@genkit-ai/ai/lib/genkit-ai.mjs.map

Genkit AI framework generative AI APIs.

{"version":3,"sources":["../src/genkit-ai.ts"],"sourcesContent":["/**\n * Copyright 2026 Google LLC\n *\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n *     http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n */\n\nimport {\n  getContext,\n  run,\n  z,\n  type ActionContext,\n  type Operation,\n} from '@genkit-ai/core';\nimport { type Registry } from '@genkit-ai/core/registry';\nimport { cancelOperation } from './cancel-operation.js';\nimport { checkOperation } from './check-operation.js';\nimport { type DocumentData } from './document.js';\nimport {\n  embed,\n  embedMany,\n  type EmbedderArgument,\n  type EmbedderParams,\n  type Embedding,\n  type EmbeddingBatch,\n} from './embedder.js';\nimport {\n  generate,\n  generateStream,\n  type GenerateOptions,\n  type GenerateResponse,\n  type GenerateStreamOptions,\n  type GenerateStreamResponse,\n} from './generate.js';\nimport { GenerationCommonConfigSchema, type Part } from './model-types.js';\n\n/**\n * `GenkitAI` encapsulates Genkit's AI APIs.\n */\nexport class GenkitAI {\n  readonly registry: Registry;\n\n  constructor(registry: Registry) {\n    this.registry = registry;\n  }\n\n  /**\n   * Embeds the given `content` using the specified `embedder`.\n   */\n  embed<CustomOptions extends z.ZodTypeAny>(\n    params: EmbedderParams<CustomOptions>\n  ): Promise<Embedding[]> {\n    return embed(this.registry, params);\n  }\n\n  /**\n   * A veneer for interacting with embedder models in bulk.\n   */\n  embedMany<ConfigSchema extends z.ZodTypeAny = z.ZodTypeAny>(params: {\n    embedder: EmbedderArgument<ConfigSchema>;\n    content: string[] | DocumentData[];\n    metadata?: Record<string, unknown>;\n    options?: z.infer<ConfigSchema>;\n  }): Promise<EmbeddingBatch> {\n    return embedMany(this.registry, params);\n  }\n\n  /**\n   * Make a generate call to the default model with a simple text prompt.\n   *\n   * ```ts\n   * const ai = genkit({\n   *   plugins: [googleAI()],\n   *   model: googleAI.model('gemini-flash-latest'), // default model\n   * })\n   *\n   * const { text } = await ai.generate('hi');\n   * ```\n   */\n  generate<O extends z.ZodTypeAny = z.ZodTypeAny>(\n    strPrompt: string\n  ): Promise<GenerateResponse<z.infer<O>>>;\n\n  /**\n   * Make a generate call to the default model with a multipart request.\n   *\n   * ```ts\n   * const ai = genkit({\n   *   plugins: [googleAI()],\n   *   model: googleAI.model('gemini-flash-latest'), // default model\n   * })\n   *\n   * const { text } = await ai.generate([\n   *   { media: {url: 'http://....'} },\n   *   { text: 'describe this image' }\n   * ]);\n   * ```\n   */\n  generate<O extends z.ZodTypeAny = z.ZodTypeAny>(\n    parts: Part[]\n  ): Promise<GenerateResponse<z.infer<O>>>;\n\n  /**\n   * Generate calls a generative model based on the provided prompt and configuration. If\n   * `messages` is provided, the generation will include a conversation history in its\n   * request. If `tools` are provided, the generate method will automatically resolve\n   * tool calls returned from the model unless `returnToolRequests` is set to `true`.\n   *\n   * See {@link GenerateOptions} for detailed information about available options.\n   *\n   * ```ts\n   * const ai = genkit({\n   *   plugins: [googleAI()],\n   * })\n   *\n   * const { text } = await ai.generate({\n   *   system: 'talk like a pirate',\n   *   prompt: [\n   *     { media: { url: 'http://....' } },\n   *     { text: 'describe this image' }\n   *   ],\n   *   messages: conversationHistory,\n   *   tools: [ userInfoLookup ],\n   *   model: googleAI.model('gemini-flash-latest'),\n   * });\n   * ```\n   */\n  generate<\n    O extends z.ZodTypeAny = z.ZodTypeAny,\n    CustomOptions extends z.ZodTypeAny = typeof GenerationCommonConfigSchema,\n  >(\n    opts:\n      | GenerateOptions<O, CustomOptions>\n      | PromiseLike<GenerateOptions<O, CustomOptions>>\n  ): Promise<GenerateResponse<z.infer<O>>>;\n\n  async generate<\n    O extends z.ZodTypeAny = z.ZodTypeAny,\n    CustomOptions extends z.ZodTypeAny = typeof GenerationCommonConfigSchema,\n  >(\n    options:\n      | string\n      | Part[]\n      | GenerateOptions<O, CustomOptions>\n      | PromiseLike<GenerateOptions<O, CustomOptions>>\n  ): Promise<GenerateResponse<z.infer<O>>> {\n    let resolvedOptions: GenerateOptions<O, CustomOptions>;\n    if (options instanceof Promise) {\n      resolvedOptions = await options;\n    } else if (typeof options === 'string' || Array.isArray(options)) {\n      resolvedOptions = {\n        prompt: options,\n      };\n    } else {\n      resolvedOptions = options as GenerateOptions<O, CustomOptions>;\n    }\n    return generate(this.registry, resolvedOptions);\n  }\n\n  /**\n   * Make a streaming generate call to the default model with a simple text prompt.\n   *\n   * ```ts\n   * const ai = genkit({\n   *   plugins: [googleAI()],\n   *   model: googleAI.model('gemini-flash-latest'), // default model\n   * })\n   *\n   * const { response, stream } = ai.generateStream('hi');\n   * for await (const chunk of stream) {\n   *   console.log(chunk.text);\n   * }\n   * console.log((await response).text);\n   * ```\n   */\n  generateStream<O extends z.ZodTypeAny = z.ZodTypeAny>(\n    strPrompt: string\n  ): GenerateStreamResponse<z.infer<O>>;\n\n  /**\n   * Make a streaming generate call to the default model with a multipart request.\n   *\n   * ```ts\n   * const ai = genkit({\n   *   plugins: [googleAI()],\n   *   model: googleAI.model('gemini-flash-latest'), // default model\n   * })\n   *\n   * const { response, stream } = ai.generateStream([\n   *   { media: {url: 'http://....'} },\n   *   { text: 'describe this image' }\n   * ]);\n   * for await (const chunk of stream) {\n   *   console.log(chunk.text);\n   * }\n   * console.log((await response).text);\n   * ```\n   */\n  generateStream<O extends z.ZodTypeAny = z.ZodTypeAny>(\n    parts: Part[]\n  ): GenerateStreamResponse<z.infer<O>>;\n\n  /**\n   * Streaming generate calls a generative model based on the provided prompt and configuration. If\n   * `messages` is provided, the generation will include a conversation history in its\n   * request. If `tools` are provided, the generate method will automatically resolve\n   * tool calls returned from the model unless `returnToolRequests` is set to `true`.\n   *\n   * See {@link GenerateOptions} for detailed information about available options.\n   *\n   * ```ts\n   * const ai = genkit({\n   *   plugins: [googleAI()],\n   * })\n   *\n   * const { response, stream } = ai.generateStream({\n   *   system: 'talk like a pirate',\n   *   prompt: [\n   *     { media: { url: 'http://....' } },\n   *     { text: 'describe this image' }\n   *   ],\n   *   messages: conversationHistory,\n   *   tools: [ userInfoLookup ],\n   *   model: googleAI.model('gemini-flash-latest'),\n   * });\n   * for await (const chunk of stream) {\n   *   console.log(chunk.text);\n   * }\n   * console.log((await response).text);\n   * ```\n   */\n  generateStream<\n    O extends z.ZodTypeAny = z.ZodTypeAny,\n    CustomOptions extends z.ZodTypeAny = typeof GenerationCommonConfigSchema,\n  >(\n    opts:\n      | GenerateStreamOptions<O, CustomOptions>\n      | PromiseLike<GenerateStreamOptions<O, CustomOptions>>\n  ): GenerateStreamResponse<z.infer<O>>;\n\n  generateStream<\n    O extends z.ZodTypeAny = z.ZodTypeAny,\n    CustomOptions extends z.ZodTypeAny = typeof GenerationCommonConfigSchema,\n  >(\n    options:\n      | string\n      | Part[]\n      | GenerateStreamOptions<O, CustomOptions>\n      | PromiseLike<GenerateStreamOptions<O, CustomOptions>>\n  ): GenerateStreamResponse<z.infer<O>> {\n    if (typeof options === 'string' || Array.isArray(options)) {\n      options = { prompt: options };\n    }\n    return generateStream(this.registry, options);\n  }\n\n  /**\n   * Checks the status of of a given operation. Returns a new operation which will contain the updated status.\n   *\n   * ```ts\n   * let operation = await ai.generateOperation({\n   *   model: googleAI.model('veo-2.0-generate-001'),\n   *   prompt: 'A banana riding a bicycle.',\n   * });\n   *\n   * while (!operation.done) {\n   *   operation = await ai.checkOperation(operation!);\n   *   await new Promise((resolve) => setTimeout(resolve, 5000));\n   * }\n   * ```\n   *\n   * @param operation\n   * @returns\n   */\n  checkOperation<T>(operation: Operation<T>): Promise<Operation<T>> {\n    return checkOperation(this.registry, operation);\n  }\n\n  /**\n   * Cancels a given operation. Returns a new operation which will contain the updated status.\n   *\n   * @param operation\n   * @returns\n   */\n  cancelOperation<T>(operation: Operation<T>): Promise<Operation<T>> {\n    return cancelOperation(this.registry, operation);\n  }\n\n  /**\n   * A flow step that executes the provided function. Each run step is recorded separately in the trace.\n   *\n   * ```ts\n   * ai.defineFlow('hello', async() => {\n   *   await ai.run('step1', async () => {\n   *     // ... step 1\n   *   });\n   *   await ai.run('step2', async () => {\n   *     // ... step 2\n   *   });\n   *   return result;\n   * })\n   * ```\n   */\n  run<T>(name: string, func: () => Promise<T>): Promise<T>;\n\n  /**\n   * A flow step that executes the provided function. Each run step is recorded separately in the trace.\n   *\n   * ```ts\n   * ai.defineFlow('hello', async(name) => {\n   *   const greeting = await ai.run('step1', name, async (input) => {\n   *     return `Hello, ${input}!`;\n   *   });\n   *   const result = await ai.run('step2', greeting, async (input) => {\n   *     // ... step 2\n   *   });\n   *   return result;\n   * })\n   */\n  run<T>(\n    name: string,\n    input: any,\n    func: (input?: any) => Promise<T>\n  ): Promise<T>;\n\n  run<T>(\n    name: string,\n    funcOrInput: () => Promise<T> | any,\n    maybeFunc?: (input?: any) => Promise<T>\n  ): Promise<T> {\n    if (maybeFunc) {\n      return run(name, funcOrInput, maybeFunc, this.registry);\n    }\n    return run(name, funcOrInput, this.registry);\n  }\n\n  /**\n   * Returns current action (or flow) invocation context. Can be used to access things like auth\n   * data set by HTTP server frameworks. If invoked outside of an action (e.g. flow or tool) will\n   * return `undefined`.\n   */\n  currentContext(): ActionContext | undefined {\n    return getContext();\n  }\n}\n"],"mappings":"AAgBA;AAAA,EACE;AAAA,EACA;AAAA,OAIK;AAEP,SAAS,uBAAuB;AAChC,SAAS,sBAAsB;AAE/B;AAAA,EACE;AAAA,EACA;AAAA,OAKK;AACP;AAAA,EACE;AAAA,EACA;AAAA,OAKK;AAMA,MAAM,SAAS;AAAA,EACX;AAAA,EAET,YAAY,UAAoB;AAC9B,SAAK,WAAW;AAAA,EAClB;AAAA;AAAA;AAAA;AAAA,EAKA,MACE,QACsB;AACtB,WAAO,MAAM,KAAK,UAAU,MAAM;AAAA,EACpC;AAAA;AAAA;AAAA;AAAA,EAKA,UAA4D,QAKhC;AAC1B,WAAO,UAAU,KAAK,UAAU,MAAM;AAAA,EACxC;AAAA,EAuEA,MAAM,SAIJ,SAKuC;AACvC,QAAI;AACJ,QAAI,mBAAmB,SAAS;AAC9B,wBAAkB,MAAM;AAAA,IAC1B,WAAW,OAAO,YAAY,YAAY,MAAM,QAAQ,OAAO,GAAG;AAChE,wBAAkB;AAAA,QAChB,QAAQ;AAAA,MACV;AAAA,IACF,OAAO;AACL,wBAAkB;AAAA,IACpB;AACA,WAAO,SAAS,KAAK,UAAU,eAAe;AAAA,EAChD;AAAA,EAmFA,eAIE,SAKoC;AACpC,QAAI,OAAO,YAAY,YAAY,MAAM,QAAQ,OAAO,GAAG;AACzD,gBAAU,EAAE,QAAQ,QAAQ;AAAA,IAC9B;AACA,WAAO,eAAe,KAAK,UAAU,OAAO;AAAA,EAC9C;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAoBA,eAAkB,WAAgD;AAChE,WAAO,eAAe,KAAK,UAAU,SAAS;AAAA,EAChD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAQA,gBAAmB,WAAgD;AACjE,WAAO,gBAAgB,KAAK,UAAU,SAAS;AAAA,EACjD;AAAA,EAuCA,IACE,MACA,aACA,WACY;AACZ,QAAI,WAAW;AACb,aAAO,IAAI,MAAM,aAAa,WAAW,KAAK,QAAQ;AAAA,IACxD;AACA,WAAO,IAAI,MAAM,aAAa,KAAK,QAAQ;AAAA,EAC7C;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOA,iBAA4C;AAC1C,WAAO,WAAW;AAAA,EACpB;AACF;","names":[]}