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Genkit MCP

Official
by firebase
index.ts5.74 kB
/** * @license * * Copyright 2025 Google LLC * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ /** * @module / */ import { EmbedderReference, ModelReference, z } from 'genkit'; import { GenkitPluginV2, ResolvableAction, genkitPluginV2, } from 'genkit/plugin'; import { ActionType } from 'genkit/registry'; import { listModels } from './client.js'; import * as embedder from './embedder.js'; import * as gemini from './gemini.js'; import * as imagen from './imagen.js'; import * as lyria from './lyria.js'; import * as veo from './veo.js'; import { VertexPluginOptions } from './types.js'; import { getDerivedOptions } from './utils.js'; export { type EmbeddingConfig } from './embedder.js'; export { type GeminiConfig } from './gemini.js'; export { type ImagenConfig } from './imagen.js'; export { type LyriaConfig } from './lyria.js'; export { type VertexPluginOptions } from './types.js'; export { type VeoConfig } from './veo.js'; async function initializer(pluginOptions?: VertexPluginOptions) { const clientOptions = await getDerivedOptions(pluginOptions); return [ ...veo.listKnownModels(clientOptions, pluginOptions), ...imagen.listKnownModels(clientOptions, pluginOptions), ...lyria.listKnownModels(clientOptions, pluginOptions), ...gemini.listKnownModels(clientOptions, pluginOptions), ...embedder.listKnownModels(clientOptions, pluginOptions), ]; } async function resolver( actionType: ActionType, actionName: string, pluginOptions?: VertexPluginOptions ): Promise<ResolvableAction | undefined> { const clientOptions = await getDerivedOptions(pluginOptions); switch (actionType) { case 'model': if (lyria.isLyriaModelName(actionName)) { return lyria.defineModel(actionName, clientOptions, pluginOptions); } else if (imagen.isImagenModelName(actionName)) { return imagen.defineModel(actionName, clientOptions, pluginOptions); } else if (veo.isVeoModelName(actionName)) { return undefined; } else { return gemini.defineModel(actionName, clientOptions, pluginOptions); } break; case 'background-model': if (veo.isVeoModelName(actionName)) { return veo.defineModel(actionName, clientOptions, pluginOptions); } break; case 'embedder': return embedder.defineEmbedder(actionName, clientOptions, pluginOptions); break; } return undefined; } async function listActions(options?: VertexPluginOptions) { try { const clientOptions = await getDerivedOptions(options); const models = await listModels(clientOptions); return [ ...gemini.listActions(models), ...imagen.listActions(models), ...lyria.listActions(models), ...veo.listActions(models), // We don't list embedders here ]; } catch (e: unknown) { // Errors are already logged in the client code. return []; } } /** * Add Google Cloud Vertex AI to Genkit. Includes Gemini and Imagen models and text embedder. */ function vertexAIPlugin(options?: VertexPluginOptions): GenkitPluginV2 { let listActionsCache; return genkitPluginV2({ name: 'vertexai', init: async () => await initializer(options), resolve: async (actionType: ActionType, actionName: string) => await resolver(actionType, actionName, options), list: async () => { if (listActionsCache) return listActionsCache; listActionsCache = await listActions(options); return listActionsCache; }, }); } export type VertexAIPlugin = { (pluginOptions?: VertexPluginOptions): GenkitPluginV2; model( name: gemini.KnownModels | (gemini.GeminiModelName & {}), config?: gemini.GeminiConfig ): ModelReference<gemini.GeminiConfigSchemaType>; model( name: imagen.KnownModels | (imagen.ImagenModelName & {}), config?: imagen.ImagenConfig ): ModelReference<imagen.ImagenConfigSchemaType>; model( name: lyria.KnownModels | (lyria.LyriaModelName & {}), config: lyria.LyriaConfig ): ModelReference<lyria.LyriaConfigSchemaType>; model( name: veo.KnownModels | (veo.VeoModelName & {}), config: veo.VeoConfig ): ModelReference<veo.VeoConfigSchemaType>; model(name: string, config?: any): ModelReference<z.ZodTypeAny>; embedder( name: string, config?: embedder.EmbeddingConfig ): EmbedderReference<embedder.EmbeddingConfigSchemaType>; }; /** * Google Cloud Vertex AI plugin for Genkit. * Includes Gemini and Imagen models and text embedder. */ export const vertexAI = vertexAIPlugin as VertexAIPlugin; // provide generic implementation for the model function overloads. (vertexAI as any).model = ( name: string, config?: any ): ModelReference<z.ZodTypeAny> => { if (imagen.isImagenModelName(name)) { return imagen.model(name, config); } if (lyria.isLyriaModelName(name)) { return lyria.model(name, config); } if (veo.isVeoModelName(name)) { return veo.model(name, config); } // gemini and unknown model families return gemini.model(name, config); }; vertexAI.embedder = ( name: string, config?: embedder.EmbeddingConfig ): EmbedderReference<embedder.EmbeddingConfigSchemaType> => { return embedder.model(name, config); }; export default vertexAI;

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