupported = await this.session.isConnectedToMongot;
+                    const isVectorSearchSupported = await this.session.isSearchSupported();
                     if (!isVectorSearchSupported) {
                         // TODO: remove hacky casts once we merge the local dev tools
                         const isLocalAtlasAvailable =
diff --git a/tests/unit/common/session.test.ts b/tests/unit/common/session.test.ts
@@ -134,15 +134,15 @@ describe("Session", () => {
             await session.connectToMongoDB({
                 connectionString: "mongodb://localhost:27017",
             });
-            expect(await session.isConnectedToMongot).toEqual(true);
+            expect(await session.isSearchSupported()).toEqual(true);
         });
 
         it("should return false if listing search indexes fail with search error", async () => {
             getSearchIndexesMock.mockRejectedValue(new Error("SearchNotEnabled"));
             await session.connectToMongoDB({
                 connectionString: "mongodb://localhost:27017",
             });
-            expect(await session.isConnectedToMongot).toEqual(false);
+            expect(await session.isSearchSupported()).toEqual(false);
         });
     });
 });
diff --git a/tests/unit/resources/common/debug.test.ts b/tests/unit/resources/common/debug.test.ts
@@ -103,7 +103,7 @@ describe("debug resource", () => {
     });
 
     it("should notify if a cluster supports search indexes", async () => {
-        vi.spyOn(session, "isConnectedToMongot", "get").mockImplementation(() => Promise.resolve(true));
+        vi.spyOn(session, "isSearchSupported").mockImplementation(() => Promise.resolve(true));
         debugResource.reduceApply("connect", undefined);
         const output = await debugResource.toOutput();
 

Original file line number	Diff line number	Diff line change
`@@ -141,7 +141,7 @@ export class Session extends EventEmitter<SessionEvents> {`
`141`	`141`	`return this.connectionManager.currentConnectionState.tag === "connected";`
`142`	`142`	`}`
`143`	`143`
`144`		`- get isConnectedToMongot(): Promise<boolean> {`
	`144`	`+ isSearchSupported(): Promise<boolean> {`
`145`	`145`	`const state = this.connectionManager.currentConnectionState;`
`146`	`146`	`if (state.tag === "connected") {`
`147`	`147`	`return state.isSearchSupported();`
Original file line number	Diff line number	Diff line change
`@@ -61,7 +61,7 @@ export class DebugResource extends ReactiveResource<`
`61`	`61`
`62`	`62`	`switch (this.current.tag) {`
`63`	`63`	`case "connected": {`
`64`		`- const searchIndexesSupported = await this.session.isConnectedToMongot;`
	`64`	`+ const searchIndexesSupported = await this.session.isSearchSupported();`
`65`	`65`	result += `The user is connected to the MongoDB cluster${searchIndexesSupported ? " with support for search indexes" : " without any support for search indexes"}.`;
`66`	`66`	`break;`
`67`	`67`	`}`