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@ai-sdk/google-vertex

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The **[Google Vertex provider](https://ai-sdk.dev/providers/ai-sdk-providers/google-vertex)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the [Google Vertex AI](https://cloud.google.com/vertex-ai) APIs.

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// src/anthropic/edge/google-vertex-anthropic-provider-edge.ts import { resolve } from "@ai-sdk/provider-utils"; // src/edge/google-vertex-auth-edge.ts import { loadOptionalSetting, loadSetting } from "@ai-sdk/provider-utils"; var loadCredentials = async () => { try { return { clientEmail: loadSetting({ settingValue: void 0, settingName: "clientEmail", environmentVariableName: "GOOGLE_CLIENT_EMAIL", description: "Google client email" }), privateKey: loadSetting({ settingValue: void 0, settingName: "privateKey", environmentVariableName: "GOOGLE_PRIVATE_KEY", description: "Google private key" }), privateKeyId: loadOptionalSetting({ settingValue: void 0, environmentVariableName: "GOOGLE_PRIVATE_KEY_ID" }) }; } catch (error) { throw new Error(`Failed to load Google credentials: ${error.message}`); } }; var base64url = (str) => { return btoa(str).replace(/\+/g, "-").replace(/\//g, "_").replace(/=/g, ""); }; var importPrivateKey = async (pemKey) => { const pemHeader = "-----BEGIN PRIVATE KEY-----"; const pemFooter = "-----END PRIVATE KEY-----"; const pemContents = pemKey.replace(pemHeader, "").replace(pemFooter, "").replace(/\s/g, ""); const binaryString = atob(pemContents); const binaryData = new Uint8Array(binaryString.length); for (let i = 0; i < binaryString.length; i++) { binaryData[i] = binaryString.charCodeAt(i); } return await crypto.subtle.importKey( "pkcs8", binaryData, { name: "RSASSA-PKCS1-v1_5", hash: "SHA-256" }, true, ["sign"] ); }; var buildJwt = async (credentials) => { const now = Math.floor(Date.now() / 1e3); const header = { alg: "RS256", typ: "JWT" }; if (credentials.privateKeyId) { header.kid = credentials.privateKeyId; } const payload = { iss: credentials.clientEmail, scope: "https://www.googleapis.com/auth/cloud-platform", aud: "https://oauth2.googleapis.com/token", exp: now + 3600, iat: now }; const privateKey = await importPrivateKey(credentials.privateKey); const signingInput = `${base64url(JSON.stringify(header))}.${base64url( JSON.stringify(payload) )}`; const encoder = new TextEncoder(); const data = encoder.encode(signingInput); const signature = await crypto.subtle.sign( "RSASSA-PKCS1-v1_5", privateKey, data ); const signatureBase64 = base64url( String.fromCharCode(...new Uint8Array(signature)) ); return `${base64url(JSON.stringify(header))}.${base64url( JSON.stringify(payload) )}.${signatureBase64}`; }; async function generateAuthToken(credentials) { try { const creds = credentials || await loadCredentials(); const jwt = await buildJwt(creds); const response = await fetch("https://oauth2.googleapis.com/token", { method: "POST", headers: { "Content-Type": "application/x-www-form-urlencoded" }, body: new URLSearchParams({ grant_type: "urn:ietf:params:oauth:grant-type:jwt-bearer", assertion: jwt }) }); if (!response.ok) { throw new Error(`Token request failed: ${response.statusText}`); } const data = await response.json(); return data.access_token; } catch (error) { throw error; } } // src/anthropic/google-vertex-anthropic-provider.ts import { NoSuchModelError } from "@ai-sdk/provider"; import { loadOptionalSetting as loadOptionalSetting2, withoutTrailingSlash } from "@ai-sdk/provider-utils"; import { anthropicTools, AnthropicMessagesLanguageModel } from "@ai-sdk/anthropic/internal"; function createVertexAnthropic(options = {}) { var _a; const location = loadOptionalSetting2({ settingValue: options.location, environmentVariableName: "GOOGLE_VERTEX_LOCATION" }); const project = loadOptionalSetting2({ settingValue: options.project, environmentVariableName: "GOOGLE_VERTEX_PROJECT" }); const baseURL = (_a = withoutTrailingSlash(options.baseURL)) != null ? _a : `https://${location}-aiplatform.googleapis.com/v1/projects/${project}/locations/${location}/publishers/anthropic/models`; const createChatModel = (modelId, settings = {}) => { var _a2; return new AnthropicMessagesLanguageModel( modelId, settings, { provider: "vertex.anthropic.messages", baseURL, headers: (_a2 = options.headers) != null ? _a2 : {}, fetch: options.fetch, supportsImageUrls: false, buildRequestUrl: (baseURL2, isStreaming) => `${baseURL2}/${modelId}:${isStreaming ? "streamRawPredict" : "rawPredict"}`, transformRequestBody: (args) => { const { model, ...rest } = args; return { ...rest, anthropic_version: "vertex-2023-10-16" }; } } ); }; const provider = function(modelId, settings) { if (new.target) { throw new Error( "The Anthropic model function cannot be called with the new keyword." ); } return createChatModel(modelId, settings); }; provider.languageModel = createChatModel; provider.chat = createChatModel; provider.messages = createChatModel; provider.textEmbeddingModel = (modelId) => { throw new NoSuchModelError({ modelId, modelType: "textEmbeddingModel" }); }; provider.tools = anthropicTools; return provider; } // src/anthropic/edge/google-vertex-anthropic-provider-edge.ts function createVertexAnthropic2(options = {}) { return createVertexAnthropic({ ...options, headers: async () => ({ Authorization: `Bearer ${await generateAuthToken( options.googleCredentials )}`, ...await resolve(options.headers) }) }); } var vertexAnthropic = createVertexAnthropic2(); export { createVertexAnthropic2 as createVertexAnthropic, vertexAnthropic }; //# sourceMappingURL=index.mjs.map