import { Runnable } from "../runnables/index.js";
import type { RunnableConfig } from "../runnables/config.js";
import type { BasePromptValueInterface } from "../prompt_values.js";
import type { BaseMessage, MessageContentComplex } from "../messages/index.js";
import type { Callbacks } from "../callbacks/manager.js";
import type { Generation, ChatGeneration } from "../outputs.js";
/**
 * Options for formatting instructions.
 */
export interface FormatInstructionsOptions {
}
/**
 * Abstract base class for parsing the output of a Large Language Model
 * (LLM) call. It provides methods for parsing the result of an LLM call
 * and invoking the parser with a given input.
 */
export declare abstract class BaseLLMOutputParser<T = unknown> extends Runnable<string | BaseMessage, T> {
    /**
     * Parses the result of an LLM call. This method is meant to be
     * implemented by subclasses to define how the output from the LLM should
     * be parsed.
     * @param generations The generations from an LLM call.
     * @param callbacks Optional callbacks.
     * @returns A promise of the parsed output.
     */
    abstract parseResult(generations: Generation[] | ChatGeneration[], callbacks?: Callbacks): Promise<T>;
    /**
     * Parses the result of an LLM call with a given prompt. By default, it
     * simply calls `parseResult`.
     * @param generations The generations from an LLM call.
     * @param _prompt The prompt used in the LLM call.
     * @param callbacks Optional callbacks.
     * @returns A promise of the parsed output.
     */
    parseResultWithPrompt(generations: Generation[] | ChatGeneration[], _prompt: BasePromptValueInterface, callbacks?: Callbacks): Promise<T>;
    protected _baseMessageToString(message: BaseMessage): string;
    protected _baseMessageContentToString(content: MessageContentComplex[]): string;
    /**
     * Calls the parser with a given input and optional configuration options.
     * If the input is a string, it creates a generation with the input as
     * text and calls `parseResult`. If the input is a `BaseMessage`, it
     * creates a generation with the input as a message and the content of the
     * input as text, and then calls `parseResult`.
     * @param input The input to the parser, which can be a string or a `BaseMessage`.
     * @param options Optional configuration options.
     * @returns A promise of the parsed output.
     */
    invoke(input: string | BaseMessage, options?: RunnableConfig): Promise<T>;
}
/**
 * Class to parse the output of an LLM call.
 */
export declare abstract class BaseOutputParser<T = unknown> extends BaseLLMOutputParser<T> {
    parseResult(generations: Generation[] | ChatGeneration[], callbacks?: Callbacks): Promise<T>;
    /**
     * Parse the output of an LLM call.
     *
     * @param text - LLM output to parse.
     * @returns Parsed output.
     */
    abstract parse(text: string, callbacks?: Callbacks): Promise<T>;
    parseWithPrompt(text: string, _prompt: BasePromptValueInterface, callbacks?: Callbacks): Promise<T>;
    /**
     * Return a string describing the format of the output.
     * @returns Format instructions.
     * @param options - Options for formatting instructions.
     * @example
     * ```json
     * {
     *  "foo": "bar"
     * }
     * ```
     */
    abstract getFormatInstructions(options?: FormatInstructionsOptions): string;
    /**
     * Return the string type key uniquely identifying this class of parser
     */
    _type(): string;
}
/**
 * Exception that output parsers should raise to signify a parsing error.
 *
 * This exists to differentiate parsing errors from other code or execution errors
 * that also may arise inside the output parser. OutputParserExceptions will be
 * available to catch and handle in ways to fix the parsing error, while other
 * errors will be raised.
 *
 * @param message - The error that's being re-raised or an error message.
 * @param llmOutput - String model output which is error-ing.
 * @param observation - String explanation of error which can be passed to a
 *     model to try and remediate the issue.
 * @param sendToLLM - Whether to send the observation and llm_output back to an Agent
 *     after an OutputParserException has been raised. This gives the underlying
 *     model driving the agent the context that the previous output was improperly
 *     structured, in the hopes that it will update the output to the correct
 *     format.
 */
export declare class OutputParserException extends Error {
    llmOutput?: string;
    observation?: string;
    sendToLLM: boolean;
    constructor(message: string, llmOutput?: string, observation?: string, sendToLLM?: boolean);
}