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node_modules/node-llama-cpp/dist/evaluator/LlamaCompletion.d.ts
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186
node_modules/node-llama-cpp/dist/evaluator/LlamaCompletion.d.ts
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import { EventRelay } from "lifecycle-utils";
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import { LLamaContextualRepeatPenalty, Token } from "../types.js";
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import { LlamaText } from "../utils/LlamaText.js";
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import { LlamaGrammar } from "./LlamaGrammar.js";
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import { EvaluationPriority } from "./LlamaContext/types.js";
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import { LlamaContextSequence } from "./LlamaContext/LlamaContext.js";
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import { TokenBias } from "./TokenBias.js";
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export type LlamaCompletionOptions = {
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contextSequence: LlamaContextSequence;
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/**
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* Automatically dispose the sequence when the object is disposed.
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*
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* Defaults to `false`.
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*/
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autoDisposeSequence?: boolean;
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};
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export type LlamaCompletionGenerationOptions = {
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/**
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* Called as the model generates a completion with the generated text chunk.
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*
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* Useful for streaming the generated completion as it's being generated.
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*/
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onTextChunk?: (text: string) => void;
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/**
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* Called as the model generates a completion with the generated tokens.
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*
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* Preferably, you'd want to use `onTextChunk` instead of this.
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*/
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onToken?: (tokens: Token[]) => void;
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/**
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* An AbortSignal to later abort the generation.
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*
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* When the signal is aborted, the generation will stop and throw `signal.reason` as the error.
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*
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* > To stop an ongoing generation without throwing an error, also set `stopOnAbortSignal` to `true`.
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*/
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signal?: AbortSignal;
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/**
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* When a completion already started being generated and then the signal is aborted,
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* the generation will stop and the completion will be returned as is instead of throwing an error.
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*
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* Defaults to `false`.
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*/
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stopOnAbortSignal?: boolean;
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/** Maximum number of tokens to generate */
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maxTokens?: number;
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/**
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* Temperature is a hyperparameter that controls the randomness of the generated text.
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* It affects the probability distribution of the model's output tokens.
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*
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* A higher temperature (e.g., 1.5) makes the output more random and creative,
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* while a lower temperature (e.g., 0.5) makes the output more focused, deterministic, and conservative.
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*
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* The suggested temperature is 0.8, which provides a balance between randomness and determinism.
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*
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* At the extreme, a temperature of 0 will always pick the most likely next token, leading to identical outputs in each run.
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*
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* Set to `0` to disable.
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* Disabled by default (set to `0`).
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*/
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temperature?: number;
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/**
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* From the next token candidates, discard the percentage of tokens with the lowest probability.
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* For example, if set to `0.05`, 5% of the lowest probability tokens will be discarded.
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* This is useful for generating more high-quality results when using a high temperature.
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* Set to a value between `0` and `1` to enable.
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*
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* Only relevant when `temperature` is set to a value greater than `0`.
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* Disabled by default.
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*/
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minP?: number;
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/**
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* Limits the model to consider only the K most likely next tokens for sampling at each step of sequence generation.
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* An integer number between `1` and the size of the vocabulary.
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* Set to `0` to disable (which uses the full vocabulary).
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*
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* Only relevant when `temperature` is set to a value greater than 0.
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*/
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topK?: number;
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/**
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* Dynamically selects the smallest set of tokens whose cumulative probability exceeds the threshold P,
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* and samples the next token only from this set.
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* A float number between `0` and `1`.
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* Set to `1` to disable.
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*
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* Only relevant when `temperature` is set to a value greater than `0`.
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*/
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topP?: number;
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/**
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* Used to control the randomness of the generated text.
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*
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* Change the seed to get different results.
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*
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* Only relevant when using `temperature`.
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*/
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seed?: number;
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/**
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* Trim whitespace from the end of the generated text
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* Disabled by default.
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*/
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trimWhitespaceSuffix?: boolean;
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repeatPenalty?: false | LLamaContextualRepeatPenalty;
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/**
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* Adjust the probability of tokens being generated.
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* Can be used to bias the model to generate tokens that you want it to lean towards,
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* or to avoid generating tokens that you want it to avoid.
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*/
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tokenBias?: TokenBias | (() => TokenBias);
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/**
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* See the parameter `evaluationPriority` on the `LlamaContextSequence.evaluate()` function for more information.
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*/
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evaluationPriority?: EvaluationPriority;
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grammar?: LlamaGrammar;
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/**
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* Custom stop triggers to stop the completion when any of the provided triggers are found.
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*/
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customStopTriggers?: readonly (LlamaText | string | readonly (string | Token)[])[];
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/**
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* The number of tokens to delete from the context window to make space for new ones.
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* Defaults to 10% of the context size.
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*/
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contextShiftSize?: number | ((sequence: LlamaContextSequence) => number | Promise<number>);
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/**
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* Context shift reconstructs the context with partial relevant data to continue generation when the context fills up.
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* This flag disables this behavior.
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* This flag will cause the generation to stop when the context fills up
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* by setting an appropriate `maxTokens` value or lowering the given `maxTokens` value when needed.
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* This flag will cause the generation to fail if there's no space for generating new tokens at all with the given inputs.
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*
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* Disabled by default. Not recommended unless you know what you're doing.
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*/
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disableContextShift?: boolean;
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};
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export type LlamaInfillGenerationOptions = LlamaCompletionGenerationOptions & {
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/**
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* The minimum number of tokens to keep from the prefix input when making a context shift.
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* Defaults to 10% of the context size.
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*/
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minPrefixKeepTokens?: number | ((sequence: LlamaContextSequence) => number | Promise<number>);
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};
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export type LlamaCompletionResponse = {
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response: string;
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metadata: {
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remainingGenerationAfterStop?: string | Token[];
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stopReason: "eogToken" | "stopGenerationTrigger" | "maxTokens" | "abort";
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} | {
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remainingGenerationAfterStop?: string | Token[];
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stopReason: "customStopTrigger";
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customStopTrigger: (string | Token)[];
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};
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};
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/**
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* @see [Text Completion](https://node-llama-cpp.withcat.ai/guide/text-completion) tutorial
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*/
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export declare class LlamaCompletion {
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readonly onDispose: EventRelay<void>;
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constructor({ contextSequence, autoDisposeSequence }: LlamaCompletionOptions);
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dispose({ disposeSequence }?: {
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disposeSequence?: boolean;
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}): void;
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/** @hidden */
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[Symbol.dispose](): void;
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get disposed(): boolean;
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get infillSupported(): boolean;
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/**
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* Generate a completion for an input.
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*/
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generateCompletion(input: Token[] | string | LlamaText, options?: LlamaCompletionGenerationOptions): Promise<string>;
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/**
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* Same as `generateCompletion`, but returns additional metadata about the generation.
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* See `generateCompletion` for more information.
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*/
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generateCompletionWithMeta(input: Token[] | string | LlamaText, { onTextChunk, onToken, signal, stopOnAbortSignal, maxTokens, temperature, minP, topK, topP, seed, trimWhitespaceSuffix, repeatPenalty, tokenBias, evaluationPriority, grammar, customStopTriggers, contextShiftSize, disableContextShift }?: LlamaCompletionGenerationOptions): Promise<LlamaCompletionResponse>;
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/**
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* Infill (also known as Fill-In-Middle), generates a completion for an input (`prefixInput`) that
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* should connect to a given continuation (`suffixInput`).
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* For example, for `prefixInput: "123"` and `suffixInput: "789"`, the model is expected to generate `456`
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* to make the final text be `123456789`.
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*/
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generateInfillCompletion(prefixInput: Token[] | string | LlamaText, suffixInput: Token[] | string | LlamaText, options?: LlamaInfillGenerationOptions): Promise<string>;
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/**
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* Same as `generateInfillCompletion`, but returns additional metadata about the generation.
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* See `generateInfillCompletion` for more information.
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*/
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generateInfillCompletionWithMeta(prefixInput: Token[] | string | LlamaText, suffixInput: Token[] | string | LlamaText, { onTextChunk, onToken, signal, stopOnAbortSignal, maxTokens, temperature, minP, topK, topP, seed, trimWhitespaceSuffix, repeatPenalty, tokenBias, evaluationPriority, grammar, contextShiftSize, customStopTriggers, minPrefixKeepTokens, disableContextShift }?: LlamaInfillGenerationOptions): Promise<LlamaCompletionResponse>;
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}
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