open-index/open-npm huggingface dataset:
npm package: @qualve/anthropic
Description: Anthropic Claude provider for Qualve LLM tasks.
Latest version: 0.0.1

# @qualve/anthropic

[Anthropic Claude](https://www.anthropic.com/) provider for [Qualve](https://npmjs.com/package/qualve) LLM tasks.

## Setup

Requires **Node.js v23+**.

```sh
npm install @qualve/anthropic
```

Set the `ANTHROPIC_API_KEY` environment variable (or add it to `.env`).
Get a key at https://platform.claude.com/settings/keys.

## Usage

```js
import "@qualve/anthropic";
```

Importing the package registers the `claude` provider with the Qualve task system.

Then use `llm: "claude"` in your task definitions:

```js
export default {
	type: "llm",
	llm: "claude",
	system: "You are a helpful assistant.",
	prompt: "Summarize this data.",
	input: [{ name: "data", schema: mySchema }],
	output: { name: "summary", schema: summarySchema },
};
```

## Models

| Model | Context window | Max output |
| --- | --- | --- |
| `claude-sonnet-4-6` (default) | 1M | 64K |
| `claude-haiku-4-6` | 200K | 64K |
| `claude-opus-4-5` | 1M | 128K |

## Capabilities

| Capability | Supported |
| --- | --- |
| Structured output (JSON schema) | Yes |
| Input file descriptions in prompt | Yes (automatic) |
| Thinking levels | No |
| Token counting | Yes |
npm package: @qualve/googleai
Description: Google Gemini provider for Qualve LLM tasks.
Latest version: 0.0.1

# @qualve/googleai

[Google Gemini](https://ai.google.dev/) provider for [Qualve](https://npmjs.com/package/qualve) LLM tasks.

## Setup

Requires **Node.js v23+**.

```sh
npm install @qualve/googleai
```

Set the `GEMINI_API_KEY` environment variable (or add it to `.env`).
Get a key at https://aistudio.google.com/api-keys.

## Usage

```js
import "@qualve/googleai";
```

Importing the package registers the `gemini` provider with the Qualve task system.

Then use `llm: "gemini"` in your task definitions:

```js
export default {
	type: "llm",
	llm: "gemini",
	system: "You are a helpful assistant.",
	prompt: "Summarize this data.",
	input: [{ name: "data", schema: mySchema }],
	output: { name: "summary", schema: summarySchema },
};
```

## Models

| Model | Context window | Max output |
| --- | --- | --- |
| `gemini-3.1-pro-preview` (default) | 1,048,576 | 65,536 |
| `gemini-3.1-flash-preview` | 1,048,576 | 65,536 |
| `gemini-3.1-flash-lite-preview` | 1,048,576 | 65,536 |

## Capabilities

| Capability | Supported |
| --- | --- |
| Structured output (JSON schema) | Yes |
| Thinking levels | Yes (`minimal`, `low`, `medium`, `high`\*) |
| Web search | Yes (pro models only) |
| Token counting | Yes |

\* Default
npm package: @qualve/graphql
Description: GraphQL inputs for Qualve Tasks
Author: Lea Verou
Latest version: 0.0.1

# @qualve/graphql

GraphQL inputs for Qualve Tasks.

## Installation

```sh
npm install @qualve/graphql
```

## Usage

In your `qualve.config.js`, import the `graphql` task:

```js
import "@qualve/graphql";

export default {
	graphql: {
		endpoint: "https://api.example.com/graphql",
	},
	model: {
		// ...
	},
};
```
npm package: @qualve/llm
Description: Core LLM task framework for Qualve.
Author: Lea Verou
Latest version: 0.0.1

# @qualve/llm

Core LLM task framework for [Qualve](https://npmjs.com/package/qualve).
Provides the `LLMTask` base class that all LLM provider adapters extend.

If you want all providers out of the box, install [@qualve/llms](https://npmjs.com/package/@qualve/llms) instead.

## Setup

Requires **Node.js v23+**.

```sh
npm install @qualve/llm
```

## Usage

Import alongside a provider to register the `llm` task type:

```js
import "@qualve/anthropic"; // or @qualve/openai, @qualve/googleai
```

### Writing a custom provider

```js
import { LLMTask } from "@qualve/llm";

export default class MyProvider extends LLMTask {
	static id = "my-provider";
	static name = "My Provider";
	static models = ["my-model-v1"];
	static capabilities = {};

	// Required: implement these abstract methods
	async uploadFile (filepath, { mimeType, contents }) { /* ... */ }
	async getFile (filepath) { /* ... */ }
	async deleteFile (filepath) { /* ... */ }
	async listFiles () { /* ... */ }
	async createStream () { /* ... */ }
}

LLMTask.register(MyProvider);
```

## API

### `LLMTask`

Extends the base Qualve `Task` class with LLM-specific functionality:

- **Provider dispatch** — `LLMTask.create()` routes to the registered provider based on `task.llm`
- **File management** — Upload, retrieve, and manage files on the provider
- **Streaming** — `handleStream()` writes streamed responses to disk with backpressure handling
- **Prompt helpers** — `this.inputFile()`, `this.inputFiles()`, `this.outputFile()` generate prompt text describing task I/O
- **Thinking levels** — Normalized across providers via `thinkingLevels` and per-provider `levelMap`
- **Stop reasons** — Normalized stop reasons (`COMPLETE`, `MAX_TOKENS`, `ABORTED`, `UNKNOWN`)

### Abstract methods (providers must implement)

| Method | Description |
| --- | --- |
| `uploadFile(filepath, { mimeType, contents })` | Upload data to the provider |
| `getFile(filepath)` | Retrieve a previously uploaded file, or `null` |
| `deleteFile(filepath)` | Delete a previously uploaded file |
| `listFiles()` | List all uploaded files |
| `createStream()` | Create the streaming API call; returns `{ stream, transformChunk, onChunk?, onFinish? }` |

### Optional overrides

| Method | Description |
| --- | --- |
| `getStatus(chunk)` | Extract a human-readable status from a streaming chunk |
| `countTokens()` | Count input tokens for a dry run |
npm package: @qualve/openai
Description: OpenAI provider for Qualve LLM tasks.
Latest version: 0.0.1

# @qualve/openai

[OpenAI](https://openai.com/) provider for [Qualve](https://npmjs.com/package/qualve) LLM tasks.

## Setup

Requires **Node.js v23+**.

```sh
npm install @qualve/openai
```

Set the `OPENAI_API_KEY` environment variable (or add it to `.env`).
Get a key at https://platform.openai.com/api-keys.

## Usage

```js
import "@qualve/openai";
```

Importing the package registers the `openai` provider with the Qualve task system.

Then use `llm: "openai"` in your task definitions:

```js
export default {
	type: "llm",
	llm: "openai",
	system: "You are a helpful assistant.",
	prompt: "Summarize this data.",
	input: [{ name: "data", schema: mySchema }],
	output: { name: "summary", schema: summarySchema },
};
```

## Models

| Model | Context window | Max output |
| --- | --- | --- |
| `gpt-5.4` (default) | 1,050,000 | 128K |
| `gpt-5-mini` | 400K | 128K |
| `gpt-5-nano` | 400K | 128K |

## Capabilities

| Capability | Supported |
| --- | --- |
| Structured output (JSON schema) | Yes |
| Thinking levels | Yes (`none`, `minimal`, `low`, `medium`\*, `high`, `xhigh`) |
| Token counting | No |

\* Default
npm package: @quame/custom-auth-library
Description: This library was generated with [Angular CLI](https://github.com/angular/angular-cli) version 13.1.0.
Latest version: 0.1.4

# CustomAuthLibrary

This library was generated with [Angular CLI](https://github.com/angular/angular-cli) version 13.1.0.

## Code scaffolding

Run `ng generate component component-name --project custom-auth-library` to generate a new component. You can also use `ng generate directive|pipe|service|class|guard|interface|enum|module --project custom-auth-library`.
> Note: Don't forget to add `--project custom-auth-library` or else it will be added to the default project in your `angular.json` file. 

## Build

Run `ng build custom-auth-library` to build the project. The build artifacts will be stored in the `dist/` directory.

## Publishing

After building your library with `ng build custom-auth-library`, go to the dist folder `cd dist/custom-auth-library` and run `npm publish`.

## Running unit tests

Run `ng test custom-auth-library` to execute the unit tests via [Karma](https://karma-runner.github.io).

## Further help

To get more help on the Angular CLI use `ng help` or go check out the [Angular CLI Overview and Command Reference](https://angular.io/cli) page.
npm package: @quame/signup-library
Description: This library was generated with [Angular CLI](https://github.com/angular/angular-cli) version 13.1.0.
Latest version: 0.0.5

# SignupLibrary

This library was generated with [Angular CLI](https://github.com/angular/angular-cli) version 13.1.0.

## Code scaffolding

Run `ng generate component component-name --project signup-library` to generate a new component. You can also use `ng generate directive|pipe|service|class|guard|interface|enum|module --project signup-library`.
> Note: Don't forget to add `--project signup-library` or else it will be added to the default project in your `angular.json` file. 

## Build

Run `ng build signup-library` to build the project. The build artifacts will be stored in the `dist/` directory.

## Publishing

After building your library with `ng build signup-library`, go to the dist folder `cd dist/signup-library` and run `npm publish`.

## Running unit tests

Run `ng test signup-library` to execute the unit tests via [Karma](https://karma-runner.github.io).

## Further help

To get more help on the Angular CLI use `ng help` or go check out the [Angular CLI Overview and Command Reference](https://angular.io/cli) page.
npm package: @quamolit/touch-control
Description: Touch Control ----
Latest version: 0.0.13


Touch Control
----

> for Quatrefoil [calcit-js](https://github.com/calcit-lang/calcit). This lib targets Chrome mobile.

Demo http://r.tiye.me/Quatrefoil-GL/touch-control/ .

### Usages

Import via calcit:

```cirru
; "renders to body"
touch-control.core/render-control!

; "where you can get states"
println touch-control.core/*control-states

; create looper
touch-control.core/start-control-loop! 300 $ fn (elapsed states delta)

; clear loop on reload
touch-control.core/clear-control-loop!

; alias of clearing and createing
touch-control.core/replace-control-loop! 300 $ fn (elapsed states delta)
```

States:

```cirru
:left-move $ [] 0 0
:right-move $ [] 0 0

:left-a? false
:left-b? false

:right-a? false
:right-b? false

:shift? false
```

Delta:

```cirru
:left-move $ [] 0 0
:right-move $ [] 0 0
```

To load styles:

```bash
npm i @quamolit/touch-control
```

```css
@import url("@quamolit/touch-control/style/touch-control.css");
```

### Workflow

https://github.com/calcit-lang/respo-calcit-workflow

### License

MIT