shennongname 1.1.0

ShennongName (神农命名)

shennongname

Documentation

The documentation for shennongname is available on the documentation website of the ShennongAlpha (ShennongDoc):

• English
• 中文

You can also contribute to the documentation on the ShennongDoc GitHub repository by submitting a pull request:

• English
• 中文

Systematic Nomenclature for Natural Medicinal Materials Algorithm (SNNMMA)

The following code shows how to use shennongname Python package to construct an NMM systematic name (NMMSN).

from shennongname.snnmma.algorithm import construct_nmmsn
from shennongname.snnmma.model import NmmsnNameElement

# Construct a Natural Medicinal Material Scientific Name (NMMSN)
input = NmmsnNameElement.model_validate(
    {
        'nmm_type': 'processed',
        'species_origins': [['Ephedra sinica', '草麻黄'], 'or', ['Ephedra intermedia', '中麻黄'], 'or', ['Ephedra equisetina', '木贼麻黄']],
        'medicinal_parts': [['stem herbaceous', '草质茎']],
        'special_descriptions': [],
        'processing_methods': [['segmented', '段制'], 'and', ['aquafried honey', '蜜炙制']]
    }
)

construct_nmmsn(input).model_dump()

The output is a Python dictionary:

{
    'success': True,
    'error_msg': 'Pipe: construct_nmmsn_spe_ori. Status: warning. Reason: Multiple species origins detected.',
    'error_msg_en_zh': {
        'en': 'Multiple species origins detected.',
        'zh': '检测到多个物种基源。'
    },
    'nmmsn': {
        'nmmsn': 'Ephedra equisetina vel intermedia vel sinica Stem-herbaceous Segmented and Aquafried-honey',
        'nmmsn_zh': {
            'zh': '蜜炙制段制木贼麻黄或中麻黄或草麻黄草质茎',
            'pinyin': 'mì zhì zhì duàn zhì mù zéi má huáng huò zhōng má huáng huò cǎo má huáng cǎo zhì jīng'
        },
        'nmmsn_name_element': {
            'nmm_type': 'processed',
            'species_origins': [['Ephedra equisetina', '木贼麻黄'], 'or', ['Ephedra intermedia', '中麻黄'], 'or', ['Ephedra sinica', '草麻黄']],
            'medicinal_parts': [['stem herbaceous', '草质茎']],
            'special_descriptions': [],
            'processing_methods': [['segmented', '段制'], 'and', ['aquafried honey', '蜜炙制']]
        },
        'nmmsn_seq': [['Ephedra equisetina vel intermedia vel sinica', '木贼麻黄或中麻黄或草麻黄'], ['Stem-herbaceous', '草质茎'], ['', ''], ['Segmented and Aquafried-honey', '蜜炙制段制']]
    }
}

Start ShennongName Flask Server

The shennongname package also provides a Flask server for constructing NMMSNs.

1. Configure the .env file

cp .env.example .env

2. Install shennongname package

pip install .

3. Run the Flask server

# Production
gunicorn -b 0.0.0.0:5001 shennongname.flask.run:app

# Development
python3 shennongname/flask/run.py

Start ShennongName Flask Server with Docker

You can also use Docker to run the Flask server.

docker build -t shennongname .
docker run -d -p 5001:5001 shennongname

Cite this work

@misc{yang2024shennongalphaaidrivensharingcollaboration,
      title={ShennongAlpha: an AI-driven sharing and collaboration platform for intelligent curation, acquisition, and translation of natural medicinal material knowledge}, 
      author={Zijie Yang and Yongjing Yin and Chaojun Kong and Tiange Chi and Wufan Tao and Yue Zhang and Tian Xu},
      year={2024},
      eprint={2401.00020},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2401.00020}, 
}