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binding of llama.cpp","maintainers":[{"name":"sharcoux","email":"f.billioud@gmail.com"},{"name":"ribeirofmatheus","email":"matheus_f.ribeiro@hotmail.com"},{"name":"matheusrdsantos","email":"matheus.r.d.s10@hotmail.com"},{"name":"gabrielnsd","email":"gabrielnsdantas@gmail.com"},{"name":"felipecantoo","email":"felipe@cantoo.fr"},{"name":"nicodemos234","email":"nicodemos54324@gmail.com"}],"readme":"# capacitor-llama\n\nCapacitor implementation for llama models\n\n## Install\n\n```bash\nnpm i @cantoo/capacitor-llama\nnpx cap sync\n```\n\n## Electron\n\nElectron has no native plugin bridge, so this package ships the two files needed to expose the plugin\nto the renderer: a main process setup that maps the plugin methods to `ipcMain` handlers, and a preload\nscript that turns those handlers back into the Capacitor plugin API on `window.CapacitorCustomPlatform`.\n\nIn your Electron main process:\n\n```js\nconst { BrowserWindow, app } = require('electron')\nconst { setupCapacitorElectronPlugins } = require('@cantoo/capacitor-llama/electron/setupCapacitorPlugins')\n\napp.whenReady().then(() => {\n  new BrowserWindow({\n    webPreferences: {\n      preload: require.resolve('@cantoo/capacitor-llama/electron/preload.js'),\n    },\n  })\n\n  setupCapacitorElectronPlugins()\n})\n```\n\nIf your app already has its own preload script, require this one from it instead of passing it to\n`webPreferences.preload`, since Electron only accepts a single preload script per window:\n\n```js\nrequire('@cantoo/capacitor-llama/electron/preload.js')\n```\n\nThe preload works with `contextIsolation` both enabled (it exposes the api through `contextBridge`)\nand disabled (it assigns it to `window` directly). If you scaffolded your app with\n`@capacitor-community/electron`, this preload replaces the generated `src/rt/electron-rt.ts`, which\ndoes the same job for the plugins listed in `src/rt/electron-plugins.js` — don't run both, since they\nwould try to expose `CapacitorCustomPlatform` twice.\n\n## API\n\n<docgen-index>\n\n* [`initContext(...)`](#initcontext)\n* [`completion(...)`](#completion)\n* [`stopCompletion(...)`](#stopcompletion)\n* [`releaseContext(...)`](#releasecontext)\n* [`releaseAllContexts()`](#releaseallcontexts)\n* [`tokenize(...)`](#tokenize)\n* [`detokenize(...)`](#detokenize)\n* [`getVocab(...)`](#getvocab)\n* [`addListener('onToken', ...)`](#addlistenerontoken-)\n* [`removeAllListeners()`](#removealllisteners)\n* [Interfaces](#interfaces)\n* [Type Aliases](#type-aliases)\n\n</docgen-index>\n\n<docgen-api>\n<!--Update the source file JSDoc comments and rerun docgen to update the docs below-->\n\n### initContext(...)\n\n```typescript\ninitContext(options: ContextParams & { id: number; }) => Promise<NativeLlamaContext>\n```\n\n| Param         | Type                                                                                                                                                                                                                                                                                                                                                                                                                                    |\n| ------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| **`options`** | <code><a href=\"#omit\">Omit</a>&lt;<a href=\"#nativecontextparams\">NativeContextParams</a>, 'cache_type_k' \\| 'cache_type_v' \\| 'pooling_type'&gt; & { 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'; } & { id: number; }</code> |\n\n**Returns:** <code>Promise&lt;<a href=\"#nativellamacontext\">NativeLlamaContext</a>&gt;</code>\n\n--------------------\n\n\n### completion(...)\n\n```typescript\ncompletion(options: { id: number; params: CompletionParams; }) => Promise<NativeCompletionResult>\n```\n\n| Param         | Type                                                                                   |\n| ------------- | -------------------------------------------------------------------------------------- |\n| **`options`** | <code>{ id: number; params: <a href=\"#completionparams\">CompletionParams</a>; }</code> |\n\n**Returns:** <code>Promise&lt;<a href=\"#nativecompletionresult\">NativeCompletionResult</a>&gt;</code>\n\n--------------------\n\n\n### stopCompletion(...)\n\n```typescript\nstopCompletion(options: { id: number; }) => Promise<void>\n```\n\n| Param         | Type                         |\n| ------------- | ---------------------------- |\n| **`options`** | <code>{ id: number; }</code> |\n\n--------------------\n\n\n### releaseContext(...)\n\n```typescript\nreleaseContext(options: { id: number; }) => Promise<void>\n```\n\n| Param         | Type                         |\n| ------------- | ---------------------------- |\n| **`options`** | <code>{ id: number; }</code> |\n\n--------------------\n\n\n### releaseAllContexts()\n\n```typescript\nreleaseAllContexts() => Promise<void>\n```\n\n--------------------\n\n\n### tokenize(...)\n\n```typescript\ntokenize(options: { id: number; text: string; specialTokens?: boolean; }) => Promise<{ tokens: number[]; }>\n```\n\n| Param         | Type                                                                |\n| ------------- | ------------------------------------------------------------------- |\n| **`options`** | <code>{ id: number; text: string; specialTokens?: boolean; }</code> |\n\n**Returns:** <code>Promise&lt;{ tokens: number[]; }&gt;</code>\n\n--------------------\n\n\n### detokenize(...)\n\n```typescript\ndetokenize(options: { id: number; tokens: number[]; }) => Promise<{ text: string; }>\n```\n\n| Param         | Type                                           |\n| ------------- | ---------------------------------------------- |\n| **`options`** | <code>{ id: number; tokens: number[]; }</code> |\n\n**Returns:** <code>Promise&lt;{ text: string; }&gt;</code>\n\n--------------------\n\n\n### getVocab(...)\n\n```typescript\ngetVocab(options: { id: number; }) => Promise<{ vocab: string[]; }>\n```\n\n| Param         | Type                         |\n| ------------- | ---------------------------- |\n| **`options`** | <code>{ id: number; }</code> |\n\n**Returns:** <code>Promise&lt;{ vocab: string[]; }&gt;</code>\n\n--------------------\n\n\n### addListener('onToken', ...)\n\n```typescript\naddListener(eventName: 'onToken', listenerFunc: TokenCallback) => Promise<PluginListenerHandle>\n```\n\n| Param              | Type                                                    |\n| ------------------ | ------------------------------------------------------- |\n| **`eventName`**    | <code>'onToken'</code>                                  |\n| **`listenerFunc`** | <code><a href=\"#tokencallback\">TokenCallback</a></code> |\n\n**Returns:** <code>Promise&lt;<a href=\"#pluginlistenerhandle\">PluginListenerHandle</a>&gt;</code>\n\n--------------------\n\n\n### removeAllListeners()\n\n```typescript\nremoveAllListeners() => Promise<void>\n```\n\nRemoves all listeners\n\n--------------------\n\n\n### Interfaces\n\n\n#### PluginListenerHandle\n\n| Prop         | Type                                      |\n| ------------ | ----------------------------------------- |\n| **`remove`** | <code>() =&gt; Promise&lt;void&gt;</code> |\n\n\n### Type Aliases\n\n\n#### NativeLlamaContext\n\n<code>{ model: { desc: string; size: number; nEmbd: number; nParams: number; nVocab: number; chatTemplates: { llamaChat: boolean; // Chat template in llama-chat.cpp minja: { // Chat template supported by minja.hpp 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: <a href=\"#record\">Record</a>&lt;string, unknown&gt;; isChatTemplateSupported: boolean; // Deprecated }; /** * Loaded library name for Android */ androidLib?: string; gpu: boolean; reasonNoGPU: string; }</code>\n\n\n#### Record\n\nConstruct a type with a set of properties K of type T\n\n<code>{\r [P in K]: T;\r }</code>\n\n\n#### ContextParams\n\n<code><a href=\"#omit\">Omit</a>&lt;<a href=\"#nativecontextparams\">NativeContextParams</a>, 'cache_type_k' | 'cache_type_v' | 'pooling_type'&gt; & { 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'; }</code>\n\n\n#### Omit\n\nConstruct a type with the properties of T except for those in type K.\n\n<code><a href=\"#pick\">Pick</a>&lt;T, <a href=\"#exclude\">Exclude</a>&lt;keyof T, K&gt;&gt;</code>\n\n\n#### Pick\n\nFrom T, pick a set of properties whose keys are in the union K\n\n<code>{\r [P in K]: T[P];\r }</code>\n\n\n#### Exclude\n\n<a href=\"#exclude\">Exclude</a> from T those types that are assignable to U\n\n<code>T extends U ? never : T</code>\n\n\n#### NativeContextParams\n\n<code>{ /** * For **android**, **iOS** and **electron** the `model` is an absolute path. Example: `/path/to/my-model.gguf` * * For **web** the `model` is an url. Example: https://huggingface.co/bartowski/Qwen2.5-0.5B-Instruct-GGUF/resolve/main/Qwen2.5-0.5B-Instruct-Q5_K_S.gguf */ model: string; /** * **Note: This option is available only on web.** * * Controls whether to load the model from the browser cache. * * - If `true` (default), the model manager first tries to load the model from cache. * If it's not cached, it will download the model and cache it for future use. * * - If `false`, the model will always be downloaded, ignoring any cached versions. */ readFromCache?: boolean; /** * Chat template to override the default one from the model. */ chat_template?: string; reasoning_format?: 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?: { path: string; scaled?: number }[]; rope_freq_base?: number; rope_freq_scale?: number; pooling_type?: number; // Embedding params embedding?: boolean; embd_normalize?: number; }</code>\n\n\n#### NativeCompletionResult\n\n<code>{ /** * Original text (Ignored reasoning_content / tool_calls) */ text: string; /** * Reasoning content (parsed for reasoning model) */ reasoning_content: string; /** * Content text (Filtered text by reasoning_content / tool_calls) */ content: string; completion_probabilities?: NativeCompletionTokenProb[]; }</code>\n\n\n#### NativeCompletionTokenProb\n\n<code>{ content: string; probs: NativeCompletionTokenProbItem[]; }</code>\n\n\n#### NativeCompletionTokenProbItem\n\n<code>{ tok_str: string; prob: number; }</code>\n\n\n#### CompletionParams\n\n<code><a href=\"#omit\">Omit</a>&lt;<a href=\"#nativecompletionparams\">NativeCompletionParams</a>, 'prompt'&gt; & <a href=\"#completionbaseparams\">CompletionBaseParams</a></code>\n\n\n#### NativeCompletionParams\n\n<code>{ prompt: string; n_threads?: number; /** * 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; /** * Lazy grammar triggers. Default: [] */ grammar_triggers?: { type: number; value: string; token: number; }[]; preserved_tokens?: string[]; chat_format?: number; /** * 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?: 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 &lt; 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` (&gt; `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?: 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?: [number, number | false][]; /** * Set the random number generator (RNG) seed. Default: `-1`, which is a random seed. */ seed?: number; emit_partial_completion: boolean; }</code>\n\n\n#### CompletionBaseParams\n\n<code>{ prompt?: string; messages?: LlamaOAICompatibleMessage[]; chat_template?: string; jinja?: boolean; tools?: <a href=\"#record\">Record</a>&lt;string, unknown&gt;; parallel_tool_calls?: <a href=\"#record\">Record</a>&lt;string, unknown&gt;; tool_choice?: string; response_format?: <a href=\"#completionresponseformat\">CompletionResponseFormat</a>; }</code>\n\n\n#### LlamaOAICompatibleMessage\n\n<code>{ role: 'user' | 'system' | 'assistant'; content?: string; }</code>\n\n\n#### CompletionResponseFormat\n\n<code>{ type: 'text' | 'json_object' | 'json_schema'; json_schema?: { strict?: boolean; schema: object; }; schema?: object; // for json_object type }</code>\n\n\n#### TokenCallback\n\n<code>(event: <a href=\"#tokenevent\">TokenEvent</a>): void</code>\n\n\n#### TokenEvent\n\n<code>{ contextId: number; tokenResult: <a href=\"#tokendata\">TokenData</a>; }</code>\n\n\n#### TokenData\n\n<code>{ token: string; completion_probabilities?: NativeCompletionTokenProb[]; }</code>\n\n</docgen-api>\n","readmeFilename":"README.md"}