First upload version 0.0.1

node_modules/node-llama-cpp/dist/evaluator/LlamaRankingContext.d.ts

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+import { EventRelay } from "lifecycle-utils";
+import { Token } from "../types.js";
+import { LlamaText } from "../utils/LlamaText.js";
+import type { LlamaModel } from "./LlamaModel/LlamaModel.js";
+export type LlamaRankingContextOptions = {
+    /**
+     * The number of tokens the model can see at once.
+     * - **`"auto"`** - adapt to the current VRAM state and attempt to set the context size as high as possible up to the size
+     * the model was trained on.
+     * - **`number`** - set the context size to a specific number of tokens.
+     * If there's not enough VRAM, an error will be thrown.
+     * Use with caution.
+     * - **`{min?: number, max?: number}`** - adapt to the current VRAM state and attempt to set the context size as high as possible
+     * up to the size the model was trained on, but at least `min` and at most `max`.
+     *
+     * Defaults to `"auto"`.
+     */
+    contextSize?: "auto" | number | {
+        min?: number;
+        max?: number;
+    };
+    /** prompt processing batch size */
+    batchSize?: number;
+    /**
+     * number of threads to use to evaluate tokens.
+     * set to 0 to use the maximum threads supported by the current machine hardware
+     */
+    threads?: number;
+    /** An abort signal to abort the context creation */
+    createSignal?: AbortSignal;
+    /**
+     * The template to use for the ranking evaluation.
+     * If not provided, the model's template will be used by default.
+     *
+     * The template is tokenized with special tokens enabled, but the provided query and document are not.
+     *
+     * **<span v-pre>`{{query}}`</span>** is replaced with the query content.
+     *
+     * **<span v-pre>`{{document}}`</span>** is replaced with the document content.
+     *
+     * It's recommended to not set this option unless you know what you're doing.
+     *
+     * Defaults to the model's template.
+     */
+    template?: `${string}{{query}}${string}{{document}}${string}` | `${string}{{document}}${string}{{query}}${string}`;
+    /**
+     * Ignore insufficient memory errors and continue with the context creation.
+     * Can cause the process to crash if there's not enough VRAM for the new context.
+     *
+     * Defaults to `false`.
+     */
+    ignoreMemorySafetyChecks?: boolean;
+};
+/**
+ * @see [Reranking Documents](https://node-llama-cpp.withcat.ai/guide/embedding#reranking) tutorial
+ */
+export declare class LlamaRankingContext {
+    readonly onDispose: EventRelay<void>;
+    private constructor();
+    /**
+     * Get the ranking score for a document for a query.
+     *
+     * A ranking score is a number between 0 and 1 representing the probability that the document is relevant to the query.
+     * @returns a ranking score between 0 and 1 representing the probability that the document is relevant to the query.
+     */
+    rank(query: Token[] | string | LlamaText, document: Token[] | string | LlamaText): Promise<number>;
+    /**
+     * Get the ranking scores for all the given documents for a query.
+     *
+     * A ranking score is a number between 0 and 1 representing the probability that the document is relevant to the query.
+     * @returns an array of ranking scores between 0 and 1 representing the probability that the document is relevant to the query.
+     */
+    rankAll(query: Token[] | string | LlamaText, documents: Array<Token[] | string | LlamaText>): Promise<number[]>;
+    /**
+     * Get the ranking scores for all the given documents for a query and sort them by score from highest to lowest.
+     *
+     * A ranking score is a number between 0 and 1 representing the probability that the document is relevant to the query.
+     */
+    rankAndSort<const T extends string>(query: Token[] | string | LlamaText, documents: T[]): Promise<Array<{
+        document: T;
+        /**
+         * A ranking score is a number between 0 and 1 representing the probability that the document is relevant to the query.
+         */
+        score: number;
+    }>>;
+    dispose(): Promise<void>;
+    /** @hidden */
+    [Symbol.asyncDispose](): Promise<void>;
+    get disposed(): boolean;
+    get model(): LlamaModel;
+}