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DataWise AI

DataWise AI is an automated machine learning and data analysis platform that converts CSV data into insights, models, and visualizations.

Quick Start

The platform is fully containerized using Docker.

1. Configuration

Create a .env file in the root directory:

GOOGLE_API_KEY=your_gemini_api_key_here

2. Execution

Launch the ecosystem using Docker Compose:

docker-compose up -d --build

Access the dashboard at http://localhost:3000.

Running Backend Only

If you prefer to run the backend without Docker:

  1. Ensure Python 3.12+ is installed.
  2. Install dependencies: pip install -r requirements.txt
  3. Set your environment variable: GOOGLE_API_KEY=your_key
  4. Run: python app/main.py

Datasets

The platform accepts any standard CSV file up to 50MB.

Using Sample Data

Several pre-verified datasets are available in the TestDatasets/ directory for immediate testing:

  • Car price prediction (Regression)
  • Amazon sales trends (Time-series/Sales)
  • Supermarket analytics (Retail)
  • Credit card churn (Classification)

Custom Data

Upload your own CSV directly through the dashboard interface once the system is running.

Project Architecture

  • Frontend: React-based dashboard served via Nginx.
  • Backend: Flask API orchestrating ML and Data Analysis logic.
  • Output: All runtime artifacts (scripts, logs, and plots) are stored in the output/ directory.

Verification

To verify the pipeline independently of the UI, run the automated test suite. It will automatically upload the sample car price dataset to the backend and execute the full ML flow:

# Basic test against Docker (localhost:3000) or local (localhost:5000)
python test_pipeline.py --host http://localhost:5000

Manual API Usage

To pass a dataset manually to the backend API, send a POST request to /api/home with:

  • Header: multipart/form-data
  • Body: A file field named file-upload containing your CSV.
  • Body: A text field named queryInput describing your analysis goal.

Tech Stack

  • Backend: Python 3.12 (Flask, Pandas, Scikit-Learn).
  • Frontend: React 18 (MUI).
  • AI: Google Gemini (2.0 Flash).

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