import type { OpenAI } from 'openai';
import type { ChatCompletionMessageParam } from 'openai/resources/chat';
import { type LLMAssistanceMessage, type LLMHistoryEntry, type LLMToolResultImage } from '../../LLMService.typedefs';
export declare class LLMAPIEntity {
    static convertAssistanceMessageToCompletion(message: LLMAssistanceMessage): ChatCompletionMessageParam;
    static convertAssistanceHistoryToCompletions(history: LLMAssistanceMessage[]): ChatCompletionMessageParam[];
    /**
     * Replays a restored conversation as Chat Completions messages: a past tool
     * round becomes an assistant message carrying `tool_calls` followed by the
     * `tool`-role results it was answered with, and a context entry becomes a
     * mid-conversation system message. A tool result is emitted with the call it
     * answers, so a result entry contributes no message of its own.
     */
    static convertHistoryToCompletions(options: {
        history: LLMHistoryEntry[];
        modelName: string;
    }): ChatCompletionMessageParam[];
    static buildToolImageMessageParts(images: LLMToolResultImage[]): OpenAI.ChatCompletionContentPart[];
    private static buildToolRoundMessages;
    private static buildToolCall;
    private static buildToolCallMessage;
    private static buildToolResultMessage;
    /**
     * Chat Completions cannot carry images in a `tool`-role message, so images a
     * restored tool result holds are surfaced the way the live loop surfaces
     * them: one user message after the round's results.
     */
    private static buildToolResultImageMessages;
}