@google-ai/generativelanguage
Version:
Generative Language API client for Node.js
666 lines (665 loc) • 37.5 kB
TypeScript
import type * as gax from 'google-gax';
import type { Callback, CallOptions, Descriptors, ClientOptions } from 'google-gax';
import * as protos from '../../protos/protos';
/**
* API for using Large Models that generate multimodal content and have
* additional capabilities beyond text generation.
* @class
* @memberof v1beta
*/
export declare class GenerativeServiceClient {
private _terminated;
private _opts;
private _providedCustomServicePath;
private _gaxModule;
private _gaxGrpc;
private _protos;
private _defaults;
private _universeDomain;
private _servicePath;
private _log;
auth: gax.GoogleAuth;
descriptors: Descriptors;
warn: (code: string, message: string, warnType?: string) => void;
innerApiCalls: {
[name: string]: Function;
};
pathTemplates: {
[name: string]: gax.PathTemplate;
};
generativeServiceStub?: Promise<{
[name: string]: Function;
}>;
/**
* Construct an instance of GenerativeServiceClient.
*
* @param {object} [options] - The configuration object.
* The options accepted by the constructor are described in detail
* in [this document](https://github.com/googleapis/gax-nodejs/blob/main/client-libraries.md#creating-the-client-instance).
* The common options are:
* @param {object} [options.credentials] - Credentials object.
* @param {string} [options.credentials.client_email]
* @param {string} [options.credentials.private_key]
* @param {string} [options.email] - Account email address. Required when
* using a .pem or .p12 keyFilename.
* @param {string} [options.keyFilename] - Full path to the a .json, .pem, or
* .p12 key downloaded from the Google Developers Console. If you provide
* a path to a JSON file, the projectId option below is not necessary.
* NOTE: .pem and .p12 require you to specify options.email as well.
* @param {number} [options.port] - The port on which to connect to
* the remote host.
* @param {string} [options.projectId] - The project ID from the Google
* Developer's Console, e.g. 'grape-spaceship-123'. We will also check
* the environment variable GCLOUD_PROJECT for your project ID. If your
* app is running in an environment which supports
* {@link https://cloud.google.com/docs/authentication/application-default-credentials Application Default Credentials},
* your project ID will be detected automatically.
* @param {string} [options.apiEndpoint] - The domain name of the
* API remote host.
* @param {gax.ClientConfig} [options.clientConfig] - Client configuration override.
* Follows the structure of {@link gapicConfig}.
* @param {boolean} [options.fallback] - Use HTTP/1.1 REST mode.
* For more information, please check the
* {@link https://github.com/googleapis/gax-nodejs/blob/main/client-libraries.md#http11-rest-api-mode documentation}.
* @param {gax} [gaxInstance]: loaded instance of `google-gax`. Useful if you
* need to avoid loading the default gRPC version and want to use the fallback
* HTTP implementation. Load only fallback version and pass it to the constructor:
* ```
* const gax = require('google-gax/build/src/fallback'); // avoids loading google-gax with gRPC
* const client = new GenerativeServiceClient({fallback: true}, gax);
* ```
*/
constructor(opts?: ClientOptions, gaxInstance?: typeof gax | typeof gax.fallback);
/**
* Initialize the client.
* Performs asynchronous operations (such as authentication) and prepares the client.
* This function will be called automatically when any class method is called for the
* first time, but if you need to initialize it before calling an actual method,
* feel free to call initialize() directly.
*
* You can await on this method if you want to make sure the client is initialized.
*
* @returns {Promise} A promise that resolves to an authenticated service stub.
*/
initialize(): Promise<{
[name: string]: Function;
}>;
/**
* The DNS address for this API service.
* @deprecated Use the apiEndpoint method of the client instance.
* @returns {string} The DNS address for this service.
*/
static get servicePath(): string;
/**
* The DNS address for this API service - same as servicePath.
* @deprecated Use the apiEndpoint method of the client instance.
* @returns {string} The DNS address for this service.
*/
static get apiEndpoint(): string;
/**
* The DNS address for this API service.
* @returns {string} The DNS address for this service.
*/
get apiEndpoint(): string;
get universeDomain(): string;
/**
* The port for this API service.
* @returns {number} The default port for this service.
*/
static get port(): number;
/**
* The scopes needed to make gRPC calls for every method defined
* in this service.
* @returns {string[]} List of default scopes.
*/
static get scopes(): never[];
getProjectId(): Promise<string>;
getProjectId(callback: Callback<string, undefined, undefined>): void;
/**
* Generates a model response given an input `GenerateContentRequest`.
* Refer to the [text generation
* guide](https://ai.google.dev/gemini-api/docs/text-generation) for detailed
* usage information. Input capabilities differ between models, including
* tuned models. Refer to the [model
* guide](https://ai.google.dev/gemini-api/docs/models/gemini) and [tuning
* guide](https://ai.google.dev/gemini-api/docs/model-tuning) for details.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.model
* Required. The name of the `Model` to use for generating the completion.
*
* Format: `models/{model}`.
* @param {google.ai.generativelanguage.v1beta.Content} [request.systemInstruction]
* Optional. Developer set [system
* instruction(s)](https://ai.google.dev/gemini-api/docs/system-instructions).
* Currently, text only.
* @param {number[]} request.contents
* Required. The content of the current conversation with the model.
*
* For single-turn queries, this is a single instance. For multi-turn queries
* like [chat](https://ai.google.dev/gemini-api/docs/text-generation#chat),
* this is a repeated field that contains the conversation history and the
* latest request.
* @param {number[]} [request.tools]
* Optional. A list of `Tools` the `Model` may use to generate the next
* response.
*
* A `Tool` is a piece of code that enables the system to interact with
* external systems to perform an action, or set of actions, outside of
* knowledge and scope of the `Model`. Supported `Tool`s are `Function` and
* `code_execution`. Refer to the [Function
* calling](https://ai.google.dev/gemini-api/docs/function-calling) and the
* [Code execution](https://ai.google.dev/gemini-api/docs/code-execution)
* guides to learn more.
* @param {google.ai.generativelanguage.v1beta.ToolConfig} [request.toolConfig]
* Optional. Tool configuration for any `Tool` specified in the request. Refer
* to the [Function calling
* guide](https://ai.google.dev/gemini-api/docs/function-calling#function_calling_mode)
* for a usage example.
* @param {number[]} [request.safetySettings]
* Optional. A list of unique `SafetySetting` instances for blocking unsafe
* content.
*
* This will be enforced on the `GenerateContentRequest.contents` and
* `GenerateContentResponse.candidates`. There should not be more than one
* setting for each `SafetyCategory` type. The API will block any contents and
* responses that fail to meet the thresholds set by these settings. This list
* overrides the default settings for each `SafetyCategory` specified in the
* safety_settings. If there is no `SafetySetting` for a given
* `SafetyCategory` provided in the list, the API will use the default safety
* setting for that category. Harm categories HARM_CATEGORY_HATE_SPEECH,
* HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
* HARM_CATEGORY_HARASSMENT, HARM_CATEGORY_CIVIC_INTEGRITY are supported.
* Refer to the [guide](https://ai.google.dev/gemini-api/docs/safety-settings)
* for detailed information on available safety settings. Also refer to the
* [Safety guidance](https://ai.google.dev/gemini-api/docs/safety-guidance) to
* learn how to incorporate safety considerations in your AI applications.
* @param {google.ai.generativelanguage.v1beta.GenerationConfig} [request.generationConfig]
* Optional. Configuration options for model generation and outputs.
* @param {string} [request.cachedContent]
* Optional. The name of the content
* [cached](https://ai.google.dev/gemini-api/docs/caching) to use as context
* to serve the prediction. Format: `cachedContents/{cachedContent}`
* @param {object} [options]
* Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing {@link protos.google.ai.generativelanguage.v1beta.GenerateContentResponse|GenerateContentResponse}.
* Please see the {@link https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods | documentation }
* for more details and examples.
* @example <caption>include:samples/generated/v1beta/generative_service.generate_content.js</caption>
* region_tag:generativelanguage_v1beta_generated_GenerativeService_GenerateContent_async
*/
generateContent(request?: protos.google.ai.generativelanguage.v1beta.IGenerateContentRequest, options?: CallOptions): Promise<[
protos.google.ai.generativelanguage.v1beta.IGenerateContentResponse,
(protos.google.ai.generativelanguage.v1beta.IGenerateContentRequest | undefined),
{} | undefined
]>;
generateContent(request: protos.google.ai.generativelanguage.v1beta.IGenerateContentRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta.IGenerateContentResponse, protos.google.ai.generativelanguage.v1beta.IGenerateContentRequest | null | undefined, {} | null | undefined>): void;
generateContent(request: protos.google.ai.generativelanguage.v1beta.IGenerateContentRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta.IGenerateContentResponse, protos.google.ai.generativelanguage.v1beta.IGenerateContentRequest | null | undefined, {} | null | undefined>): void;
/**
* Generates a grounded answer from the model given an input
* `GenerateAnswerRequest`.
*
* @param {Object} request
* The request object that will be sent.
* @param {google.ai.generativelanguage.v1beta.GroundingPassages} request.inlinePassages
* Passages provided inline with the request.
* @param {google.ai.generativelanguage.v1beta.SemanticRetrieverConfig} request.semanticRetriever
* Content retrieved from resources created via the Semantic Retriever
* API.
* @param {string} request.model
* Required. The name of the `Model` to use for generating the grounded
* response.
*
* Format: `model=models/{model}`.
* @param {number[]} request.contents
* Required. The content of the current conversation with the `Model`. For
* single-turn queries, this is a single question to answer. For multi-turn
* queries, this is a repeated field that contains conversation history and
* the last `Content` in the list containing the question.
*
* Note: `GenerateAnswer` only supports queries in English.
* @param {google.ai.generativelanguage.v1beta.GenerateAnswerRequest.AnswerStyle} request.answerStyle
* Required. Style in which answers should be returned.
* @param {number[]} [request.safetySettings]
* Optional. A list of unique `SafetySetting` instances for blocking unsafe
* content.
*
* This will be enforced on the `GenerateAnswerRequest.contents` and
* `GenerateAnswerResponse.candidate`. There should not be more than one
* setting for each `SafetyCategory` type. The API will block any contents and
* responses that fail to meet the thresholds set by these settings. This list
* overrides the default settings for each `SafetyCategory` specified in the
* safety_settings. If there is no `SafetySetting` for a given
* `SafetyCategory` provided in the list, the API will use the default safety
* setting for that category. Harm categories HARM_CATEGORY_HATE_SPEECH,
* HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
* HARM_CATEGORY_HARASSMENT are supported.
* Refer to the
* [guide](https://ai.google.dev/gemini-api/docs/safety-settings)
* for detailed information on available safety settings. Also refer to the
* [Safety guidance](https://ai.google.dev/gemini-api/docs/safety-guidance) to
* learn how to incorporate safety considerations in your AI applications.
* @param {number} [request.temperature]
* Optional. Controls the randomness of the output.
*
* Values can range from [0.0,1.0], inclusive. A value closer to 1.0 will
* produce responses that are more varied and creative, while a value closer
* to 0.0 will typically result in more straightforward responses from the
* model. A low temperature (~0.2) is usually recommended for
* Attributed-Question-Answering use cases.
* @param {object} [options]
* Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing {@link protos.google.ai.generativelanguage.v1beta.GenerateAnswerResponse|GenerateAnswerResponse}.
* Please see the {@link https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods | documentation }
* for more details and examples.
* @example <caption>include:samples/generated/v1beta/generative_service.generate_answer.js</caption>
* region_tag:generativelanguage_v1beta_generated_GenerativeService_GenerateAnswer_async
*/
generateAnswer(request?: protos.google.ai.generativelanguage.v1beta.IGenerateAnswerRequest, options?: CallOptions): Promise<[
protos.google.ai.generativelanguage.v1beta.IGenerateAnswerResponse,
(protos.google.ai.generativelanguage.v1beta.IGenerateAnswerRequest | undefined),
{} | undefined
]>;
generateAnswer(request: protos.google.ai.generativelanguage.v1beta.IGenerateAnswerRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta.IGenerateAnswerResponse, protos.google.ai.generativelanguage.v1beta.IGenerateAnswerRequest | null | undefined, {} | null | undefined>): void;
generateAnswer(request: protos.google.ai.generativelanguage.v1beta.IGenerateAnswerRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta.IGenerateAnswerResponse, protos.google.ai.generativelanguage.v1beta.IGenerateAnswerRequest | null | undefined, {} | null | undefined>): void;
/**
* Generates a text embedding vector from the input `Content` using the
* specified [Gemini Embedding
* model](https://ai.google.dev/gemini-api/docs/models/gemini#text-embedding).
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.model
* Required. The model's resource name. This serves as an ID for the Model to
* use.
*
* This name should match a model name returned by the `ListModels` method.
*
* Format: `models/{model}`
* @param {google.ai.generativelanguage.v1beta.Content} request.content
* Required. The content to embed. Only the `parts.text` fields will be
* counted.
* @param {google.ai.generativelanguage.v1beta.TaskType} [request.taskType]
* Optional. Optional task type for which the embeddings will be used. Not
* supported on earlier models (`models/embedding-001`).
* @param {string} [request.title]
* Optional. An optional title for the text. Only applicable when TaskType is
* `RETRIEVAL_DOCUMENT`.
*
* Note: Specifying a `title` for `RETRIEVAL_DOCUMENT` provides better quality
* embeddings for retrieval.
* @param {number} [request.outputDimensionality]
* Optional. Optional reduced dimension for the output embedding. If set,
* excessive values in the output embedding are truncated from the end.
* Supported by newer models since 2024 only. You cannot set this value if
* using the earlier model (`models/embedding-001`).
* @param {object} [options]
* Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing {@link protos.google.ai.generativelanguage.v1beta.EmbedContentResponse|EmbedContentResponse}.
* Please see the {@link https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods | documentation }
* for more details and examples.
* @example <caption>include:samples/generated/v1beta/generative_service.embed_content.js</caption>
* region_tag:generativelanguage_v1beta_generated_GenerativeService_EmbedContent_async
*/
embedContent(request?: protos.google.ai.generativelanguage.v1beta.IEmbedContentRequest, options?: CallOptions): Promise<[
protos.google.ai.generativelanguage.v1beta.IEmbedContentResponse,
(protos.google.ai.generativelanguage.v1beta.IEmbedContentRequest | undefined),
{} | undefined
]>;
embedContent(request: protos.google.ai.generativelanguage.v1beta.IEmbedContentRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta.IEmbedContentResponse, protos.google.ai.generativelanguage.v1beta.IEmbedContentRequest | null | undefined, {} | null | undefined>): void;
embedContent(request: protos.google.ai.generativelanguage.v1beta.IEmbedContentRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta.IEmbedContentResponse, protos.google.ai.generativelanguage.v1beta.IEmbedContentRequest | null | undefined, {} | null | undefined>): void;
/**
* Generates multiple embedding vectors from the input `Content` which
* consists of a batch of strings represented as `EmbedContentRequest`
* objects.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.model
* Required. The model's resource name. This serves as an ID for the Model to
* use.
*
* This name should match a model name returned by the `ListModels` method.
*
* Format: `models/{model}`
* @param {number[]} request.requests
* Required. Embed requests for the batch. The model in each of these requests
* must match the model specified `BatchEmbedContentsRequest.model`.
* @param {object} [options]
* Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing {@link protos.google.ai.generativelanguage.v1beta.BatchEmbedContentsResponse|BatchEmbedContentsResponse}.
* Please see the {@link https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods | documentation }
* for more details and examples.
* @example <caption>include:samples/generated/v1beta/generative_service.batch_embed_contents.js</caption>
* region_tag:generativelanguage_v1beta_generated_GenerativeService_BatchEmbedContents_async
*/
batchEmbedContents(request?: protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsRequest, options?: CallOptions): Promise<[
protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsResponse,
(protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsRequest | undefined),
{} | undefined
]>;
batchEmbedContents(request: protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsResponse, protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsRequest | null | undefined, {} | null | undefined>): void;
batchEmbedContents(request: protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsResponse, protos.google.ai.generativelanguage.v1beta.IBatchEmbedContentsRequest | null | undefined, {} | null | undefined>): void;
/**
* Runs a model's tokenizer on input `Content` and returns the token count.
* Refer to the [tokens guide](https://ai.google.dev/gemini-api/docs/tokens)
* to learn more about tokens.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.model
* Required. The model's resource name. This serves as an ID for the Model to
* use.
*
* This name should match a model name returned by the `ListModels` method.
*
* Format: `models/{model}`
* @param {number[]} [request.contents]
* Optional. The input given to the model as a prompt. This field is ignored
* when `generate_content_request` is set.
* @param {google.ai.generativelanguage.v1beta.GenerateContentRequest} [request.generateContentRequest]
* Optional. The overall input given to the `Model`. This includes the prompt
* as well as other model steering information like [system
* instructions](https://ai.google.dev/gemini-api/docs/system-instructions),
* and/or function declarations for [function
* calling](https://ai.google.dev/gemini-api/docs/function-calling).
* `Model`s/`Content`s and `generate_content_request`s are mutually
* exclusive. You can either send `Model` + `Content`s or a
* `generate_content_request`, but never both.
* @param {object} [options]
* Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing {@link protos.google.ai.generativelanguage.v1beta.CountTokensResponse|CountTokensResponse}.
* Please see the {@link https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods | documentation }
* for more details and examples.
* @example <caption>include:samples/generated/v1beta/generative_service.count_tokens.js</caption>
* region_tag:generativelanguage_v1beta_generated_GenerativeService_CountTokens_async
*/
countTokens(request?: protos.google.ai.generativelanguage.v1beta.ICountTokensRequest, options?: CallOptions): Promise<[
protos.google.ai.generativelanguage.v1beta.ICountTokensResponse,
(protos.google.ai.generativelanguage.v1beta.ICountTokensRequest | undefined),
{} | undefined
]>;
countTokens(request: protos.google.ai.generativelanguage.v1beta.ICountTokensRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta.ICountTokensResponse, protos.google.ai.generativelanguage.v1beta.ICountTokensRequest | null | undefined, {} | null | undefined>): void;
countTokens(request: protos.google.ai.generativelanguage.v1beta.ICountTokensRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta.ICountTokensResponse, protos.google.ai.generativelanguage.v1beta.ICountTokensRequest | null | undefined, {} | null | undefined>): void;
/**
* Generates a [streamed
* response](https://ai.google.dev/gemini-api/docs/text-generation?lang=python#generate-a-text-stream)
* from the model given an input `GenerateContentRequest`.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.model
* Required. The name of the `Model` to use for generating the completion.
*
* Format: `models/{model}`.
* @param {google.ai.generativelanguage.v1beta.Content} [request.systemInstruction]
* Optional. Developer set [system
* instruction(s)](https://ai.google.dev/gemini-api/docs/system-instructions).
* Currently, text only.
* @param {number[]} request.contents
* Required. The content of the current conversation with the model.
*
* For single-turn queries, this is a single instance. For multi-turn queries
* like [chat](https://ai.google.dev/gemini-api/docs/text-generation#chat),
* this is a repeated field that contains the conversation history and the
* latest request.
* @param {number[]} [request.tools]
* Optional. A list of `Tools` the `Model` may use to generate the next
* response.
*
* A `Tool` is a piece of code that enables the system to interact with
* external systems to perform an action, or set of actions, outside of
* knowledge and scope of the `Model`. Supported `Tool`s are `Function` and
* `code_execution`. Refer to the [Function
* calling](https://ai.google.dev/gemini-api/docs/function-calling) and the
* [Code execution](https://ai.google.dev/gemini-api/docs/code-execution)
* guides to learn more.
* @param {google.ai.generativelanguage.v1beta.ToolConfig} [request.toolConfig]
* Optional. Tool configuration for any `Tool` specified in the request. Refer
* to the [Function calling
* guide](https://ai.google.dev/gemini-api/docs/function-calling#function_calling_mode)
* for a usage example.
* @param {number[]} [request.safetySettings]
* Optional. A list of unique `SafetySetting` instances for blocking unsafe
* content.
*
* This will be enforced on the `GenerateContentRequest.contents` and
* `GenerateContentResponse.candidates`. There should not be more than one
* setting for each `SafetyCategory` type. The API will block any contents and
* responses that fail to meet the thresholds set by these settings. This list
* overrides the default settings for each `SafetyCategory` specified in the
* safety_settings. If there is no `SafetySetting` for a given
* `SafetyCategory` provided in the list, the API will use the default safety
* setting for that category. Harm categories HARM_CATEGORY_HATE_SPEECH,
* HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
* HARM_CATEGORY_HARASSMENT, HARM_CATEGORY_CIVIC_INTEGRITY are supported.
* Refer to the [guide](https://ai.google.dev/gemini-api/docs/safety-settings)
* for detailed information on available safety settings. Also refer to the
* [Safety guidance](https://ai.google.dev/gemini-api/docs/safety-guidance) to
* learn how to incorporate safety considerations in your AI applications.
* @param {google.ai.generativelanguage.v1beta.GenerationConfig} [request.generationConfig]
* Optional. Configuration options for model generation and outputs.
* @param {string} [request.cachedContent]
* Optional. The name of the content
* [cached](https://ai.google.dev/gemini-api/docs/caching) to use as context
* to serve the prediction. Format: `cachedContents/{cachedContent}`
* @param {object} [options]
* Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
* @returns {Stream}
* An object stream which emits {@link protos.google.ai.generativelanguage.v1beta.GenerateContentResponse|GenerateContentResponse} on 'data' event.
* Please see the {@link https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#server-streaming | documentation }
* for more details and examples.
* @example <caption>include:samples/generated/v1beta/generative_service.stream_generate_content.js</caption>
* region_tag:generativelanguage_v1beta_generated_GenerativeService_StreamGenerateContent_async
*/
streamGenerateContent(request?: protos.google.ai.generativelanguage.v1beta.IGenerateContentRequest, options?: CallOptions): gax.CancellableStream;
/**
* Low-Latency bidirectional streaming API that supports audio and video
* streaming inputs can produce multimodal output streams (audio and text).
*
* @param {object} [options]
* Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
* @returns {Stream}
* An object stream which is both readable and writable. It accepts objects
* representing {@link protos.google.ai.generativelanguage.v1beta.BidiGenerateContentClientMessage|BidiGenerateContentClientMessage} for write() method, and
* will emit objects representing {@link protos.google.ai.generativelanguage.v1beta.BidiGenerateContentServerMessage|BidiGenerateContentServerMessage} on 'data' event asynchronously.
* Please see the {@link https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#bi-directional-streaming | documentation }
* for more details and examples.
* @example <caption>include:samples/generated/v1beta/generative_service.bidi_generate_content.js</caption>
* region_tag:generativelanguage_v1beta_generated_GenerativeService_BidiGenerateContent_async
*/
bidiGenerateContent(options?: CallOptions): gax.CancellableStream;
/**
* Return a fully-qualified cachedContent resource name string.
*
* @param {string} id
* @returns {string} Resource name string.
*/
cachedContentPath(id: string): string;
/**
* Parse the id from CachedContent resource.
*
* @param {string} cachedContentName
* A fully-qualified path representing CachedContent resource.
* @returns {string} A string representing the id.
*/
matchIdFromCachedContentName(cachedContentName: string): string | number;
/**
* Return a fully-qualified chunk resource name string.
*
* @param {string} corpus
* @param {string} document
* @param {string} chunk
* @returns {string} Resource name string.
*/
chunkPath(corpus: string, document: string, chunk: string): string;
/**
* Parse the corpus from Chunk resource.
*
* @param {string} chunkName
* A fully-qualified path representing Chunk resource.
* @returns {string} A string representing the corpus.
*/
matchCorpusFromChunkName(chunkName: string): string | number;
/**
* Parse the document from Chunk resource.
*
* @param {string} chunkName
* A fully-qualified path representing Chunk resource.
* @returns {string} A string representing the document.
*/
matchDocumentFromChunkName(chunkName: string): string | number;
/**
* Parse the chunk from Chunk resource.
*
* @param {string} chunkName
* A fully-qualified path representing Chunk resource.
* @returns {string} A string representing the chunk.
*/
matchChunkFromChunkName(chunkName: string): string | number;
/**
* Return a fully-qualified corpus resource name string.
*
* @param {string} corpus
* @returns {string} Resource name string.
*/
corpusPath(corpus: string): string;
/**
* Parse the corpus from Corpus resource.
*
* @param {string} corpusName
* A fully-qualified path representing Corpus resource.
* @returns {string} A string representing the corpus.
*/
matchCorpusFromCorpusName(corpusName: string): string | number;
/**
* Return a fully-qualified corpusPermission resource name string.
*
* @param {string} corpus
* @param {string} permission
* @returns {string} Resource name string.
*/
corpusPermissionPath(corpus: string, permission: string): string;
/**
* Parse the corpus from CorpusPermission resource.
*
* @param {string} corpusPermissionName
* A fully-qualified path representing corpus_permission resource.
* @returns {string} A string representing the corpus.
*/
matchCorpusFromCorpusPermissionName(corpusPermissionName: string): string | number;
/**
* Parse the permission from CorpusPermission resource.
*
* @param {string} corpusPermissionName
* A fully-qualified path representing corpus_permission resource.
* @returns {string} A string representing the permission.
*/
matchPermissionFromCorpusPermissionName(corpusPermissionName: string): string | number;
/**
* Return a fully-qualified document resource name string.
*
* @param {string} corpus
* @param {string} document
* @returns {string} Resource name string.
*/
documentPath(corpus: string, document: string): string;
/**
* Parse the corpus from Document resource.
*
* @param {string} documentName
* A fully-qualified path representing Document resource.
* @returns {string} A string representing the corpus.
*/
matchCorpusFromDocumentName(documentName: string): string | number;
/**
* Parse the document from Document resource.
*
* @param {string} documentName
* A fully-qualified path representing Document resource.
* @returns {string} A string representing the document.
*/
matchDocumentFromDocumentName(documentName: string): string | number;
/**
* Return a fully-qualified file resource name string.
*
* @param {string} file
* @returns {string} Resource name string.
*/
filePath(file: string): string;
/**
* Parse the file from File resource.
*
* @param {string} fileName
* A fully-qualified path representing File resource.
* @returns {string} A string representing the file.
*/
matchFileFromFileName(fileName: string): string | number;
/**
* Return a fully-qualified model resource name string.
*
* @param {string} model
* @returns {string} Resource name string.
*/
modelPath(model: string): string;
/**
* Parse the model from Model resource.
*
* @param {string} modelName
* A fully-qualified path representing Model resource.
* @returns {string} A string representing the model.
*/
matchModelFromModelName(modelName: string): string | number;
/**
* Return a fully-qualified tunedModel resource name string.
*
* @param {string} tuned_model
* @returns {string} Resource name string.
*/
tunedModelPath(tunedModel: string): string;
/**
* Parse the tuned_model from TunedModel resource.
*
* @param {string} tunedModelName
* A fully-qualified path representing TunedModel resource.
* @returns {string} A string representing the tuned_model.
*/
matchTunedModelFromTunedModelName(tunedModelName: string): string | number;
/**
* Return a fully-qualified tunedModelPermission resource name string.
*
* @param {string} tuned_model
* @param {string} permission
* @returns {string} Resource name string.
*/
tunedModelPermissionPath(tunedModel: string, permission: string): string;
/**
* Parse the tuned_model from TunedModelPermission resource.
*
* @param {string} tunedModelPermissionName
* A fully-qualified path representing tuned_model_permission resource.
* @returns {string} A string representing the tuned_model.
*/
matchTunedModelFromTunedModelPermissionName(tunedModelPermissionName: string): string | number;
/**
* Parse the permission from TunedModelPermission resource.
*
* @param {string} tunedModelPermissionName
* A fully-qualified path representing tuned_model_permission resource.
* @returns {string} A string representing the permission.
*/
matchPermissionFromTunedModelPermissionName(tunedModelPermissionName: string): string | number;
/**
* Terminate the gRPC channel and close the client.
*
* The client will no longer be usable and all future behavior is undefined.
* @returns {Promise} A promise that resolves when the client is closed.
*/
close(): Promise<void>;
}