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

import { type BaseMessage } from "@langchain/core/messages";
import { type BaseLanguageModelCallOptions } from "@langchain/core/language_models/base";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { type BaseChatModelParams, BaseChatModel } from "@langchain/core/language_models/chat_models";
import Prem, { ChatCompletionStreamingCompletionData, CreateChatCompletionRequest, CreateChatCompletionResponse } from "@premai/prem-sdk";
import { ChatGenerationChunk, ChatResult } from "@langchain/core/outputs";
export type RoleEnum = "user" | "assistant";
/**
 * Input to chat model class.
 */
export interface ChatPremInput extends BaseChatModelParams {
    project_id?: number | string;
    session_id?: string;
    messages?: {
        role: "user" | "assistant";
        content: string;
        [k: string]: unknown;
    }[];
    model?: string;
    system_prompt?: string;
    frequency_penalty?: number;
    logit_bias?: {
        [k: string]: unknown;
    };
    max_tokens?: number;
    n?: number;
    presence_penalty?: number;
    response_format?: {
        [k: string]: unknown;
    };
    seed?: number;
    stop?: string;
    temperature?: number;
    top_p?: number;
    tools?: {
        [k: string]: unknown;
    }[];
    user?: string;
    /**
     * The Prem API key to use for requests.
     * @default process.env.PREM_API_KEY
     */
    apiKey?: string;
    streaming?: boolean;
}
export interface ChatCompletionCreateParamsNonStreaming extends CreateChatCompletionRequest {
    stream?: false;
}
export interface ChatCompletionCreateParamsStreaming extends CreateChatCompletionRequest {
    stream: true;
}
export type ChatCompletionCreateParams = ChatCompletionCreateParamsNonStreaming | ChatCompletionCreateParamsStreaming;
export declare function messageToPremRole(message: BaseMessage): RoleEnum;
/**
 * Integration with a chat model.
 */
export declare class ChatPrem<CallOptions extends BaseLanguageModelCallOptions = BaseLanguageModelCallOptions> extends BaseChatModel<CallOptions> implements ChatPremInput {
    client: Prem;
    apiKey?: string;
    project_id: number;
    session_id?: string;
    messages: {
        [k: string]: unknown;
        role: "user" | "assistant";
        content: string;
    }[];
    model?: string;
    system_prompt?: string;
    frequency_penalty?: number;
    logit_bias?: {
        [k: string]: unknown;
    };
    max_tokens?: number;
    n?: number;
    presence_penalty?: number;
    response_format?: {
        [k: string]: unknown;
    };
    seed?: number;
    stop?: string;
    temperature?: number;
    top_p?: number;
    tools?: {
        [k: string]: unknown;
    }[];
    user?: string;
    streaming: boolean;
    [k: string]: unknown;
    static lc_name(): string;
    lc_serializable: boolean;
    /**
     * Replace with any secrets this class passes to `super`.
     * See {@link ../../langchain-cohere/src/chat_model.ts} for
     * an example.
     */
    get lc_secrets(): {
        [key: string]: string;
    } | undefined;
    get lc_aliases(): {
        [key: string]: string;
    } | undefined;
    constructor(fields?: ChatPremInput);
    _llmType(): string;
    completionWithRetry(request: ChatCompletionCreateParamsStreaming, options?: any): Promise<AsyncIterable<ChatCompletionStreamingCompletionData>>;
    completionWithRetry(request: ChatCompletionCreateParams, options?: any): Promise<CreateChatCompletionResponse>;
    invocationParams(options: this["ParsedCallOptions"]): any;
    /**
     * Implement to support streaming.
     * Should yield chunks iteratively.
     */
    _streamResponseChunks(messages: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<ChatGenerationChunk>;
    /** @ignore */
    _combineLLMOutput(): never[];
    _generate(messages: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): Promise<ChatResult>;
}