https://github.com/pasteurlabs/tesseract-core
Universal, autodiff-native software components for Simulation Intelligence. 📦
https://github.com/pasteurlabs/tesseract-core
api-rest automatic-differentiation containers differentiable-programming remote-procedure-calls scientific-machine-learning
Last synced: about 1 month ago
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Universal, autodiff-native software components for Simulation Intelligence. 📦
- Host: GitHub
- URL: https://github.com/pasteurlabs/tesseract-core
- Owner: pasteurlabs
- License: apache-2.0
- Created: 2025-02-24T11:01:07.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-09-02T10:08:21.000Z (5 months ago)
- Last Synced: 2025-09-04T09:43:45.675Z (5 months ago)
- Topics: api-rest, automatic-differentiation, containers, differentiable-programming, remote-procedure-calls, scientific-machine-learning
- Language: Python
- Homepage: https://docs.pasteurlabs.ai/projects/tesseract-core/latest/
- Size: 14.4 MB
- Stars: 70
- Watchers: 4
- Forks: 4
- Open Issues: 30
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Codeowners: .github/CODEOWNERS
Awesome Lists containing this project
README
### Tesseract Core
Universal, autodiff-native software components for Simulation Intelligence. :package:
[Read the docs](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/) |
[Report an issue](https://github.com/pasteurlabs/tesseract-core/issues) |
[Talk to the community](https://si-tesseract.discourse.group/) |
[Contribute](https://github.com/pasteurlabs/tesseract-core/blob/main/CONTRIBUTING.md)
---
[](https://doi.org/10.21105/joss.08385)
**Tesseract Core** bundles:
1. Tools to define, create, and run Tesseracts, via the `tesseract` CLI and `tesseract_core` Python API.
2. The Tesseract Runtime, a lightweight, high-performance execution environment for Tesseracts.
## What is a Tesseract?
Tesseracts are components that expose experimental, research-grade software to the world. They are self-contained, self-documenting, and self-executing, via command line and HTTP. They are designed to be easy to create, easy to use, and easy to share, including in a production environment. This repository contains all you need to define your own and execute them.
Tesseracts provide built-in support for [differentiable programming](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/content/introduction/differentiable-programming.html) by propagating gradient information at the level of individual components, making it easy to build complex, diverse software pipelines that can be optimized end-to-end.
## Quick start
> [!NOTE]
> Before proceeding, make sure you have a [working installation of Docker](https://docs.docker.com/engine/install/) and a modern Python installation (Python 3.10+); if you prefer Docker Desktop for your platform, see [our extended installation instructions](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/content/introduction/installation.html#basic-installation).
1. Install Tesseract Core:
```bash
$ pip install tesseract-core
```
2. Build an example Tesseract:
```bash
$ git clone https://github.com/pasteurlabs/tesseract-core
$ tesseract build tesseract-core/examples/vectoradd
```
3. Display its API documentation:
```bash
$ tesseract apidoc vectoradd
```
4. Run the Tesseract:
```bash
$ tesseract run vectoradd apply '{"inputs": {"a": [1], "b": [2]}}'
{"result":{"object_type":"array","shape":[1],"dtype":"float64","data":{"buffer":[3.0],"encoding":"json"}}}⏎
```
> [!TIP]
> Now you're ready to dive into the [documentation](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/) for more information on
> [installation](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/content/introduction/installation.html),
> [creating Tesseracts](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/content/creating-tesseracts/create.html), and
> [invoking them](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/content/using-tesseracts/use.html).
## License
Tesseract Core is licensed under the [Apache License 2.0](https://github.com/pasteurlabs/tesseract-core/blob/main/LICENSE) and is free to use, modify, and distribute (under the terms of the license).
Tesseract is a registered trademark of Pasteur Labs, Inc. and may not be used without permission.