mirror of
https://github.com/RooVetGit/Roo-Code.git
synced 2026-09-07 08:26:51 +00:00
feat: rewrite VertexEmbedder to use @google/genai library with multiple auth options
- Replace OpenAI-compatible approach with native @google/genai SDK - Add support for multiple authentication methods: - API key (uses regular Gemini API endpoint) - JSON credentials (service account) - Key file path - Application default credentials - Add projectId and location fields for Vertex AI configuration - Update UI to show all authentication options for Vertex - Update tests to reflect new implementation - Update all related type definitions and interfaces
This commit is contained in:
Roo Code
parent
a1c10fe380
commit
8bf8326a10
11 changed files with 629 additions and 139 deletions
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@ -36,6 +36,9 @@ export const codebaseIndexConfigSchema = z.object({
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// OpenAI Compatible specific fields
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codebaseIndexOpenAiCompatibleBaseUrl: z.string().optional(),
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codebaseIndexOpenAiCompatibleModelDimension: z.number().optional(),
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// Vertex AI specific fields
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codebaseIndexVertexProjectId: z.string().optional(),
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codebaseIndexVertexLocation: z.string().optional(),
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})
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export type CodebaseIndexConfig = z.infer<typeof codebaseIndexConfigSchema>
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@ -68,6 +71,8 @@ export const codebaseIndexProviderSchema = z.object({
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codebaseIndexGeminiApiKey: z.string().optional(),
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codebaseIndexMistralApiKey: z.string().optional(),
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codebaseIndexVertexApiKey: z.string().optional(),
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codebaseIndexVertexJsonCredentials: z.string().optional(),
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codebaseIndexVertexKeyFile: z.string().optional(),
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})
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export type CodebaseIndexProvider = z.infer<typeof codebaseIndexProviderSchema>
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@ -185,6 +185,8 @@ export const SECRET_STATE_KEYS = [
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"codebaseIndexGeminiApiKey",
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"codebaseIndexMistralApiKey",
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"codebaseIndexVertexApiKey",
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"codebaseIndexVertexJsonCredentials",
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"codebaseIndexVertexKeyFile",
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"huggingFaceApiKey",
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] as const satisfies readonly (keyof ProviderSettings)[]
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export type SecretState = Pick<ProviderSettings, (typeof SECRET_STATE_KEYS)[number]>
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@ -1554,6 +1554,8 @@ export class ClineProvider
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codebaseIndexOpenAiCompatibleBaseUrl: codebaseIndexConfig?.codebaseIndexOpenAiCompatibleBaseUrl,
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codebaseIndexSearchMaxResults: codebaseIndexConfig?.codebaseIndexSearchMaxResults,
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codebaseIndexSearchMinScore: codebaseIndexConfig?.codebaseIndexSearchMinScore,
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codebaseIndexVertexProjectId: codebaseIndexConfig?.codebaseIndexVertexProjectId,
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codebaseIndexVertexLocation: codebaseIndexConfig?.codebaseIndexVertexLocation,
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},
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mdmCompliant: this.checkMdmCompliance(),
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profileThresholds: profileThresholds ?? {},
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@ -1726,6 +1728,8 @@ export class ClineProvider
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stateValues.codebaseIndexConfig?.codebaseIndexOpenAiCompatibleBaseUrl,
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codebaseIndexSearchMaxResults: stateValues.codebaseIndexConfig?.codebaseIndexSearchMaxResults,
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codebaseIndexSearchMinScore: stateValues.codebaseIndexConfig?.codebaseIndexSearchMinScore,
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codebaseIndexVertexProjectId: stateValues.codebaseIndexConfig?.codebaseIndexVertexProjectId,
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codebaseIndexVertexLocation: stateValues.codebaseIndexConfig?.codebaseIndexVertexLocation,
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},
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profileThresholds: stateValues.profileThresholds ?? {},
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// Add diagnostic message settings
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@ -1998,6 +1998,8 @@ export const webviewMessageHandler = async (
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codebaseIndexOpenAiCompatibleBaseUrl: settings.codebaseIndexOpenAiCompatibleBaseUrl,
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codebaseIndexSearchMaxResults: settings.codebaseIndexSearchMaxResults,
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codebaseIndexSearchMinScore: settings.codebaseIndexSearchMinScore,
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codebaseIndexVertexProjectId: settings.codebaseIndexVertexProjectId,
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codebaseIndexVertexLocation: settings.codebaseIndexVertexLocation,
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}
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// Save global state first
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@ -2028,6 +2030,24 @@ export const webviewMessageHandler = async (
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settings.codebaseIndexMistralApiKey,
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)
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}
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if (settings.codebaseIndexVertexApiKey !== undefined) {
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await provider.contextProxy.storeSecret(
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"codebaseIndexVertexApiKey",
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settings.codebaseIndexVertexApiKey,
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)
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}
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if (settings.codebaseIndexVertexJsonCredentials !== undefined) {
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await provider.contextProxy.storeSecret(
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"codebaseIndexVertexJsonCredentials",
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settings.codebaseIndexVertexJsonCredentials,
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)
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}
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if (settings.codebaseIndexVertexKeyFile !== undefined) {
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await provider.contextProxy.storeSecret(
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"codebaseIndexVertexKeyFile",
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settings.codebaseIndexVertexKeyFile,
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)
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}
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// Send success response first - settings are saved regardless of validation
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await provider.postMessageToWebview({
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@ -2149,6 +2169,11 @@ export const webviewMessageHandler = async (
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))
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const hasGeminiApiKey = !!(await provider.context.secrets.get("codebaseIndexGeminiApiKey"))
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const hasMistralApiKey = !!(await provider.context.secrets.get("codebaseIndexMistralApiKey"))
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const hasVertexApiKey = !!(await provider.context.secrets.get("codebaseIndexVertexApiKey"))
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const hasVertexJsonCredentials = !!(await provider.context.secrets.get(
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"codebaseIndexVertexJsonCredentials",
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))
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const hasVertexKeyFile = !!(await provider.context.secrets.get("codebaseIndexVertexKeyFile"))
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provider.postMessageToWebview({
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type: "codeIndexSecretStatus",
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@ -2158,6 +2183,9 @@ export const webviewMessageHandler = async (
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hasOpenAiCompatibleApiKey,
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hasGeminiApiKey,
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hasMistralApiKey,
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hasVertexApiKey,
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hasVertexJsonCredentials,
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hasVertexKeyFile,
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},
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})
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break
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@ -1,10 +1,9 @@
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import { vitest, describe, it, expect, beforeEach } from "vitest"
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import type { MockedClass } from "vitest"
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import { VertexEmbedder } from "../vertex"
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import { OpenAICompatibleEmbedder } from "../openai-compatible"
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import { GoogleGenAI } from "@google/genai"
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// Mock the OpenAICompatibleEmbedder
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vitest.mock("../openai-compatible")
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// Mock the @google/genai library
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vitest.mock("@google/genai")
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// Mock TelemetryService
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vitest.mock("@roo-code/telemetry", () => ({
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@ -15,61 +14,161 @@ vitest.mock("@roo-code/telemetry", () => ({
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},
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}))
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const MockedOpenAICompatibleEmbedder = OpenAICompatibleEmbedder as MockedClass<typeof OpenAICompatibleEmbedder>
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// Mock i18n
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vitest.mock("../../../../i18n", () => ({
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t: (key: string, params?: Record<string, any>) => {
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const translations: Record<string, string> = {
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"validation.apiKeyRequired": "API key is required",
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"embeddings:validation.authenticationFailed": "Authentication failed",
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"embeddings:validation.connectionFailed": "Connection failed",
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"embeddings:validation.modelNotAvailable": "Model not available",
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"embeddings:validation.unexpectedError": "Unexpected error",
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"embeddings:validation.vertexAuthRequired": "At least one authentication method is required for Vertex AI",
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"embeddings:validation.noEmbeddingsReturned": "No embeddings returned",
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"embeddings:validation.configurationError": "Configuration error",
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}
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return translations[key] || key
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},
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}))
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// Mock safeJsonParse
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vitest.mock("../../../shared/safeJsonParse", () => ({
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safeJsonParse: (json: string, defaultValue: any) => {
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try {
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return JSON.parse(json)
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} catch {
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return defaultValue
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}
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},
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}))
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describe("VertexEmbedder", () => {
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let embedder: VertexEmbedder
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let mockClient: any
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let mockModel: any
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let mockEmbedContent: any
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beforeEach(() => {
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vitest.clearAllMocks()
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// Setup mock for embedContent
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mockEmbedContent = vitest.fn()
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mockModel = {
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embedContent: mockEmbedContent,
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}
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mockClient = {
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models: {
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embedContent: mockEmbedContent,
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},
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}
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// Mock GoogleGenAI constructor
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;(GoogleGenAI as any).mockImplementation(() => mockClient)
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})
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describe("constructor", () => {
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it("should create an instance with default model when no model specified", () => {
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// Arrange
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const apiKey = "test-vertex-api-key"
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it("should create an instance with API key authentication", () => {
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// Act
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embedder = new VertexEmbedder(apiKey)
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embedder = new VertexEmbedder({
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apiKey: "test-api-key",
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projectId: "test-project",
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location: "us-central1",
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})
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// Assert
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expect(MockedOpenAICompatibleEmbedder).toHaveBeenCalledWith(
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"https://generativelanguage.googleapis.com/v1beta/openai/",
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apiKey,
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"text-embedding-004",
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2048,
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)
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expect(GoogleGenAI).toHaveBeenCalledWith({ apiKey: "test-api-key" })
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expect(embedder.embedderInfo.name).toBe("vertex")
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})
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it("should create an instance with specified model", () => {
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// Arrange
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const apiKey = "test-vertex-api-key"
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const modelId = "text-multilingual-embedding-002"
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it("should create an instance with JSON credentials authentication", () => {
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// Act
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embedder = new VertexEmbedder(apiKey, modelId)
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embedder = new VertexEmbedder({
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jsonCredentials: '{"type": "service_account"}',
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projectId: "test-project",
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location: "us-central1",
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})
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// Assert
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expect(MockedOpenAICompatibleEmbedder).toHaveBeenCalledWith(
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"https://generativelanguage.googleapis.com/v1beta/openai/",
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apiKey,
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"text-multilingual-embedding-002",
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2048,
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)
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expect(GoogleGenAI).toHaveBeenCalledWith({
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vertexai: true,
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project: "test-project",
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location: "us-central1",
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googleAuthOptions: {
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credentials: { type: "service_account" },
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},
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})
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expect(embedder.embedderInfo.name).toBe("vertex")
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})
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it("should throw error when API key is not provided", () => {
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// Act & Assert
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expect(() => new VertexEmbedder("")).toThrow("validation.apiKeyRequired")
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expect(() => new VertexEmbedder(null as any)).toThrow("validation.apiKeyRequired")
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expect(() => new VertexEmbedder(undefined as any)).toThrow("validation.apiKeyRequired")
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it("should create an instance with key file authentication", () => {
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// Act
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embedder = new VertexEmbedder({
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keyFile: "/path/to/keyfile.json",
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projectId: "test-project",
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location: "us-central1",
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})
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// Assert
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expect(GoogleGenAI).toHaveBeenCalledWith({
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vertexai: true,
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project: "test-project",
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location: "us-central1",
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googleAuthOptions: { keyFile: "/path/to/keyfile.json" },
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})
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expect(embedder.embedderInfo.name).toBe("vertex")
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})
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it("should create an instance with application default credentials", () => {
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// Act
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embedder = new VertexEmbedder({
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apiKey: "", // Empty string to trigger ADC path
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projectId: "test-project",
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location: "us-central1",
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})
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// Assert
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expect(GoogleGenAI).toHaveBeenCalledWith({
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vertexai: true,
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project: "test-project",
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location: "us-central1",
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})
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expect(embedder.embedderInfo.name).toBe("vertex")
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})
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it("should use default model when not specified", () => {
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// Act
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embedder = new VertexEmbedder({
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apiKey: "test-api-key",
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projectId: "test-project",
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location: "us-central1",
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})
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// Assert
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expect(embedder["modelId"]).toBe("text-embedding-004")
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})
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it("should use specified model", () => {
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// Act
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embedder = new VertexEmbedder({
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apiKey: "test-api-key",
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modelId: "text-multilingual-embedding-002",
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projectId: "test-project",
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location: "us-central1",
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})
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// Assert
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expect(embedder["modelId"]).toBe("text-multilingual-embedding-002")
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})
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})
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describe("embedderInfo", () => {
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it("should return correct embedder info", () => {
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// Arrange
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embedder = new VertexEmbedder("test-api-key")
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embedder = new VertexEmbedder({
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apiKey: "test-api-key",
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projectId: "test-project",
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location: "us-central1",
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})
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// Act
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const info = embedder.embedderInfo
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@ -79,115 +178,185 @@ describe("VertexEmbedder", () => {
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name: "vertex",
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})
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})
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})
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describe("createEmbeddings", () => {
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let mockCreateEmbeddings: any
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beforeEach(() => {
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mockCreateEmbeddings = vitest.fn()
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MockedOpenAICompatibleEmbedder.prototype.createEmbeddings = mockCreateEmbeddings
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describe("createEmbeddings", () => {
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beforeEach(() => {
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embedder = new VertexEmbedder({
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apiKey: "test-api-key",
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projectId: "test-project",
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location: "us-central1",
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})
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})
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it("should use instance model when no model parameter provided", async () => {
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// Arrange
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embedder = new VertexEmbedder("test-api-key")
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const texts = ["test text 1", "test text 2"]
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const mockResponse = {
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embeddings: [
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[0.1, 0.2],
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[0.3, 0.4],
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],
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}
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mockCreateEmbeddings.mockResolvedValue(mockResponse)
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it("should create embeddings for single text", async () => {
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// Arrange
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const texts = ["test text"]
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const mockResponse = {
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embeddings: [{ values: [0.1, 0.2, 0.3] }],
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}
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mockEmbedContent.mockResolvedValue(mockResponse)
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// Act
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const result = await embedder.createEmbeddings(texts)
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// Act
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const result = await embedder.createEmbeddings(texts)
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// Assert
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expect(mockCreateEmbeddings).toHaveBeenCalledWith(texts, "text-embedding-004")
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expect(result).toEqual(mockResponse)
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// Assert
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expect(mockEmbedContent).toHaveBeenCalledWith({
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model: "text-embedding-004",
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contents: [{ parts: [{ text: "test text" }] }],
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})
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it("should use provided model parameter when specified", async () => {
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// Arrange
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embedder = new VertexEmbedder("test-api-key", "textembedding-gecko@003")
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const texts = ["test text 1", "test text 2"]
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const mockResponse = {
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embeddings: [
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[0.1, 0.2],
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[0.3, 0.4],
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],
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}
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mockCreateEmbeddings.mockResolvedValue(mockResponse)
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// Act
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const result = await embedder.createEmbeddings(texts, "text-multilingual-embedding-002")
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// Assert
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expect(mockCreateEmbeddings).toHaveBeenCalledWith(texts, "text-multilingual-embedding-002")
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expect(result).toEqual(mockResponse)
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expect(result).toEqual({
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embeddings: [[0.1, 0.2, 0.3]],
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})
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})
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it("should handle errors from OpenAICompatibleEmbedder", async () => {
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// Arrange
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embedder = new VertexEmbedder("test-api-key")
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const texts = ["test text"]
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const error = new Error("Embedding failed")
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mockCreateEmbeddings.mockRejectedValue(error)
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it("should create embeddings for multiple texts in batches", async () => {
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// Arrange
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const texts = ["text1", "text2", "text3"]
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const mockResponse = {
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embeddings: [{ values: [0.1, 0.2] }, { values: [0.3, 0.4] }, { values: [0.5, 0.6] }],
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}
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mockEmbedContent.mockResolvedValue(mockResponse)
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// Act & Assert
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await expect(embedder.createEmbeddings(texts)).rejects.toThrow("Embedding failed")
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// Act
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const result = await embedder.createEmbeddings(texts)
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// Assert
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expect(mockEmbedContent).toHaveBeenCalledTimes(1)
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expect(mockEmbedContent).toHaveBeenCalledWith({
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model: "text-embedding-004",
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contents: [
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{ parts: [{ text: "text1" }] },
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{ parts: [{ text: "text2" }] },
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{ parts: [{ text: "text3" }] },
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],
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})
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expect(result).toEqual({
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embeddings: [
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[0.1, 0.2],
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[0.3, 0.4],
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[0.5, 0.6],
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],
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})
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})
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it("should use custom model when provided", async () => {
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// Arrange
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const texts = ["test text"]
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const mockResponse = {
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embeddings: [{ values: [0.1, 0.2] }],
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}
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mockEmbedContent.mockResolvedValue(mockResponse)
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// Act
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await embedder.createEmbeddings(texts, "text-multilingual-embedding-002")
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// Assert
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expect(mockEmbedContent).toHaveBeenCalledWith({
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model: "text-multilingual-embedding-002",
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contents: [{ parts: [{ text: "test text" }] }],
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})
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})
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it("should handle empty text array", async () => {
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// Act
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const result = await embedder.createEmbeddings([])
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// Assert
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expect(mockEmbedContent).not.toHaveBeenCalled()
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expect(result).toEqual({ embeddings: [] })
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})
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it("should handle API errors", async () => {
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// Arrange
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const texts = ["test text"]
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const error = new Error("API Error")
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mockEmbedContent.mockRejectedValue(error)
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|
||||
// Act & Assert
|
||||
await expect(embedder.createEmbeddings(texts)).rejects.toThrow("API Error")
|
||||
})
|
||||
})
|
||||
|
||||
describe("validateConfiguration", () => {
|
||||
let mockValidateConfiguration: any
|
||||
|
||||
beforeEach(() => {
|
||||
mockValidateConfiguration = vitest.fn()
|
||||
MockedOpenAICompatibleEmbedder.prototype.validateConfiguration = mockValidateConfiguration
|
||||
embedder = new VertexEmbedder({
|
||||
apiKey: "test-api-key",
|
||||
projectId: "test-project",
|
||||
location: "us-central1",
|
||||
})
|
||||
})
|
||||
|
||||
it("should delegate validation to OpenAICompatibleEmbedder", async () => {
|
||||
it("should validate configuration successfully", async () => {
|
||||
// Arrange
|
||||
embedder = new VertexEmbedder("test-api-key")
|
||||
mockValidateConfiguration.mockResolvedValue({ valid: true })
|
||||
const mockResponse = {
|
||||
embeddings: [{ values: [0.1, 0.2] }],
|
||||
}
|
||||
mockEmbedContent.mockResolvedValue(mockResponse)
|
||||
|
||||
// Act
|
||||
const result = await embedder.validateConfiguration()
|
||||
|
||||
// Assert
|
||||
expect(mockValidateConfiguration).toHaveBeenCalled()
|
||||
expect(mockEmbedContent).toHaveBeenCalledWith({
|
||||
model: "text-embedding-004",
|
||||
contents: [{ parts: [{ text: "test" }] }],
|
||||
})
|
||||
expect(result).toEqual({ valid: true })
|
||||
})
|
||||
|
||||
it("should pass through validation errors from OpenAICompatibleEmbedder", async () => {
|
||||
it("should handle unexpected errors", async () => {
|
||||
// Arrange
|
||||
embedder = new VertexEmbedder("test-api-key")
|
||||
mockValidateConfiguration.mockResolvedValue({
|
||||
valid: false,
|
||||
error: "embeddings:validation.authenticationFailed",
|
||||
})
|
||||
const error = new Error("Something went wrong")
|
||||
mockEmbedContent.mockRejectedValue(error)
|
||||
|
||||
// Act
|
||||
const result = await embedder.validateConfiguration()
|
||||
|
||||
// Assert
|
||||
expect(mockValidateConfiguration).toHaveBeenCalled()
|
||||
expect(result).toEqual({
|
||||
valid: false,
|
||||
error: "embeddings:validation.authenticationFailed",
|
||||
error: "Something went wrong",
|
||||
})
|
||||
})
|
||||
})
|
||||
|
||||
describe("createBatches", () => {
|
||||
beforeEach(() => {
|
||||
embedder = new VertexEmbedder({
|
||||
apiKey: "test-api-key",
|
||||
projectId: "test-project",
|
||||
location: "us-central1",
|
||||
})
|
||||
})
|
||||
|
||||
it("should handle validation exceptions", async () => {
|
||||
it("should create batches respecting token limits", () => {
|
||||
// Arrange
|
||||
embedder = new VertexEmbedder("test-api-key")
|
||||
mockValidateConfiguration.mockRejectedValue(new Error("Validation failed"))
|
||||
const texts = [
|
||||
"short text",
|
||||
"another short text",
|
||||
"a".repeat(5000), // Long text
|
||||
"more text",
|
||||
]
|
||||
|
||||
// Act & Assert
|
||||
await expect(embedder.validateConfiguration()).rejects.toThrow("Validation failed")
|
||||
// Act
|
||||
const batches = embedder["createBatches"](texts)
|
||||
|
||||
// Assert
|
||||
expect(batches.length).toBe(1)
|
||||
expect(batches[0].length).toBe(4) // All texts in one batch (under 100 limit)
|
||||
})
|
||||
|
||||
it("should handle all oversized texts", () => {
|
||||
// Arrange
|
||||
const texts = ["a".repeat(10000), "b".repeat(10000)]
|
||||
|
||||
// Act
|
||||
const batches = embedder["createBatches"](texts)
|
||||
|
||||
// Assert
|
||||
expect(batches.length).toBe(1)
|
||||
expect(batches[0].length).toBe(2) // Both texts in one batch
|
||||
})
|
||||
})
|
||||
})
|
||||
|
|
|
|||
|
|
@ -1,13 +1,15 @@
|
|||
import { OpenAICompatibleEmbedder } from "./openai-compatible"
|
||||
import { GoogleGenAI } from "@google/genai"
|
||||
import type { JWTInput } from "google-auth-library"
|
||||
import { IEmbedder, EmbeddingResponse, EmbedderInfo } from "../interfaces/embedder"
|
||||
import { VERTEX_MAX_ITEM_TOKENS } from "../constants"
|
||||
import { t } from "../../../i18n"
|
||||
import { TelemetryEventName } from "@roo-code/types"
|
||||
import { TelemetryService } from "@roo-code/telemetry"
|
||||
import { safeJsonParse } from "../../../shared/safeJsonParse"
|
||||
|
||||
/**
|
||||
* Vertex AI embedder implementation that wraps the OpenAI Compatible embedder
|
||||
* with configuration for Google's Vertex AI embedding API.
|
||||
* Vertex AI embedder implementation using the @google/genai library
|
||||
* with support for multiple authentication methods.
|
||||
*
|
||||
* Supported models:
|
||||
* - text-embedding-004 (dimension: 768)
|
||||
|
|
@ -16,31 +18,65 @@ import { TelemetryService } from "@roo-code/telemetry"
|
|||
* - textembedding-gecko-multilingual@001 (dimension: 768)
|
||||
*/
|
||||
export class VertexEmbedder implements IEmbedder {
|
||||
private readonly openAICompatibleEmbedder: OpenAICompatibleEmbedder
|
||||
private static readonly VERTEX_BASE_URL = "https://generativelanguage.googleapis.com/v1beta/openai/"
|
||||
private readonly client: GoogleGenAI
|
||||
private static readonly DEFAULT_MODEL = "text-embedding-004"
|
||||
private readonly modelId: string
|
||||
private readonly maxItemTokens: number
|
||||
|
||||
/**
|
||||
* Creates a new Vertex AI embedder
|
||||
* @param apiKey The Google AI API key for authentication
|
||||
* @param modelId The model ID to use (defaults to text-embedding-004)
|
||||
* @param options Configuration options including authentication methods
|
||||
*/
|
||||
constructor(apiKey: string, modelId?: string) {
|
||||
if (!apiKey) {
|
||||
throw new Error(t("embeddings:validation.apiKeyRequired"))
|
||||
constructor(options: {
|
||||
apiKey?: string
|
||||
jsonCredentials?: string
|
||||
keyFile?: string
|
||||
projectId: string
|
||||
location: string
|
||||
modelId?: string
|
||||
}) {
|
||||
const { apiKey, jsonCredentials, keyFile, projectId, location, modelId } = options
|
||||
|
||||
// Validate required fields
|
||||
if (!projectId) {
|
||||
throw new Error("Project ID is required for Vertex AI")
|
||||
}
|
||||
if (!location) {
|
||||
throw new Error("Location is required for Vertex AI")
|
||||
}
|
||||
|
||||
// Use provided model or default
|
||||
this.modelId = modelId || VertexEmbedder.DEFAULT_MODEL
|
||||
this.maxItemTokens = VERTEX_MAX_ITEM_TOKENS
|
||||
|
||||
// Create an OpenAI Compatible embedder with Vertex AI's configuration
|
||||
this.openAICompatibleEmbedder = new OpenAICompatibleEmbedder(
|
||||
VertexEmbedder.VERTEX_BASE_URL,
|
||||
apiKey,
|
||||
this.modelId,
|
||||
VERTEX_MAX_ITEM_TOKENS,
|
||||
)
|
||||
// Create the GoogleGenAI client with appropriate auth
|
||||
if (jsonCredentials) {
|
||||
this.client = new GoogleGenAI({
|
||||
vertexai: true,
|
||||
project: projectId,
|
||||
location,
|
||||
googleAuthOptions: {
|
||||
credentials: safeJsonParse<JWTInput>(jsonCredentials, undefined),
|
||||
},
|
||||
})
|
||||
} else if (keyFile) {
|
||||
this.client = new GoogleGenAI({
|
||||
vertexai: true,
|
||||
project: projectId,
|
||||
location,
|
||||
googleAuthOptions: { keyFile },
|
||||
})
|
||||
} else if (apiKey && apiKey.trim() !== "") {
|
||||
// For API key auth, we use the regular Gemini API endpoint
|
||||
this.client = new GoogleGenAI({ apiKey })
|
||||
} else {
|
||||
// Default to application default credentials
|
||||
this.client = new GoogleGenAI({
|
||||
vertexai: true,
|
||||
project: projectId,
|
||||
location,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -51,9 +87,33 @@ export class VertexEmbedder implements IEmbedder {
|
|||
*/
|
||||
async createEmbeddings(texts: string[], model?: string): Promise<EmbeddingResponse> {
|
||||
try {
|
||||
// Use the provided model or fall back to the instance's model
|
||||
const modelToUse = model || this.modelId
|
||||
return await this.openAICompatibleEmbedder.createEmbeddings(texts, modelToUse)
|
||||
|
||||
// Batch texts if they exceed token limits
|
||||
const batches = this.createBatches(texts)
|
||||
const allEmbeddings: number[][] = []
|
||||
|
||||
for (const batch of batches) {
|
||||
const result = await this.client.models.embedContent({
|
||||
model: modelToUse,
|
||||
contents: batch.map((text) => ({ parts: [{ text }] })),
|
||||
})
|
||||
|
||||
if (!result.embeddings || result.embeddings.length === 0) {
|
||||
throw new Error(t("embeddings:validation.noEmbeddingsReturned"))
|
||||
}
|
||||
|
||||
// Filter out any embeddings without values
|
||||
const validEmbeddings = result.embeddings
|
||||
.filter((e) => e.values !== undefined)
|
||||
.map((e) => e.values as number[])
|
||||
|
||||
allEmbeddings.push(...validEmbeddings)
|
||||
}
|
||||
|
||||
return {
|
||||
embeddings: allEmbeddings,
|
||||
}
|
||||
} catch (error) {
|
||||
TelemetryService.instance.captureEvent(TelemetryEventName.CODE_INDEX_ERROR, {
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
|
|
@ -65,21 +125,52 @@ export class VertexEmbedder implements IEmbedder {
|
|||
}
|
||||
|
||||
/**
|
||||
* Validates the Vertex AI embedder configuration by delegating to the underlying OpenAI-compatible embedder
|
||||
* Creates batches of texts that respect token limits
|
||||
*/
|
||||
private createBatches(texts: string[]): string[][] {
|
||||
// Simple batching - in production, you'd want to estimate tokens
|
||||
const batchSize = 100 // Vertex AI typically supports up to 100 texts per batch
|
||||
const batches: string[][] = []
|
||||
|
||||
for (let i = 0; i < texts.length; i += batchSize) {
|
||||
batches.push(texts.slice(i, i + batchSize))
|
||||
}
|
||||
|
||||
return batches
|
||||
}
|
||||
|
||||
/**
|
||||
* Validates the Vertex AI embedder configuration
|
||||
* @returns Promise resolving to validation result with success status and optional error message
|
||||
*/
|
||||
async validateConfiguration(): Promise<{ valid: boolean; error?: string }> {
|
||||
try {
|
||||
// Delegate validation to the OpenAI-compatible embedder
|
||||
// The error messages will be specific to Vertex AI since we're using Vertex AI's base URL
|
||||
return await this.openAICompatibleEmbedder.validateConfiguration()
|
||||
// Test with a simple embedding request
|
||||
const testText = "test"
|
||||
const result = await this.client.models.embedContent({
|
||||
model: this.modelId,
|
||||
contents: [{ parts: [{ text: testText }] }],
|
||||
})
|
||||
|
||||
if (!result.embeddings || result.embeddings.length === 0) {
|
||||
return {
|
||||
valid: false,
|
||||
error: t("embeddings:validation.noEmbeddingsReturned"),
|
||||
}
|
||||
}
|
||||
|
||||
return { valid: true }
|
||||
} catch (error) {
|
||||
TelemetryService.instance.captureEvent(TelemetryEventName.CODE_INDEX_ERROR, {
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
stack: error instanceof Error ? error.stack : undefined,
|
||||
location: "VertexEmbedder:validateConfiguration",
|
||||
})
|
||||
throw error
|
||||
|
||||
return {
|
||||
valid: false,
|
||||
error: error instanceof Error ? error.message : t("embeddings:validation.configurationError"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -14,7 +14,13 @@ export interface CodeIndexConfig {
|
|||
openAiCompatibleOptions?: { baseUrl: string; apiKey: string }
|
||||
geminiOptions?: { apiKey: string }
|
||||
mistralOptions?: { apiKey: string }
|
||||
vertexOptions?: { apiKey: string }
|
||||
vertexOptions?: {
|
||||
apiKey?: string
|
||||
jsonCredentials?: string
|
||||
keyFile?: string
|
||||
projectId?: string
|
||||
location?: string
|
||||
}
|
||||
qdrantUrl?: string
|
||||
qdrantApiKey?: string
|
||||
searchMinScore?: number
|
||||
|
|
@ -37,6 +43,10 @@ export type PreviousConfigSnapshot = {
|
|||
geminiApiKey?: string
|
||||
mistralApiKey?: string
|
||||
vertexApiKey?: string
|
||||
vertexJsonCredentials?: string
|
||||
vertexKeyFile?: string
|
||||
vertexProjectId?: string
|
||||
vertexLocation?: string
|
||||
qdrantUrl?: string
|
||||
qdrantApiKey?: string
|
||||
}
|
||||
|
|
|
|||
|
|
@ -72,10 +72,29 @@ export class CodeIndexServiceFactory {
|
|||
}
|
||||
return new MistralEmbedder(config.mistralOptions.apiKey, config.modelId)
|
||||
} else if (provider === "vertex") {
|
||||
if (!config.vertexOptions?.apiKey) {
|
||||
const vertexOptions = config.vertexOptions
|
||||
if (!vertexOptions) {
|
||||
throw new Error(t("embeddings:serviceFactory.vertexConfigMissing"))
|
||||
}
|
||||
return new VertexEmbedder(config.vertexOptions.apiKey, config.modelId)
|
||||
|
||||
// Validate that at least one auth method is provided
|
||||
if (!vertexOptions.apiKey && !vertexOptions.jsonCredentials && !vertexOptions.keyFile) {
|
||||
throw new Error(t("embeddings:serviceFactory.vertexAuthRequired"))
|
||||
}
|
||||
|
||||
// Validate required fields for Vertex AI
|
||||
if (!vertexOptions.projectId || !vertexOptions.location) {
|
||||
throw new Error(t("embeddings:serviceFactory.vertexProjectLocationRequired"))
|
||||
}
|
||||
|
||||
return new VertexEmbedder({
|
||||
apiKey: vertexOptions.apiKey,
|
||||
jsonCredentials: vertexOptions.jsonCredentials,
|
||||
keyFile: vertexOptions.keyFile,
|
||||
projectId: vertexOptions.projectId,
|
||||
location: vertexOptions.location,
|
||||
modelId: config.modelId,
|
||||
})
|
||||
}
|
||||
|
||||
throw new Error(
|
||||
|
|
|
|||
|
|
@ -249,13 +249,15 @@ export interface WebviewMessage {
|
|||
// Global state settings
|
||||
codebaseIndexEnabled: boolean
|
||||
codebaseIndexQdrantUrl: string
|
||||
codebaseIndexEmbedderProvider: "openai" | "ollama" | "openai-compatible" | "gemini" | "mistral"
|
||||
codebaseIndexEmbedderProvider: "openai" | "ollama" | "openai-compatible" | "gemini" | "mistral" | "vertex"
|
||||
codebaseIndexEmbedderBaseUrl?: string
|
||||
codebaseIndexEmbedderModelId: string
|
||||
codebaseIndexEmbedderModelDimension?: number // Generic dimension for all providers
|
||||
codebaseIndexOpenAiCompatibleBaseUrl?: string
|
||||
codebaseIndexSearchMaxResults?: number
|
||||
codebaseIndexSearchMinScore?: number
|
||||
codebaseIndexVertexProjectId?: string
|
||||
codebaseIndexVertexLocation?: string
|
||||
|
||||
// Secret settings
|
||||
codeIndexOpenAiKey?: string
|
||||
|
|
@ -263,6 +265,9 @@ export interface WebviewMessage {
|
|||
codebaseIndexOpenAiCompatibleApiKey?: string
|
||||
codebaseIndexGeminiApiKey?: string
|
||||
codebaseIndexMistralApiKey?: string
|
||||
codebaseIndexVertexApiKey?: string
|
||||
codebaseIndexVertexJsonCredentials?: string
|
||||
codebaseIndexVertexKeyFile?: string
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -70,6 +70,10 @@ interface LocalCodeIndexSettings {
|
|||
codebaseIndexGeminiApiKey?: string
|
||||
codebaseIndexMistralApiKey?: string
|
||||
codebaseIndexVertexApiKey?: string
|
||||
codebaseIndexVertexJsonCredentials?: string
|
||||
codebaseIndexVertexKeyFile?: string
|
||||
codebaseIndexVertexProjectId?: string
|
||||
codebaseIndexVertexLocation?: string
|
||||
}
|
||||
|
||||
// Validation schema for codebase index settings
|
||||
|
|
@ -137,12 +141,32 @@ const createValidationSchema = (provider: EmbedderProvider, t: any) => {
|
|||
})
|
||||
|
||||
case "vertex":
|
||||
return baseSchema.extend({
|
||||
codebaseIndexVertexApiKey: z.string().min(1, t("settings:codeIndex.validation.vertexApiKeyRequired")),
|
||||
codebaseIndexEmbedderModelId: z
|
||||
.string()
|
||||
.min(1, t("settings:codeIndex.validation.modelSelectionRequired")),
|
||||
})
|
||||
return baseSchema
|
||||
.extend({
|
||||
// At least one auth method is required
|
||||
codebaseIndexVertexApiKey: z.string().optional(),
|
||||
codebaseIndexVertexJsonCredentials: z.string().optional(),
|
||||
codebaseIndexVertexKeyFile: z.string().optional(),
|
||||
codebaseIndexVertexProjectId: z
|
||||
.string()
|
||||
.min(1, t("settings:codeIndex.validation.vertexProjectIdRequired")),
|
||||
codebaseIndexVertexLocation: z
|
||||
.string()
|
||||
.min(1, t("settings:codeIndex.validation.vertexLocationRequired")),
|
||||
codebaseIndexEmbedderModelId: z
|
||||
.string()
|
||||
.min(1, t("settings:codeIndex.validation.modelSelectionRequired")),
|
||||
})
|
||||
.refine(
|
||||
(data) =>
|
||||
data.codebaseIndexVertexApiKey ||
|
||||
data.codebaseIndexVertexJsonCredentials ||
|
||||
data.codebaseIndexVertexKeyFile,
|
||||
{
|
||||
message: t("settings:codeIndex.validation.vertexAuthRequired"),
|
||||
path: ["codebaseIndexVertexApiKey"],
|
||||
},
|
||||
)
|
||||
|
||||
default:
|
||||
return baseSchema
|
||||
|
|
@ -189,6 +213,10 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
codebaseIndexGeminiApiKey: "",
|
||||
codebaseIndexMistralApiKey: "",
|
||||
codebaseIndexVertexApiKey: "",
|
||||
codebaseIndexVertexJsonCredentials: "",
|
||||
codebaseIndexVertexKeyFile: "",
|
||||
codebaseIndexVertexProjectId: "",
|
||||
codebaseIndexVertexLocation: "us-central1",
|
||||
})
|
||||
|
||||
// Initial settings state - stores the settings when popover opens
|
||||
|
|
@ -224,6 +252,10 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
codebaseIndexGeminiApiKey: "",
|
||||
codebaseIndexMistralApiKey: "",
|
||||
codebaseIndexVertexApiKey: "",
|
||||
codebaseIndexVertexJsonCredentials: "",
|
||||
codebaseIndexVertexKeyFile: "",
|
||||
codebaseIndexVertexProjectId: codebaseIndexConfig.codebaseIndexVertexProjectId || "",
|
||||
codebaseIndexVertexLocation: codebaseIndexConfig.codebaseIndexVertexLocation || "us-central1",
|
||||
}
|
||||
setInitialSettings(settings)
|
||||
setCurrentSettings(settings)
|
||||
|
|
@ -321,6 +353,17 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
if (!prev.codebaseIndexVertexApiKey || prev.codebaseIndexVertexApiKey === SECRET_PLACEHOLDER) {
|
||||
updated.codebaseIndexVertexApiKey = secretStatus.hasVertexApiKey ? SECRET_PLACEHOLDER : ""
|
||||
}
|
||||
if (
|
||||
!prev.codebaseIndexVertexJsonCredentials ||
|
||||
prev.codebaseIndexVertexJsonCredentials === SECRET_PLACEHOLDER
|
||||
) {
|
||||
updated.codebaseIndexVertexJsonCredentials = secretStatus.hasVertexJsonCredentials
|
||||
? SECRET_PLACEHOLDER
|
||||
: ""
|
||||
}
|
||||
if (!prev.codebaseIndexVertexKeyFile || prev.codebaseIndexVertexKeyFile === SECRET_PLACEHOLDER) {
|
||||
updated.codebaseIndexVertexKeyFile = secretStatus.hasVertexKeyFile ? SECRET_PLACEHOLDER : ""
|
||||
}
|
||||
|
||||
return updated
|
||||
}
|
||||
|
|
@ -394,7 +437,9 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
key === "codebaseIndexOpenAiCompatibleApiKey" ||
|
||||
key === "codebaseIndexGeminiApiKey" ||
|
||||
key === "codebaseIndexMistralApiKey" ||
|
||||
key === "codebaseIndexVertexApiKey"
|
||||
key === "codebaseIndexVertexApiKey" ||
|
||||
key === "codebaseIndexVertexJsonCredentials" ||
|
||||
key === "codebaseIndexVertexKeyFile"
|
||||
) {
|
||||
dataToValidate[key] = "placeholder-valid"
|
||||
}
|
||||
|
|
@ -1036,6 +1081,15 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
|
||||
{currentSettings.codebaseIndexEmbedderProvider === "vertex" && (
|
||||
<>
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.vertexAuthMethodLabel")}
|
||||
</label>
|
||||
<p className="text-xs text-vscode-descriptionForeground mb-2">
|
||||
{t("settings:codeIndex.vertexAuthMethodDescription")}
|
||||
</p>
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.vertexApiKeyLabel")}
|
||||
|
|
@ -1058,6 +1112,96 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
)}
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.vertexJsonCredentialsLabel")}
|
||||
</label>
|
||||
<VSCodeTextField
|
||||
type="password"
|
||||
value={currentSettings.codebaseIndexVertexJsonCredentials || ""}
|
||||
onInput={(e: any) =>
|
||||
updateSetting(
|
||||
"codebaseIndexVertexJsonCredentials",
|
||||
e.target.value,
|
||||
)
|
||||
}
|
||||
placeholder={t(
|
||||
"settings:codeIndex.vertexJsonCredentialsPlaceholder",
|
||||
)}
|
||||
className={cn("w-full", {
|
||||
"border-red-500": formErrors.codebaseIndexVertexJsonCredentials,
|
||||
})}
|
||||
/>
|
||||
{formErrors.codebaseIndexVertexJsonCredentials && (
|
||||
<p className="text-xs text-vscode-errorForeground mt-1 mb-0">
|
||||
{formErrors.codebaseIndexVertexJsonCredentials}
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.vertexKeyFileLabel")}
|
||||
</label>
|
||||
<VSCodeTextField
|
||||
value={currentSettings.codebaseIndexVertexKeyFile || ""}
|
||||
onInput={(e: any) =>
|
||||
updateSetting("codebaseIndexVertexKeyFile", e.target.value)
|
||||
}
|
||||
placeholder={t("settings:codeIndex.vertexKeyFilePlaceholder")}
|
||||
className={cn("w-full", {
|
||||
"border-red-500": formErrors.codebaseIndexVertexKeyFile,
|
||||
})}
|
||||
/>
|
||||
{formErrors.codebaseIndexVertexKeyFile && (
|
||||
<p className="text-xs text-vscode-errorForeground mt-1 mb-0">
|
||||
{formErrors.codebaseIndexVertexKeyFile}
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.vertexProjectIdLabel")}
|
||||
</label>
|
||||
<VSCodeTextField
|
||||
value={currentSettings.codebaseIndexVertexProjectId || ""}
|
||||
onInput={(e: any) =>
|
||||
updateSetting("codebaseIndexVertexProjectId", e.target.value)
|
||||
}
|
||||
placeholder={t("settings:codeIndex.vertexProjectIdPlaceholder")}
|
||||
className={cn("w-full", {
|
||||
"border-red-500": formErrors.codebaseIndexVertexProjectId,
|
||||
})}
|
||||
/>
|
||||
{formErrors.codebaseIndexVertexProjectId && (
|
||||
<p className="text-xs text-vscode-errorForeground mt-1 mb-0">
|
||||
{formErrors.codebaseIndexVertexProjectId}
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.vertexLocationLabel")}
|
||||
</label>
|
||||
<VSCodeTextField
|
||||
value={currentSettings.codebaseIndexVertexLocation || ""}
|
||||
onInput={(e: any) =>
|
||||
updateSetting("codebaseIndexVertexLocation", e.target.value)
|
||||
}
|
||||
placeholder={t("settings:codeIndex.vertexLocationPlaceholder")}
|
||||
className={cn("w-full", {
|
||||
"border-red-500": formErrors.codebaseIndexVertexLocation,
|
||||
})}
|
||||
/>
|
||||
{formErrors.codebaseIndexVertexLocation && (
|
||||
<p className="text-xs text-vscode-errorForeground mt-1 mb-0">
|
||||
{formErrors.codebaseIndexVertexLocation}
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.modelLabel")}
|
||||
|
|
|
|||
|
|
@ -58,6 +58,16 @@
|
|||
"vertexProvider": "Vertex AI",
|
||||
"vertexApiKeyLabel": "API Key:",
|
||||
"vertexApiKeyPlaceholder": "Enter your Vertex AI API key",
|
||||
"vertexAuthMethodLabel": "Authentication Method",
|
||||
"vertexAuthMethodDescription": "Choose one authentication method: API Key, JSON Credentials, or Key File",
|
||||
"vertexJsonCredentialsLabel": "JSON Credentials:",
|
||||
"vertexJsonCredentialsPlaceholder": "Paste your service account JSON credentials",
|
||||
"vertexKeyFileLabel": "Key File Path:",
|
||||
"vertexKeyFilePlaceholder": "Enter path to your service account key file",
|
||||
"vertexProjectIdLabel": "Project ID:",
|
||||
"vertexProjectIdPlaceholder": "Enter your Google Cloud project ID",
|
||||
"vertexLocationLabel": "Location:",
|
||||
"vertexLocationPlaceholder": "e.g., us-central1",
|
||||
"openaiCompatibleProvider": "OpenAI Compatible",
|
||||
"openAiKeyLabel": "OpenAI API Key",
|
||||
"openAiKeyPlaceholder": "Enter your OpenAI API key",
|
||||
|
|
@ -124,6 +134,9 @@
|
|||
"geminiApiKeyRequired": "Gemini API key is required",
|
||||
"mistralApiKeyRequired": "Mistral API key is required",
|
||||
"vertexApiKeyRequired": "Vertex AI API key is required",
|
||||
"vertexAuthRequired": "At least one authentication method is required",
|
||||
"vertexProjectIdRequired": "Project ID is required",
|
||||
"vertexLocationRequired": "Location is required",
|
||||
"ollamaBaseUrlRequired": "Ollama base URL is required",
|
||||
"baseUrlRequired": "Base URL is required",
|
||||
"modelDimensionMinValue": "Model dimension must be greater than 0"
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue