Janex: PyTorch Edition
A free open-source framework which can be used to build Machine Learning tools, LLMs, and Natural Language Processing scripts with full simplicity. This edition of Janex is built reliant on the main Janex library, and utilises PyTorch and the Natural Language Toolkit to attempt a slightly different approach of Intent Classification.
How to use?
Firstly, you need to install the Janex: PyTorch Edition library.
pip install JanexPT
Secondly, you need to import JanexPT into your code.
from JanexPT import *
Next, create an instance of the JanexPT class and define the path to your intents, thesaurus, and the name you wish to give to your AI.
intents_file_path = "intents.json"
janexpt = JanexPT(intents_file_path)
Then, you will need to train your intents data into a pth file. If you do not have a training program, it will curl install the pre-built one from this repo.
janexpt.trainpt()
Next, you need to give the program some text you wish to send to your AI, and then send it.
YourInput = input("You: ")
classification = JanexPT.pattern_compare(YourInput)
print(classification)
And there we have it, the code will use a triple-layer NeuralNet to predict which class your input belongs in, and then uses the Janex library to pick the best response from those available.
Metadata
Release files for JanexPT 0.0.52
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| JanexPT-0.0.52.tar.gz | 6.8 kB | Without provenance | Details for JanexPT-0.0.52.tar.gz |
Release files / JanexPT-0.0.52.tar.gz
| Download URL | JanexPT-0.0.52.tar.gz |
|---|---|
| Size | 6.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2c4e0c40e08aa3dcc3cdb97ea719ceadfba1a1acb71920a2526c266dce74308f
|
|
BLAKE2b-256 checksum How to use checksums |
e6e33d85e88298bd625713f81f6d3c28d91ea0fa9768324113e725608500f76c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.8.0 colorama/0.4.4 importlib-metadata/4.6.4 keyring/23.5.0 pkginfo/1.8.2 readme-renderer/34.0 requests-toolbelt/0.9.1 requests/2.31.0 rfc3986/1.5.0 tqdm/4.66.1 urllib3/1.26.5 CPython/3.10.12
|
Security for JanexPT 0.0.52
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.