agsamantha/node_modules/@langchain/community/dist/chat_models/baiduwenxin.d.ts

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2024-10-02 15:15:21 -05:00
import { BaseChatModel, type BaseChatModelParams } from "@langchain/core/language_models/chat_models";
import { BaseMessage } from "@langchain/core/messages";
import { ChatGenerationChunk, ChatResult } from "@langchain/core/outputs";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
/**
* Type representing the role of a message in the Wenxin chat model.
*/
export type WenxinMessageRole = "assistant" | "user";
/**
* Interface representing a message in the Wenxin chat model.
*/
interface WenxinMessage {
role: WenxinMessageRole;
content: string;
}
/**
* Interface representing a request for a chat completion.
*/
interface ChatCompletionRequest {
messages: WenxinMessage[];
stream?: boolean;
user_id?: string;
temperature?: number;
top_p?: number;
penalty_score?: number;
system?: string;
}
/**
* Interface defining the input to the ChatBaiduWenxin class.
*/
declare interface BaiduWenxinChatInput {
/**
* Model name to use. Available options are: ERNIE-Bot, ERNIE-Bot-turbo, ERNIE-Bot-4
* Alias for `model`
* @default "ERNIE-Bot-turbo"
*/
modelName: string;
/** Model name to use. Available options are: ERNIE-Bot, ERNIE-Bot-turbo, ERNIE-Bot-4
* @default "ERNIE-Bot-turbo"
*/
model: string;
/** Whether to stream the results or not. Defaults to false. */
streaming?: boolean;
/** Messages to pass as a prefix to the prompt */
prefixMessages?: WenxinMessage[];
/**
* ID of the end-user who made requests.
*/
userId?: string;
/**
* API key to use when making requests. Defaults to the value of
* `BAIDU_API_KEY` environment variable.
* Alias for `apiKey`
*/
baiduApiKey?: string;
/**
* API key to use when making requests. Defaults to the value of
* `BAIDU_API_KEY` environment variable.
*/
apiKey?: string;
/**
* Secret key to use when making requests. Defaults to the value of
* `BAIDU_SECRET_KEY` environment variable.
*/
baiduSecretKey?: string;
/** Amount of randomness injected into the response. Ranges
* from 0 to 1 (0 is not included). Use temp closer to 0 for analytical /
* multiple choice, and temp closer to 1 for creative
* and generative tasks. Defaults to 0.95.
*/
temperature?: number;
/** Total probability mass of tokens to consider at each step. Range
* from 0 to 1.0. Defaults to 0.8.
*/
topP?: number;
/** Penalizes repeated tokens according to frequency. Range
* from 1.0 to 2.0. Defaults to 1.0.
*/
penaltyScore?: number;
}
/**
* @deprecated Install and import from @langchain/baidu-qianfan instead.
* Wrapper around Baidu ERNIE large language models that use the Chat endpoint.
*
* To use you should have the `BAIDU_API_KEY` and `BAIDU_SECRET_KEY`
* environment variable set.
*
* @augments BaseLLM
* @augments BaiduERNIEInput
* @example
* ```typescript
* const ernieTurbo = new ChatBaiduWenxin({
* apiKey: "YOUR-API-KEY",
* baiduSecretKey: "YOUR-SECRET-KEY",
* });
*
* const ernie = new ChatBaiduWenxin({
* model: "ERNIE-Bot",
* temperature: 1,
* apiKey: "YOUR-API-KEY",
* baiduSecretKey: "YOUR-SECRET-KEY",
* });
*
* const messages = [new HumanMessage("Hello")];
*
* let res = await ernieTurbo.call(messages);
*
* res = await ernie.call(messages);
* ```
*/
export declare class ChatBaiduWenxin extends BaseChatModel implements BaiduWenxinChatInput {
static lc_name(): string;
get callKeys(): string[];
get lc_secrets(): {
[key: string]: string;
} | undefined;
get lc_aliases(): {
[key: string]: string;
} | undefined;
lc_serializable: boolean;
baiduApiKey?: string;
apiKey?: string;
baiduSecretKey?: string;
accessToken: string;
streaming: boolean;
prefixMessages?: WenxinMessage[];
userId?: string;
modelName: string;
model: string;
apiUrl: string;
temperature?: number | undefined;
topP?: number | undefined;
penaltyScore?: number | undefined;
constructor(fields?: Partial<BaiduWenxinChatInput> & BaseChatModelParams);
/**
* Method that retrieves the access token for making requests to the Baidu
* API.
* @param options Optional parsed call options.
* @returns The access token for making requests to the Baidu API.
*/
getAccessToken(options?: this["ParsedCallOptions"]): Promise<any>;
/**
* Get the parameters used to invoke the model
*/
invocationParams(): Omit<ChatCompletionRequest, "messages">;
/**
* Get the identifying parameters for the model
*/
identifyingParams(): {
stream?: boolean | undefined;
temperature?: number | undefined;
system?: string | undefined;
top_p?: number | undefined;
user_id?: string | undefined;
penalty_score?: number | undefined;
model_name: string;
};
private _ensureMessages;
/** @ignore */
_generate(messages: BaseMessage[], options?: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): Promise<ChatResult>;
/** @ignore */
completionWithRetry(request: ChatCompletionRequest, stream: boolean, signal?: AbortSignal, onmessage?: (event: MessageEvent) => void): Promise<any>;
private getFullApiUrl;
private createWenxinStream;
private _deserialize;
_streamResponseChunks(messages: BaseMessage[], options?: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<ChatGenerationChunk>;
_llmType(): string;
/** @ignore */
_combineLLMOutput(): never[];
}
export {};