cui-llama.rn/lib/typescript/NativeRNLlama.d.ts

Fork of llama.rn for ChatterUI

import type { TurboModule } from 'react-native';
export type NativeEmbeddingParams = {
    embd_normalize?: number;
};
export type 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;
    /**
     * 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;
    embedding?: boolean;
    embd_normalize?: number;
};
export type 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.  Default: no grammar
     */
    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 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 = {
    /**
     * Original text (Ignored reasoning_content / tool_calls)
     */
    text: string;
    /**
     * Reasoning content (parsed for reasoning model)
     */
    reasoning_content: string;
    /**
     * Tool calls
     */
    tool_calls: Array<{
        type: 'function';
        function: {
            name: string;
            arguments: string;
        };
        id?: string;
    }>;
    /**
     * Content text (Filtered text by reasoning_content / tool_calls)
     */
    content: 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>;
    audio_tokens?: Array<number>;
};
export type 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 type NativeEmbeddingResult = {
    embedding: Array<number>;
};
export type 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 type NativeSessionLoadResult = {
    tokens_loaded: number;
    prompt: string;
};
export type NativeLlamaMessagePart = {
    type: 'text';
    text: string;
};
export type NativeLlamaChatMessage = {
    role: string;
    content: string | Array<NativeLlamaMessagePart>;
};
export type NativeCPUFeatures = {
    armv8: boolean;
    i8mm: boolean;
    dotprod: boolean;
};
export type FormattedChatResult = {
    type: 'jinja' | 'llama-chat';
    prompt: string;
    has_media: boolean;
    media_paths?: Array<string>;
};
export type JinjaFormattedChatResult = 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 type NativeImageProcessingResult = {
    success: boolean;
    prompt: string;
    error?: string;
};
export type NativeRerankParams = {
    normalize?: number;
};
export type NativeRerankResult = {
    score: number;
    index: number;
};
export interface Spec extends TurboModule {
    toggleNativeLog(enabled: boolean): Promise<void>;
    setContextLimit(limit: number): Promise<void>;
    modelInfo(path: string, skip?: string[]): Promise<Object>;
    initContext(contextId: number, params: NativeContextParams): Promise<NativeLlamaContext>;
    getFormattedChat(contextId: number, messages: string, chatTemplate?: string, params?: {
        jinja?: boolean;
        json_schema?: string;
        tools?: string;
        parallel_tool_calls?: string;
        tool_choice?: string;
        enable_thinking?: boolean;
    }): Promise<JinjaFormattedChatResult | 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>;
    tokenizeAsync(contextId: number, text: string, imagePaths?: Array<string>): Promise<NativeTokenizeResult>;
    tokenizeSync(contextId: number, text: string, imagePaths?: Array<string>): NativeTokenizeResult;
    getCpuFeatures(): Promise<NativeCPUFeatures>;
    detokenize(contextId: number, tokens: number[]): Promise<string>;
    embedding(contextId: number, text: string, params: NativeEmbeddingParams): Promise<NativeEmbeddingResult>;
    rerank(contextId: number, query: string, documents: Array<string>, params?: NativeRerankParams): Promise<Array<NativeRerankResult>>;
    bench(contextId: number, pp: number, tg: number, pl: number, nr: number): Promise<string>;
    applyLoraAdapters(contextId: number, loraAdapters: Array<{
        path: string;
        scaled?: number;
    }>): Promise<void>;
    removeLoraAdapters(contextId: number): Promise<void>;
    getLoadedLoraAdapters(contextId: number): Promise<Array<{
        path: string;
        scaled?: number;
    }>>;
    initMultimodal(contextId: number, params: {
        path: string;
        use_gpu: boolean;
    }): Promise<boolean>;
    isMultimodalEnabled(contextId: number): Promise<boolean>;
    getMultimodalSupport(contextId: number): Promise<{
        vision: boolean;
        audio: boolean;
    }>;
    releaseMultimodal(contextId: number): Promise<void>;
    initVocoder(contextId: number, vocoderModelPath: string): Promise<boolean>;
    isVocoderEnabled(contextId: number): Promise<boolean>;
    getFormattedAudioCompletion(contextId: number, speakerJsonStr: string, textToSpeak: string): Promise<string>;
    getAudioCompletionGuideTokens(contextId: number, textToSpeak: string): Promise<Array<number>>;
    decodeAudioTokens(contextId: number, tokens: number[]): Promise<Array<number>>;
    releaseVocoder(contextId: number): Promise<void>;
    releaseContext(contextId: number): Promise<void>;
    releaseAllContexts(): Promise<void>;
}
declare const _default: Spec;
export default _default;
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