open-index/open-npm huggingface dataset:
npm package: @lumen-ui/static.css
Description: A drop-in collection of CSS styles to establish common stylings.
Author: EQ Works
Latest version: 0.1.0

# static.css

A drop-in collection of CSS styles to establish common stylings.

---

## Development

1. Ensure your environment has [Git](https://git-scm.com/), [Node.js](https://nodejs.org/en/), and [npm](https://www.npmjs.com/) installed.
2. Clone repository, run `git clone git@github.com:lumen-ui/static.css.git`.
3. Install dependencies, run `yarn`.
4. Make changes to the styles in the src directory, and perform one of the options:

   - Manually compile Sass to plain CSS, run `yarn sass`.
   - Watch for Sass changes to automatically compile to plain CSS, run `yarn sass-watch`.

5. To add [vendor prefixes](https://developer.mozilla.org/en-US/docs/Glossary/Vendor_Prefix) to the compiled `dist/static.css file`, run `yarn build`.

---

## Usage

We are currently in the process of publishing the static.css file for easy integration (e.g. `<link rel="stylesheet" href="https://unpkg.com/@lumen-ui/static.css" />`), until that is setup, you can do the following:

1. Download/clone the repository.
2. Copy/paste the `dist/static.css file` file into your project (e.g. inside your `styles/vendor` folder).
3. Link the stylesheet inside the head section of your HTML page, `<link rel="stylesheet" href="styles/vendor/static.css">`.
npm package: @lumenchain/langchain-gigachat
Description: GigaChat integration for LangChain.js
Author: Mikelarg, Mrikaev K.
Latest version: 0.0.3

<div align="center" id="top">

[![GitHub License](https://img.shields.io/github/license/ai-forever/langchain-gigachat?style=flat-square)](https://opensource.org/license/MIT)
![npm](https://img.shields.io/npm/dm/langchain-gigachat)
[![GitHub star chart](https://img.shields.io/github/stars/ai-forever/langchainjs?style=flat-square)](https://www.star-history.com/#ai-forever/langchainjs)

[English](README.md) | [Русский](README-ru_RU.md)

</div>

# langchain-gigachat

This is a library integration with [GigaChat](https://giga.chat/).

## Installation

```bash
npm install --save langchain-gigachat
```

## Quickstart

Follow these simple steps to get up and running quickly.

### Installation

To install the package use following command:

```shell
npm install --save langchain-gigachat
```

### Initialization

To initialize chat model:

```js
import { GigaChat } from "langchain-gigachat"
import { Agent } from 'node:https';

const httpsAgent = new Agent({
    rejectUnauthorized: false,
});

const giga = new GigaChat({
    credentials: 'YOUR_AUTHORIZATION_KEY',
    model: 'GigaChat-Max',
    httpsAgent
})
```

### Usage

Use the GigaChat object to generate responses:

```typescript
import { HumanMessage, SystemMessage } from "@langchain/core/messages";

const messages = [
    new SystemMessage("Translate following messages to portugese"),
    new HumanMessage("Hello, world!"),
];

const resp = await giga.invoke(messages);

console.log(resp.content);
```

Use the GigaChat object to create embeddings:

```js
import { GigaChatEmbeddings } from "langchain-gigachat";
import { Agent } from 'node:https';

const httpsAgent = new Agent({
    rejectUnauthorized: false,
});

async function main() {
  const embeddings = new GigaChatEmbeddings({
    credentials: 'YOUR_AUTHORIZATION_KEY',
    httpsAgent
  });

  console.log(await embeddings.embedDocuments(["Словасловаслова"]));
}

main();
```

Now you can use the GigaChat object with LangChainJS's standard primitives to create LLM-applications.
npm package: @lumendigitaldev/lumen-feedback
Description: Reusable Velt-powered client feedback components for Next.js sites
Latest version: 1.0.2

# @lumendigitaldev/lumen-feedback

Reusable Velt-powered client feedback components for Next.js projects.

## Features

- Drop-in `FeedbackGate` component for env-driven setup
- Lower-level `ClientFeedback` component for custom wiring
- Project-wide Velt document ID with per-route location syncing
- LocalStorage-backed reviewer identity
- Optional query param prefills for reviewer name/email
- Packaged CSS entrypoint for the floating controls

## Installation

Choose any standard package manager.

```bash
npm install @lumendigitaldev/lumen-feedback @veltdev/react @veltdev/client
```

```bash
bun add @lumendigitaldev/lumen-feedback @veltdev/react @veltdev/client
```

## Usage

Import the styles once, then render the gate in your root layout.

```tsx
import '@lumendigitaldev/lumen-feedback/styles.css'
import { FeedbackGate } from '@lumendigitaldev/lumen-feedback'

export default function RootLayout({ children }: { children: React.ReactNode }) {
  return (
    <html>
      <body>
        {children}
        <FeedbackGate />
      </body>
    </html>
  )
}
```

## Environment variables

```bash
NEXT_PUBLIC_ENABLE_FEEDBACK=true
NEXT_PUBLIC_VELT_API_KEY=your_velt_api_key
NEXT_PUBLIC_PROJECT_SLUG=project-slug
NEXT_PUBLIC_PROJECT_NAME="Project Name"
```

`NEXT_PUBLIC_PROJECT_NAME` is optional.

## Advanced usage

```tsx
import '@lumendigitaldev/lumen-feedback/styles.css'
import { ClientFeedback } from '@lumendigitaldev/lumen-feedback'

<ClientFeedback
  apiKey={process.env.NEXT_PUBLIC_VELT_API_KEY!}
  documentId="project-slug"
  projectName="Project Name"
  storageKey="lumen-feedback-user"
/>
```

## Reviewer identity

Reviewers can prefill identity with query params:

- `?feedbackName=Chase`
- `?feedbackEmail=chase@example.com`

Those values are cached in localStorage for later visits.

## Compatibility

- Next.js 15 or 16
- React 18 or 19
- Node.js 18+

## Publishing

```bash
bun run build
npm publish --access public
```