open-index/open-npm huggingface dataset:
npm package: @kharioki/storybook-design-system
Description: A design stem for common react components built with storybook
Author: kharioki
Latest version: 0.2.0

# Storybook design system tutorial

The Storybook design system tutorial is a subset of the full [Storybook design system](https://github.com/storybookjs/design-system/), created as a learning resource for those interested in learning how to write and publish a design system using best in practice techniques.

Learn more in [Storybook tutorials](https://storybook.js.org/tutorials/).
npm package: @kharioki/storybook-outline-addon
Description: A Storybook addon to diplay css outlines in our stories
Author: kharioki
Latest version: 0.1.4

## @kharioki/storybook-outline-addon

This addon is a product of a full [Storybook addon](https://storybook.js.org/tutorials/create-an-addon/) tutorial, that details how to create and publish a Storybook addon using best practices.

Learn more in [Storybook tutorials](https://storybook.js.org/tutorials/).
npm package: @khasama/media-downloader
Description: Video downloader from some platforms like ixigua, douyin, ...
Author: khasama
Latest version: 1.0.2

**Installation:**

Install the library using npm:

```bash
npm install @khasama/media-downloader
```

**Usage:**

1. Import the required function:

   ```javascript
   import { ixiguaDownloader } from "@khasama/media-downloader";
   ```

2. Call the `ixiguaDownloader` function with the following arguments:

   - `url`: The URL of the Ixigua video you want to download (string).
   - `dir`: The directory where you want to save the downloaded video (string). This directory will be created if it doesn't exist.
   - `callback` ({ process, filename, err }): callback function.

**Example:**

```javascript
import { ixiguaDownloader } from "@khasama/media-downloader";
const videoUrl = "https://www.ixigua.com/7161999829802209795/";
const downloadDir = "./downloads";

ixiguaDownloader(videoUrl, downloadDir, ({ err }) => {
  if (err) {
    console.error("Error downloading video:", err);
  } else {
    console.log("Video downloaded successfully!");
  }
});
```
npm package: @khashi/stringer
Description: Convert your string
Latest version: 1.0.1

# @khashi/stringer

[![npm](https://img.shields.io/npm/v/@khashi/stringer)](https://www.npmjs.com/package/@khashi/stringer)
[![NPM](https://img.shields.io/npm/l/@khashi/stringer?color=blue)](https://www.npmjs.com/package/@khashi/stringer)


Convert your string

## Install

```
$ npm install @khashi/stringer
```

## Usage

```js
const stringer = require("@khashi/stringer");

stringer.isUpperCase("DEVELOPER");
//=> "true"

stringer.toLowerCase(123);
//=> Uncaught TypeError: stringer wants a string!
```
## API
Here is a list of currently available stringers.

Stringer | Description
------------ | -------------
toUpperCase(str) | convert string to uppercase letters
toLowerCase(str) | convert string to lowercase letters
isUpperCase(str) | checks if all letters are uppercase
isLowerCase(str) | checks if all letters are lowercase


## License

@khashi/stringer is released under the terms of the MIT License.
npm package: @khashi/tiny
Description: Removes all spaces from a string
Latest version: 2.0.4

# @khashi/tiny

[![npm](https://img.shields.io/npm/v/@khashi/tiny?color=blue&label=npm%20)](https://www.npmjs.com/package/@khashi/tiny)
[![NPM](https://img.shields.io/npm/l/@khashi/tiny?color=blue)](https://www.npmjs.com/package/@khashi/tiny)


Removes all spaces from a string.

## Install

```
$ npm install @khashi/tiny
```

## Usage

```js
const tiny = require("@khashi/tiny");

tiny("So much space!");
//=> "Somuchspace!"

tiny(1337);
//=> Uncaught TypeError: Tiny wants a string!
//    at tiny (<anonymous>:2:41)
//    at <anonymous>:1:1
```
## License

@khashi/tiny is released under the terms of the MIT License.
npm package: @khattakdev/gitbot
Description: A CLI Based Application to help you learn Git and GitHub.
Author: Arsalan Khattak
Latest version: 1.1.7

<h1 align="center">Welcome to Gitbot 👋</h1>
<p>
  <img alt="Version" src="https://img.shields.io/badge/version-1.0.0-blue.svg?cacheSeconds=2592000" />
  <a href="#" target="_blank">
    <img alt="License: ISC" src="https://img.shields.io/badge/License-ISC-yellow.svg" />
  </a>
  <a href="https://twitter.com/khattakdev" target="_blank">
    <img alt="Twitter: khattakdev" src="https://img.shields.io/twitter/follow/khattakdev.svg?style=social" />
  </a>
</p>

> A CLI Based Application to help you learn Git.

## Install

```sh
npm install -g @khattakdev/gitbot
```

## Usage

Open an empty folder in your terminal, type:

```sh
gitbot
```

## Demo
![Demo](https://user-images.githubusercontent.com/37709578/112744394-353f6180-8fb9-11eb-8d75-92aab29564fb.gif)
## Author

👤 **Arsalan Khattak**

-   Website: [khattak.dev](https://khattak.dev)
-   Twitter: [@khattakdev](https://twitter.com/khattakdev)
-   Github: [@khattak.dev](https://github.com/khattakdev)
-   LinkedIn: [@khattakdev](https://linkedin.com/in/khattakdev)

## License

[MIT](LICENSE)

## Show your support

Give a ⭐️ and follow [@khattakdev](https://github.com/khattakdev) if this project helped you!

---
npm package: @khaveeai/providers-pgvector
Description: PostgreSQL + pgvector provider for Khavee AI SDK
Author: KhaveeAI
Latest version: 0.1.3

# @khaveeai/providers-pgvector

PostgreSQL + pgvector provider for the Khavee AI SDK. Bring your own Postgres database and get document storage, CSV import, and vector similarity search out of the box.

## Installation

```bash
npm install @khaveeai/providers-pgvector
# requires: pg, openai (peer)
```

## Quick start

```ts
import { PgVectorProvider } from "@khaveeai/providers-pgvector";

const db = new PgVectorProvider({
  connectionString: process.env.DATABASE_URL!,
  openaiApiKey:     process.env.OPENAI_API_KEY!,
});

// 1. Create schema on first run
await db.migrate();

// 2. Insert a document
await db.insertDocument("Hello my name is Non", { category: "greeting" });

// 3. Import a CSV
await db.importCSV(csvString); // must have a "content" column

// 4. Vector search
const results = await db.search("what is your name?", 5, 0.3);
// → [{ id, content, metadata, createdAt, similarity }]

// 5. Browse all
const docs = await db.listDocuments(20);
```

## CSV format

The CSV **must** have a `content` column (or set `contentColumn` in options).  
All other columns become `metadata`.

```csv
content,category,author
"Hello my name is Non",greeting,Non
"The Eiffel Tower is in Paris",geography,system
```

```ts
await db.importCSV(csvString, { contentColumn: "content", concurrency: 5 });
```

## Config

| Option | Type | Default | Description |
|---|---|---|---|
| `connectionString` | string | **required** | PostgreSQL connection URL |
| `openaiApiKey` | string | **required** | OpenAI key for embeddings |
| `embeddingModel` | string | `text-embedding-3-small` | Any OpenAI embedding model |
| `embeddingDimensions` | number | `1536` | Must match the model |
| `tableName` | string | `documents` | Table to read/write |
| `defaultTopK` | number | `5` | Default search results |
| `defaultThreshold` | number | `0.3` | Default min similarity |
| `defaultConcurrency` | number | `5` | Parallel embed calls |

## Use with OpenAI Realtime (RAG)

```ts
import { OpenAIRealtimeProvider } from "@khaveeai/providers-openai-realtime";
import { PgVectorProvider } from "@khaveeai/providers-pgvector";

const vectorDB = new PgVectorProvider({ connectionString, openaiApiKey });

const provider = new OpenAIRealtimeProvider({
  useProxy: true,
  rag: {
    provider: vectorDB,
    topK: 5,
    threshold: 0.3,
    systemPromptPrefix: "Use the following context to answer questions:",
  },
});
```