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CODE_OF_CONDUCT.md
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@ -55,7 +55,7 @@ a project may be further defined and clarified by project maintainers.
## Enforcement ## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported by contacting the project team at <conduct@allegro.ai>. All reported by contacting the project team at <conduct@clear.ml>. All
complaints will be reviewed and investigated and will result in a response that complaints will be reviewed and investigated and will result in a response that
is deemed necessary and appropriate to the circumstances. The project team is is deemed necessary and appropriate to the circumstances. The project team is
obligated to maintain confidentiality with regard to the reporter of an incident. obligated to maintain confidentiality with regard to the reporter of an incident.

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LICENSE
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@ -186,7 +186,7 @@
same "printed page" as the copyright notice for easier same "printed page" as the copyright notice for easier
identification within third-party archives. identification within third-party archives.
Copyright 2024 ClearML Copyright 2025 ClearML Inc
Licensed under the Apache License, Version 2.0 (the "License"); Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License. you may not use this file except in compliance with the License.

57
README.md
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@ -7,8 +7,8 @@
**[ClearML](https://clear.ml) - Auto-Magical Suite of tools to streamline your AI workflow **[ClearML](https://clear.ml) - Auto-Magical Suite of tools to streamline your AI workflow
</br>Experiment Manager, MLOps/LLMOps and Data-Management** </br>Experiment Manager, MLOps/LLMOps and Data-Management**
[![GitHub license](https://img.shields.io/github/license/allegroai/clearml.svg)](https://img.shields.io/github/license/allegroai/clearml.svg) [![PyPI pyversions](https://img.shields.io/pypi/pyversions/clearml.svg)](https://img.shields.io/pypi/pyversions/clearml.svg) [![PyPI version shields.io](https://img.shields.io/pypi/v/clearml.svg)](https://pypi.org/project/clearml/) [![Conda version shields.io](https://img.shields.io/conda/v/clearml/clearml)](https://anaconda.org/clearml/clearml) [![Optuna](https://img.shields.io/badge/Optuna-integrated-blue)](https://optuna.org)<br> [![GitHub license](https://img.shields.io/github/license/clearml/clearml.svg)](https://img.shields.io/github/license/clearml/clearml.svg) [![PyPI pyversions](https://img.shields.io/pypi/pyversions/clearml.svg)](https://img.shields.io/pypi/pyversions/clearml.svg) [![PyPI version shields.io](https://img.shields.io/pypi/v/clearml.svg)](https://pypi.org/project/clearml/) [![Conda version shields.io](https://img.shields.io/conda/v/clearml/clearml)](https://anaconda.org/clearml/clearml) [![Optuna](https://img.shields.io/badge/Optuna-integrated-blue)](https://optuna.org)<br>
[![PyPI Downloads](https://static.pepy.tech/badge/clearml/month)](https://pypi.org/project/clearml/) [![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/allegroai)](https://artifacthub.io/packages/search?repo=allegroai) [![Youtube](https://img.shields.io/badge/ClearML-DD0000?logo=youtube&logoColor=white)](https://www.youtube.com/c/clearml) [![Slack Channel](https://img.shields.io/badge/slack-%23clearml--community-blueviolet?logo=slack)](https://joinslack.clear.ml) [![Signup](https://img.shields.io/badge/Clear%7CML-Signup-brightgreen)](https://app.clear.ml) [![PyPI Downloads](https://static.pepy.tech/badge/clearml/month)](https://pypi.org/project/clearml/) [![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/clearml)](https://artifacthub.io/packages/search?repo=clearml) [![Youtube](https://img.shields.io/badge/ClearML-DD0000?logo=youtube&logoColor=white)](https://www.youtube.com/c/clearml) [![Slack Channel](https://img.shields.io/badge/slack-%23clearml--community-blueviolet?logo=slack)](https://joinslack.clear.ml) [![Signup](https://img.shields.io/badge/Clear%7CML-Signup-brightgreen)](https://app.clear.ml)
`🌟 ClearML is open-source - Leave a star to support the project! 🌟` `🌟 ClearML is open-source - Leave a star to support the project! 🌟`
@ -17,21 +17,20 @@
--- ---
### ClearML ### ClearML
<sup>*Formerly known as Allegro Trains*<sup>
ClearML is a ML/DL development and production suite. It contains FIVE main modules: ClearML is a ML/DL development and production suite. It contains FIVE main modules:
- [Experiment Manager](#clearml-experiment-manager) - Automagical experiment tracking, environments and results - [Experiment Manager](#clearml-experiment-manager) - Automagical experiment tracking, environments and results
- [MLOps / LLMOps](https://github.com/allegroai/clearml-agent) - Orchestration, Automation & Pipelines solution for ML/DL/GenAI jobs (Kubernetes / Cloud / bare-metal) - [MLOps / LLMOps](https://github.com/clearml/clearml-agent) - Orchestration, Automation & Pipelines solution for ML/DL/GenAI jobs (Kubernetes / Cloud / bare-metal)
- [Data-Management](https://github.com/allegroai/clearml/blob/master/docs/datasets.md) - Fully differentiable data management & version control solution on top of object-storage - [Data-Management](https://github.com/clearml/clearml/blob/master/docs/datasets.md) - Fully differentiable data management & version control solution on top of object-storage
(S3 / GS / Azure / NAS) (S3 / GS / Azure / NAS)
- [Model-Serving](https://github.com/allegroai/clearml-serving) - *cloud-ready* Scalable model serving solution! - [Model-Serving](https://github.com/clearml/clearml-serving) - *cloud-ready* Scalable model serving solution!
- **Deploy new model endpoints in under 5 minutes** - **Deploy new model endpoints in under 5 minutes**
- Includes optimized GPU serving support backed by Nvidia-Triton - Includes optimized GPU serving support backed by Nvidia-Triton
- **with out-of-the-box Model Monitoring** - **with out-of-the-box Model Monitoring**
- [Reports](https://clear.ml/docs/latest/docs/webapp/webapp_reports) - Create and share rich MarkDown documents supporting embeddable online content - [Reports](https://clear.ml/docs/latest/docs/webapp/webapp_reports) - Create and share rich MarkDown documents supporting embeddable online content
- :fire: [Orchestration Dashboard](https://clear.ml/docs/latest/docs/webapp/webapp_orchestration_dash/) - Live rich dashboard for your entire compute cluster (Cloud / Kubernetes / On-Prem) - :fire: [Orchestration Dashboard](https://clear.ml/docs/latest/docs/webapp/webapp_orchestration_dash/) - Live rich dashboard for your entire compute cluster (Cloud / Kubernetes / On-Prem)
- **NEW** 💥 [Fractional GPUs](https://github.com/allegroai/clearml-fractional-gpu) - Container based, driver level GPU memory limitation 🙀 !!! - **NEW** 💥 [Fractional GPUs](https://github.com/clearml/clearml-fractional-gpu) - Container based, driver level GPU memory limitation 🙀 !!!
Instrumenting these components is the **ClearML-server**, see [Self-Hosting](https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server) & [Free tier Hosting](https://app.clear.ml) Instrumenting these components is the **ClearML-server**, see [Self-Hosting](https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server) & [Free tier Hosting](https://app.clear.ml)
@ -48,20 +47,20 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting](htt
<table> <table>
<tbody> <tbody>
<tr> <tr>
<td><a href="https://github.com/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb"><b>Step 1</b></a> - Experiment Management</td> <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb"><b>Step 1</b></a> - Experiment Management</td>
<td><a target="_blank" href="https://colab.research.google.com/github/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb"> <td><a target="_blank" href="https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_1_Experiment_Management.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a></td> </a></td>
</tr> </tr>
<tr> <tr>
<td><a href="https://github.com/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb"><b>Step 2</b></a> - Remote Execution Agent Setup</td> <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb"><b>Step 2</b></a> - Remote Execution Agent Setup</td>
<td><a target="_blank" href="https://colab.research.google.com/github/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb"> <td><a target="_blank" href="https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_2_Setting_Up_Agent.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a></td> </a></td>
</tr> </tr>
<tr> <tr>
<td><a href="https://github.com/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb"><b>Step 3</b></a> - Remotely Execute Tasks</td> <td><a href="https://github.com/clearml/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb"><b>Step 3</b></a> - Remotely Execute Tasks</td>
<td><a target="_blank" href="https://colab.research.google.com/github/allegroai/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb"> <td><a target="_blank" href="https://colab.research.google.com/github/clearml/clearml/blob/master/docs/tutorials/Getting_Started_3_Remote_Execution.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a></td> </a></td>
</tr> </tr>
@ -79,8 +78,8 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting](htt
<td>Datasets</td> <td>Datasets</td>
</tr> </tr>
<tr> <tr>
<td><a href="https://app.clear.ml"><img src="https://github.com/allegroai/clearml/blob/master/docs/experiment_manager.gif?raw=true" width="100%"></a></td> <td><a href="https://app.clear.ml"><img src="https://github.com/clearml/clearml/blob/master/docs/experiment_manager.gif?raw=true" width="100%"></a></td>
<td><a href="https://app.clear.ml/datasets"><img src="https://github.com/allegroai/clearml/blob/master/docs/datasets.gif?raw=true" width="100%"></a></td> <td><a href="https://app.clear.ml/datasets"><img src="https://github.com/clearml/clearml/blob/master/docs/datasets.gif?raw=true" width="100%"></a></td>
</tr> </tr>
<tr> <tr>
<td colspan="2" height="24px"></td> <td colspan="2" height="24px"></td>
@ -90,8 +89,8 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting](htt
<td>Pipelines</td> <td>Pipelines</td>
</tr> </tr>
<tr> <tr>
<td><a href="https://app.clear.ml/workers-and-queues/autoscalers"><img src="https://github.com/allegroai/clearml/blob/master/docs/orchestration.gif?raw=true" width="100%"></a></td> <td><a href="https://app.clear.ml/workers-and-queues/autoscalers"><img src="https://github.com/clearml/clearml/blob/master/docs/orchestration.gif?raw=true" width="100%"></a></td>
<td><a href="https://app.clear.ml/pipelines"><img src="https://github.com/allegroai/clearml/blob/master/docs/pipelines.gif?raw=true" width="100%"></a></td> <td><a href="https://app.clear.ml/pipelines"><img src="https://github.com/clearml/clearml/blob/master/docs/pipelines.gif?raw=true" width="100%"></a></td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -115,13 +114,13 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting](htt
* Resource Monitoring (CPU/GPU utilization, temperature, IO, network, etc.) * Resource Monitoring (CPU/GPU utilization, temperature, IO, network, etc.)
* Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http) * Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http)
* Artifacts log & store (Shared folder, S3, GS, Azure, Http) * Artifacts log & store (Shared folder, S3, GS, Azure, Http)
* Tensorboard/[TensorboardX](https://github.com/allegroai/clearml/tree/master/examples/frameworks/tensorboardx) scalars, metrics, histograms, **images, audio and video samples** * Tensorboard/[TensorboardX](https://github.com/clearml/clearml/tree/master/examples/frameworks/tensorboardx) scalars, metrics, histograms, **images, audio and video samples**
* [Matplotlib & Seaborn](https://github.com/allegroai/clearml/tree/master/examples/frameworks/matplotlib) * [Matplotlib & Seaborn](https://github.com/clearml/clearml/tree/master/examples/frameworks/matplotlib)
* [ClearML Logger](https://clear.ml/docs/latest/docs/fundamentals/logger) interface for complete flexibility. * [ClearML Logger](https://clear.ml/docs/latest/docs/fundamentals/logger) interface for complete flexibility.
* Extensive platform support and integrations * Extensive platform support and integrations
* Supported ML/DL frameworks: [PyTorch](https://github.com/allegroai/clearml/tree/master/examples/frameworks/pytorch) (incl' [ignite](https://github.com/allegroai/clearml/tree/master/examples/frameworks/ignite) / [lightning](https://github.com/allegroai/clearml/tree/master/examples/frameworks/pytorch-lightning)), [Tensorflow](https://github.com/allegroai/clearml/tree/master/examples/frameworks/tensorflow), [Keras](https://github.com/allegroai/clearml/tree/master/examples/frameworks/keras), [AutoKeras](https://github.com/allegroai/clearml/tree/master/examples/frameworks/autokeras), [FastAI](https://github.com/allegroai/clearml/tree/master/examples/frameworks/fastai), [XGBoost](https://github.com/allegroai/clearml/tree/master/examples/frameworks/xgboost), [LightGBM](https://github.com/allegroai/clearml/tree/master/examples/frameworks/lightgbm), [MegEngine](https://github.com/allegroai/clearml/tree/master/examples/frameworks/megengine) and [Scikit-Learn](https://github.com/allegroai/clearml/tree/master/examples/frameworks/scikit-learn) * Supported ML/DL frameworks: [PyTorch](https://github.com/clearml/clearml/tree/master/examples/frameworks/pytorch) (incl' [ignite](https://github.com/clearml/clearml/tree/master/examples/frameworks/ignite) / [lightning](https://github.com/clearml/clearml/tree/master/examples/frameworks/pytorch-lightning)), [Tensorflow](https://github.com/clearml/clearml/tree/master/examples/frameworks/tensorflow), [Keras](https://github.com/clearml/clearml/tree/master/examples/frameworks/keras), [AutoKeras](https://github.com/clearml/clearml/tree/master/examples/frameworks/autokeras), [FastAI](https://github.com/clearml/clearml/tree/master/examples/frameworks/fastai), [XGBoost](https://github.com/clearml/clearml/tree/master/examples/frameworks/xgboost), [LightGBM](https://github.com/clearml/clearml/tree/master/examples/frameworks/lightgbm), [MegEngine](https://github.com/clearml/clearml/tree/master/examples/frameworks/megengine) and [Scikit-Learn](https://github.com/clearml/clearml/tree/master/examples/frameworks/scikit-learn)
* Seamless integration (including version control) with [**Jupyter Notebook**](https://jupyter.org/) * Seamless integration (including version control) with [**Jupyter Notebook**](https://jupyter.org/)
and [*PyCharm* remote debugging](https://github.com/allegroai/trains-pycharm-plugin) and [*PyCharm* remote debugging](https://github.com/clearml/trains-pycharm-plugin)
#### [Start using ClearML](https://clear.ml/docs/latest/docs/getting_started/ds/ds_first_steps) #### [Start using ClearML](https://clear.ml/docs/latest/docs/getting_started/ds/ds_first_steps)
@ -163,13 +162,13 @@ The ClearML run-time components:
* The ClearML Server - for storing experiment, model, and workflow data; supporting the Web UI experiment manager and MLOps automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server. * The ClearML Server - for storing experiment, model, and workflow data; supporting the Web UI experiment manager and MLOps automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server.
* The ClearML Agent - for MLOps orchestration, experiment and workflow reproducibility, and scalability. * The ClearML Agent - for MLOps orchestration, experiment and workflow reproducibility, and scalability.
<img src="https://raw.githubusercontent.com/allegroai/clearml-docs/main/docs/img/clearml_architecture.png" width="100%" alt="clearml-architecture"> <img src="https://raw.githubusercontent.com/clearml/clearml-docs/main/docs/img/clearml_architecture.png" width="100%" alt="clearml-architecture">
## Additional Modules ## Additional Modules
- [clearml-session](https://github.com/allegroai/clearml-session) - **Launch remote JupyterLab / VSCode-server inside any docker, on Cloud/On-Prem machines** - [clearml-session](https://github.com/clearml/clearml-session) - **Launch remote JupyterLab / VSCode-server inside any docker, on Cloud/On-Prem machines**
- [clearml-task](https://github.com/allegroai/clearml/blob/master/docs/clearml-task.md) - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib & Console outputs - [clearml-task](https://github.com/clearml/clearml/blob/master/docs/clearml-task.md) - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib & Console outputs
- [clearml-data](https://github.com/allegroai/clearml/blob/master/docs/datasets.md) - **CLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS** - [clearml-data](https://github.com/clearml/clearml/blob/master/docs/datasets.md) - **CLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS**
- [AWS Auto-Scaler](https://clear.ml/docs/latest/docs/guides/services/aws_autoscaler) - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for AKE! - [AWS Auto-Scaler](https://clear.ml/docs/latest/docs/guides/services/aws_autoscaler) - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for AKE!
- [Hyper-Parameter Optimization](https://clear.ml/docs/latest/docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt) - Optimize any code with black-box approach and state-of-the-art Bayesian optimization algorithms - [Hyper-Parameter Optimization](https://clear.ml/docs/latest/docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt) - Optimize any code with black-box approach and state-of-the-art Bayesian optimization algorithms
- [Automation Pipeline](https://clear.ml/docs/latest/docs/guides/pipeline/pipeline_controller) - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines! - [Automation Pipeline](https://clear.ml/docs/latest/docs/guides/pipeline/pipeline_controller) - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines!
@ -212,7 +211,7 @@ If ClearML is part of your development process / project / publication, please c
@misc{clearml, @misc{clearml,
title = {ClearML - Your entire MLOps stack in one open-source tool}, title = {ClearML - Your entire MLOps stack in one open-source tool},
year = {2024}, year = {2024},
note = {Software available from http://github.com/allegroai/clearml}, note = {Software available from http://github.com/clearml/clearml},
url={https://clear.ml/}, url={https://clear.ml/},
author = {ClearML}, author = {ClearML},
} }
@ -222,17 +221,17 @@ author = {ClearML},
For more information, see the [official documentation](https://clear.ml/docs) and [on YouTube](https://www.youtube.com/c/ClearML). For more information, see the [official documentation](https://clear.ml/docs) and [on YouTube](https://www.youtube.com/c/ClearML).
For examples and use cases, check the [examples folder](https://github.com/allegroai/clearml/tree/master/examples) and [corresponding documentation](https://clear.ml/docs/latest/docs/guides). For examples and use cases, check the [examples folder](https://github.com/clearml/clearml/tree/master/examples) and [corresponding documentation](https://clear.ml/docs/latest/docs/guides).
If you have any questions: post on our [Slack Channel](https://joinslack.clear.ml), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/clearml) with '**[clearml](https://stackoverflow.com/questions/tagged/clearml)**' tag (*previously [trains](https://stackoverflow.com/questions/tagged/trains) tag*). If you have any questions: post on our [Slack Channel](https://joinslack.clear.ml), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/clearml) with '**[clearml](https://stackoverflow.com/questions/tagged/clearml)**' tag (*previously [trains](https://stackoverflow.com/questions/tagged/trains) tag*).
For feature requests or bug reports, please use [GitHub issues](https://github.com/allegroai/clearml/issues). For feature requests or bug reports, please use [GitHub issues](https://github.com/clearml/clearml/issues).
Additionally, you can always find us at *info@clear.ml* Additionally, you can always find us at *info@clear.ml*
## Contributing ## Contributing
**PRs are always welcome** :heart: See more details in the ClearML [Guidelines for Contributing](https://github.com/allegroai/clearml/blob/master/docs/contributing.md). **PRs are always welcome** :heart: See more details in the ClearML [Guidelines for Contributing](https://github.com/clearml/clearml/blob/master/docs/contributing.md).
_May the force (and the goddess of learning rates) be with you!_ _May the force (and the goddess of learning rates) be with you!_

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setup.py
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@ -1,6 +1,6 @@
""" """
ClearML - Artificial Intelligence Version Control ClearML Inc
https://github.com/allegroai/clearml https://github.com/clearml/clearml
""" """
import os.path import os.path
@ -21,7 +21,7 @@ long_description = read_text(os.path.join(here, 'README.md'))
# fix github, dark logo hack. # fix github, dark logo hack.
long_description = long_description.replace( long_description = long_description.replace(
"""<img align="center" src="docs/clearml-logo.svg#gh-light-mode-only" alt="Clear|ML"><img align="center" src="docs/clearml-logo-dark.svg#gh-dark-mode-only" alt="Clear|ML">""", # noqa """<img align="center" src="docs/clearml-logo.svg#gh-light-mode-only" alt="Clear|ML"><img align="center" src="docs/clearml-logo-dark.svg#gh-dark-mode-only" alt="Clear|ML">""", # noqa
"""<a href="https://app.clear.ml"><img src="https://github.com/allegroai/clearml/blob/master/docs/clearml-logo.svg?raw=true" width="250px"></a>""", # noqa """<a href="https://app.clear.ml"><img src="https://github.com/clearml/clearml/blob/master/docs/clearml-logo.svg?raw=true" width="250px"></a>""", # noqa
1 1
) )
@ -46,7 +46,7 @@ setup(
long_description=long_description, long_description=long_description,
long_description_content_type='text/markdown', long_description_content_type='text/markdown',
# The project's main homepage. # The project's main homepage.
url='https://github.com/allegroai/clearml', url='https://github.com/clearml/clearml',
author='ClearML', author='ClearML',
author_email='support@clear.ml', author_email='support@clear.ml',
license='Apache License 2.0', license='Apache License 2.0',