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CortexMind

CortexMind is a full-stack AI-powered chat application that simulates the functionality of modern large language model (LLM) platforms like ChatGPT and DeepSeek. This is a project that demonstrates several full-stack development skills, including real-time message streaming, authentication, API integration, and data persistence.


Screenshots

Chat in Progress (Real-Time Streaming with Code Blocks)

Clean, Responsive Chat Interface (Empty State)

Sidebar Displaying User Chat Sessions

When a user clicks on a chat session, a request is sent to the backend to fetch all messages for that session, populating the page with the existing chat history.

Response Style Selector

Controls the temperature parameter of the DeepSeek-chat model, allowing users to adjust response creativity and style. More information can be found here: DeepSeek Parameter Settings


Project Tech Stack

  • Frontend: React, Tailwind CSS, Zustand
  • Backend: Express.js, Node.js
  • Database: PostgreSQL
  • Authentication: Auth0
  • AI Integration: DeepSeek LLM API

Key Features

  • 🔹 Real-Time AI Chat
    Integrates with DeepSeek's deepseek-chat model to stream conversational responses incrementally.

  • 🔹 Responsive UI
    Built with React and Tailwind CSS for a sleek and responsive chat interface.

  • 🔹 User Authentication
    Secure login and session handling powered by Auth0, with chat history tied to user accounts.

  • 🔹 Persistent Storage
    All messages and sessions are stored in PostgreSQL.


How It Works

  1. Users log in through Auth0.
  2. Frontend sends prompts to the backend.
  3. Backend communicates with DeepSeek’s API, streams responses in real-time, and updates the database.
  4. Stored messages are retrieved from PostgreSQL per user session.

What I Learned

  • Building real-time, stream-based chat UX
  • Managing auth workflows across frontend and backend
  • Structuring scalable database schemas for user-generated content
  • Handling full-stack API integrations (LLM, Auth0, database)

Note

This project was created for portfolio and learning purposes. It is not intended for production use and may lack certain security or scalability optimizations.

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