import { Token } from "../types.js";
import { LlamaNuma } from "./types.js";
export type BindingModule = {
    AddonModel: {
        new (modelPath: string, params: {
            addonExports?: BindingModule;
            gpuLayers?: number;
            vocabOnly?: boolean;
            useMmap?: boolean;
            useDirectIo?: boolean;
            useMlock?: boolean;
            checkTensors?: boolean;
            onLoadProgress?(loadPercentage: number): void;
            hasLoadAbortSignal?: boolean;
            overridesList?: Array<[key: string, value: number | bigint | boolean | string, type: 0 | 1 | undefined]>;
        }): AddonModel;
    };
    AddonModelLora: {
        new (model: AddonModel, filePath: string): AddonModelLora;
    };
    AddonContext: {
        new (model: AddonModel, params: {
            contextSize?: number;
            batchSize?: number;
            sequences?: number;
            flashAttention?: boolean;
            logitsAll?: boolean;
            embeddings?: boolean;
            ranking?: boolean;
            threads?: number;
            performanceTracking?: boolean;
            swaFullCache?: boolean;
        }): AddonContext;
    };
    AddonGrammar: {
        new (grammarPath: string, params?: {
            addonExports?: BindingModule;
            rootRuleName?: string;
        }): AddonGrammar;
    };
    AddonGrammarEvaluationState: {
        new (model: AddonModel, grammar: AddonGrammar): AddonGrammarEvaluationState;
        new (existingState: AddonGrammarEvaluationState): AddonGrammarEvaluationState;
    };
    AddonSampler: {
        new (model: AddonModel): AddonSampler;
        acceptGrammarEvaluationStateToken(grammarEvaluationState: AddonGrammarEvaluationState, token: Token): void;
        canBeNextTokenForGrammarEvaluationState(grammarEvaluationState: AddonGrammarEvaluationState, token: Token): boolean;
    };
    markLoaded(): boolean;
    systemInfo(): string;
    getSupportsGpuOffloading(): boolean;
    getSupportsMmap(): boolean;
    getGpuSupportsMmap(): boolean;
    getSupportsMlock(): boolean;
    getMathCores(): number;
    getBlockSizeForGgmlType(ggmlType: number): number | undefined;
    getTypeSizeForGgmlType(ggmlType: number): number | undefined;
    getGgmlGraphOverheadCustom(size: number, grads: boolean): number;
    getConsts(): {
        ggmlMaxDims: number;
        ggmlTypeF16Size: number;
        ggmlTypeF32Size: number;
        ggmlTensorOverhead: number;
        llamaPosSize: number;
        llamaSeqIdSize: number;
    };
    setLogger(logger: (level: number, message: string) => void): void;
    setLoggerLogLevel(level: number): void;
    getGpuVramInfo(): {
        total: number;
        used: number;
        unifiedSize: number;
    };
    getGpuDeviceInfo(): {
        deviceNames: string[];
    };
    getGpuType(): "cuda" | "vulkan" | "metal" | false | undefined;
    ensureGpuDeviceIsSupported(): void;
    getSwapInfo(): {
        total: number;
        maxSize: number;
        free: number;
    };
    getMemoryInfo(): {
        total: number;
    };
    init(): Promise<void>;
    setNuma(numa?: LlamaNuma): void;
    loadBackends(forceLoadLibrariesSearchPath?: string): void;
    dispose(): Promise<void>;
};
export type AddonModel = {
    init(): Promise<boolean>;
    loadLora(lora: AddonModelLora): Promise<void>;
    abortActiveModelLoad(): void;
    dispose(): Promise<void>;
    tokenize(text: string, specialTokens: boolean): Uint32Array;
    detokenize(tokens: Uint32Array, specialTokens?: boolean): string;
    getTrainContextSize(): number;
    getEmbeddingVectorSize(): number;
    getTotalSize(): number;
    getTotalParameters(): number;
    getModelDescription(): ModelTypeDescription;
    tokenBos(): Token;
    tokenEos(): Token;
    tokenNl(): Token;
    prefixToken(): Token;
    middleToken(): Token;
    suffixToken(): Token;
    eotToken(): Token;
    sepToken(): Token;
    getTokenString(token: number): string;
    getTokenAttributes(token: Token): number;
    isEogToken(token: Token): boolean;
    getVocabularyType(): number;
    shouldPrependBosToken(): boolean;
    shouldAppendEosToken(): boolean;
    getModelSize(): number;
};
export type AddonContext = {
    init(): Promise<boolean>;
    dispose(): Promise<void>;
    getContextSize(): number;
    initBatch(size: number): void;
    addToBatch(sequenceId: number, firstTokenSequenceIndex: number, tokens: Uint32Array, logitIndexes: Uint32Array): Uint32Array;
    decodeBatch(): Promise<void>;
    sampleToken(batchLogitIndex: BatchLogitIndex, sampler: AddonSampler): Promise<Token | -1>;
    sampleToken(batchLogitIndex: BatchLogitIndex, sampler: AddonSampler, probabilities: boolean, confidence?: boolean): Promise<[token: Token | -1, probabilities: (Token | number)[] | undefined, confidence: number | undefined]>;
    disposeSequence(sequenceId: number): void;
    removeTokenCellsFromSequence(sequenceId: number, startPos: number, endPos: number): boolean;
    shiftSequenceTokenCells(sequenceId: number, startPos: number, endPos: number, shiftDelta: number): void;
    getSequenceKvCacheMinPosition(sequenceId: number): number;
    getSequenceKvCacheMaxPosition(sequenceId: number): number;
    getEmbedding(inputTokensLength: number, maxVectorSize?: number): Float64Array;
    getStateSize(): number;
    getThreads(): number;
    setThreads(threads: number): void;
    printTimings(): void;
    ensureDraftContextIsCompatibleForSpeculative(draftContext: AddonContext): void;
    saveSequenceStateToFile(filePath: string, sequenceId: number, tokens: Uint32Array): Promise<number>;
    loadSequenceStateFromFile(filePath: string, sequenceId: number, maxContextSize: number): Promise<Uint32Array>;
    setLoras(loras: AddonModelLora[], scales: number[]): void;
};
export type BatchLogitIndex = number & {
    readonly __batchLogitIndex: never;
};
export type AddonGrammar = {
    isTextCompatible(testText: string): boolean;
};
export type AddonGrammarEvaluationState = "AddonGrammarEvaluationState" & {
    readonly __brand: never;
};
export type AddonSampler = {
    dispose(): void;
    applyConfig(config: {
        temperature?: number;
        minP?: number;
        topK?: number;
        topP?: number;
        seed?: number;
        xtcProbability?: number;
        xtcThreshold?: number;
        repeatPenalty?: number;
        repeatPenaltyMaxTokens?: number;
        repeatPenaltyTokens?: Uint32Array;
        repeatPenaltyPresencePenalty?: number;
        repeatPenaltyFrequencyPenalty?: number;
        dryRepeatPenaltyStrength?: number;
        dryRepeatPenaltyBase?: number;
        dryRepeatPenaltyAllowedLength?: number;
        dryRepeatPenaltyLastTokens?: number;
        dryRepeatPenaltySequenceBreakers?: false | string[];
        grammarEvaluationState?: AddonGrammarEvaluationState;
        tokenBiasKeys?: Uint32Array;
        tokenBiasValues?: Float32Array;
    }): void;
};
export type AddonModelLora = {
    usages: number;
    readonly filePath: string;
    readonly disposed: boolean;
    dispose(): Promise<void>;
};
export type ModelTypeDescription = `${AddonModelArchName} ${AddonModelTypeName} ${AddonModelFileTypeName}`;
export type AddonModelArchName = "unknown" | "llama" | "falcon" | "gpt2" | "gptj" | "gptneox" | "mpt" | "baichuan" | "starcoder" | "persimmon" | "refact" | "bloom" | "stablelm";
export type AddonModelTypeName = "1B" | "3B" | "7B" | "8B" | "13B" | "15B" | "30B" | "34B" | "40B" | "65B" | "70B" | "?B";
export type AddonModelFileTypeName = _AddonModelFileTypeName | `${_AddonModelFileTypeName} (guessed)`;
type _AddonModelFileTypeName = "all F32" | "mostly F16" | "mostly Q4_0" | "mostly Q4_1" | "mostly Q4_1, some F16" | "mostly Q5_0" | "mostly Q5_1" | "mostly Q8_0" | "mostly Q2_K" | "mostly Q3_K - Small" | "mostly Q3_K - Medium" | "mostly Q3_K - Large" | "mostly Q4_K - Small" | "mostly Q4_K - Medium" | "mostly Q5_K - Small" | "mostly Q5_K - Medium" | "mostly Q6_K" | "unknown, may not work";
export {};