import { GoogleGenAI } from '@google/genai';
import { type LLMAssistanceOptions, type LLMAssistanceResult, type LLMAssistanceMessage, type LLMCreateChatOptions, type LLMCreateChatResult, type LLMCreateFileStorageOptions, type LLMCreateFileStorageResult, type LLMInstanceOptions, type LLMModel, LLMProviders, type LLMUploadedFile, type LLMUploadFileOptions, type LLMUploadFileResult, type LLMStructuredResult } from '../../../LLMService.typedefs';
import { type LLMLoggerInterface } from '../../../utilities/logger';
import { type LLMReporterInterface } from '../../../utilities/reporter';
import { LLMAssistanceService } from '../../../services';
import { type LLMSchemaInterface } from '../../../utilities/schema';
export declare class GoogleGenerativeAIAssistanceService<Reporter extends LLMReporterInterface<any> | undefined> extends LLMAssistanceService<LLMProviders.GoogleGenerativeAI, Reporter> {
    private cachedContent;
    private chatSessions;
    private uploadedFiles;
    private uncachedFileStorages;
    private chatInstructions;
    constructor(logger: LLMLoggerInterface | undefined, reporter: Reporter, options?: LLMInstanceOptions[LLMProviders.GoogleGenerativeAI]);
    get instance(): GoogleGenAI;
    uploadFile(fileOptions: LLMUploadFileOptions<Reporter>): Promise<LLMUploadFileResult>;
    getFile(path: string): Promise<LLMUploadedFile | null>;
    deleteFile(fileId: string): Promise<void>;
    createFileStorage(options: LLMCreateFileStorageOptions<LLMProviders.GoogleGenerativeAI, Reporter>): Promise<LLMCreateFileStorageResult>;
    deleteFileStorage(fileStorageId: string): Promise<void>;
    createChat(options: LLMCreateChatOptions<LLMProviders.GoogleGenerativeAI, Reporter>): Promise<LLMCreateChatResult>;
    deleteChat(chatId: string): Promise<void>;
    private getStorageFileParts;
    protected assistInChatText(options: LLMAssistanceOptions<LLMProviders.GoogleGenerativeAI, Reporter>): Promise<LLMAssistanceResult>;
    protected assistInChatStructured(options: LLMAssistanceOptions<LLMProviders.GoogleGenerativeAI, Reporter> & {
        schema: LLMSchemaInterface;
    }): Promise<LLMStructuredResult>;
    private prepareChatMessage;
    private sendStructuredFollowUp;
    /**
     * The conversation one round was sent with: the chat's system instruction,
     * the history the SDK holds for the session, and the parts this round adds.
     * Built before the request goes out so a round that throws traces the same
     * transcript a successful one does.
     */
    private buildRoundConversation;
    /**
     * One round's usage, mapped exactly as the run total is mapped for metrics,
     * so the per-round generations add up to the single metrics point the run
     * still writes.
     */
    private buildUsageMetrics;
    private readonly buildRoundOutcome;
    private extractUsageFromResponse;
    private combineUsage;
    private convertCustomToolsToGoogle;
    private executeGoogleToolLoop;
    /**
     * The visible assistant text a continuing tool-loop round produced, joined
     * from the response's text parts. Thinking parts (`part.thought`) are
     * excluded so only the visible narration channel is surfaced.
     */
    private extractVisibleToolRoundText;
    private executeGoogleFunctionCalls;
    private buildFunctionResponseParts;
    private executeSingleGoogleFunctionCall;
    /**
     * Gemini 3 models accept image bytes inside `functionResponse.parts`. Each
     * image blob carries a unique `displayName` the `response` payload then
     * references via `{ $ref: displayName }`.
     */
    private buildNativeFunctionResponsePart;
    /**
     * Gemini 2.5 models cannot carry images in a function response, so image
     * bytes are appended as sibling user-content parts after every function
     * response in the same message.
     */
    private buildAppendedFunctionResponseParts;
    private buildInlineImageParts;
    private fetchToolImageBlob;
    countTokens(messages: LLMAssistanceMessage[], model: LLMModel<LLMProviders.GoogleGenerativeAI>): Promise<number>;
}