📊 Dynamic Pipeline Platform (React + Vite)

A modern web-based platform for building, visualizing, and managing end-to-end machine learning pipelines. It supports interactive pipeline stages, reporting, knowledge graphs, and admin management features.

🎥 Demo

Watch the project demo on YouTube:

Or click here: https://youtu.be/zhy_DKZh07o?si=nPciWyuvFxrJ1yxd

🚀 Features

🧠 Dynamic ML Pipeline Builder

• Preprocessing
• EDA (Exploratory Data Analysis)
• Feature Engineering
• Model Selection
• Training
• Evaluation
• Deployment

📊 Visualization Tools

• Pipeline step visualization
• Charts and metrics (Recharts)
• Knowledge Graph view

📁 Dataset Management

• Upload datasets
• View processed results
• Report generation

🔐 Authentication System

• Login / Signup
• Password reset / forgot password

🧑‍💼 Admin Dashboard

• Manage users
• View reports
• Handle complaints

💬 Communication

• Messages module
• Chat widget support

🏗️ Project Structure

src/
├── Components/
│   ├── Hooks/ # Custom React hooks
│   ├── Other/
│   │   ├── CardsCarousel/
│   │   ├── Carousel/
│   │   ├── ChatWidget/
│   │   ├── KnowledgeGraph/
│   │   ├── Loader/
│   │   ├── Pagination/
│   │   ├── ReportStepper/
│   │   └── Visualization/
│   ├── Pages/
│   │   ├── HomePage/
│   │   ├── Login/
│   │   ├── SignUp/
│   │   ├── UploadDataset/
│   │   ├── Reports/
│   │   ├── ViewReport/
│   │   ├── KnowledgeGraph/
│   │   ├── Dynamic/ # Main pipeline flow
│   │   │   ├── DynamicPreprocessing/
│   │   │   ├── DynamicEda/
│   │   │   ├── DynamicFeatureEngineering/
│   │   │   ├── DynamicModelSelection/
│   │   │   ├── DynamicTraining/
│   │   │   ├── DynamicEvaluation/
│   │   │   └── DynamicDeployment/
│   │   ├── AdminUsers/
│   │   ├── AdminReports/
│   │   └── AdminComplaints/
│   └── Sections/
│       ├── NavBar/
│       ├── SideBar/
│       └── Footer/
├── Layouts/
└── assets/
└── dynamic_pipeline/
└── (generated pipeline visualizations)

📌 Tech Stack

• React
• Vite
• Redux
• React Flow
• Recharts
• Radix
• Mongo
• Express

⚙️ Environment Setup

Use env.example as a sample file to create your local .env file before starting the app.

cp env.example .env

🤖 AI Server

Run the AI server with api.py:

python api.py

🔗 Repository Links

• Frontend / Backend: https://github.com/ahany42/DTD-Website
• AI server: https://github.com/ahany42/DTD-Automl

🧩 Core Idea

This platform automates and visualizes the full ML lifecycle, making it easier to:

• Build pipelines step-by-step
• Track model performance
• Visualize transformations
• Deploy models efficiently