Metadata-Version: 2.1
Name: neuralite
Version: 0.0.3
Summary: A streamlined Python framework for rapidly building and deploying machine learning-based AIs.
Author: Dark25 (Ruben Roy)
Author-email: me@ruben-roy.com
Keywords: python,neural,machine learning,chatbots,chat,artificial intelligence,virtual assistant
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown


# Neuralite

*A Streamlined Python Framework for Rapidly Building and Deploying Machine Learning-Based Conversational Agents*



Build, deploy, and scale your AI projects with Neuralite! Whether you're a seasoned AI developer or just starting out, Neuralite offers a simple and efficient way to implement AI features into your software.



## Getting Started 🚀

To get started, install Neuralite with pip:

```bash

pip install Neuralite

```



## Basic Chatbot 🤖

Creating a basic chatbot is simple:

```python

from neuralite.interpreter import ai # Imports framework



assistant = ai('dataset.json') # Loads dataset



cycle_end = False # Starts the AI cycle



while not cycle_end: # Main cycle

    message = input("Enter a message: ") # Prompts user with message

    if message.lower() == "stop": # Exit with 'stop'

        cycle_end = True # Ends cycle

    else:

        print(assistant.process_input(message)) # Prints the response

```



# Customizable Training Epochs 🔄

Train your AI model with a customizable number of epochs. The higher the epochs, the more refined your model will be.

```python

from neuralite.interpreter import ai # Imports framework



# Initialize the AI model with 200 epochs

assistant = ai('dataset.json', epochs=200)



# Continue with your chatbot as usual

```



# Compiling Your Model 📦

To make your dataset unreadable, load faster, and to package it into a neat file.



```python

from neuralite.interpreter import ai # Imports framework



assistant = ai('dataset.json') # Loads dataset



assistant.compile('model.nlite') # Packages dataset to 'model.nlite'

```



# Loading a Compiled Model 🔓

To load a precompiled model.



```python

from neuralite.interpreter import ai # Imports framework



assistant = ai.compiled('model.nlite') # Loads the compiled model



cycle_end = False # Starts the AI cycle



while not cycle_end: # Main cycle

    message = input("Enter a message: ") # Prompts user with message

    if message.lower() == "stop": # Exit with 'stop'

        cycle_end = True # Ends cycle

    else:

        print(assistant.process_input(message)) # Prints the response

```

# Example Conversational Dataset 💬

```json

{

  "greeting": ["Hi", "Hello", "Hey there"],

  "greeting_responses": ["Hello!", "Hi, how can I help?", "Hey! What's up?"],

  "farewell": ["Goodbye", "See you", "Ciao"],

  "farewell_responses": ["Goodbye!", "See you soon!", "Take care!"],

  "how_are_you": ["How are you?", "How's it going?", "What's up?"],

  "how_are_you_responses": ["I'm good, thank you!", "I'm doing well. How about you?", "Not much, what about you?"],

  "compliment": ["You're great!", "You're amazing!", "You're awesome!"],

  "compliment_responses": ["Thank you! You're pretty awesome too.", "Thanks! You're great as well!", "Thanks! That means a lot."],

  "name": ["What's your name?", "Who are you?", "Tell me your name."],

  "name_responses": ["I'm Neuralite, your AI assistant.", "Call me Neuralite.", "I'm Neuralite! Nice to meet you."],

  "jokes": ["Tell me a joke.", "Do you know any jokes?", "Make me laugh."],

  "jokes_responses": ["Why did the scarecrow win an award? Because he was outstanding in his field!", "I told my computer I needed a break. Now it won't stop sending me Kit-Kats.", "Why did the math book look sad? Because it had too many problems."]

}

```
