Metadata-Version: 2.4
Name: embedl-hub
Version: 2025.6.0.dev2
Summary: The official Embedl Hub Python client library.
Author-email: Embedl AB <support@embedl.com>
Project-URL: Homepage, https://hub.embedl.com
Project-URL: Documentation, https://hub.embedl.com/docs
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Embedded Systems
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: NOTICE
Requires-Dist: Jinja2>=3.1.5
Requires-Dist: lightning>=2.5.0
Requires-Dist: mergedeep>=1.3.4
Requires-Dist: onnx>=1.17
Requires-Dist: onnxruntime>=1.18
Requires-Dist: pydantic>=2.8.2
Requires-Dist: PyYAML~=6.0.2
Requires-Dist: qai-hub>=0.28.0
Requires-Dist: requests>=2.32.3
Requires-Dist: rich>=13.7
Requires-Dist: timm>=1.0.15
Requires-Dist: torch>=2.6.0
Requires-Dist: torchvision>=0.21.0
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Provides-Extra: dev
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Requires-Dist: mkdocstrings[python]; extra == "dev"
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Dynamic: license-file

# Embedl Hub Python library

[Embedl Hub](https://hub.embedl.com) is a platform for building efficient edge AI applications.
With Embedl Hub, you can:

- Find the best model for your application using on-device benchmarks.
- Fine-tune the model on your own dataset and benchmark it on your target device.
- Deploy your application with the confidence that your model meets your performance requirements.

The Embedl Hub Python library (`embedl-hub`) lets you interact with Embedl Hub in scripts
and from your terminal. [Create a free Embedl Hub account](https://hub.embedl.com/docs#getting-started)
to get started with the `embedl-hub` library.

## Installation

The simplest way to install `embedl-hub` is through `pip`:

```shell
pip install embedl-hub
```

## Quickstart

We recommend using our end-to-end workflow CLI to quickly get started building your edge AI application:

```shell
 Usage: embedl-hub [OPTIONS] COMMAND [ARGS]...

 embedl-hub end-to-end Edge-AI workflow CLI


╭─ Options ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --version             -V               Print embedl-hub version and exit.                                                                   │
│ --verbose             -v      INTEGER  Increase verbosity (-v, -vv, -vvv).                                                                  │
│ --install-completion                   Install completion for the current shell.                                                            │
│ --show-completion                      Show completion for the current shell, to copy it or customize the installation.                     │
│ --help                                 Show this message and exit.                                                                          │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ init           Create new or load existing project and/or experiment.                                                                       │
│ show           Print active project/experiment IDs and names.                                                                               │
│ tune           Fine-tune a model on your dataset.                                                                                           │
│ export         Compile a TorchScript model into an ONNX model using Qualcomm AI Hub.                                                        │
│ quantize       Quantize an ONNX model using Qualcomm AI Hub.                                                                                │
│ compile        Compile an ONNX model into a device ready binary using Qualcomm AI Hub.                                                      │
│ benchmark      Profile compiled model on device and measure it's performance.                                                               │
│ list-devices   List all available target devices.                                                                                           │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
```

## License

Copyright (C) 2025 Embedl AB

This software is subject to the [Embedl Hub Software License Agreement](https://hub.embedl.com/embedl-hub-sla.txt).

<!-- Copyright (C) 2025 Embedl AB -->
