MStack Course Lecture Notes

Overview

• Instructor: Nickel
• Purpose: Building an AI chatbot like ChatGPT using the MStack.
  • MStack: MongoDB, Express, React, Node.js
  • Integrating OpenAI's capabilities
  • Production-ready, scalable, secure SaaS chatbot platform

Application Features

• Responsive Web Page: Works on any screen size.
• Authentication: Users can log in and register.
• Chat Functionality: Users can communicate with the chatbot.
• Database: Conversations stored in MongoDB.
• Code Block Support: Chatbot can display code snippets.
• Session Management: Sessions valid for 7 days with HTTP-only cookies.

Demo Sections

• Home Screen: Users can log in/register and start conversations.
• User Interface:
  • Display chatbot responses with code snippets.
  • Clear conversation functionality.
  • Responsive design.
• Security:
  • Cookies are HTTP-only.
  • Token revalidation for security.

Tech Stack Details

Backend

• Node.js & Express: For creating REST APIs.
• MongoDB: For efficient data storage and retrieval.
• Auth & Security: Bcrypt for password encryption, JWT for tokens, HTTP-only cookies.

Frontend

• React & Material UI: For creating dynamic and responsive UIs.
• State Management: Using Context API for global state.

Implementing the Backend

1. Setup Express Application: Configure routes, middlewares.
2. Database Connection: Connect to MongoDB Cloud.
3. API Keys & Security:
   • OpenAI API integration.
   • Store API keys securely.
4. Authentication System:
   • Sign up, login, and session management endpoints.
   • Middleware for data validation and token verification.
5. Chat Functionality:
   • Integrate with OpenAI's GPT-3.5 Turbo.
   • Handle chat completions, store and retrieve chats.

Key Functions and Middleware

Middlewares

• Data Validation: Using express-validator.
• Token Verification: Middleware to check if a user token is valid.
• Role Assignment: Differentiate between user and assistant roles.

API Endpoints

• Sign Up: Create new users, hash passwords before storing.
• Login: Authenticate users, return tokens, and set cookies.
• Logout: Clear session cookies.
• Fetch Chats: Retrieve user chats.
• Post New Chat: Add new messages and get responses from OpenAI.
• Clear Conversations: Remove all user chats from the database.

Models and Schemas

• User Model: Contains user details, password, and chat logs.
• Chat Schema: Stores each chat with role and content.

Frontend Implementation

1. Setting Up React with Vite: Faster build times and smaller bundles.
2. Material UI Integration: For pre-built UI components and styling.
3. Authentication Management: Using Context API for global state.
4. API Communication: Axios for making HTTP requests.
5. Chat Page:
   • Components: Chat items, input fields, and send buttons.
   • Context Use: Fetch user details and chat logs on page load.
6. Animations: Integrate typing animation for a dynamic UI.
7. Protected Routes: Ensure only authenticated users can access chat functionalities.
8. Logout Handling: Clear authentication tokens.

Final Touches

• Responsiveness: Ensure the UI works well on all screen sizes.
• Code Block Rendering: Handle code snippets in chat messages using react-syntax-highlighter.
• Footer and Other UI Elements: Build with consistent design practices.
• Error Handling and Notifications: Use toast notifications for user feedback.

Summary and Success

• Mon Stack Mastery: Proficient in MongoDB, Express.js, React.js, Node.js.
• Full Stack Development: Build secure and scalable full-stack applications.
• OpenAI Integration: Seamless integration of AI chat functionality.
• Modern UI/UX: Leveraging Material UI for responsive, interactive user interfaces.

Action Items:

• Like and subscribe to the instructor's YouTube channel for more tutorials.
• Use this project to apply for job opportunities and showcase in resumes.