Metadata-Version: 2.4
Name: simaticai
Version: 2.9.0
Summary: AI Software Development Kit
License: MIT
Author: Siemens AG
Requires-Python: >=3.10.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
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Requires-Dist: onnx (>=1.20)
Requires-Dist: onnxruntime (>=1.22)
Requires-Dist: opencv-python-headless (>=4.9.0.80)
Requires-Dist: pip (>=26.0)
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Requires-Dist: wheel (>=0.46.2)
Project-URL: Changelog, https://github.com/industrial-edge/ai-sdk/blob/main/CHANGELOG.md
Project-URL: Documentation, https://github.com/industrial-edge/ai-sdk-tutorials
Project-URL: Homepage, https://www.siemens.com/global/en/products/automation/topic-areas/industrial-ai/industrial-ai-suite.html
Project-URL: Issues, https://github.com/industrial-edge/ai-sdk/issues
Project-URL: Repository, https://github.com/industrial-edge/ai-sdk.git
Description-Content-Type: text/markdown

<img src="https://github.com/industrial-edge/ai-sdk/raw/main/documentation/assets/images/logo-siemens.png" width="120px" />
<br/>

# AI Software Development Kit
## Siemens AG - Industrial AI Suite
### Streamline Industrial AI Development and Deployment
 
The AI Software Development Kit (the `simaticai` Python Package) is a comprehensive Python library designed to simplify the creation, packaging, and testing of AI inference pipelines for the `Industrial AI Suite`. Part of Siemens' Industrial Edge ecosystem, this SDK accelerates the integration of AI solutions into manufacturing environments.

### Key Features
+ **Complete ML Pipeline Support**: Create and package AI inference pipelines with ease
+ **Notebook-Based Tutorials**: Ready-to-use [End to End Tutorials](https://github.com/industrial-edge/ai-sdk-tutorials/) for model training and deployment
+ **Industrial Edge Integration**: Seamless connectivity with SIMATIC and Industrial Edge infrastructure
+ **Cloud Compatibility**: Native integration with leading cloud-based ML environments (such as [Microsoft Azure](https://github.com/industrial-edge/reference-architecture-for-industrial-ai-on-azure)) <br>
+ **GPU Acceleration**: Optimized for NVIDIA GPU-powered Industrial PCs
+ **Production-Ready**: Built for industrial-grade reliability and performance

### Python support
+ simaticai python library 2.9.0 is installable and operable under 3.10+ Python environments
+ library is integration tested with the latest versions of Python 3.10, 3.11 and 3.12 at the time of writing
+ Python version for pipeline components is limited to 3.11 and 3.12 because AI Inference Server only supports these environments

Please be aware of the above information when you create, package and test your inference pipelines before deploying them on AI Inference Server. 

### Quick Links
#### Documentation & Resources
+ [Industrial AI Suite Overview](https://www.siemens.com/global/en/products/automation/topic-areas/industrial-ai/industrial-ai-suite.html) <br>
+ [Developer Documentation](http://docs.industrial-operations-x.siemens.cloud/access?ft:title=AI%20SDK%20Operation%20Manual&Language=en-US) <br>
+ [AI SDK Tutorials](https://github.com/industrial-edge/ai-sdk-tutorials) <br>
+ [Microsoft Azure Reference Architecture](https://github.com/industrial-edge/reference-architecture-for-industrial-ai-on-azure)

#### Support
+ Enterprise-grade Siemens support <br>
+ Industrial Edge ecosystem backing <br>
+ Regular updates and security patches <br>
+ Technical consultation available <br>
+ Website: https://support.industry.siemens.com/

### Quick Start
The code examples only represent the main steps to create an AI Inference Pipeline using Package simaticai, to enjoy the full experience, please study the [public tutorials](https://github.com/industrial-edge/ai-sdk-tutorials/) or discover the [code repository](https://github.com/industrial-edge/ai-sdk) on Github.

### Create an AI inference pipeline
```python
from simaticai.deployment import PythonComponent, Pipeline
# creating a Pipeline Step for classification
classification = PythonComponent(name="classification")

# [..] additional steps to add resources and defining the environment

# creating of the Pipeline
pipeline = Pipeline("Image Classification")
# adding the classification step
pipeline.add_component(classification)

# [..] final steps to define the Pipeline properties and behavior
```

### Package for deployment
```python
# saving the Pipeline for deployment
package_path = pipeline.export("./deploy")
```

### Prerequisites
+ Python >=3.10
+ pip >= 21.3.1 (automatically upgraded during installation)
+ Compatible with Industrial Edge devices
+ NVIDIA GPU support (recommended)

## Why choose AI SDK?
🏭 Bridge the gap between AI development and shop floor deployment <br>
🚀 Accelerate time-to-value for industrial AI solutions <br>
🔄 Streamline ML operations across multiple locations <br>
🛠️ User-friendly tools for automation engineers <br>
🔌 Native integration with SIMATIC and Industrial Edge ecosystem <br>
☁️ Cloud-ready architecture

## Part of Industrial AI Suite
This SDK is a core component of the Industrial AI Suite, which provides:
+ Seamless cloud integration <br>
+ Complete MLOps infrastructure <br>
+ Multi-location model scaling <br>
+ Industrial Edge ecosystem integration <br>
+ User-friendly deployment tools <br>
+ Production monitoring capabilities <br>


## Benefits
### For Data Scientists
+ Focus on model development while we handle deployment <br>
+ Familiar notebook-based workflows <br>
+ Seamless integration with existing ML tools <br>
+ Support for most used frameworks and multiple libraries <br>

### For Automation Engineers
+ No prior data science experience required <br>
+ User-friendly deployment interfaces <br>
+ Integrated monitoring solutions <br>

### For Operations
+ Scale AI solutions across locations <br>
+ Reliable industrial-grade performance <br>
+ Fast return on investment <br>

# License
MIT license - Contact Siemens for licensing options

