From 492d0328feabb2d5036550fdd7eca44d4666c457 Mon Sep 17 00:00:00 2001
From: Cory Grinstead <universalmind.candy@gmail.com>
Date: Tue, 23 Jul 2024 13:46:32 -0700
Subject: [PATCH] chore: update readme to point to lancedb package (#1470)

---
 README.md               | 28 +++++++++++++---------------
 nodejs/lancedb/table.ts |  3 +++
 2 files changed, 16 insertions(+), 15 deletions(-)

diff --git a/README.md b/README.md
index 4b91bcd4..ad2a63f5 100644
--- a/README.md
+++ b/README.md
@@ -7,8 +7,8 @@
 
 <a href='https://github.com/lancedb/vectordb-recipes/tree/main' target="_blank"><img alt='LanceDB' src='https://img.shields.io/badge/VectorDB_Recipes-100000?style=for-the-badge&logo=LanceDB&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
 <a href='https://lancedb.github.io/lancedb/' target="_blank"><img alt='lancdb' src='https://img.shields.io/badge/DOCS-100000?style=for-the-badge&logo=lancdb&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
-[![Blog](https://img.shields.io/badge/Blog-12100E?style=for-the-badge&logoColor=white)](https://blog.lancedb.com/) 
-[![Discord](https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/zMM32dvNtd) 
+[![Blog](https://img.shields.io/badge/Blog-12100E?style=for-the-badge&logoColor=white)](https://blog.lancedb.com/)
+[![Discord](https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/zMM32dvNtd)
 [![Twitter](https://img.shields.io/badge/Twitter-%231DA1F2.svg?style=for-the-badge&logo=Twitter&logoColor=white)](https://twitter.com/lancedb)
 
 </p>
@@ -44,26 +44,24 @@ LanceDB's core is written in Rust 🦀 and is built using <a href="https://githu
 
 **Javascript**
 ```shell
-npm install vectordb
+npm install @lancedb/lancedb
 ```
 
 ```javascript
-const lancedb = require('vectordb');
-const db = await lancedb.connect('data/sample-lancedb');
+import * as lancedb from "@lancedb/lancedb";
 
-const table = await db.createTable({
-  name: 'vectors',
-  data:  [
-    { id: 1, vector: [0.1, 0.2], item: "foo", price: 10 },
-    { id: 2, vector: [1.1, 1.2], item: "bar", price: 50 }
-  ]
-})
+const db = await lancedb.connect("data/sample-lancedb");
+const table = await db.createTable("vectors", [
+	{ id: 1, vector: [0.1, 0.2], item: "foo", price: 10 },
+	{ id: 2, vector: [1.1, 1.2], item: "bar", price: 50 },
+], {mode: 'overwrite'});
 
-const query = table.search([0.1, 0.3]).limit(2);
-const results = await query.execute();
+
+const query = table.vectorSearch([0.1, 0.3]).limit(2);
+const results = await query.toArray();
 
 // You can also search for rows by specific criteria without involving a vector search.
-const rowsByCriteria = await table.search(undefined).where("price >= 10").execute();
+const rowsByCriteria = await table.query().where("price >= 10").toArray();
 ```
 
 **Python**
diff --git a/nodejs/lancedb/table.ts b/nodejs/lancedb/table.ts
index 557c62c0..acf9bd98 100644
--- a/nodejs/lancedb/table.ts
+++ b/nodejs/lancedb/table.ts
@@ -275,12 +275,15 @@ export abstract class Table {
    * of the given query vector
    * @param {string} query - the query. This will be converted to a vector using the table's provided embedding function
    * @note  If no embedding functions are defined in the table, this will error when collecting the results.
+   *
+   * This is just a convenience method for calling `.query().nearestTo(await myEmbeddingFunction(query))`
    */
   abstract search(query: string): VectorQuery;
   /**
    * Create a search query to find the nearest neighbors
    * of the given query vector
    * @param {IntoVector} query - the query vector
+   * This is just a convenience method for calling `.query().nearestTo(query)`
    */
   abstract search(query: IntoVector): VectorQuery;
   /**