open-index/open-npm huggingface dataset:
npm package: @medianect/axios-bundled-as-es-module
Description: mirror of axios, bundled and exposed as ES module
Author: Mikhail Bashkirov
Latest version: 0.21.0

# axios

This is a mirror of [axios](https://www.npmjs.com/package/axios), bundled and exposed as ES module.

## Install

```
npm install @bundled-es-modules/axios
bower install bundled-es-modules/axios
```

## Use

```html
<script type="module">
  // from main file
  import { axios } from 'axios';
  // or directly
  import axios from 'axios/axios.js';
  console.log(axios);
</script>
```

Make sure you added `@bundled-es-modules` scope to the path if used via npm.
npm package: @mediapipe/camera_utils
Description: Mediapipe Camera Utilities
Author: mhays@google.com
Latest version: 0.3.1675466862

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/control_utils
Description: Mediapipe Simple Control Panel
Author: mhays@google.com
Latest version: 0.6.1675466023

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/control_utils_3d
Description: Mediapipe Simple Control Panel 3D
Author: mhays@google.com
Latest version: 0.3.1675466062

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/drawing_utils
Description: Mediapipe Simple Drawing Utilities
Author: mhays@google.com
Latest version: 0.3.1675466124

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/face_detection
Description: Mediapipe Face Detection Solution
Author: mhays@google.com
Latest version: 0.4.1646425229

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/face_mesh
Description: Mediapipe Face Mesh Solution
Author: mhays@google.com
Latest version: 0.4.1633559619

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/hands
Description: Mediapipe Hands Solution
Author: mhays@google.com
Latest version: 0.4.1675469240

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/holistic
Description: Mediapipe Holistic Solution
Author: mhays@google.com
Latest version: 0.5.1675471629

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/objectron
Description: Mediapipe Objectron Solution
Author: mhays@google.com
Latest version: 0.4.1675468480

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/pose
Description: Mediapipe Pose Solution
Author: mhays@google.com
Latest version: 0.5.1675469404

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/selfie_segmentation
Description: Mediapipe Selfie Segmentation Solution
Author: mhays@google.com
Latest version: 0.1.1675465747

# MediaPipe JavaScript Solutions

MediaPipe offers out of the box solutions to use our ML technology with live and streaming media.

Visit us as [mediapipe.dev]()

See live demos of our JavaScript solutions at [code.mediapipe.dev/codepen]()

For more information on each of the solutions and how to use them, visit https://google.github.io/mediapipe/getting_started/javascript.
npm package: @mediapipe/tasks-audio
Description: MediaPipe Audio Tasks
Author: mediapipe@google.com
Latest version: 0.10.34

# MediaPipe Tasks Vision Package

This package contains the audio tasks for MediaPipe.

## Audio Classifier

The MediaPipe Audio Classifier task performs classification on audio data.

```
const audio = await FilesetResolver.forAudioTasks(
    "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-audio/wasm"
);
const audioClassifier = await AudioClassifier.createFromModelPath(audio,
    "https://storage.googleapis.com/mediapipe-models/audio_classifier/yamnet/float32/1/yamnet.tflite
);
const classifications = audioClassifier.classify(audioData);
```

For more information, refer to the [Audio Classifier](https://developers.google.com/mediapipe/solutions/audio/audio_classifier/web_js) documentation.

## Audio Embedding

The MediaPipe Audio Embedding task extracts embeddings from audio data.

```
const audio = await FilesetResolver.forAudioTasks(
    "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-audio/wasm"
);
const audioEmbedder = await AudioEmbedder.createFromModelPath(audio,
    "https://storage.googleapis.com/mediapipe-assets/yamnet_embedding_metadata.tflite?generation=1668295071595506"
);
const embeddings = audioEmbedder.embed(audioData);
```
npm package: @mediapipe/tasks-genai
Description: MediaPipe GenAI Tasks
Author: mediapipe@google.com
Latest version: 0.10.27

# MediaPipe Tasks GenAI Package

This package contains the GenAI tasks for MediaPipe.

## LLM Inference

The MediaPipe LLM Inference task generates text responses from input text. For
Gemma 3n models, it can process input images and audio as well.

In order to begin, you must have a model available. You can download one of these:

- [Gemma 4 E2B](https://huggingface.co/litert-community/gemma-4-E2B-it-litert-lm/blob/main/gemma-4-E2B-it-web.task)
- [Gemma 4 E4B](https://huggingface.co/litert-community/gemma-4-E4B-it-litert-lm/blob/main/gemma-4-E4B-it-web.task)
- [Gemma 3n
E2B](https://huggingface.co/google/gemma-3n-E2B-it-litert-lm/blob/main/gemma-3n-E2B-it-int4-Web.litertlm)
- [Gemma 3n E4B](https://huggingface.co/google/gemma-3n-E4B-it-litert-lm/blob/main/gemma-3n-E4B-it-int4-Web.litertlm)

Alternatively, you can browse for more pre-converted models on our [LiteRT HuggingFace community](https://huggingface.co/litert-community/models), where files named "-web.task" are
specially converted to run optimally in the browser. All text-only variants of
Gemma 3 are available there, as well as [MedGemma-27B-Text](https://huggingface.co/litert-community/MedGemma-27B-IT/blob/main/medgemma-27b-it-int8-web.task). See
our web inference [guide](https://developers.google.com/mediapipe/solutions/genai/llm_inference/web_js) for more information.
Note that only models encoded for the GPU backend are currently supported.

```
const genai = await FilesetResolver.forGenAiTasks(
    "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-genai/wasm"
);
const llmInference = await LlmInference.createFromModelPath(genai, MODEL_URL);
const response = await llmInference.generateResponse(inputText);
```
npm package: @mediapipe/tasks-genai-experimental
Description: MediaPipe GenAI Experimental Tasks
Author: mediapipe@google.com
Latest version: 0.10.22-rc.20250304

# MediaPipe Tasks GenAI Experimental Package

This package contains experimental GenAI tasks for MediaPipe.

## RAG Pipeline Inference

You can use the RAG Pipeline to augment an LLM Inference Task with existing
knowledge.

```
const genaiFileset = await FilesetResolver.forGenAiTasks();
const genaiExperimentalFileset =
  await FilesetResolver.forGenAiExperimentalTasks();
const llmInference = await LlmInference.createFromModelPath(genaiFileset, ...);
const ragPipeline = await RagPipeline.createWithEmbeddingModel(
  genaiExperimentalFileset,
  llmInference,
  EMBEDDING_MODEL_URL,
);
await ragPipeline.recordBatchedMemory([
  'Paris is the capital of France.',
  'Berlin is the capital of Germany.',
]);
const result = await ragPipeline.generateResponse(
  'What is the capital of France?',
);
console.log(result);
```
npm package: @mediapipe/tasks-text
Description: MediaPipe Text Tasks
Author: mediapipe@google.com
Latest version: 0.10.34

# MediaPipe Tasks Text Package

This package contains the text tasks for MediaPipe.

## Language Detector

The MediaPipe Language Detector task predicts the language of an input text.

```
const text = await FilesetResolver.forTextTasks(
    "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-text/wasm"
);
const languageDetector = await LanguageDetector.createFromModelPath(text,
    "https://storage.googleapis.com/mediapipe-models/language_detector/language_detector/float32/1/language_detector.tflite
);
const result = languageDetector.detect(textData);
```

For more information, refer to the [Language Detector](https://developers.google.com/mediapipe/solutions/text/language_detector/web_js) documentation.

## Text Classifier

The MediaPipe Text Classifier task lets you classify text into a set of defined
categories, such as positive or negative sentiment.

```
const text = await FilesetResolver.forTextTasks(
    "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-text/wasm"
);
const textClassifier = await TextClassifier.createFromModelPath(text,
    "https://storage.googleapis.com/mediapipe-models/text_classifier/bert_classifier/float32/1/bert_classifier.tflite"
);
const classifications = textClassifier.classify(textData);
```

For more information, refer to the [Text Classification](https://developers.google.com/mediapipe/solutions/text/text_classifier/web_js) documentation.

## Text Embedder

The MediaPipe Text Embedder task extracts embeddings from text data.

```
const text = await FilesetResolver.forTextTasks(
    "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-text/wasm"
);
const textEmbedder = await TextEmbedder.createFromModelPath(text,
    "https://storage.googleapis.com/mediapipe-models/text_embedder/universal_sentence_encoder/float32/1/universal_sentence_encoder.tflite"
);
const embeddings = textEmbedder.embed(textData);
```

For more information, refer to the [Text Embedder](https://developers.google.com/mediapipe/solutions/text/text_embedder/web_js) documentation.