Docs: TypeScript docs factual errors

javascript/lib.cpp

@@ -187,11 +187,11 @@ void Index::Add(Napi::CallbackInfo const& ctx) {
     if (ctx.Length() < 2 || !ctx[0].IsNumber() || !ctx[1].IsTypedArray())
         return Napi::TypeError::New(env, "Expects an integral key and a float vector").ThrowAsJavaScriptException();
 
-    Napi::Number label_js = ctx[0].As<Napi::Number>();
+    Napi::Number key_js = ctx[0].As<Napi::Number>();
     Napi::Float32Array vector_js = ctx[1].As<Napi::Float32Array>();
 
     using key_t = typename index_dense_t::key_t;
-    key_t key = label_js.Uint32Value();
+    key_t key = key_js.Uint32Value();
     float const* vector = vector_js.Data();
     std::size_t dimensions = static_cast<std::size_t>(vector_js.ElementLength());
     if (dimensions != native_->dimensions())

javascript/usearch.d.ts

@@ -0,0 +1,87 @@
+
+/** Search result object. */
+export interface SearchResults {
+    /** The labels of the nearest neighbors found, size n*k. */
+    labels: BigUint64Array,
+    /** The disances of the nearest negihbors found, size n*k. */
+    distances: Float32Array,
+    /** The disances of the nearest negihbors found, size n*k. */
+    count: number
+}
+
+/** K-Approximate Nearest Neighbors search index. */
+export class Index {
+
+    /**
+     * Constructs a new index.
+     * 
+     * @param {number} dimensions
+     * @param {string} metric
+     * @param {string} quantization
+     * @param {number} capacity
+     * @param {number} connectivity
+     * @param {number} expansion_add
+     * @param {number} expansion_search
+     */
+    constructor(...args);
+
+    /**
+     * Returns the dimensionality of vectors.
+     * @return {number} The dimensionality of vectors.
+     */
+    dimensions(): number;
+
+    /**
+     * Returns the number of vectors currently indexed.
+     * @return {number} The number of vectors currently indexed.
+     */
+    size(): number;
+
+    /**
+     * Returns index capacity.
+     * @return {numbers} The capacity of index.
+     */
+    capacity(): number;
+
+    /**
+     * Returns connectivity.
+     * @return {number} The connectivity of index.
+     */
+    connectivity(): number;
+
+    /** 
+     * Write index to a file.
+     * @param {string} path File path to write.
+     */
+    save(path: string): void;
+
+    /** 
+     * Load index from a file.
+     * @param {string} path File path to read.
+     */
+    load(path: string): void;
+
+    /** 
+     * View index from a file, without loading into RAM.
+     * @param {string} path File path to read.
+     */
+    load(path: string): void;
+
+    /** 
+     * Add n vectors of dimension d to the index.
+     * 
+     * @param {BigUint64Array} keys Input identifiers for every vector.
+     * @param {Float32Array} mat Input matrix, matrix of size n * d.
+     */
+    add(keys: BigUint64Array, mat: Float32Array): void;
+
+    /** 
+     * Query n vectors of dimension d to the index. Return at most k vectors for each. 
+     * If there are not enough results for a query, the result array is padded with -1s.
+     *
+     * @param {Float32Array} mat Input vectors to search, matrix of size n * d.
+     * @param {number} k The number of nearest neighbors to search for.
+     * @return {SearchResults} Output of the search result.
+     */
+    search(mat: Float32Array, k: number): SearchResults;
+}