Add VertexAI extension

docs/src/pages/docs/remote-models/vertexai.mdx

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+---
+title: VertexAI API
+description: A step-by-step guide on integrating Jan with VertexAI.
+keywords:
+  [
+    Jan,
+    Customizable Intelligence, LLM,
+    local AI,
+    privacy focus,
+    free and open source,
+    private and offline,
+    conversational AI,
+    no-subscription fee,
+    large language models,
+    integration,
+    VertexAI,
+    Google,
+    GCP
+  ]
+---
+
+import { Callout, Steps } from 'nextra/components'
+
+
+
+# VertexAI API
+
+<Callout type='info'>
+The VertexAI Extension can be used select models that [support the openai endpoints](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/call-vertex-using-openai-library) on vertexAI's.
+</Callout>
+
+## How to Integrate VertexAI API with Jan
+This guide provides step-by-step instructions for integrating the VertexAI API with Jan, allowing users to utilize VertexAI's capabilities within Jan's conversational interface.
+
+## Integration Steps
+<Steps>
+### Step 1: Configure GCP Service Account
+1. Open the [Credentials page](https://console.cloud.google.com/apis/credentials) in GCP
+2. Select your project
+3. Create Credentials -> Service Account
+4. Give your service account a name
+5. Give at least the "Vertex AI Online Prediction Service Agent" role
+6. Click on the account, then the "Keys" tab
+7. Create new key -> select json.
+8. Copy the exact project id, private key id, private key, and client email into your JAN configuration.
+9. Set the region to what is appropriate for your instance
+
+### Step 2: Start Chatting with the Model
+
+1. Select the VertexAI model you want to use.
+2. Specify the model's parameters.
+3. Start the conversation with the VertexAI model.
+</Steps>
+
+### VertexAI Models
+
+You can also use specific VertexAI models you cannot find in the **Hub** section by customizing the `model.yaml` file, which you can see in the `~/jan/data/models/`. Follow the steps in the [Manage Models](/docs/models/manage-models) to manually add a model.
+
+<Callout type='info'>
+- You can find the list of available models in the [VertexAI documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/call-vertex-using-openai-library).
+- The `id` property must match the model name in the list.
+  - For example, if you want to use the Gemini 1.0 Pro model you must set the `id` property to `google/gemini-1.0-pro-002`.
+</Callout>
+
+## Troubleshooting
+
+If you encounter any issues during the integration process or while using VertexAI with Jan, consider the following troubleshooting steps:
+
+- Double-check your service account is active.
+- Confirm the model you selected is available in your selected region.
+- Ensure the model is enabled in VertexAI model garden.
+- Check for error messages or logs that may provide insight into the issue.

extensions/inference-vertexai-extension/README.md

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+# VertexAI Engine Extension
+
+Created using Jan extension example
+
+# Create a Jan Extension using Typescript
+
+Use this template to bootstrap the creation of a TypeScript Jan extension. 🚀
+
+## Create Your Own Extension
+
+To create your own extension, you can use this repository as a template! Just follow the below instructions:
+
+1. Click the Use this template button at the top of the repository
+2. Select Create a new repository
+3. Select an owner and name for your new repository
+4. Click Create repository
+5. Clone your new repository
+
+## Initial Setup
+
+After you've cloned the repository to your local machine or codespace, you'll need to perform some initial setup steps before you can develop your extension.
+
+> [!NOTE]
+>
+> You'll need to have a reasonably modern version of
+> [Node.js](https://nodejs.org) handy. If you are using a version manager like
+> [`nodenv`](https://github.com/nodenv/nodenv) or
+> [`nvm`](https://github.com/nvm-sh/nvm), you can run `nodenv install` in the
+> root of your repository to install the version specified in
+> [`package.json`](./package.json). Otherwise, 20.x or later should work!
+
+1. :hammer_and_wrench: Install the dependencies
+
+   ```bash
+   npm install
+   ```
+
+1. :building_construction: Package the TypeScript for distribution
+
+   ```bash
+   npm run bundle
+   ```
+
+1. :white_check_mark: Check your artifact
+
+   There will be a tgz file in your extension directory now
+
+## Update the Extension Metadata
+
+The [`package.json`](package.json) file defines metadata about your extension, such as
+extension name, main entry, description and version.
+
+When you copy this repository, update `package.json` with the name, description for your extension.
+
+## Update the Extension Code
+
+The [`src/`](./src/) directory is the heart of your extension! This contains the
+source code that will be run when your extension functions are invoked. You can replace the
+contents of this directory with your own code.
+
+There are a few things to keep in mind when writing your extension code:
+
+- Most Jan Extension functions are processed asynchronously.
+  In `index.ts`, you will see that the extension function will return a `Promise<any>`.
+
+  ```typescript
+  import { events, MessageEvent, MessageRequest } from '@janhq/core'
+
+  function onStart(): Promise<any> {
+    return events.on(MessageEvent.OnMessageSent, (data: MessageRequest) =>
+      this.inference(data)
+    )
+  }
+  ```
+
+  For more information about the Jan Extension Core module, see the
+  [documentation](https://github.com/janhq/jan/blob/main/core/README.md).
+
+So, what are you waiting for? Go ahead and start customizing your extension!

extensions/inference-vertexai-extension/jest.config.js

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+/** @type {import('ts-jest').JestConfigWithTsJest} */
+module.exports = {
+  preset: 'ts-jest',
+  testEnvironment: 'node',
+  transform: {
+    'node_modules/@janhq/core/.+\\.(j|t)s?$': 'ts-jest',
+  },
+  transformIgnorePatterns: ['node_modules/(?!@janhq/core/.*)'],
+}

extensions/inference-vertexai-extension/package.json

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+{
+  "name": "@janhq/inference-vertexai-extension",
+  "productName": "VertexAI Inference Engine",
+  "version": "1.0.0",
+  "description": "This extension enables Vertex chat completion API calls",
+  "main": "dist/index.js",
+  "module": "dist/module.js",
+  "engine": "vertexai",
+  "author": "Jan <[email protected]>",
+  "license": "AGPL-3.0",
+  "scripts": {
+    "build": "rolldown -c rolldown.config.mjs",
+    "build:publish": "rimraf *.tgz --glob || true && yarn build && npm pack && cpx *.tgz ../../pre-install"
+  },
+  "devDependencies": {
+    "cpx": "^1.5.0",
+    "rimraf": "^3.0.2",
+    "rolldown": "1.0.0-beta.1",
+    "ts-loader": "^9.5.0",
+    "typescript": "^5.7.2"
+  },
+  "dependencies": {
+    "@janhq/core": "../../core/package.tgz",
+    "fetch-retry": "^5.0.6",
+    "jose": "^5.9.6",
+    "ulidx": "^2.3.0"
+  },
+  "engines": {
+    "node": ">=18.0.0"
+  },
+  "files": [
+    "dist/*",
+    "package.json",
+    "README.md"
+  ],
+  "bundleDependencies": [
+    "fetch-retry"
+  ],
+  "installConfig": {
+    "hoistingLimits": "workspaces"
+  },
+  "packageManager": "[email protected]"
+}

extensions/inference-vertexai-extension/resources/models.json

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+[
+  {
+    "sources": [
+      {
+        "url": "https://cloud.google.com/vertex-ai"
+      }
+    ],
+    "id": "google/gemini-1.5-flash-002",
+    "object": "model",
+    "name": "Gemini 1.5 Flash",
+    "version": "1.5",
+    "description": "Gemini 1.5 Flash is a high-performance general-purpose model designed for fast and efficient use cases.",
+    "format": "api",
+    "settings": {
+      "vision_model": true
+    },
+    "parameters": {
+      "max_tokens": 8192,
+      "temperature": 0.7,
+      "top_p": 0.95,
+      "stream": true,
+      "stop": [],
+      "frequency_penalty": 0,
+      "presence_penalty": 0
+    },
+    "metadata": {
+      "author": "Google",
+      "tags": [
+        "General"
+      ]
+    },
+    "engine": "vertexai"
+  },
+  {
+    "sources": [
+      {
+        "url": "https://cloud.google.com/vertex-ai"
+      }
+    ],
+    "id": "google/gemini-2.0-flash-exp",
+    "object": "model",
+    "name": "Gemini 2.0 Flash",
+    "version": "2.0",
+    "description": "Gemini 2.0 Flash is an enhanced version of the Flash series, offering robust performance for general tasks",
+    "format": "api",
+    "settings": {
+      "vision_model": true
+    },
+    "parameters": {
+      "max_tokens": 8192,
+      "temperature": 0.7,
+      "top_p": 0.95,
+      "stream": true,
+      "stop": [],
+      "frequency_penalty": 0,
+      "presence_penalty": 0
+    },
+    "metadata": {
+      "author": "Google",
+      "tags": [
+        "General"
+      ]
+    },
+    "engine": "vertexai"
+  },
+  {
+    "sources": [
+      {
+        "url": "https://cloud.google.com/vertex-ai"
+      }
+    ],
+    "id": "google/gemini-1.5-pro-002",
+    "object": "model",
+    "name": "Gemini 1.5 Pro",
+    "version": "1.5",
+    "description": "Gemini 1.5 Pro is a professional-grade model optimized for versatile and high-quality applications",
+    "format": "api",
+    "settings": {
+      "vision_model": true
+    },
+    "parameters": {
+      "max_tokens": 8192,
+      "temperature": 0.7,
+      "top_p": 0.95,
+      "stream": true,
+      "stop": [],
+      "frequency_penalty": 0,
+      "presence_penalty": 0
+    },
+    "metadata": {
+      "author": "Google",
+      "tags": [
+        "General"
+      ]
+    },
+    "engine": "vertexai"
+  }
+]

extensions/inference-vertexai-extension/resources/settings.json

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+[
+  {
+    "key": "projectId",
+    "title": "Project ID",
+    "description": "The specific GCP project ID you want to use.",
+    "controllerType": "input",
+    "controllerProps": {
+      "placeholder": "Project Id",
+      "value": ""
+    }
+  },
+  {
+    "key": "location",
+    "title": "location",
+    "description": "The location of your GCP instance",
+    "controllerType": "input",
+    "controllerProps": {
+      "placeholder": "us-central1",
+      "value": "us-central1"
+    }
+  },
+  {
+    "key": "privateKey",
+    "title": "Private Key",
+    "description": "The private key of your service account Learn more: https://cloud.google.com/iam/docs/keys-create-delete",
+    "controllerType": "input",
+    "controllerProps": {
+      "placeholder": "Insert Private Key",
+      "value": ""
+    }
+  },
+  {
+    "key": "serviceEmail",
+    "title": "service Email",
+    "description": "Service Account Email",
+    "controllerType": "input",
+    "controllerProps": {
+      "placeholder": "Enter service email here",
+      "value": ""
+    }
+  },
+  {
+    "key": "vertexai-api-key",
+    "title": "Private Key ID",
+    "description": "The Private Key ID for your service account",
+    "controllerType": "input",
+    "controllerProps": {
+      "placeholder": "Enter private key id here",
+      "value": ""
+    }
+  }
+]

extensions/inference-vertexai-extension/rolldown.config.mjs

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+import { defineConfig } from 'rolldown'
+import pkgJson from './package.json' with { type: 'json' }
+import settingJson from './resources/settings.json' with { type: 'json' }
+import modelsJson from './resources/models.json' with { type: 'json' }
+
+export default defineConfig({
+  input: 'src/index.ts',
+  output: {
+    format: 'esm',
+    file: 'dist/index.js',
+  },
+  platform: 'browser',
+  define: {
+    MODELS: JSON.stringify(modelsJson),
+    SETTINGS: JSON.stringify(settingJson),
+    ENGINE: JSON.stringify(pkgJson.engine),
+  },
+})

extensions/inference-vertexai-extension/src/env.d.ts

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+declare const SETTINGS: SettingComponentProps[]
+declare const MODELS: Model[]