84 lines
2.8 KiB
JavaScript
84 lines
2.8 KiB
JavaScript
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"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.LlamaCppEmbeddings = void 0;
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const embeddings_1 = require("@langchain/core/embeddings");
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const llama_cpp_js_1 = require("../utils/llama_cpp.cjs");
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/**
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* @example
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* ```typescript
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* // Initialize LlamaCppEmbeddings with the path to the model file
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* const embeddings = new LlamaCppEmbeddings({
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* modelPath: "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin",
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* });
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*
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* // Embed a query string using the Llama embeddings
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* const res = embeddings.embedQuery("Hello Llama!");
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*
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* // Output the resulting embeddings
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* console.log(res);
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*
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* ```
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*/
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class LlamaCppEmbeddings extends embeddings_1.Embeddings {
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constructor(inputs) {
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super(inputs);
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Object.defineProperty(this, "_model", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: void 0
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});
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Object.defineProperty(this, "_context", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: void 0
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});
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const _inputs = inputs;
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_inputs.embedding = true;
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this._model = (0, llama_cpp_js_1.createLlamaModel)(_inputs);
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this._context = (0, llama_cpp_js_1.createLlamaContext)(this._model, _inputs);
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}
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/**
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* Generates embeddings for an array of texts.
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* @param texts - An array of strings to generate embeddings for.
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* @returns A Promise that resolves to an array of embeddings.
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*/
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async embedDocuments(texts) {
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const tokensArray = [];
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for (const text of texts) {
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const encodings = await this.caller.call(() => new Promise((resolve) => {
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resolve(this._context.encode(text));
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}));
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tokensArray.push(encodings);
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}
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const embeddings = [];
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for (const tokens of tokensArray) {
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const embedArray = [];
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for (let i = 0; i < tokens.length; i += 1) {
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const nToken = +tokens[i];
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embedArray.push(nToken);
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}
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embeddings.push(embedArray);
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}
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return embeddings;
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}
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/**
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* Generates an embedding for a single text.
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* @param text - A string to generate an embedding for.
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* @returns A Promise that resolves to an array of numbers representing the embedding.
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*/
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async embedQuery(text) {
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const tokens = [];
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const encodings = await this.caller.call(() => new Promise((resolve) => {
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resolve(this._context.encode(text));
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}));
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for (let i = 0; i < encodings.length; i += 1) {
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const token = +encodings[i];
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tokens.push(token);
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}
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return tokens;
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}
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}
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exports.LlamaCppEmbeddings = LlamaCppEmbeddings;
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