import type OpenAI from "openai";
import { ChatCompletionMessage, CompletionRequest } from "../../models/prompt";
import type { Attachment } from "../../types";
import { ILogWriter } from "../types";
import { EvaluatableBaseContainer } from "./base";
/**
 * Represents an error that occurred during LLM generation.
 */
export interface GenerationError {
    message: string;
    code?: string;
    type?: string;
}
/**
 * Represents the result of an LLM chat completion.
 */
export interface ChatCompletionResult {
    id: string;
    object: string;
    created: number;
    model: string;
    choices: Array<ChatCompletionChoice>;
    usage: Usage;
    cost?: Cost;
    error?: GenerationError;
}
/**
 * Represents the result of an LLM text completion.
 */
export interface TextCompletionResult {
    id: string;
    object: string;
    created: number;
    model: string;
    choices: Array<TextCompletionChoice>;
    usage: Usage;
    cost?: Cost;
    error?: GenerationError;
}
export interface Logprobs {
    text_offset?: Array<number>;
    token_logprobs?: Array<number>;
    tokens?: Array<string>;
    top_logprobs?: Array<Record<string, number>>;
}
export interface ChatCompletionChoice {
    index: number;
    message: ChatCompletionMessage;
    logprobs: Logprobs | null;
    finish_reason: string;
}
export interface TextCompletionChoice {
    index: number;
    text: string;
    logprobs: Logprobs | null;
    finish_reason: string;
}
/**
 * Token usage statistics for a generation request.
 */
export interface Usage {
    prompt_tokens: number;
    completion_tokens: number;
    total_tokens: number;
}
/**
 * Cost statistics for a generation request.
 */
export interface Cost {
    input: number;
    output: number;
    total: number;
}
/**
 * Configuration object for generation.
 */
export type GenerationConfig = {
    id: string;
    name?: string;
    provider: "openai" | "bedrock" | "anthropic" | "huggingface" | "azure" | "together" | "groq" | "google" | "elevenlabs";
    model: string;
    maximPromptId?: string;
    maximPromptVersionId?: string;
    messages: (CompletionRequest | ChatCompletionMessage)[];
    modelParameters: Record<string, any>;
    tags?: Record<string, string>;
    /**
     * Optional explicit start timestamp. If not provided, defaults to current time.
     */
    startTimestamp?: Date;
    /**
     * Optional explicit end timestamp. Can be set during creation for completed operations.
     */
    endTimestamp?: Date;
};
/**
 * Represents an LLM generation or completion.
 *
 * The Generation class tracks the complete lifecycle of LLM requests,
 * including input messages, model parameters, results, and any errors.
 * It supports both chat and text completion formats.
 *
 * @class Generation
 * @extends EvaluatableBaseContainer
 * @example
 * const generation = container.generation({
 *   id: 'gen-001',
 *   name: 'User Query Response',
 *   provider: 'openai',
 *   model: 'gpt-4',
 *   messages: [
 *     { role: 'system', content: 'You are a helpful assistant.' },
 *     { role: 'user', content: 'What is the capital of France?' }
 *   ],
 *   modelParameters: { temperature: 0.7, max_tokens: 150 }
 * });
 *
 * // Record the result
 * generation.result({
 *   id: 'cmpl-123',
 *   object: 'chat.completion',
 *   created: Date.now(),
 *   model: 'gpt-4',
 *   choices: [{
 *     index: 0,
 *     message: { role: 'assistant', content: 'The capital of France is Paris.' },
 *     finish_reason: 'stop',
 *     logprobs: null
 *   }],
 *   usage: { prompt_tokens: 25, completion_tokens: 8, total_tokens: 33 }
 * });
 */
export declare class Generation extends EvaluatableBaseContainer {
    private model?;
    private provider?;
    private maximPromptId?;
    private maximPromptVersionId?;
    private modelParameters?;
    /**
     * Creates a new generation log entry.
     *
     * @param config - Configuration object defining the generation
     * @param writer - Log writer instance for persisting generation data
     * @example
     * const generation = container.generation({
     *   id: 'response-gen-001',
     *   name: 'Customer Query Response',
     *   provider: 'openai',
     *   model: 'gpt-4',
     *   messages: [
     *     { role: 'system', content: 'You are a helpful assistant.' },
     *     { role: 'user', content: 'How do I reset my password?' }
     *   ],
     *   modelParameters: { temperature: 0.7, max_tokens: 200 }
     * });
     */
    constructor(config: GenerationConfig, writer: ILogWriter);
    /**
     * Updates the model being used for this generation.
     *
     * @param model - The new model name or identifier
     * @returns void
     * @example
     * generation.setModel('gpt-4-turbo');
     */
    setModel(model: string): void;
    /**
     * Static method to update the model for any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param model - The new model name
     * @returns void
     */
    static setModel_(writer: ILogWriter, id: string, model: string): void;
    /**
     * Updates the name being used for this generation.
     *
     * @param name - The new name
     * @returns void
     * @example
     * generation.setName('Customer Query Response');
     */
    setName(name: string): void;
    /**
     * Static method to update the name for any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param name - The new name
     * @returns void
     */
    static setName_(writer: ILogWriter, id: string, name: string): void;
    /**
     * Adds additional messages to this generation's conversation.
     *
     * @param messages - Array of messages to add
     * @returns void
     * @example
     * generation.addMessages([
     *   { role: 'user', content: 'Can you clarify that?' },
     * ]);
     */
    addMessages(messages: (CompletionRequest | ChatCompletionMessage)[]): void;
    /**
     * Static method to add messages to any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param messages - Array of messages to add
     * @returns void
     */
    static addMessages_(writer: ILogWriter, id: string, messages: (CompletionRequest | ChatCompletionMessage)[]): void;
    /**
     * Updates the model parameters for this generation.
     *
     * @param modelParameters - Object containing model-specific parameters
     * @returns void
     * @example
     * generation.setModelParameters({
     *   temperature: 0.9,
     *   max_tokens: 500,
     *   top_p: 0.95,
     *   frequency_penalty: 0.2
     * });
     */
    setModelParameters(modelParameters: Record<string, any>): void;
    /**
     * Static method to update model parameters for any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param modelParameters - Model parameters to update
     * @returns void
     */
    static setModelParameters_(writer: ILogWriter, id: string, modelParameters: Record<string, any>): void;
    /**
     * Records the successful result of this generation and ends it.
     *
     * @param result - The completion result from the LLM
     * @returns void
     * @example
     * generation.result({
     *   id: 'cmpl-123',
     *   object: 'chat.completion',
     *   created: Date.now(),
     *   model: 'gpt-4',
     *   choices: [{
     *     index: 0,
     *     message: { role: 'assistant', content: 'Here is the answer...' },
     *     finish_reason: 'stop',
     *     logprobs: null
     *   }],
     *   usage: { prompt_tokens: 50, completion_tokens: 25, total_tokens: 75 }
     * });
     */
    result(result: TextCompletionResult | ChatCompletionResult | OpenAI.Responses.Response): void;
    /**
     * Static method to record a result for any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param result - The completion result
     * @returns void
     */
    static result_(writer: ILogWriter, id: string, result: TextCompletionResult | ChatCompletionResult | OpenAI.Responses.Response): void;
    /**
     * Records an error that occurred during this generation.
     *
     * @param error - Error information including message, code, and type
     * @returns void
     * @example
     * generation.error({
     *   message: 'API request timed out',
     *   code: 'TIMEOUT_ERROR',
     *   type: 'NetworkError'
     * });
     */
    error(error: GenerationError): void;
    /**
     * Static method to record an error for any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param error - Error information
     * @returns void
     */
    static error_(writer: ILogWriter, id: string, error: GenerationError): void;
    /**
     * Adds a numeric metric to this generation.
     *
     * Records quantitative values such as generation quality metrics, token accounting,
     * and streaming/throughput characteristics under a named metric. Each call adds
     * or updates a single metric entry.
     *
     * Common examples include: `tokens_in`, `tokens_out`, `output_tokens`, `ttft_ms` (Time To First Token),
     * `tps` (tokens per second), `avg_logprob`.
     *
     * @param name - Name of the metric
     * @param value - Numeric value of the metric (numeric)
     * @returns void
     * @example
     * generation.addMetric('tokens_in', 312);
     * generation.addMetric('tokens_out', 87);
     * generation.addMetric('output_tokens', 87);
     * generation.addMetric('ttft_ms', 180.5);
     * generation.addMetric('tps', 15.8);
     * generation.addMetric('avg_logprob', -0.32);
     */
    addMetric(name: string, value: number): void;
    /**
     * Static method to add a metric to any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param name - Name of the metric
     * @param value - Numeric value of the metric (float/number)
     * @returns void
     */
    static addMetric_(writer: ILogWriter, id: string, name: string, value: number): void;
    /**
     * Adds an attachment to this generation (can be of type `file`, `data`, or `url`).
     *
     * @param attachment - The attachment to add (file, data, or URL)
     * @returns void
     * @example
     * generation.addAttachment({
     *   id: 'input-document',
     *   type: 'file',
     *   path: './uploads/user_document.pdf',
     *   name: 'User Document'
     * });
     */
    addAttachment(attachment: Attachment): void;
    /**
     * Static method to add an attachment to any generation by ID.
     *
     * @param writer - The log writer instance
     * @param id - The generation ID
     * @param attachment - The attachment to add
     * @returns void
     */
    static addAttachment_(writer: ILogWriter, id: string, attachment: Attachment): void;
    /**
     * Returns the complete data representation of this generation.
     *
     * @returns Generation data.
     * @example
     * const genData = generation.data();
     */
    data(): any;
}