ClearML/clearml-agent
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LICENSE
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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 2019 allegro.ai 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.

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README.md
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<div align="center"> <div align="center">
<img src="https://github.com/allegroai/clearml-agent/blob/master/docs/clearml_agent_logo.png?raw=true" width="250px"> <img src="https://github.com/clearml/clearml-agent/blob/master/docs/clearml_agent_logo.png?raw=true" width="250px">
**ClearML Agent - MLOps/LLMOps made easy **ClearML Agent - MLOps/LLMOps made easy
MLOps/LLMOps scheduler & orchestration solution supporting Linux, macOS and Windows** MLOps/LLMOps scheduler & orchestration solution supporting Linux, macOS and Windows**
[![GitHub license](https://img.shields.io/github/license/allegroai/clearml-agent.svg)](https://img.shields.io/github/license/allegroai/clearml-agent.svg) [![GitHub license](https://img.shields.io/github/license/clearml/clearml-agent.svg)](https://img.shields.io/github/license/clearml/clearml-agent.svg)
[![PyPI pyversions](https://img.shields.io/pypi/pyversions/clearml-agent.svg)](https://img.shields.io/pypi/pyversions/clearml-agent.svg) [![PyPI pyversions](https://img.shields.io/pypi/pyversions/clearml-agent.svg)](https://img.shields.io/pypi/pyversions/clearml-agent.svg)
[![PyPI version shields.io](https://img.shields.io/pypi/v/clearml-agent.svg)](https://img.shields.io/pypi/v/clearml-agent.svg) [![PyPI version shields.io](https://img.shields.io/pypi/v/clearml-agent.svg)](https://img.shields.io/pypi/v/clearml-agent.svg)
[![PyPI Downloads](https://pepy.tech/badge/clearml-agent/month)](https://pypi.org/project/clearml-agent/) [![PyPI Downloads](https://pepy.tech/badge/clearml-agent/month)](https://pypi.org/project/clearml-agent/)
[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/allegroai)](https://artifacthub.io/packages/search?repo=allegroai) [![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/clearml)](https://artifacthub.io/packages/search?repo=clearml)
`🌟 ClearML is open-source - Leave a star to support the project! 🌟` `🌟 ClearML is open-source - Leave a star to support the project! 🌟`
@ -33,21 +33,21 @@ It is a zero configuration fire-and-forget execution agent, providing a full ML/
**Full Automation in 5 steps** **Full Automation in 5 steps**
1. ClearML Server [self-hosted](https://github.com/allegroai/clearml-server) 1. ClearML Server [self-hosted](https://github.com/clearml/clearml-server)
or [free tier hosting](https://app.clear.ml) or [free tier hosting](https://app.clear.ml)
2. `pip install clearml-agent` ([install](#installing-the-clearml-agent) the ClearML Agent on any GPU machine: 2. `pip install clearml-agent` ([install](#installing-the-clearml-agent) the ClearML Agent on any GPU machine:
on-premises / cloud / ...) on-premises / cloud / ...)
3. Create a [job](https://clear.ml/docs/latest/docs/apps/clearml_task) or 3. Create a [job](https://clear.ml/docs/latest/docs/apps/clearml_task) or
add [ClearML](https://github.com/allegroai/clearml) to your code with just 2 lines of code add [ClearML](https://github.com/clearml/clearml) to your code with just 2 lines of code
4. Change the [parameters](#using-the-clearml-agent) in the UI & schedule for [execution](#using-the-clearml-agent) (or 4. Change the [parameters](#using-the-clearml-agent) in the UI & schedule for [execution](#using-the-clearml-agent) (or
automate with an [AutoML pipeline](#automl-and-orchestration-pipelines-)) automate with an [AutoML pipeline](#automl-and-orchestration-pipelines-))
5. :chart_with_downwards_trend: :chart_with_upwards_trend: :eyes: :beer: 5. :chart_with_downwards_trend: :chart_with_upwards_trend: :eyes: :beer:
"All the Deep/Machine-Learning DevOps your research needs, and then some... Because ain't nobody got time for that" "All the Deep/Machine-Learning DevOps your research needs, and then some... Because ain't nobody got time for that"
**Try ClearML now** [Self Hosted](https://github.com/allegroai/clearml-server) **Try ClearML now** [Self Hosted](https://github.com/clearml/clearml-server)
or [Free tier Hosting](https://app.clear.ml) or [Free tier Hosting](https://app.clear.ml)
<a href="https://app.clear.ml"><img src="https://github.com/allegroai/clearml-agent/blob/master/docs/screenshots.gif?raw=true" width="100%"></a> <a href="https://app.clear.ml"><img src="https://github.com/clearml/clearml-agent/blob/master/docs/screenshots.gif?raw=true" width="100%"></a>
### Simple, Flexible Experiment Orchestration ### Simple, Flexible Experiment Orchestration
@ -71,7 +71,7 @@ or [Free tier Hosting](https://app.clear.ml)
We think Kubernetes is awesome, but it is not a must to get started with remote execution agents and cluster management. We think Kubernetes is awesome, but it is not a must to get started with remote execution agents and cluster management.
We designed `clearml-agent` so you can run both bare-metal and on top of Kubernetes, in any combination that fits your environment. We designed `clearml-agent` so you can run both bare-metal and on top of Kubernetes, in any combination that fits your environment.
You can find the Dockerfiles in the [docker folder](./docker) and the helm Chart in https://github.com/allegroai/clearml-helm-charts You can find the Dockerfiles in the [docker folder](./docker) and the helm Chart in https://github.com/clearml/clearml-helm-charts
#### Benefits of integrating existing Kubernetes cluster with ClearML #### Benefits of integrating existing Kubernetes cluster with ClearML
@ -86,8 +86,8 @@ You can find the Dockerfiles in the [docker folder](./docker) and the helm Chart
- **Enterprise Features**: RBAC, vault, multi-tenancy, scheduler, quota management, fractional GPU support - **Enterprise Features**: RBAC, vault, multi-tenancy, scheduler, quota management, fractional GPU support
**Run the agent in Kubernetes Glue mode an map ClearML jobs directly to K8s jobs:** **Run the agent in Kubernetes Glue mode an map ClearML jobs directly to K8s jobs:**
- Use the [ClearML Agent Helm Chart](https://github.com/allegroai/clearml-helm-charts/tree/main/charts/clearml-agent) to spin an agent pod acting as a controller - Use the [ClearML Agent Helm Chart](https://github.com/clearml/clearml-helm-charts/tree/main/charts/clearml-agent) to spin an agent pod acting as a controller
- Or run the [clearml-k8s glue](https://github.com/allegroai/clearml-agent/blob/master/examples/k8s_glue_example.py) on - Or run the [clearml-k8s glue](https://github.com/clearml/clearml-agent/blob/master/examples/k8s_glue_example.py) on
a Kubernetes cpu node a Kubernetes cpu node
- The clearml-k8s glue pulls jobs from the ClearML job execution queue and prepares a Kubernetes job (based on provided - The clearml-k8s glue pulls jobs from the ClearML job execution queue and prepares a Kubernetes job (based on provided
yaml template) yaml template)
@ -151,7 +151,7 @@ The ClearML Agent executes experiments using the following process:
#### System Design & Flow #### System Design & Flow
<img src="https://github.com/allegroai/clearml-agent/blob/master/docs/clearml_architecture.png" width="100%" alt="clearml-architecture"> <img src="https://github.com/clearml/clearml-agent/blob/master/docs/clearml_architecture.png" width="100%" alt="clearml-architecture">
#### Installing the ClearML Agent #### Installing the ClearML Agent
@ -279,7 +279,7 @@ clearml-agent daemon --detached --gpus 0 --queue default --docker nvidia/cuda:11
### How do I create an experiment on the ClearML Server? <a name="from-scratch"></a> ### How do I create an experiment on the ClearML Server? <a name="from-scratch"></a>
* Integrate [ClearML](https://github.com/allegroai/clearml) with your code * Integrate [ClearML](https://github.com/clearml/clearml) with your code
* Execute the code on your machine (Manually / PyCharm / Jupyter Notebook) * Execute the code on your machine (Manually / PyCharm / Jupyter Notebook)
* As your code is running, **ClearML** creates an experiment logging all the necessary execution information: * As your code is running, **ClearML** creates an experiment logging all the necessary execution information:
- Git repository link and commit ID (or an entire jupyter notebook) - Git repository link and commit ID (or an entire jupyter notebook)
@ -326,21 +326,21 @@ The ClearML Agent can also be used to implement AutoML orchestration and Experim
ClearML package. ClearML package.
Sample AutoML & Orchestration examples can be found in the Sample AutoML & Orchestration examples can be found in the
ClearML [example/automation](https://github.com/allegroai/clearml/tree/master/examples/automation) folder. ClearML [example/automation](https://github.com/clearml/clearml/tree/master/examples/automation) folder.
AutoML examples: AutoML examples:
- [Toy Keras training experiment](https://github.com/allegroai/clearml/blob/master/examples/optimization/hyper-parameter-optimization/base_template_keras_simple.py) - [Toy Keras training experiment](https://github.com/clearml/clearml/blob/master/examples/optimization/hyper-parameter-optimization/base_template_keras_simple.py)
- In order to create an experiment-template in the system, this code must be executed once manually - In order to create an experiment-template in the system, this code must be executed once manually
- [Random Search over the above Keras experiment-template](https://github.com/allegroai/clearml/blob/master/examples/automation/manual_random_param_search_example.py) - [Random Search over the above Keras experiment-template](https://github.com/clearml/clearml/blob/master/examples/automation/manual_random_param_search_example.py)
- This example will create multiple copies of the Keras experiment-template, with different hyperparameter - This example will create multiple copies of the Keras experiment-template, with different hyperparameter
combinations combinations
Experiment Pipeline examples: Experiment Pipeline examples:
- [First step experiment](https://github.com/allegroai/clearml/blob/master/examples/automation/task_piping_example.py) - [First step experiment](https://github.com/clearml/clearml/blob/master/examples/automation/task_piping_example.py)
- This example will "process data", and once done, will launch a copy of the 'second step' experiment-template - This example will "process data", and once done, will launch a copy of the 'second step' experiment-template
- [Second step experiment](https://github.com/allegroai/clearml/blob/master/examples/automation/toy_base_task.py) - [Second step experiment](https://github.com/clearml/clearml/blob/master/examples/automation/toy_base_task.py)
- In order to create an experiment-template in the system, this code must be executed once manually - In order to create an experiment-template in the system, this code must be executed once manually
### License ### License

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setup.py
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""" """
ClearML Inc. ClearML Inc.
CLEARML-AGENT DevOps for machine/deep learning CLEARML-AGENT DevOps for machine/deep learning
https://github.com/allegroai/clearml-agent https://github.com/clearml/clearml-agent
""" """
import os.path import os.path
@ -39,7 +39,7 @@ 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-agent', url='https://github.com/clearml/clearml-agent',
author='clearml', author='clearml',
author_email='clearml@clearml.ai', author_email='clearml@clearml.ai',
license='Apache License 2.0', license='Apache License 2.0',