Metadata-Version: 2.1
Name: JanexPT
Version: 0.0.3
Home-page: https://github.com/Cipher58/Janex-Pytorch
Download-URL: https://github.com/Cipher58/Janex-Pytorch
Author: Cipher58
Author-email: cipher58public@gmail.com
License: Lily 1.0
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

# Janex
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.

<h3> How to use? </h3>

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, thesaurus_file_path, UIName = "intents.json", "thesaurus.json", "May" # Use whichever name you like.

JanexPT = JanexPT(intents_file_path, thesaurus_file_path, UIName)

```

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: ")
YourName = "Bob" # Whatever you wish your AI to refer to you as

Response = JanexPT.SayToAI(YourInput, YourName)

print(Response)
```

And there we have it, the code will use a NeuralNet to predict which class your input belongs in, and then uses the Janex library to pick the best response from those available.
