import type { TurboModule } from 'react-native';
export type NativeContextParams = {
    model: string;
    is_model_asset?: boolean;
    embedding?: boolean;
    n_ctx?: number;
    n_batch?: number;
    n_threads?: number;
    n_gpu_layers?: number;
    use_mlock?: boolean;
    use_mmap?: boolean;
    vocab_only?: boolean;
    lora?: string;
    lora_scaled?: number;
    rope_freq_base?: number;
    rope_freq_scale?: number;
};
export type NativeCompletionParams = {
    prompt: string;
    grammar?: string;
    stop?: Array<string>;
    n_threads?: number;
    n_predict?: number;
    n_probs?: number;
    top_k?: number;
    top_p?: number;
    min_p?: number;
    xtc_threshold?: number;
    xtc_probability?: number;
    tfs_z?: number;
    typical_p?: number;
    temperature?: number;
    penalty_last_n?: number;
    penalty_repeat?: number;
    penalty_freq?: number;
    penalty_present?: number;
    mirostat?: number;
    mirostat_tau?: number;
    mirostat_eta?: number;
    penalize_nl?: boolean;
    seed?: number;
    ignore_eos?: boolean;
    logit_bias?: Array<Array<number>>;
    emit_partial_completion: boolean;
};
export type NativeCompletionTokenProbItem = {
    tok_str: string;
    prob: number;
};
export type NativeCompletionTokenProb = {
    content: string;
    probs: Array<NativeCompletionTokenProbItem>;
};
export type NativeCompletionResultTimings = {
    prompt_n: number;
    prompt_ms: number;
    prompt_per_token_ms: number;
    prompt_per_second: number;
    predicted_n: number;
    predicted_ms: number;
    predicted_per_token_ms: number;
    predicted_per_second: number;
};
export type NativeCompletionResult = {
    text: string;
    tokens_predicted: number;
    tokens_evaluated: number;
    truncated: boolean;
    stopped_eos: boolean;
    stopped_word: string;
    stopped_limit: number;
    stopping_word: string;
    tokens_cached: number;
    timings: NativeCompletionResultTimings;
    completion_probabilities?: Array<NativeCompletionTokenProb>;
};
export type NativeTokenizeResult = {
    tokens: Array<number>;
};
export type NativeEmbeddingResult = {
    embedding: Array<number>;
};
export type NativeLlamaContext = {
    contextId: number;
    gpu: boolean;
    reasonNoGPU: string;
    model: Object;
};
export type NativeSessionLoadResult = {
    tokens_loaded: number;
    prompt: string;
};
export type NativeLlamaChatMessage = {
    role: string;
    content: string;
};
export interface Spec extends TurboModule {
    setContextLimit(limit: number): Promise<void>;
    initContext(params: NativeContextParams): Promise<NativeLlamaContext>;
    getFormattedChat(contextId: number, messages: NativeLlamaChatMessage[], chatTemplate?: string): Promise<string>;
    loadSession(contextId: number, filepath: string): Promise<NativeSessionLoadResult>;
    saveSession(contextId: number, filepath: string, size: number): Promise<number>;
    completion(contextId: number, params: NativeCompletionParams): Promise<NativeCompletionResult>;
    stopCompletion(contextId: number): Promise<void>;
    tokenize(contextId: number, text: string): Promise<NativeTokenizeResult>;
    detokenize(contextId: number, tokens: number[]): Promise<string>;
    embedding(contextId: number, text: string): Promise<NativeEmbeddingResult>;
    bench(contextId: number, pp: number, tg: number, pl: number, nr: number): Promise<string>;
    releaseContext(contextId: number): Promise<void>;
    releaseAllContexts(): Promise<void>;
}
declare const _default: Spec;
export default _default;
//# sourceMappingURL=NativeRNLlama.d.ts.map