@ai-sdk/google-vertex/dist/maas/index.js

import { fetchWithValidatedEndpoint, isBrowserRuntime, isSameOrigin, isValidHostnamePart, loadOptionalSetting, loadSetting, resolve, withoutTrailingSlash } from "@ai-sdk/provider-utils";
import { GoogleAuth } from "google-auth-library";
import { InvalidArgumentError } from "@ai-sdk/provider";
import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
//#region src/google-vertex-auth-google-auth-library.ts
function createAuthTokenGenerator(options) {
	const auth = new GoogleAuth({
		scopes: ["https://www.googleapis.com/auth/cloud-platform"],
		...options
	});
	return async function generateAuthToken() {
		return (await (await auth.getClient()).getAccessToken())?.token ?? null;
	};
}
//#endregion
//#region src/google-vertex-model-catalog-config.ts
function requestConfig(modelId) {
	const embedContent = modelId === "gemini-embedding-2" || modelId === "gemini-embedding-2-preview";
	return {
		language: {
			endpoint: modelId.startsWith("endpoints/"),
			maxOutputTokens: modelId === "meta/llama-4-maverick-17b-128e-instruct-maas" || modelId === "meta/llama-4-scout-17b-16e-instruct-maas" ? 8192 : void 0
		},
		image: { gemini: modelId.startsWith("gemini-") },
		embedding: {
			endpoint: embedContent ? "embedContent" : "predict",
			maxEmbeddingsPerCall: embedContent ? 1 : 250
		},
		speech: { api: modelId.startsWith("chirp") ? "cloud-tts" : "gemini" },
		transcription: {
			api: modelId.startsWith("gemini") ? "gemini" : "cloud-speech",
			live: modelId.includes("-live")
		}
	};
}
function getGoogleVertexRequestConfig(modelId) {
	return requestConfig(modelId);
}
//#endregion
//#region src/maas/google-vertex-maas-provider.ts
function transformGoogleVertexMaasRequestBody(args) {
	const maxOutputTokens = getGoogleVertexRequestConfig(args.model).language?.maxOutputTokens;
	return maxOutputTokens != null && args.max_tokens === void 0 ? {
		...args,
		max_tokens: maxOutputTokens
	} : args;
}
/**
* Loads the base URL of the MaaS API from the settings or from the project and
* location. Settings are loaded on each call so environment variables are read
* at runtime.
*/
function loadGoogleVertexMaasBaseURL(options) {
	const loadLocation = () => {
		const location = loadOptionalSetting({
			settingValue: options.location,
			environmentVariableName: "GOOGLE_VERTEX_LOCATION"
		}) ?? "global";
		if (!isValidHostnamePart(location)) throw new InvalidArgumentError({
			argument: "location",
			message: "Invalid Google Vertex location. Expected a single DNS label (letters, digits, and hyphens). Use `baseURL` for custom endpoints."
		});
		return location;
	};
	const loadProject = () => loadSetting({
		settingValue: options.project,
		settingName: "project",
		environmentVariableName: "GOOGLE_VERTEX_PROJECT",
		description: "Google Vertex project"
	});
	const getHost = (location) => {
		if (location === "global") return "aiplatform.googleapis.com";
		else if (location === "eu" || location === "us") return `aiplatform.${location}.rep.googleapis.com`;
		else return `${location}-aiplatform.googleapis.com`;
	};
	const constructBaseURL = () => {
		const projectId = loadProject();
		const location = loadLocation();
		return `https://${getHost(location)}/v1/projects/${projectId}/locations/${location}/endpoints/openapi`;
	};
	return withoutTrailingSlash(options.baseURL ?? "") || constructBaseURL();
}
/**
* Create a Google Vertex AI MaaS (Model as a Service) provider instance.
* Uses the OpenAI-compatible Chat Completions API for partner and open models.
*
* @see https://cloud.google.com/vertex-ai/generative-ai/docs/maas/use-open-models
*/
function createGoogleVertexMaas$1(options = {}) {
	let cachedProvider;
	const getProvider = () => cachedProvider ??= createOpenAICompatible({
		name: "vertex.maas",
		baseURL: loadGoogleVertexMaasBaseURL(options),
		fetch: options.fetch,
		transformRequestBody: transformGoogleVertexMaasRequestBody
	});
	const provider = (modelId) => getProvider()(modelId);
	provider.specificationVersion = "v4";
	provider.languageModel = (modelId) => getProvider().languageModel(modelId);
	provider.chatModel = (modelId) => getProvider().chatModel(modelId);
	provider.completionModel = (modelId) => getProvider().completionModel(modelId);
	provider.embeddingModel = (modelId) => getProvider().embeddingModel(modelId);
	provider.textEmbeddingModel = (modelId) => getProvider().textEmbeddingModel(modelId);
	provider.imageModel = (modelId) => getProvider().imageModel(modelId);
	return provider;
}
//#endregion
//#region src/maas/google-vertex-maas-provider-node.ts
/**
* Create a Google Vertex AI MaaS (Model as a Service) provider instance for Node.js.
* Uses the OpenAI-compatible Chat Completions API for partner and open models.
* Automatically handles Google Cloud authentication.
*
* @see https://cloud.google.com/vertex-ai/generative-ai/docs/maas/use-open-models
*/
function createGoogleVertexMaas(options = {}) {
	const generateAuthToken = createAuthTokenGenerator(options.googleAuthOptions);
	const customFetch = async (url, init) => {
		const href = typeof url === "string" ? url : url instanceof URL ? url.href : url.url;
		if (!isSameOrigin(href, loadGoogleVertexMaasBaseURL(options))) {
			if (isBrowserRuntime() && init?.redirect === "follow") return (options.fetch ?? fetch)(url, init);
			return fetchWithValidatedEndpoint({
				url: href,
				init,
				fetch: options.fetch,
				redirect: "manual"
			});
		}
		const token = await generateAuthToken();
		const authHeaders = {
			...await resolve(options.headers),
			Authorization: `Bearer ${token}`
		};
		const fetchInit = {
			...init,
			headers: {
				...init?.headers,
				...authHeaders
			}
		};
		return (options.fetch ?? fetch)(url, fetchInit);
	};
	return createGoogleVertexMaas$1({
		...options,
		fetch: customFetch,
		headers: void 0
	});
}
/**
* Default Google Vertex AI MaaS provider instance for Node.js.
*/
const googleVertexMaas = createGoogleVertexMaas();
//#endregion
export { createGoogleVertexMaas, createGoogleVertexMaas as createVertexMaas, googleVertexMaas, googleVertexMaas as vertexMaas };

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