feat: add Google Vertex AI Vector Search support to vector store factory (#5791)

Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai> Co-authored-by: divyansh-1009 <divyansh-1009@users.noreply.github.com>
2026-07-06 22:54:24 +05:30
parent 7fb3feb5cd
commit 2bc2f763d9
8 changed files with 813 additions and 3 deletions
@@ -8,8 +8,8 @@ description: "Use Google Cloud Vertex AI Vector Search as a managed vector store

 To use Google Cloud Vertex AI Vector Search with `mem0`, you need to configure the `vector_store` in your `mem0` config:

-
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory

@@ -20,7 +20,7 @@ config = {
        "provider": "vertex_ai_vector_search",
        "config": {
            "endpoint_id": "YOUR_ENDPOINT_ID",            # Required: Vector Search endpoint ID
-            "index_id": "YOUR_INDEX_ID",                  # Required: Vector Search index ID 
+            "index_id": "YOUR_INDEX_ID",                  # Required: Vector Search index ID
            "deployment_index_id": "YOUR_DEPLOYMENT_INDEX_ID",  # Required: Deployment-specific ID
            "project_id": "YOUR_PROJECT_ID",              # Required: Google Cloud project ID
            "project_number": "YOUR_PROJECT_NUMBER",      # Required: Google Cloud project number
@@ -34,9 +34,40 @@ m = Memory.from_config(config)
 m.add("Your text here", user_id="user", metadata={"category": "example"})
 ```

+```typescript TypeScript
+import { Memory } from "mem0ai/oss";
+
+// Authenticate with GOOGLE_APPLICATION_CREDENTIALS in your environment,
+// or pass credentialsPath / serviceAccountJson in the config below.
+const config = {
+  vectorStore: {
+    provider: "vertex_ai_vector_search",
+    config: {
+      endpointId: "YOUR_ENDPOINT_ID", // Required: Vector Search endpoint ID
+      indexId: "YOUR_INDEX_ID", // Required: Vector Search index ID
+      deploymentIndexId: "YOUR_DEPLOYMENT_INDEX_ID", // Required: Deployment-specific ID
+      projectId: "YOUR_PROJECT_ID", // Required: Google Cloud project ID
+      projectNumber: "YOUR_PROJECT_NUMBER", // Required: Google Cloud project number
+      region: "YOUR_REGION", // Required: Google Cloud region
+      credentialsPath: "path/to/credentials.json", // Optional: defaults to GOOGLE_APPLICATION_CREDENTIALS
+      vectorSearchApiEndpoint: "YOUR_API_ENDPOINT", // Required for search/get operations
+    },
+  },
+};
+
+const memory = new Memory(config);
+await memory.add("Your text here", {
+  userId: "user",
+  metadata: { category: "example" },
+});
+```
+</CodeGroup>
+

 ### Required Parameters

+<Tabs>
+<Tab title="Python">
 | Parameter | Description | Required |
 |-----------|-------------|----------|
 | `endpoint_id` | Vector Search endpoint ID | Yes |
@@ -48,3 +79,18 @@ m.add("Your text here", user_id="user", metadata={"category": "example"})
 | `region` | Google Cloud region | Yes |
 | `credentials_path` | Path to service account credentials | No (defaults to GOOGLE_APPLICATION_CREDENTIALS) |
 | `service_account_json` | Service account credentials as a dictionary (alternative to `credentials_path`) | `None` |
+</Tab>
+<Tab title="TypeScript">
+| Parameter | Description | Required |
+|-----------|-------------|----------|
+| `endpointId` | Vector Search endpoint ID | Yes |
+| `indexId` | Vector Search index ID | Yes |
+| `deploymentIndexId` | Deployment-specific index ID | Yes |
+| `projectId` | Google Cloud project ID | Yes |
+| `projectNumber` | Google Cloud project number | Yes |
+| `vectorSearchApiEndpoint` | Vector search API endpoint | Yes (for get operations) |
+| `region` | Google Cloud region | Yes |
+| `credentialsPath` | Path to service account credentials | No (defaults to GOOGLE_APPLICATION_CREDENTIALS) |
+| `serviceAccountJson` | Service account credentials as an object (alternative to `credentialsPath`) | No |
+</Tab>
+</Tabs>
@@ -112,6 +112,7 @@
    "@azure/identity": "^4.0.0",
    "@azure/search-documents": "^12.0.0",
    "@cloudflare/workers-types": "^4.20250504.0",
+    "@google-cloud/aiplatform": "^6.8.0",
    "@google/genai": "^1.40.0",
    "@langchain/core": "^1.1.47",
    "@mistralai/mistralai": "^1.5.2",
@@ -44,6 +44,9 @@ importers:
      '@cloudflare/workers-types':
        specifier: ^4.20250504.0
        version: 4.20260611.1
+      '@google-cloud/aiplatform':
+        specifier: ^6.8.0
+        version: 6.8.1
      '@google/genai':
        specifier: ^1.40.0
        version: 1.52.0
@@ -695,6 +698,10 @@ packages:
    cpu: [x64]
    os: [win32]

+  '@google-cloud/aiplatform@6.8.1':
+    resolution: {integrity: sha512-8O64485bzBzQQ1VlgEhaLJcOvVlfC/V8MB5nQ5y2Dcl8UAfGXW5LkXK1CEfZ7c6IZYxpkJ9U818ldc8pg7eteg==}
+    engines: {node: '>=18'}
+
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    engines: {node: '>=20.0.0'}
@@ -704,6 +711,15 @@ packages:
      '@modelcontextprotocol/sdk':
        optional: true

+  '@grpc/grpc-js@1.14.4':
+    resolution: {integrity: sha512-k9Dj3DV/itK9D06Y8f190Qgop7/Ui+D0njFV3LHMPwPT75DpXLQohE9Wmz0QElrJnzsjB7KPWiKJbOl7IPDArQ==}
+    engines: {node: '>=12.10.0'}
+
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+    engines: {node: '>=6'}
+    hasBin: true
+
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    resolution: {integrity: sha512-Bq7B5qabyjrJfhBsl85Jd2QBtf+HzRD7h7A9GfN2lzrrsABhOa5evVPgzoCTxR7Ub0QFj7YDK1YkYRWBU25+2w==}

@@ -822,6 +838,9 @@ packages:
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+  '@js-sdsl/ordered-map@4.4.2':
+    resolution: {integrity: sha512-iUKgm52T8HOE/makSxjqoWhe95ZJA1/G1sYsGev2JDKUSS14KAgg1LHb+Ba+IPow0xflbnSkOsZcO08C7w1gYw==}
+
  '@langchain/core@1.1.48':
    resolution: {integrity: sha512-fQU6Guyb1pwc2fEplmA8FPbKfOMAofjnyJzExevro0FxEiuGHE18Ov/ZHmT9trWCDTZRI9eW1VIc6aChxV8pAQ==}
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    engines: {node: '>= 0.4'}

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+
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    engines: {node: '>= 0.4'}

+  google-auth-library@10.5.0:
+    resolution: {integrity: sha512-7ABviyMOlX5hIVD60YOfHw4/CxOfBhyduaYB+wbFWCWoni4N7SLcV46hrVRktuBbZjFC9ONyqamZITN7q3n32w==}
+    engines: {node: '>=18'}
+
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    engines: {node: '>=18'}

+  google-gax@5.0.7:
+    resolution: {integrity: sha512-EhiqaWWJ+9h7sCcKJTsoo6tMcjokVHhWsbSuWCnZJT4vIBP3y4mAoFLnt9SzgkVZeq24ZsFaArr06nnYYku2yA==}
+    engines: {node: '>=18'}
+
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    engines: {node: '>=14'}
@@ -2048,6 +2078,10 @@ packages:
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+  gtoken@8.0.0:
+    resolution: {integrity: sha512-+CqsMbHPiSTdtSO14O51eMNlrp9N79gmeqmXeouJOhfucAedHw9noVe/n5uJk3tbKE6a+6ZCQg3RPhVhHByAIw==}
+    engines: {node: '>=18'}
+
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    resolution: {integrity: sha512-4E71E0rpOaQuJR2A3xDZ+GM1HyWYv1clR58tC8emQNeQe3RH7MAzSbat+V0wG78LQBo6m6bzSG/L4pBuCsgnUQ==}
    engines: {node: '>=0.4.7'}
@@ -2447,6 +2481,9 @@ packages:
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    engines: {node: '>=8'}

+  lodash.camelcase@4.3.0:
+    resolution: {integrity: sha512-TwuEnCnxbc3rAvhf/LbG7tJUDzhqXyFnv3dtzLOPgCG/hODL7WFnsbwktkD7yUV0RrreP/l1PALq/YSg6VvjlA==}
+
  lodash.defaults@4.2.0:
    resolution: {integrity: sha512-qjxPLHd3r5DnsdGacqOMU6pb/avJzdh9tFX2ymgoZE27BmjXrNy/y4LoaiTeAb+O3gL8AfpJGtqfX/ae2leYYQ==}

@@ -2708,6 +2745,10 @@ packages:
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    engines: {node: '>=0.10.0'}

+  object-hash@3.0.0:
+    resolution: {integrity: sha512-RSn9F68PjH9HqtltsSnqYC1XXoWe9Bju5+213R98cNGttag9q9yAOTzdbsqvIa7aNm5WffBZFpWYr2aWrklWAw==}
+    engines: {node: '>= 6'}
+
  object-keys@1.1.1:
    resolution: {integrity: sha512-NuAESUOUMrlIXOfHKzD6bpPu3tYt3xvjNdRIQ+FeT0lNb4K8WR70CaDxhuNguS2XG+GjkyMwOzsN5ZktImfhLA==}
    engines: {node: '>= 0.4'}
@@ -2965,6 +3006,10 @@ packages:
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    engines: {node: '>= 6'}

+  proto3-json-serializer@3.0.4:
+    resolution: {integrity: sha512-E1sbAYg3aEbXrq0n1ojJkRHQJGE1kaE/O6GLA94y8rnJBfgvOPTOd1b9hOceQK1FFZI9qMh1vBERCyO2ifubcw==}
+    engines: {node: '>=18'}
+
  protobufjs@7.6.3:
    resolution: {integrity: sha512-+k0vdJKNdW+Vu+dYe8tZA/VvQb6XKNWexC6URwBFXxNnjLJz9nQJCemGyNgRAWD+B7+nGNc9qMPGwcD7s4nzUw==}
    engines: {node: '>=12.0.0'}
@@ -3048,6 +3093,10 @@ packages:
    engines: {node: '>= 0.4'}
    hasBin: true

+  retry-request@8.0.3:
+    resolution: {integrity: sha512-qqoc4kkGgP9cmQDWELlOpAmfgJOg0Yi7MT82ZjiPWu451ayju4itwomjM4/dBEliify8C1b3tSaeCOldugtwPQ==}
+    engines: {node: '>=18'}
+
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    resolution: {integrity: sha512-XQBQ3I8W1Cge0Seh+6gjj03LbmRFWuoszgK9ooCpwYIrhhoO80pfq4cUkU5DkknwfOfFteRwlZ56PYOGYyFWdg==}
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@@ -3178,6 +3227,12 @@ packages:
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    engines: {node: '>=0.10.0'}

+  stream-events@1.0.5:
+    resolution: {integrity: sha512-E1GUzBSgvct8Jsb3v2X15pjzN1tYebtbLaMg+eBOUOAxgbLoSbT2NS91ckc5lJD1KfLjId+jXJRgo0qnV5Nerg==}
+
+  stream-shift@1.0.3:
+    resolution: {integrity: sha512-76ORR0DO1o1hlKwTbi/DM3EXWGf3ZJYO8cXX5RJwnul2DEg2oyoZyjLNoQM8WsvZiFKCRfC1O0J7iCvie3RZmQ==}
+
  string-length@4.0.2:
    resolution: {integrity: sha512-+l6rNN5fYHNhZZy41RXsYptCjA2Igmq4EG7kZAYFQI1E1VTXarr6ZPXBg6eq7Y6eK4FEhY6AJlyuFIb/v/S0VQ==}
    engines: {node: '>=10'}
@@ -3220,6 +3275,9 @@ packages:
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+  stubs@3.0.0:
+    resolution: {integrity: sha512-PdHt7hHUJKxvTCgbKX9C1V/ftOcjJQgz8BZwNfV5c4B6dcGqlpelTbJ999jBGZ2jYiPAwcX5dP6oBwVlBlUbxw==}
+
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    resolution: {integrity: sha512-DhuTmvZWux4H1UOnWMB3sk0sbaCVOoQZjv8u1rDoTV0HTdGem9hkAZtl4JZy8P2z4Bg0nT+YMeOFyVr4zcG5Tw==}
    engines: {node: '>=16 || 14 >=14.17'}
@@ -3264,6 +3322,10 @@ packages:
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    engines: {node: '>=18'}

+  teeny-request@10.1.3:
+    resolution: {integrity: sha512-5yDliI1uWkYPo7W+Zvrxg6YmoWuj5iC5EydewqrRTvc68nyMTZhlPPlLg6cptUGfbQAb+N9XDPDPzF6N081lug==}
+    engines: {node: '>=18'}
+
  test-exclude@6.0.0:
    resolution: {integrity: sha512-cAGWPIyOHU6zlmg88jwm7VRyXnMN7iV68OGAbYDk/Mh/xC/pzVPlQtY6ngoIH/5/tciuhGfvESU8GrHrcxD56w==}
    engines: {node: '>=8'}
@@ -4351,6 +4413,12 @@ snapshots:
  '@esbuild/win32-x64@0.28.1':
    optional: true

+  '@google-cloud/aiplatform@6.8.1':
+    dependencies:
+      google-gax: 5.0.7
+    transitivePeerDependencies:
+      - supports-color
+
  '@google/genai@1.52.0':
    dependencies:
      google-auth-library: 10.7.0
@@ -4362,6 +4430,18 @@ snapshots:
      - supports-color
      - utf-8-validate

+  '@grpc/grpc-js@1.14.4':
+    dependencies:
+      '@grpc/proto-loader': 0.8.1
+      '@js-sdsl/ordered-map': 4.4.2
+
+  '@grpc/proto-loader@0.8.1':
+    dependencies:
+      lodash.camelcase: 4.3.0
+      long: 5.3.2
+      protobufjs: 7.6.3
+      yargs: 17.7.2
+
  '@huggingface/blake3-jit@0.0.2': {}

  '@huggingface/hub@2.13.2':
@@ -4589,6 +4669,8 @@ snapshots:
      '@jridgewell/resolve-uri': 3.1.2
      '@jridgewell/sourcemap-codec': 1.5.5

+  '@js-sdsl/ordered-map@4.4.2': {}
+
  '@langchain/core@1.1.48(openai@4.104.0(ws@8.21.0)(zod@3.25.76))(ws@8.21.0)':
    dependencies:
      '@cfworker/json-schema': 4.1.1
@@ -5520,6 +5602,13 @@ snapshots:
      es-errors: 1.3.0
      gopd: 1.2.0

+  duplexify@4.1.3:
+    dependencies:
+      end-of-stream: 1.4.5
+      inherits: 2.0.4
+      readable-stream: 3.6.2
+      stream-shift: 1.0.3
+
  eastasianwidth@0.2.0: {}

  ecdsa-sig-formatter@1.0.11:
@@ -5814,6 +5903,18 @@ snapshots:
      define-properties: 1.2.1
      gopd: 1.2.0

+  google-auth-library@10.5.0:
+    dependencies:
+      base64-js: 1.5.1
+      ecdsa-sig-formatter: 1.0.11
+      gaxios: 7.1.5
+      gcp-metadata: 8.1.2
+      google-logging-utils: 1.1.3
+      gtoken: 8.0.0
+      jws: 4.0.1
+    transitivePeerDependencies:
+      - supports-color
+
  google-auth-library@10.7.0:
    dependencies:
      base64-js: 1.5.1
@@ -5825,6 +5926,22 @@ snapshots:
    transitivePeerDependencies:
      - supports-color

+  google-gax@5.0.7:
+    dependencies:
+      '@grpc/grpc-js': 1.14.4
+      '@grpc/proto-loader': 0.8.1
+      duplexify: 4.1.3
+      google-auth-library: 10.5.0
+      google-logging-utils: 1.1.3
+      node-fetch: 3.3.2
+      object-hash: 3.0.0
+      proto3-json-serializer: 3.0.4
+      protobufjs: 7.6.3
+      retry-request: 8.0.3
+      rimraf: 5.0.10
+    transitivePeerDependencies:
+      - supports-color
+
  google-logging-utils@1.1.3: {}

  gopd@1.2.0: {}
@@ -5847,6 +5964,13 @@ snapshots:
    transitivePeerDependencies:
      - encoding

+  gtoken@8.0.0:
+    dependencies:
+      gaxios: 7.1.5
+      jws: 4.0.1
+    transitivePeerDependencies:
+      - supports-color
+
  handlebars@4.7.9:
    dependencies:
      minimist: 1.2.8
@@ -6414,6 +6538,8 @@ snapshots:
    dependencies:
      p-locate: 4.1.0

+  lodash.camelcase@4.3.0: {}
+
  lodash.defaults@4.2.0: {}

  lodash.includes@4.3.0: {}
@@ -6658,6 +6784,8 @@ snapshots:

  object-assign@4.1.1: {}

+  object-hash@3.0.0: {}
+
  object-keys@1.1.1: {}

  obuf@1.1.2: {}
@@ -6905,6 +7033,10 @@ snapshots:
      kleur: 3.0.3
      sisteransi: 1.0.5

+  proto3-json-serializer@3.0.4:
+    dependencies:
+      protobufjs: 7.6.3
+
  protobufjs@7.6.3:
    dependencies:
      '@protobufjs/aspromise': 1.1.2
@@ -7006,6 +7138,13 @@ snapshots:
      path-parse: 1.0.7
      supports-preserve-symlinks-flag: 1.0.0

+  retry-request@8.0.3:
+    dependencies:
+      extend: 3.0.2
+      teeny-request: 10.1.3
+    transitivePeerDependencies:
+      - supports-color
+
  retry@0.13.1: {}

  reusify@1.1.0: {}
@@ -7141,6 +7280,12 @@ snapshots:

  stopwords-iso@1.1.0: {}

+  stream-events@1.0.5:
+    dependencies:
+      stubs: 3.0.0
+
+  stream-shift@1.0.3: {}
+
  string-length@4.0.2:
    dependencies:
      char-regex: 1.0.2
@@ -7182,6 +7327,8 @@ snapshots:
    dependencies:
      anynum: 1.0.1

+  stubs@3.0.0: {}
+
  sucrase@3.35.1:
    dependencies:
      '@jridgewell/gen-mapping': 0.3.13
@@ -7242,6 +7389,15 @@ snapshots:
      minizlib: 3.1.0
      yallist: 5.0.0

+  teeny-request@10.1.3:
+    dependencies:
+      http-proxy-agent: 7.0.2
+      https-proxy-agent: 7.0.6
+      node-fetch: 3.3.2
+      stream-events: 1.0.5
+    transitivePeerDependencies:
+      - supports-color
+
  test-exclude@6.0.0:
    dependencies:
      '@istanbuljs/schema': 0.1.6
@@ -34,4 +34,5 @@ export * from "./vector_stores/azure_ai_search";
 export * from "./vector_stores/pgvector";
 export * from "./vector_stores/cassandra";
 export * from "./vector_stores/s3_vectors";
+export * from "./vector_stores/vertex_ai_vector_search";
 export * from "./utils/factory";
@@ -42,6 +42,7 @@ import { LangchainEmbedder } from "../embeddings/langchain";
 import { LangchainVectorStore } from "../vector_stores/langchain";
 import { AzureAISearch } from "../vector_stores/azure_ai_search";
 import { PGVector } from "../vector_stores/pgvector";
+import { VertexAIVectorSearch } from "../vector_stores/vertex_ai_vector_search";
 import { CassandraDB } from "../vector_stores/cassandra";
 import { PineconeDB } from "../vector_stores/pinecone";
 import { S3Vectors } from "../vector_stores/s3_vectors";
@@ -129,6 +130,8 @@ export class VectorStoreFactory {
        return new VectorizeDB(config as any);
      case "azure-ai-search":
        return new AzureAISearch(config as any);
+      case "vertex_ai_vector_search":
+        return new VertexAIVectorSearch(config as any);
      case "pgvector":
        return new PGVector(config as any);
      case "cassandra":
@@ -0,0 +1,360 @@
+import { VectorStore } from "./base";
+import { SearchFilters, VectorStoreConfig, VectorStoreResult } from "../types";
+
+export interface GoogleMatchingEngineConfig extends VectorStoreConfig {
+  projectId: string;
+  projectNumber: string;
+  region: string;
+  endpointId: string;
+  indexId: string;
+  deploymentIndexId: string;
+  collectionName?: string;
+  credentialsPath?: string;
+  serviceAccountJson?: Record<string, any>;
+  vectorSearchApiEndpoint?: string;
+}
+
+export class VertexAIVectorSearch implements VectorStore {
+  private config: GoogleMatchingEngineConfig;
+  private matchClient: any;
+  private indexClient: any;
+  private _initPromise?: Promise<void>;
+
+  constructor(config: GoogleMatchingEngineConfig) {
+    this.config = { ...config };
+    if (!this.config.collectionName) {
+      this.config.collectionName =
+        this.config.indexId || this.config.deploymentIndexId;
+    }
+    this.initialize().catch(console.error);
+  }
+
+  async initialize(): Promise<void> {
+    if (!this._initPromise) {
+      this._initPromise = this._doInitialize();
+    }
+    return this._initPromise;
+  }
+
+  private async _doInitialize(): Promise<void> {
+    try {
+      const aiplatform = await import("@google-cloud/aiplatform");
+      const { MatchServiceClient, IndexServiceClient } = aiplatform.v1;
+
+      const clientOptions: any = {
+        projectId: this.config.projectId,
+        apiEndpoint:
+          this.config.vectorSearchApiEndpoint ||
+          `${this.config.region}-aiplatform.googleapis.com`,
+      };
+
+      if (this.config.credentialsPath) {
+        clientOptions.keyFilename = this.config.credentialsPath;
+      } else if (this.config.serviceAccountJson) {
+        clientOptions.credentials = {
+          client_email: this.config.serviceAccountJson.client_email,
+          private_key: this.config.serviceAccountJson.private_key,
+        };
+      }
+
+      this.matchClient = new MatchServiceClient(clientOptions);
+      this.indexClient = new IndexServiceClient(clientOptions);
+    } catch (error) {
+      console.error(
+        "Failed to initialize Vertex AI client. Make sure @google-cloud/aiplatform is installed.",
+        error,
+      );
+      throw error;
+    }
+  }
+
+  private _createRestriction(key: string, value: any): any {
+    return {
+      namespace: key,
+      allowList: [String(value)],
+    };
+  }
+
+  private _createDatapoint(
+    vectorId: string,
+    vector: number[],
+    payload: Record<string, any> = {},
+  ): any {
+    const restricts = Object.entries(payload).map(([key, value]) =>
+      this._createRestriction(key, value),
+    );
+    return {
+      datapointId: vectorId,
+      featureVector: vector,
+      restricts: restricts.length > 0 ? restricts : undefined,
+    };
+  }
+
+  private get indexPath(): string {
+    return `projects/${this.config.projectNumber}/locations/${this.config.region}/indexes/${this.config.indexId}`;
+  }
+
+  private get indexEndpointPath(): string {
+    return `projects/${this.config.projectNumber}/locations/${this.config.region}/indexEndpoints/${this.config.endpointId}`;
+  }
+
+  async insert(
+    vectors: number[][],
+    ids: string[],
+    payloads: Record<string, any>[],
+  ): Promise<void> {
+    await this.initialize();
+    const datapoints = vectors.map((vector, i) =>
+      this._createDatapoint(ids[i], vector, payloads[i] || {}),
+    );
+
+    await this.indexClient.upsertDatapoints({
+      index: this.indexPath,
+      datapoints,
+    });
+  }
+
+  async search(
+    query: number[],
+    topK: number = 5,
+    filters?: SearchFilters,
+  ): Promise<VectorStoreResult[]> {
+    if (!this.config.vectorSearchApiEndpoint) {
+      throw new Error(
+        "vectorSearchApiEndpoint is required for search operation",
+      );
+    }
+    await this.initialize();
+
+    const restricts: any[] = [];
+    if (filters) {
+      for (const [key, value] of Object.entries(filters)) {
+        if (typeof value === "object" && value !== null) {
+          const includes = value.include || [];
+          const excludes = value.exclude || [];
+          restricts.push({
+            namespace: key,
+            allowList: includes.map(String),
+            denyList: excludes.map(String),
+          });
+        } else {
+          restricts.push({
+            namespace: key,
+            allowList: [String(value)],
+          });
+        }
+      }
+    }
+
+    const request = {
+      indexEndpoint: this.indexEndpointPath,
+      deployedIndexId: this.config.deploymentIndexId,
+      queries: [
+        {
+          datapoint: {
+            featureVector: query,
+            restricts: restricts.length > 0 ? restricts : undefined,
+          },
+          neighborCount: topK,
+        },
+      ],
+      returnFullDatapoint: true,
+    };
+
+    const [response] = await this.matchClient.findNeighbors(request);
+
+    if (
+      !response ||
+      !response.nearestNeighbors ||
+      response.nearestNeighbors.length === 0
+    ) {
+      return [];
+    }
+
+    const neighbors = response.nearestNeighbors[0].neighbors || [];
+    return neighbors
+      .filter(
+        (neighbor: any) =>
+          neighbor.datapoint?.datapointId !== "mem0-user-id-record",
+      )
+      .map((neighbor: any) => {
+        const payload: Record<string, any> = {};
+        if (neighbor.datapoint?.restricts) {
+          for (const restrict of neighbor.datapoint.restricts) {
+            if (restrict.allowList && restrict.allowList.length > 0) {
+              payload[restrict.namespace] = restrict.allowList[0];
+            }
+          }
+        }
+
+        const score =
+          neighbor.distance !== undefined
+            ? Math.max(0.0, 1.0 - neighbor.distance)
+            : undefined;
+        return {
+          id: neighbor.datapoint.datapointId,
+          payload,
+          score,
+        };
+      });
+  }
+
+  async get(vectorId: string): Promise<VectorStoreResult | null> {
+    if (!this.config.vectorSearchApiEndpoint) {
+      throw new Error("vectorSearchApiEndpoint is required for get operation");
+    }
+    await this.initialize();
+
+    const request = {
+      indexEndpoint: this.indexEndpointPath,
+      deployedIndexId: this.config.deploymentIndexId,
+      queries: [
+        {
+          datapoint: {
+            datapointId: vectorId,
+          },
+          neighborCount: 1,
+        },
+      ],
+      returnFullDatapoint: true,
+    };
+
+    const [response] = await this.matchClient.findNeighbors(request);
+
+    if (
+      !response ||
+      !response.nearestNeighbors ||
+      response.nearestNeighbors.length === 0
+    ) {
+      return null;
+    }
+
+    const neighbors = response.nearestNeighbors[0].neighbors || [];
+    if (neighbors.length === 0) {
+      return null;
+    }
+
+    const neighbor = neighbors[0];
+    if (neighbor.datapoint?.datapointId !== vectorId) {
+      return null;
+    }
+
+    const payload: Record<string, any> = {};
+    if (neighbor.datapoint?.restricts) {
+      for (const restrict of neighbor.datapoint.restricts) {
+        if (restrict.allowList && restrict.allowList.length > 0) {
+          payload[restrict.namespace] = restrict.allowList[0];
+        }
+      }
+    }
+
+    const score =
+      neighbor.distance !== undefined
+        ? Math.max(0.0, 1.0 - neighbor.distance)
+        : undefined;
+    return {
+      id: neighbor.datapoint.datapointId,
+      payload,
+      score,
+    };
+  }
+
+  async keywordSearch(
+    query: string,
+    topK?: number,
+    filters?: SearchFilters,
+  ): Promise<VectorStoreResult[] | null> {
+    return null;
+  }
+
+  async update(
+    vectorId: string,
+    vector: number[],
+    payload: Record<string, any>,
+  ): Promise<void> {
+    await this.initialize();
+
+    // Verify existence first
+    const existing = await this.get(vectorId);
+    if (!existing) {
+      console.warn(`Vector not found for id: ${vectorId}`);
+      return;
+    }
+
+    const datapoint = this._createDatapoint(vectorId, vector, payload);
+    await this.indexClient.upsertDatapoints({
+      index: this.indexPath,
+      datapoints: [datapoint],
+    });
+  }
+
+  async delete(vectorId: string): Promise<void> {
+    await this.initialize();
+    try {
+      await this.indexClient.removeDatapoints({
+        index: this.indexPath,
+        datapointIds: [vectorId],
+      });
+    } catch (error: any) {
+      // Ignore if not found
+      if (error.code !== 5) {
+        // 5 is NOT_FOUND in gRPC
+        throw error;
+      }
+    }
+  }
+
+  async deleteCol(): Promise<void> {
+    console.warn(
+      "Delete collection operation is not supported for Google Matching Engine",
+    );
+  }
+
+  async list(
+    filters?: SearchFilters,
+    topK: number = 10000,
+  ): Promise<[VectorStoreResult[], number]> {
+    await this.initialize();
+
+    // We do not have dimension natively, usually 768 or 1536.
+    // Vertex AI returns error if vector size is wrong, but some setups might allow empty vector.
+    // In Python SDK, it uses a zero vector of size 768.
+    const dimension = this.config.dimension || 768;
+    const zeroVector = Array(dimension).fill(0.0);
+
+    const results = await this.search(zeroVector, topK, filters);
+    return [results, results.length];
+  }
+
+  async getUserId(): Promise<string> {
+    // Vertex AI doesn't easily let us create arbitrary new indexes dynamically.
+    // So we use a special datapoint in the same index, with a specific ID.
+    const userIdDatapointId = "mem0-user-id-record";
+    const existing = await this.get(userIdDatapointId);
+    if (existing && existing.payload?.user_id) {
+      return existing.payload.user_id;
+    }
+
+    const randomUserId =
+      Math.random().toString(36).substring(2, 15) +
+      Math.random().toString(36).substring(2, 15);
+
+    await this.setUserId(randomUserId);
+    return randomUserId;
+  }
+
+  async setUserId(userId: string): Promise<void> {
+    await this.initialize();
+    const userIdDatapointId = "mem0-user-id-record";
+    const dimension = this.config.dimension || 768;
+    const zeroVector = Array(dimension).fill(0.0);
+
+    const datapoint = this._createDatapoint(userIdDatapointId, zeroVector, {
+      user_id: userId,
+    });
+    await this.indexClient.upsertDatapoints({
+      index: this.indexPath,
+      datapoints: [datapoint],
+    });
+  }
+}
@@ -0,0 +1,242 @@
+/// <reference types="jest" />
+import { VertexAIVectorSearch } from "../src/vector_stores/vertex_ai_vector_search";
+
+jest.mock("@google-cloud/aiplatform", () => {
+  const MatchServiceClient = jest.fn().mockImplementation(() => ({
+    findNeighbors: jest.fn().mockResolvedValue([{ nearestNeighbors: [] }]),
+  }));
+  const IndexServiceClient = jest.fn().mockImplementation(() => ({
+    upsertDatapoints: jest.fn().mockResolvedValue([{}]),
+    removeDatapoints: jest.fn().mockResolvedValue([{}]),
+  }));
+  return {
+    v1: {
+      MatchServiceClient,
+      IndexServiceClient,
+    },
+  };
+});
+
+describe("VertexAIVectorSearch", () => {
+  let store: VertexAIVectorSearch;
+
+  beforeEach(() => {
+    store = new VertexAIVectorSearch({
+      projectId: "test-project",
+      projectNumber: "123456789",
+      region: "us-central1",
+      endpointId: "test-endpoint",
+      indexId: "test-index",
+      deploymentIndexId: "test-deployment",
+      vectorSearchApiEndpoint: "test-api-endpoint",
+    });
+  });
+
+  it("should initialize with correct collection name", () => {
+    expect((store as any).config.collectionName).toBe("test-index");
+  });
+
+  it("should insert vectors", async () => {
+    await store.insert([[1, 2, 3]], ["id1"], [{ key: "value" }]);
+    expect((store as any).indexClient.upsertDatapoints).toHaveBeenCalled();
+  });
+
+  it("should search vectors", async () => {
+    const results = await store.search([1, 2, 3], 5);
+    expect((store as any).matchClient.findNeighbors).toHaveBeenCalled();
+    expect(results).toEqual([]);
+  });
+
+  it("should search vectors and return populated results", async () => {
+    const mockFindNeighbors = jest.fn().mockResolvedValue([
+      {
+        nearestNeighbors: [
+          {
+            neighbors: [
+              {
+                datapoint: {
+                  datapointId: "id1",
+                  restricts: [{ namespace: "key", allowList: ["value"] }],
+                },
+                distance: 0.1,
+              },
+            ],
+          },
+        ],
+      },
+    ]);
+    (store as any).matchClient.findNeighbors = mockFindNeighbors;
+
+    const results = await store.search([1, 2, 3], 5, { key: "value" });
+
+    expect(mockFindNeighbors).toHaveBeenCalled();
+    // It should map payload correctly and score should be 1.0 - distance
+    expect(results).toEqual([
+      {
+        id: "id1",
+        payload: { key: "value" },
+        score: 0.9,
+      },
+    ]);
+  });
+
+  it("should get vector by id", async () => {
+    const result = await store.get("id1");
+    expect((store as any).matchClient.findNeighbors).toHaveBeenCalled();
+    expect(result).toBeNull();
+  });
+
+  it("should build allowList/denyList restricts from include/exclude filters", async () => {
+    const spy = jest.fn().mockResolvedValue([{ nearestNeighbors: [] }]);
+    (store as any).matchClient.findNeighbors = spy;
+
+    await store.search([1, 2, 3], 5, {
+      key: { include: ["a"], exclude: ["b"] },
+    });
+
+    const request = spy.mock.calls[0][0];
+    expect(request.queries[0].datapoint.restricts).toEqual([
+      { namespace: "key", allowList: ["a"], denyList: ["b"] },
+    ]);
+  });
+
+  it("should exclude the mem0-user-id-record sentinel from search results", async () => {
+    (store as any).matchClient.findNeighbors = jest.fn().mockResolvedValue([
+      {
+        nearestNeighbors: [
+          {
+            neighbors: [
+              {
+                datapoint: { datapointId: "mem0-user-id-record" },
+                distance: 0.0,
+              },
+              { datapoint: { datapointId: "id1" }, distance: 0.1 },
+            ],
+          },
+        ],
+      },
+    ]);
+
+    const results = await store.search([1, 2, 3], 5);
+    expect(results.map((r) => r.id)).toEqual(["id1"]);
+  });
+
+  it("should update an existing vector", async () => {
+    (store as any).matchClient.findNeighbors = jest.fn().mockResolvedValue([
+      {
+        nearestNeighbors: [
+          {
+            neighbors: [{ datapoint: { datapointId: "id1" }, distance: 0.1 }],
+          },
+        ],
+      },
+    ]);
+
+    await store.update("id1", [4, 5, 6], { key: "new" });
+    expect((store as any).indexClient.upsertDatapoints).toHaveBeenCalled();
+  });
+
+  it("should skip update when the vector does not exist", async () => {
+    const warnSpy = jest.spyOn(console, "warn").mockImplementation(() => {});
+
+    // default findNeighbors returns empty → get() resolves null
+    await store.update("missing", [4, 5, 6], { key: "new" });
+
+    expect((store as any).indexClient.upsertDatapoints).not.toHaveBeenCalled();
+    expect(warnSpy).toHaveBeenCalled();
+    warnSpy.mockRestore();
+  });
+
+  it("should delete a vector by id", async () => {
+    await store.delete("id1");
+    expect((store as any).indexClient.removeDatapoints).toHaveBeenCalledWith({
+      index: expect.any(String),
+      datapointIds: ["id1"],
+    });
+  });
+
+  it("should ignore NOT_FOUND (gRPC code 5) on delete", async () => {
+    (store as any).indexClient.removeDatapoints = jest
+      .fn()
+      .mockRejectedValue({ code: 5 });
+    await expect(store.delete("missing")).resolves.toBeUndefined();
+  });
+
+  it("should rethrow non-NOT_FOUND errors on delete", async () => {
+    (store as any).indexClient.removeDatapoints = jest
+      .fn()
+      .mockRejectedValue({ code: 13 });
+    await expect(store.delete("id1")).rejects.toEqual({ code: 13 });
+  });
+
+  it("should list vectors via a zero-vector search", async () => {
+    (store as any).matchClient.findNeighbors = jest.fn().mockResolvedValue([
+      {
+        nearestNeighbors: [
+          {
+            neighbors: [{ datapoint: { datapointId: "id1" }, distance: 0.2 }],
+          },
+        ],
+      },
+    ]);
+
+    const [results, count] = await store.list();
+    expect((store as any).matchClient.findNeighbors).toHaveBeenCalled();
+    expect(count).toBe(1);
+    expect(results[0].id).toBe("id1");
+  });
+
+  it("should return null for keywordSearch (unsupported)", async () => {
+    await expect(store.keywordSearch("hello")).resolves.toBeNull();
+  });
+
+  it("should warn and no-op on deleteCol (unsupported)", async () => {
+    const warnSpy = jest.spyOn(console, "warn").mockImplementation(() => {});
+    await store.deleteCol();
+    expect(warnSpy).toHaveBeenCalled();
+    warnSpy.mockRestore();
+  });
+
+  it("should set a user id via the sentinel datapoint", async () => {
+    await store.setUserId("user-123");
+
+    expect((store as any).indexClient.upsertDatapoints).toHaveBeenCalled();
+    const request = (store as any).indexClient.upsertDatapoints.mock
+      .calls[0][0];
+    expect(request.datapoints[0].datapointId).toBe("mem0-user-id-record");
+  });
+
+  it("should return an existing user id from the sentinel record", async () => {
+    (store as any).matchClient.findNeighbors = jest.fn().mockResolvedValue([
+      {
+        nearestNeighbors: [
+          {
+            neighbors: [
+              {
+                datapoint: {
+                  datapointId: "mem0-user-id-record",
+                  restricts: [
+                    { namespace: "user_id", allowList: ["existing-user"] },
+                  ],
+                },
+                distance: 0.0,
+              },
+            ],
+          },
+        ],
+      },
+    ]);
+
+    const userId = await store.getUserId();
+    expect(userId).toBe("existing-user");
+  });
+
+  it("should generate and persist a new user id when none exists", async () => {
+    // default findNeighbors empty → get() null → generate + setUserId
+    const userId = await store.getUserId();
+
+    expect(typeof userId).toBe("string");
+    expect(userId.length).toBeGreaterThan(0);
+    expect((store as any).indexClient.upsertDatapoints).toHaveBeenCalled();
+  });
+});
@@ -17,6 +17,7 @@ const external = [
  "iovalkey",
  "ollama",
  "@google/genai",
+  "@google-cloud/aiplatform",
  "@mistralai/mistralai",
  "@supabase/supabase-js",
  "@azure/search-documents",