https://github.com/jona42-ui/nmstate_nlp_module

Demo for using natural language to generate nmstate YAML for linux bridge
https://github.com/jona42-ui/nmstate_nlp_module

bridge linux networking nlp nmstate python python-script

Last synced: about 1 month ago
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Demo for using natural language to generate nmstate YAML for linux bridge

• Host: GitHub
• URL: https://github.com/jona42-ui/nmstate_nlp_module
• Owner: jona42-ui
• Created: 2024-03-19T08:17:57.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-03-19T08:54:24.000Z (10 months ago)
• Last Synced: 2024-03-19T09:36:18.673Z (10 months ago)
• Topics: bridge, linux, networking, nlp, nmstate, python, python-script
• Language: Python
• Homepage: https://nmstate.io/devel/design/networking-api.html
• Size: 255 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# nmstate_nlp_module

https://github.com/nmstate/nmstate/issues/2583

This small module basically demonstrates the power of NLP in network configuration I.e

Our demo project aims to develop a natural language interface that allows users to create Linux bridge configurations using simple, human-readable commands. The interface will leverage natural language processing (NLP) techniques to parse user input and generate YAML configurations compatible with nmstate, a declarative API for host network management in Linux.

[nlpdemo.webm](https://github.com/jona42-ui/nmstate_nlp_module/assets/78595738/ba6fac02-8bca-4466-88aa-cdf16c2dd3ab)

Currently, it's only extracting the interface name (eth1) from the natural language input and generating a configuration entry for it, but it's missing the bridge name (br0) and the second interface (eth2).

TODO: improving the output

# usage

1. clone the repo

2. install the dependencies

3. spaCy requires language models forexample for English language processing, you can download the small English model by running:

   python -m spacy download en_core_web_sm

4. Execute the script : 

python nmstate_nlp_demo.py

5. on prompt put an input like: Please create a linux bridge br0 using eth1 and eth2

6. analyse the output

NB:  we are parsing  and interpreting  user intentions directly from textual descriptions using NLP parsing not regex parsing on input