import { type ClientOptions, OpenAI as OpenAIClient } from "openai";
import { CallbackManagerForLLMRun } from "../callbacks/manager.js";
import { BaseMessage, ChatGenerationChunk, ChatResult } from "../schema/index.js";
import { StructuredTool } from "../tools/base.js";
import { AzureOpenAIInput, OpenAICallOptions, OpenAIChatInput, OpenAICoreRequestOptions, LegacyOpenAIInput } from "../types/openai-types.js";
import { BaseChatModel, BaseChatModelParams } from "./base.js";
import { BaseFunctionCallOptions } from "../base_language/index.js";
export { AzureOpenAIInput, OpenAICallOptions, OpenAIChatInput };
interface TokenUsage {
    completionTokens?: number;
    promptTokens?: number;
    totalTokens?: number;
}
interface OpenAILLMOutput {
    tokenUsage: TokenUsage;
}
export interface ChatOpenAICallOptions extends OpenAICallOptions, BaseFunctionCallOptions {
    tools?: StructuredTool[];
    promptIndex?: number;
}
/**
 * Wrapper around OpenAI large language models that use the Chat endpoint.
 *
 * To use you should have the `openai` package installed, with the
 * `OPENAI_API_KEY` environment variable set.
 *
 * To use with Azure you should have the `openai` package installed, with the
 * `AZURE_OPENAI_API_KEY`,
 * `AZURE_OPENAI_API_INSTANCE_NAME`,
 * `AZURE_OPENAI_API_DEPLOYMENT_NAME`
 * and `AZURE_OPENAI_API_VERSION` environment variable set.
 * `AZURE_OPENAI_BASE_PATH` is optional and will override `AZURE_OPENAI_API_INSTANCE_NAME` if you need to use a custom endpoint.
 *
 * @remarks
 * Any parameters that are valid to be passed to {@link
 * https://platform.openai.com/docs/api-reference/chat/create |
 * `openai.createChatCompletion`} can be passed through {@link modelKwargs}, even
 * if not explicitly available on this class.
 */
export declare class ChatOpenAI<CallOptions extends ChatOpenAICallOptions = ChatOpenAICallOptions> extends BaseChatModel<CallOptions> implements OpenAIChatInput, AzureOpenAIInput {
    static lc_name(): string;
    get callKeys(): string[];
    lc_serializable: boolean;
    get lc_secrets(): {
        [key: string]: string;
    } | undefined;
    get lc_aliases(): Record<string, string>;
    temperature: number;
    topP: number;
    frequencyPenalty: number;
    presencePenalty: number;
    n: number;
    logitBias?: Record<string, number>;
    modelName: string;
    modelKwargs?: OpenAIChatInput["modelKwargs"];
    stop?: string[];
    user?: string;
    timeout?: number;
    streaming: boolean;
    maxTokens?: number;
    openAIApiKey?: string;
    azureOpenAIApiVersion?: string;
    azureOpenAIApiKey?: string;
    azureOpenAIApiInstanceName?: string;
    azureOpenAIApiDeploymentName?: string;
    azureOpenAIBasePath?: string;
    organization?: string;
    private client;
    private clientConfig;
    constructor(fields?: Partial<OpenAIChatInput> & Partial<AzureOpenAIInput> & BaseChatModelParams & {
        configuration?: ClientOptions & LegacyOpenAIInput;
    }, 
    /** @deprecated */
    configuration?: ClientOptions & LegacyOpenAIInput);
    /**
     * Get the parameters used to invoke the model
     */
    invocationParams(options?: this["ParsedCallOptions"]): Omit<OpenAIClient.Chat.ChatCompletionCreateParams, "messages">;
    /** @ignore */
    _identifyingParams(): Omit<OpenAIClient.Chat.ChatCompletionCreateParams, "messages"> & {
        model_name: string;
    } & ClientOptions;
    _streamResponseChunks(messages: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<ChatGenerationChunk>;
    /**
     * Get the identifying parameters for the model
     */
    identifyingParams(): Omit<OpenAIClient.Chat.Completions.ChatCompletionCreateParams, "messages"> & {
        model_name: string;
    } & ClientOptions;
    /** @ignore */
    _generate(messages: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): Promise<ChatResult>;
    getNumTokensFromMessages(messages: BaseMessage[]): Promise<{
        totalCount: number;
        countPerMessage: number[];
    }>;
    /**
     * Calls the OpenAI API with retry logic in case of failures.
     * @param request The request to send to the OpenAI API.
     * @param options Optional configuration for the API call.
     * @returns The response from the OpenAI API.
     */
    completionWithRetry(request: OpenAIClient.Chat.ChatCompletionCreateParamsStreaming, options?: OpenAICoreRequestOptions): Promise<AsyncIterable<OpenAIClient.Chat.Completions.ChatCompletionChunk>>;
    completionWithRetry(request: OpenAIClient.Chat.ChatCompletionCreateParamsNonStreaming, options?: OpenAICoreRequestOptions): Promise<OpenAIClient.Chat.Completions.ChatCompletion>;
    private _getClientOptions;
    _llmType(): string;
    /** @ignore */
    _combineLLMOutput(...llmOutputs: OpenAILLMOutput[]): OpenAILLMOutput;
}
export declare class PromptLayerChatOpenAI extends ChatOpenAI {
    promptLayerApiKey?: string;
    plTags?: string[];
    returnPromptLayerId?: boolean;
    constructor(fields?: ConstructorParameters<typeof ChatOpenAI>[0] & {
        promptLayerApiKey?: string;
        plTags?: string[];
        returnPromptLayerId?: boolean;
    });
    _generate(messages: BaseMessage[], options?: string[] | ChatOpenAICallOptions, runManager?: CallbackManagerForLLMRun): Promise<ChatResult>;
}