Metadata-Version: 2.4
Name: ai4science
Version: 0.1.1
Summary: A Hugging Face-style framework for AI-powered scientific workflows across biology, chemistry, physics, and other scientific domains.
Author-email: Shaobo Cui <shaobo.cui@sjtu.edu.cn>
License: Apache-2.0
Project-URL: Homepage, https://github.com/cui-shaobo/ai4science
Project-URL: Repository, https://github.com/cui-shaobo/ai4science
Project-URL: Issues, https://github.com/cui-shaobo/ai4science/issues
Project-URL: Documentation, https://github.com/cui-shaobo/ai4science/tree/main/docs
Keywords: ai4science,scientific ai,biology,chemistry,physics,bioinformatics,plugins,transformers-like,machine learning
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Typing :: Typed
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Provides-Extra: biology
Requires-Dist: ai4science-biology>=0.1.0; extra == "biology"
Provides-Extra: all
Requires-Dist: ai4science-biology>=0.1.0; extra == "all"
Dynamic: license-file

# ai4science (core)

ai4science is a small, stable framework for AI-for-Science components with a Transformers-like user experience:

- unified `from_pretrained()` / `save_pretrained()`
- plugin-based domains
- predictable I/O container (`Batch`) and composition via `pipeline()`

Install core:

```bash
pip install ai4science
```

Install domain plugins:

```bash
pip install ai4science[biology]
# or
pip install ai4science-biology
```

## Minimal example

```python
from ai4science import AutoTool

tool = AutoTool.from_pretrained("ai4science-biology/seq-cleaner")
print(tool({"sequence": "MKT..xxAA"}))
```
