agsamantha/node_modules/@langchain/community/dist/llms/friendli.d.ts
2024-10-02 15:15:21 -05:00

97 lines
3.5 KiB
TypeScript

import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { type BaseLLMCallOptions, type BaseLLMParams, LLM } from "@langchain/core/language_models/llms";
import { GenerationChunk } from "@langchain/core/outputs";
/**
* The FriendliParams interface defines the input parameters for
* the Friendli class.
*/
export interface FriendliParams extends BaseLLMParams {
/**
* Model name to use.
*/
model?: string;
/**
* Base endpoint url.
*/
baseUrl?: string;
/**
* Friendli personal access token to run as.
*/
friendliToken?: string;
/**
* Friendli team ID to run as.
*/
friendliTeam?: string;
/**
* Number between -2.0 and 2.0. Positive values penalizes tokens that have been
* sampled, taking into account their frequency in the preceding text. This
* penalization diminishes the model's tendency to reproduce identical lines
* verbatim.
*/
frequencyPenalty?: number;
/**
* Number between -2.0 and 2.0. Positive values penalizes tokens that have been
* sampled at least once in the existing text.
* presence_penalty: Optional[float] = None
* The maximum number of tokens to generate. The length of your input tokens plus
* `max_tokens` should not exceed the model's maximum length (e.g., 2048 for OpenAI
* GPT-3)
*/
maxTokens?: number;
/**
* When one of the stop phrases appears in the generation result, the API will stop
* generation. The phrase is included in the generated result. If you are using
* beam search, all of the active beams should contain the stop phrase to terminate
* generation. Before checking whether a stop phrase is included in the result, the
* phrase is converted into tokens.
*/
stop?: string[];
/**
* Sampling temperature. Smaller temperature makes the generation result closer to
* greedy, argmax (i.e., `top_k = 1`) sampling. If it is `None`, then 1.0 is used.
*/
temperature?: number;
/**
* Tokens comprising the top `top_p` probability mass are kept for sampling. Numbers
* between 0.0 (exclusive) and 1.0 (inclusive) are allowed. If it is `None`, then 1.0
* is used by default.
*/
topP?: number;
/**
* Additional kwargs to pass to the model.
*/
modelKwargs?: Record<string, unknown>;
}
/**
* The Friendli class is used to interact with Friendli inference Endpoint models.
* This requires your Friendli Token and Friendli Team which is autoloaded if not specified.
*/
export declare class Friendli extends LLM<BaseLLMCallOptions> {
lc_serializable: boolean;
static lc_name(): string;
get lc_secrets(): {
[key: string]: string;
} | undefined;
model: string;
baseUrl: string;
friendliToken?: string;
friendliTeam?: string;
frequencyPenalty?: number;
maxTokens?: number;
stop?: string[];
temperature?: number;
topP?: number;
modelKwargs?: Record<string, unknown>;
constructor(fields: FriendliParams);
_llmType(): string;
private constructHeaders;
private constructBody;
/**
* Calls the Friendli endpoint and retrieves the result.
* @param {string} prompt The input prompt.
* @returns {Promise<string>} A promise that resolves to the generated string.
*/
/** @ignore */
_call(prompt: string, _options: this["ParsedCallOptions"]): Promise<string>;
_streamResponseChunks(prompt: string, _options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<GenerationChunk>;
}