AI Decision-Making Model

The AI Decision-Making Model is a machine learning-based solution designed to classify text input (such as questions or queries) into one of three categories: Yes, No, or Maybe. Built using Python, Scikit-learn, and Flask, this model leverages the Multinomial Naive Bayes algorithm to process natural language data. It is packaged as a simple REST API for easy integration into other applications.

Whether you're building an automated assistant, recommendation system, or decision-support tool, this model can be customized and extended to meet your needs. It is lightweight, easy to use, and deployable to platforms like Heroku.

Authors

• @3n881

Installation

To install this project run

Step 1: Clone the Repository

git clone https://github.com/your-username/ai-decision-making.git
cd ai-decision-making

Step 2: Create a Virtual Environment

On Windows:

python -m venv venv
venv\Scripts\activate

On macOS/Linux:

python3 -m venv venv
source venv/bin/activate

Step 3: Install Dependencies

pip install -r requirements.txt

Usage

Step 1: Train the Model

python train_model.py

Step 2: Run the Flask Application

python app.py

App will run at http://127.0.0.1:5000/

API Usage

Test the API Example Request (cURL):

curl -X POST http://127.0.0.1:5000/predict -H "Content-Type: application/json" -d '{"input": "Should I buy a new phone?"}'

Example Response:

{
  "decision": "Maybe"
}

Deployment

Deploy on Heroku Login to Heroku:

heroku login

Create a New App:

heroku create your-app-name

Deploy the App:

git push heroku master

Open the App:

heroku open