Personal Website with Interactive AI Chatbot

This repository contains the source code for a personal website built using Next.js. The website features an AI-powered chatbot connected to a backend built with Django and hosted on AWS EC2 with Nginx. The chatbot is capable of answering queries related to professional experience, skills, and personality traits by leveraging LangChain RAG and Agentic AI. Chat logs are stored securely on Azure for future reference. You can view the deployed personal website and interact with the AI chatbot at the following link:
https://manuvimal.vercel.app/

Features

• Interactive Chatbot: Engage with an AI chatbot that can remember context and uses LangChain RAG and Agentic AI to answer queries.
• Chat Log Storage: Stores chat logs in Azure using APIs defined in the Next.js backend.
• Seamless Deployment:
  • Frontend hosted on Vercel.
  • Backend hosted on AWS EC2 with Nginx.

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Project Structure

Frontend (Next.js)

• Hosted on Vercel.
• Includes:
  • A landing page introducing the website.
  • Chat interface to interact with the AI chatbot.
  • API endpoints for managing chat logs.

Backend (Django)

• Hosted on AWS EC2 with Nginx.
• Handles:
  • Chatbot functionality using LangChain RAG and Agentic AI.
  • Memory persistence for user sessions.
  • Integration with ChromaDB for vector storage.

Storage

• Chat Logs: Stored on Azure using APIs defined in the Next.js backend.

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Installation and Setup

Prerequisites

1. Frontend: Node.js 16+
2. Backend: Python 3.8+
3. Azure Storage Account
4. AWS EC2 Instance with Nginx configured.

Frontend Setup

1. Clone the repository:

   git clone https://github.com/manugeorge04/Portfolio_Website.git

2. Install dependencies:

   npm install

3. Configure environment variables: Create a .env.local file in the frontend folder with the following content:

   AZURE_STORAGE_KEY=your_azure_storage_key
   AZURE_STORAGE_ACCOUNT=your_azure_storage_account
   

4. Run the development server:

   npm run dev

5. Deploy to Vercel:

   • Follow Vercel's deployment guide to deploy the frontend.

Backend Setup

The backend for this project is based on the PersonaAI repository. Please refer to the PersonaAI GitHub Repository for detailed setup instructions, including environment configuration and dependencies.

Host the backend on AWS EC2 with Nginx as a reverse proxy.

By integrating the PersonaAI backend, you ensure a seamless AI chatbot experience on your website.

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Deployment

Frontend

• Deploy the Next.js app to Vercel using your Vercel account.

Backend

• Deploy the Django app to AWS EC2.
• Use Nginx to proxy requests to the Django server.

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Usage

1. Navigate to the deployed website.
2. Interact with the chatbot via the chat interface.
3. Chat logs are automatically stored in Azure for analysis and debugging.

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Technologies Used

• Frontend: Next.js, TailwindCSS
• Backend: Django, LangChain, ChromaDB
• Hosting: Vercel (Frontend), AWS EC2 + Nginx (Backend)
• Storage: Azure, ChromaDB
• AI Models: OpenAI (GPT-based LLM)