🧠 Pythonaibrain

Make your first AI Assistant in Python with just an intents.json file. No complex setup. No advanced coding. Just install, configure, and run!

🚀 Features

✅ Simple setup using JSON-based intents

🧠 Built-in NER (Named Entity Recognition) training

🔁 AI prediction and response handling

📚 Easy to integrate into chatbots

🔧 Installation

pip install pythonaibrain

🧪 Quick Start

1. Create an intents.json file like this:
   {
"intents": [
{
"tag": "greeting",
"patterns": ["Hi", "Hello", "How are you?"],
"responses": ["Hello!", "Hi there!", "Greetings!"]
},
{
"tag": "goodbye",
"patterns": ["Bye", "See you", "Goodbye"],
"responses": ["Goodbye!", "Take care!", "See you soon!"]
}
]
}


2. Create your Python file:
   `
   from os import system
   from pyai import Brain

brain = Brain("your/dataset/path/intents.json") # Enter Path of your dataset.

while True:
message = input('Message : ')
message_type = brain.predict_message_type(message)

if message_type == 'Question' or message_type == "Answer":
    brain.pyai_say(brain.process_messages(message))

if message_type == "Shutdown":
    system(message)

`

📦 Project Links

📌 PyPI: https://pypi.org/project/pythonaibrain/1.0.1/

🌐 GitHub: https://github.com/World-Of-Programming-And-Technology/PythonAI

🛠️ How It Works

NER Training: Tags patterns with named entities

Model Building: Learns from examples using deep learning

Prediction Engine: Returns the best matching response for input

❗ Trouble?

If you see an error like:

ValueError: num_samples should be a positive integer value, but got num_samples=0
Make sure your intents.json has at least one tag with non-empty patterns.

📜 License

LGPL-2.1 license – feel free to use, modify, and share!