@lancedb/lancedb - npm Package Compare versions

Comparing version 0.13.0-beta.1 to 0.13.0

dist/embedding/index.d.ts

		import { Schema } from "../arrow";
		import { EmbeddingFunction } from "./embedding_function";
		export { EmbeddingFunction, TextEmbeddingFunction } from "./embedding_function";
		export * from "./openai";
		export * from "./transformers";
		export * from "./registry";
		@@ -7,0 +5,0 @@ /**

dist/embedding/index.js

		@@ -38,5 +38,2 @@ "use strict";
		Object.defineProperty(exports, "TextEmbeddingFunction", { enumerable: true, get: function () { return embedding_function_1.TextEmbeddingFunction; } });
		// We need to explicitly export '*' so that the `register` decorator actually registers the class.
		__exportStar(require("./openai"), exports);
		__exportStar(require("./transformers"), exports);
		__exportStar(require("./registry"), exports);
		@@ -43,0 +40,0 @@ /**

dist/embedding/registry.d.ts

		import { type EmbeddingFunction, type EmbeddingFunctionConstructor } from "./embedding_function";
		import "reflect-metadata";
		import { OpenAIEmbeddingFunction } from "./openai";
		import { TransformersEmbeddingFunction } from "./transformers";
		type CreateReturnType<T> = T extends {
		@@ -30,4 +28,2 @@ init: () => Promise<void>;
		register<T extends EmbeddingFunctionConstructor = EmbeddingFunctionConstructor>(this: EmbeddingFunctionRegistry, alias?: string): (ctor: T) => any;
		get(name: "openai"): EmbeddingFunctionCreate<OpenAIEmbeddingFunction>;
		get(name: "huggingface"): EmbeddingFunctionCreate<TransformersEmbeddingFunction>;
		get<T extends EmbeddingFunction<unknown>>(name: string): EmbeddingFunctionCreate<T> \| undefined;
		@@ -34,0 +30,0 @@ /**

dist/embedding/transformers.js

		@@ -69,13 +69,13 @@ "use strict";
		// since typescript transpiles `import` to `require`, we need to do this in an unsafe way
		// We can't use `require` because `@xenova/transformers` is an ESM module
		// We can't use `require` because `@huggingface/transformers` is an ESM module
		// and we can't use `import` directly because typescript will transpile it to `require`.
		// and we want to remain compatible with both ESM and CJS modules
		// so we use `eval` to bypass typescript for this specific import.
		transformers = await eval('import("@xenova/transformers")');
		transformers = await eval('import("@huggingface/transformers")');
		}
		catch (e) {
		throw new Error(`error loading @xenova/transformers\nReason: ${e}`);
		throw new Error(`error loading @huggingface/transformers\nReason: ${e}`);
		}
		try {
		this.#model = await transformers.AutoModel.from_pretrained(this.#modelName);
		this.#model = await transformers.AutoModel.from_pretrained(this.#modelName, { dtype: "fp32" });
		}
		@@ -99,3 +99,4 @@ catch (e) {
		const config = this.#model.config;
		const ndims = config["hidden_size"];
		// biome-ignore lint/style/useNamingConvention: we don't control this name.
		const ndims = config.hidden_size;
		if (!ndims) {
		@@ -102,0 +103,0 @@ throw new Error("hidden_size not found in model config, you may need to manually specify the embedding dimensions. ");

dist/native.d.ts

		@@ -277,2 +277,3 @@ /* tslint:disable */
		column(column: string): void
		addQueryVector(vector: Float32Array): void
		distanceType(distanceType: string): void
		@@ -279,0 +280,0 @@ postfilter(): void

dist/query.d.ts

		@@ -270,2 +270,3 @@ import { Table as ArrowTable, type IntoVector, RecordBatch } from "./arrow";
		bypassVectorIndex(): VectorQuery;
		addQueryVector(vector: IntoVector): VectorQuery;
		}
		@@ -313,2 +314,3 @@ /** A builder for LanceDB queries. */
		nearestTo(vector: IntoVector): VectorQuery;
		nearestToText(query: string, columns?: string[]): Query;
		}

dist/query.js

		@@ -412,2 +412,37 @@ "use strict";
		}
		/*
		* Add a query vector to the search
		*
		* This method can be called multiple times to add multiple query vectors
		* to the search. If multiple query vectors are added, then they will be searched
		* in parallel, and the results will be concatenated. A column called `query_index`
		* will be added to indicate the index of the query vector that produced the result.
		*
		* Performance wise, this is equivalent to running multiple queries concurrently.
		*/
		addQueryVector(vector) {
		if (vector instanceof Promise) {
		const res = (async () => {
		try {
		const v = await vector;
		const arr = Float32Array.from(v);
		//
		// biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
		const value = this.addQueryVector(arr);
		const inner = value.inner;
		return inner;
		}
		catch (e) {
		return Promise.reject(e);
		}
		})();
		return new VectorQuery(res);
		}
		else {
		super.doCall((inner) => {
		inner.addQueryVector(Float32Array.from(vector));
		});
		return this;
		}
		}
		}
		@@ -492,3 +527,7 @@ exports.VectorQuery = VectorQuery;
		}
		nearestToText(query, columns) {
		this.doCall((inner) => inner.fullTextSearch(query, columns));
		return this;
		}
		}
		exports.Query = Query;

package.json

		@@ -13,7 +13,9 @@ {
		],
		"version": "0.13.0-beta.1",
		"version": "0.13.0",
		"main": "dist/index.js",
		"exports": {
		".": "./dist/index.js",
		"./embedding": "./dist/embedding/index.js"
		"./embedding": "./dist/embedding/index.js",
		"./embedding/openai": "./dist/embedding/openai.js",
		"./embedding/transformers": "./dist/embedding/transformers.js"
		},
		@@ -96,7 +98,7 @@ "types": "dist/index.d.ts",
		"optionalDependencies": {
		"@lancedb/lancedb-darwin-arm64": "0.13.0-beta.1",
		"@lancedb/lancedb-linux-arm64-gnu": "0.13.0-beta.1",
		"@lancedb/lancedb-darwin-x64": "0.13.0-beta.1",
		"@lancedb/lancedb-linux-x64-gnu": "0.13.0-beta.1",
		"@lancedb/lancedb-win32-x64-msvc": "0.13.0-beta.1"
		"@lancedb/lancedb-darwin-arm64": "0.13.0",
		"@lancedb/lancedb-linux-arm64-gnu": "0.13.0",
		"@lancedb/lancedb-darwin-x64": "0.13.0",
		"@lancedb/lancedb-linux-x64-gnu": "0.13.0",
		"@lancedb/lancedb-win32-x64-msvc": "0.13.0"
		},
		@@ -103,0 +105,0 @@ "peerDependencies": {

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