export interface NativeEmbeddingParams {
    embd_normalize?: number;
}
export interface NativeContextParams {
    model: string;
    /**
     * Chat template to override the default one from the model.
     */
    chat_template?: string;
    is_model_asset?: boolean;
    use_progress_callback?: boolean;
    n_ctx?: number;
    n_batch?: number;
    n_ubatch?: number;
    n_threads?: number;
    /**
     * Path to draft model for speculative decoding (mobile optimization)
     */
    draft_model?: string;
    /**
     * Number of tokens to predict speculatively (default: 3 for mobile)
     */
    speculative_samples?: number;
    /**
     * Enable mobile-optimized speculative decoding
     */
    mobile_speculative?: boolean;
    /**
     * Number of layers to store in VRAM (Currently only for iOS)
     */
    n_gpu_layers?: number;
    /**
     * Skip GPU devices (iOS only)
     */
    no_gpu_devices?: boolean;
    /**
     * Enable flash attention, only recommended in GPU device (Experimental in llama.cpp)
     */
    flash_attn?: boolean;
    /**
     * KV cache data type for the K (Experimental in llama.cpp)
     */
    cache_type_k?: string;
    /**
     * KV cache data type for the V (Experimental in llama.cpp)
     */
    cache_type_v?: string;
    use_mlock?: boolean;
    use_mmap?: boolean;
    vocab_only?: boolean;
    /**
     * Single LoRA adapter path
     */
    lora?: string;
    /**
     * Single LoRA adapter scale
     */
    lora_scaled?: number;
    /**
     * LoRA adapter list
     */
    lora_list?: Array<{
        path: string;
        scaled?: number;
    }>;
    rope_freq_base?: number;
    rope_freq_scale?: number;
    pooling_type?: number;
    /**
     * Enable context shifting to handle prompts larger than context size
     */
    ctx_shift?: boolean;
    /**
     * Use a unified buffer across the input sequences when computing the attention.
     * Try to disable when n_seq_max > 1 for improved performance when the sequences do not share a large prefix.
     */
    kv_unified?: boolean;
    /**
     * Use full-size SWA cache (https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055)
     */
    swa_full?: boolean;
    /**
     * Number of layers to keep MoE weights on CPU
     */
    n_cpu_moe?: number;
    embedding?: boolean;
    embd_normalize?: number;
}
export interface NativeCompletionParams {
    prompt: string;
    n_threads?: number;
    /**
     * Enable Jinja. Default: true if supported by the model
     */
    jinja?: boolean;
    /**
     * JSON schema for convert to grammar for structured JSON output.
     * It will be override by grammar if both are set.
     */
    json_schema?: string;
    /**
     * Set grammar for grammar-based sampling (GBNF format). Default: no grammar
     * This will override json_schema if both are provided.
     */
    grammar?: string;
    /**
     * Lazy grammar sampling, trigger by grammar_triggers. Default: false
     */
    grammar_lazy?: boolean;
    /**
     * Enable thinking if jinja is enabled. Default: true
     */
    enable_thinking?: boolean;
    /**
     * Force thinking to be open. Default: false
     */
    thinking_forced_open?: boolean;
    /**
     * Lazy grammar triggers. Default: []
     */
    grammar_triggers?: Array<{
        type: number;
        value: string;
        token: number;
    }>;
    preserved_tokens?: Array<string>;
    chat_format?: number;
    reasoning_format?: string;
    /**
     * Path to an image file to process before generating text.
     * When provided, the image will be processed and added to the context.
     * Requires multimodal support to be enabled via initMultimodal.
     */
    media_paths?: Array<string>;
    /**
     * Specify a JSON array of stopping strings.
     * These words will not be included in the completion, so make sure to add them to the prompt for the next iteration. Default: `[]`
     */
    stop?: Array<string>;
    /**
     * Set the maximum number of tokens to predict when generating text.
     * **Note:** May exceed the set limit slightly if the last token is a partial multibyte character.
     * When 0,no tokens will be generated but the prompt is evaluated into the cache. Default: `-1`, where `-1` is infinity.
     */
    n_predict?: number;
    /**
     * If greater than 0, the response also contains the probabilities of top N tokens for each generated token given the sampling settings.
     * Note that for temperature < 0 the tokens are sampled greedily but token probabilities are still being calculated via a simple softmax of the logits without considering any other sampler settings.
     * Default: `0`
     */
    n_probs?: number;
    /**
     * Limit the next token selection to the K most probable tokens.  Default: `40`
     */
    top_k?: number;
    /**
     * Limit the next token selection to a subset of tokens with a cumulative probability above a threshold P. Default: `0.95`
     */
    top_p?: number;
    /**
     * The minimum probability for a token to be considered, relative to the probability of the most likely token. Default: `0.05`
     */
    min_p?: number;
    /**
     * Set the chance for token removal via XTC sampler. Default: `0.0`, which is disabled.
     */
    xtc_probability?: number;
    /**
     * Set a minimum probability threshold for tokens to be removed via XTC sampler. Default: `0.1` (> `0.5` disables XTC)
     */
    xtc_threshold?: number;
    /**
     * Enable locally typical sampling with parameter p. Default: `1.0`, which is disabled.
     */
    typical_p?: number;
    /**
     * Adjust the randomness of the generated text. Default: `0.8`
     */
    temperature?: number;
    /**
     * Last n tokens to consider for penalizing repetition. Default: `64`, where `0` is disabled and `-1` is ctx-size.
     */
    penalty_last_n?: number;
    /**
     * Control the repetition of token sequences in the generated text. Default: `1.0`
     */
    penalty_repeat?: number;
    /**
     * Repeat alpha frequency penalty. Default: `0.0`, which is disabled.
     */
    penalty_freq?: number;
    /**
     * Repeat alpha presence penalty. Default: `0.0`, which is disabled.
     */
    penalty_present?: number;
    /**
     * Enable Mirostat sampling, controlling perplexity during text generation. Default: `0`, where `0` is disabled, `1` is Mirostat, and `2` is Mirostat 2.0.
     */
    mirostat?: number;
    /**
     * Set the Mirostat target entropy, parameter tau. Default: `5.0`
     */
    mirostat_tau?: number;
    /**
     * Set the Mirostat learning rate, parameter eta. Default: `0.1`
     */
    mirostat_eta?: number;
    /**
     * Set the DRY (Don't Repeat Yourself) repetition penalty multiplier. Default: `0.0`, which is disabled.
     */
    dry_multiplier?: number;
    /**
     * Set the DRY repetition penalty base value. Default: `1.75`
     */
    dry_base?: number;
    /**
     * Tokens that extend repetition beyond this receive exponentially increasing penalty: multiplier * base ^ (length of repeating sequence before token - allowed length). Default: `2`
     */
    dry_allowed_length?: number;
    /**
     * How many tokens to scan for repetitions. Default: `-1`, where `0` is disabled and `-1` is context size.
     */
    dry_penalty_last_n?: number;
    /**
     * Specify an array of sequence breakers for DRY sampling. Only a JSON array of strings is accepted. Default: `['\n', ':', '"', '*']`
     */
    dry_sequence_breakers?: Array<string>;
    /**
     * Top n sigma sampling as described in academic paper "Top-nσ: Not All Logits Are You Need" https://arxiv.org/pdf/2411.07641. Default: `-1.0` (Disabled)
     */
    top_n_sigma?: number;
    /**
     * Ignore end of stream token and continue generating. Default: `false`
     */
    ignore_eos?: boolean;
    /**
     * Modify the likelihood of a token appearing in the generated text completion.
     * For example, use `"logit_bias": [[15043,1.0]]` to increase the likelihood of the token 'Hello', or `"logit_bias": [[15043,-1.0]]` to decrease its likelihood.
     * Setting the value to false, `"logit_bias": [[15043,false]]` ensures that the token `Hello` is never produced. The tokens can also be represented as strings,
     * e.g.`[["Hello, World!",-0.5]]` will reduce the likelihood of all the individual tokens that represent the string `Hello, World!`, just like the `presence_penalty` does.
     * Default: `[]`
     */
    logit_bias?: Array<Array<number>>;
    /**
     * Set the random number generator (RNG) seed. Default: `-1`, which is a random seed.
     */
    seed?: number;
    /**
     * Guide tokens for the completion.
     * Help prevent hallucinations by forcing the TTS to use the correct words.
     * Default: `[]`
     */
    guide_tokens?: Array<number>;
    emit_partial_completion: boolean;
}
export interface NativeCompletionTokenProbItem {
    tok_str: string;
    prob: number;
}
export interface NativeCompletionTokenProb {
    content: string;
    probs: Array<NativeCompletionTokenProbItem>;
}
export interface 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 interface NativeCompletionResult {
    /**
     * Original text (Ignored reasoning_content / tool_calls)
     */
    text: string;
    /**
     * Reasoning content (parsed for reasoning model)
     */
    reasoning_content: string;
    /**
     * Tool calls (parsed from response)
     */
    tool_calls: Array<{
        type: 'function';
        function: {
            name: string;
            arguments: string;
        };
        id?: string;
    }>;
    /**
     * Content text (Filtered text by reasoning_content / tool_calls)
     */
    content: string;
    chat_format: number;
    tokens_predicted: number;
    tokens_evaluated: number;
    truncated: boolean;
    stopped_eos: boolean;
    stopped_word: string;
    stopped_limit: number;
    stopping_word: string;
    context_full: boolean;
    interrupted: boolean;
    tokens_cached: number;
    timings: NativeCompletionResultTimings;
    completion_probabilities?: Array<NativeCompletionTokenProb>;
    audio_tokens?: Array<number>;
}
export interface NativeTokenizeResult {
    tokens: Array<number>;
    /**
     * Whether the tokenization contains images
     */
    has_images: boolean;
    /**
     * Bitmap hashes of the images
     */
    bitmap_hashes: Array<number>;
    /**
     * Chunk positions of the text and images
     */
    chunk_pos: Array<number>;
    /**
     * Chunk positions of the images
     */
    chunk_pos_images: Array<number>;
}
export interface NativeEmbeddingResult {
    embedding: Array<number>;
}
export interface NativeLlamaContext {
    contextId: number;
    model: {
        desc: string;
        size: number;
        nEmbd: number;
        nParams: number;
        chatTemplates: {
            llamaChat: boolean;
            minja: {
                default: boolean;
                defaultCaps: {
                    tools: boolean;
                    toolCalls: boolean;
                    toolResponses: boolean;
                    systemRole: boolean;
                    parallelToolCalls: boolean;
                    toolCallId: boolean;
                };
                toolUse: boolean;
                toolUseCaps: {
                    tools: boolean;
                    toolCalls: boolean;
                    toolResponses: boolean;
                    systemRole: boolean;
                    parallelToolCalls: boolean;
                    toolCallId: boolean;
                };
            };
        };
        metadata: Object;
        isChatTemplateSupported: boolean;
    };
    /**
     * Loaded library name for Android
     */
    androidLib?: string;
    gpu: boolean;
    reasonNoGPU: string;
}
export interface NativeSessionLoadResult {
    tokens_loaded: number;
    prompt: string;
}
export interface NativeLlamaMessagePart {
    type: 'text';
    text: string;
}
export interface NativeLlamaChatMessage {
    role: string;
    content: string | Array<NativeLlamaMessagePart>;
}
export interface FormattedChatResult {
    type: 'jinja' | 'llama-chat';
    prompt: string;
    has_media: boolean;
    media_paths?: Array<string>;
}
export interface JinjaFormattedChatResult extends FormattedChatResult {
    chat_format?: number;
    grammar?: string;
    grammar_lazy?: boolean;
    grammar_triggers?: Array<{
        type: number;
        value: string;
        token: number;
    }>;
    thinking_forced_open?: boolean;
    preserved_tokens?: Array<string>;
    additional_stops?: Array<string>;
}
export interface NativeImageProcessingResult {
    success: boolean;
    prompt: string;
    error?: string;
}
export interface NativeRerankParams {
    normalize?: number;
}
export interface NativeRerankResult {
    score: number;
    index: number;
}
export interface LlamaCppMessagePart {
    type: string;
    text?: string;
    image_url?: {
        url?: string;
    };
    input_audio?: {
        format: string;
        data?: string;
        url?: string;
    };
}
export interface LlamaCppOAICompatibleMessage {
    role: string;
    content?: string | LlamaCppMessagePart[];
}
export interface ToolCall {
    type: 'function';
    id?: string;
    function: {
        name: string;
        arguments: string;
    };
}
export interface TokenData {
    token: string;
    completion_probabilities?: Array<NativeCompletionTokenProb>;
    content?: string;
    reasoning_content?: string;
    tool_calls?: Array<ToolCall>;
    accumulated_text?: string;
}
export interface ContextParams extends Omit<NativeContextParams, 'cache_type_k' | 'cache_type_v' | 'pooling_type'> {
    cache_type_k?: 'f16' | 'f32' | 'q8_0' | 'q4_0' | 'q4_1' | 'iq4_nl' | 'q5_0' | 'q5_1';
    cache_type_v?: 'f16' | 'f32' | 'q8_0' | 'q4_0' | 'q4_1' | 'iq4_nl' | 'q5_0' | 'q5_1';
    pooling_type?: 'none' | 'mean' | 'cls' | 'last' | 'rank';
}
export interface EmbeddingParams extends NativeEmbeddingParams {
}
export interface RerankParams {
    normalize?: number;
}
export interface RerankResult {
    score: number;
    index: number;
    document?: string;
}
export interface CompletionResponseFormat {
    type: 'text' | 'json_object' | 'json_schema';
    json_schema?: {
        strict?: boolean;
        schema: object;
    };
    schema?: object;
}
export interface CompletionBaseParams {
    prompt?: string;
    messages?: LlamaCppOAICompatibleMessage[];
    chatTemplate?: string;
    chat_template?: string;
    jinja?: boolean;
    tools?: object;
    parallel_tool_calls?: object;
    tool_choice?: string;
    response_format?: CompletionResponseFormat;
    media_paths?: string[];
    add_generation_prompt?: boolean;
    now?: string | number;
    chat_template_kwargs?: Record<string, string>;
    /**
     * Prefill text to be used for chat parsing (Generation Prompt + Content)
     * Used for if last assistant message is for prefill purpose
     */
    prefill_text?: string;
}
export interface CompletionParams extends Omit<NativeCompletionParams, 'emit_partial_completion' | 'prompt'> {
    prompt?: string;
    messages?: LlamaCppOAICompatibleMessage[];
    chatTemplate?: string;
    chat_template?: string;
    jinja?: boolean;
    /**
     * GBNF grammar for structured output. Takes precedence over json_schema.
     */
    grammar?: string;
    tools?: object;
    parallel_tool_calls?: object;
    tool_choice?: string;
    response_format?: CompletionResponseFormat;
    media_paths?: string[];
    add_generation_prompt?: boolean;
    now?: string | number;
    chat_template_kwargs?: Record<string, string>;
    /**
     * Prefill text to be used for chat parsing (Generation Prompt + Content)
     * Used for if last assistant message is for prefill purpose
     */
    prefill_text?: string;
}
export interface BenchResult {
    modelDesc: string;
    modelSize: number;
    modelNParams: number;
    ppAvg: number;
    ppStd: number;
    tgAvg: number;
    tgStd: number;
}
export interface LlamaCppPlugin {
    toggleNativeLog(options: {
        enabled: boolean;
    }): Promise<void>;
    setContextLimit(options: {
        limit: number;
    }): Promise<void>;
    modelInfo(options: {
        path: string;
        skip?: string[];
    }): Promise<Object>;
    initContext(options: {
        contextId: number;
        params: NativeContextParams;
    }): Promise<NativeLlamaContext>;
    releaseContext(options: {
        contextId: number;
    }): Promise<void>;
    releaseAllContexts(): Promise<void>;
    getFormattedChat(options: {
        contextId: number;
        messages: string;
        chatTemplate?: string;
        params?: {
            jinja?: boolean;
            json_schema?: string;
            tools?: string;
            parallel_tool_calls?: string;
            tool_choice?: string;
            enable_thinking?: boolean;
            add_generation_prompt?: boolean;
            now?: string;
            chat_template_kwargs?: string;
        };
    }): Promise<JinjaFormattedChatResult | string>;
    completion(options: {
        contextId: number;
        params: NativeCompletionParams;
    }): Promise<NativeCompletionResult>;
    chat(options: {
        contextId: number;
        messages: LlamaCppOAICompatibleMessage[];
        system?: string;
        chatTemplate?: string;
        params?: Omit<NativeCompletionParams, 'prompt' | 'messages'>;
    }): Promise<NativeCompletionResult>;
    chatWithSystem(options: {
        contextId: number;
        system: string;
        message: string;
        params?: Omit<NativeCompletionParams, 'prompt' | 'messages'>;
    }): Promise<NativeCompletionResult>;
    generateText(options: {
        contextId: number;
        prompt: string;
        params?: Omit<NativeCompletionParams, 'prompt' | 'messages'>;
    }): Promise<NativeCompletionResult>;
    stopCompletion(options: {
        contextId: number;
    }): Promise<void>;
    loadSession(options: {
        contextId: number;
        filepath: string;
    }): Promise<NativeSessionLoadResult>;
    saveSession(options: {
        contextId: number;
        filepath: string;
        size: number;
    }): Promise<number>;
    tokenize(options: {
        contextId: number;
        text: string;
        imagePaths?: Array<string>;
    }): Promise<NativeTokenizeResult>;
    detokenize(options: {
        contextId: number;
        tokens: number[];
    }): Promise<string>;
    embedding(options: {
        contextId: number;
        text: string;
        params: NativeEmbeddingParams;
    }): Promise<NativeEmbeddingResult>;
    rerank(options: {
        contextId: number;
        query: string;
        documents: Array<string>;
        params?: NativeRerankParams;
    }): Promise<Array<NativeRerankResult>>;
    bench(options: {
        contextId: number;
        pp: number;
        tg: number;
        pl: number;
        nr: number;
    }): Promise<string>;
    applyLoraAdapters(options: {
        contextId: number;
        loraAdapters: Array<{
            path: string;
            scaled?: number;
        }>;
    }): Promise<void>;
    removeLoraAdapters(options: {
        contextId: number;
    }): Promise<void>;
    getLoadedLoraAdapters(options: {
        contextId: number;
    }): Promise<Array<{
        path: string;
        scaled?: number;
    }>>;
    initMultimodal(options: {
        contextId: number;
        params: {
            path: string;
            use_gpu: boolean;
        };
    }): Promise<boolean>;
    isMultimodalEnabled(options: {
        contextId: number;
    }): Promise<boolean>;
    getMultimodalSupport(options: {
        contextId: number;
    }): Promise<{
        vision: boolean;
        audio: boolean;
    }>;
    releaseMultimodal(options: {
        contextId: number;
    }): Promise<void>;
    initVocoder(options: {
        contextId: number;
        params: {
            path: string;
            n_batch?: number;
        };
    }): Promise<boolean>;
    isVocoderEnabled(options: {
        contextId: number;
    }): Promise<boolean>;
    getFormattedAudioCompletion(options: {
        contextId: number;
        speakerJsonStr: string;
        textToSpeak: string;
    }): Promise<{
        prompt: string;
        grammar?: string;
    }>;
    getAudioCompletionGuideTokens(options: {
        contextId: number;
        textToSpeak: string;
    }): Promise<Array<number>>;
    decodeAudioTokens(options: {
        contextId: number;
        tokens: number[];
    }): Promise<Array<number>>;
    releaseVocoder(options: {
        contextId: number;
    }): Promise<void>;
    downloadModel(options: {
        url: string;
        filename: string;
    }): Promise<string>;
    getDownloadProgress(options: {
        url: string;
    }): Promise<{
        progress: number;
        completed: boolean;
        failed: boolean;
        errorMessage?: string;
        localPath?: string;
        downloadedBytes: number;
        totalBytes: number;
    }>;
    cancelDownload(options: {
        url: string;
    }): Promise<boolean>;
    getAvailableModels(): Promise<Array<{
        name: string;
        path: string;
        size: number;
    }>>;
    convertJsonSchemaToGrammar(options: {
        schema: string;
    }): Promise<string>;
    addListener(eventName: string, listenerFunc: (data: any) => void): Promise<void>;
    removeAllListeners(eventName: string): Promise<void>;
}