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ACTIVE DEVELOPMENT

AI Chat with RAG

Production-ready AI chat with Retrieval-Augmented Generation

GitHub
Java 17 Spring Boot 3.2 Python 3.11+ Flask Langchain FAISS OpenAI H2 Database
AI Chat with RAG

The Problem I Solved

Building this RAG-powered chat application presented unique challenges in integrating multiple technology stacks. Bridging Java and Python services required careful API design and error handling. Implementing efficient vector search with FAISS while maintaining response latency was crucial.

Duration
Completed
Role
Solo Project
Status
In Development
KEY FEATURES

What Makes It Special

RAG-Powered Responses

Intelligent answers using document context for accurate, relevant responses

Desktop UI

Java Swing interface with custom hot reload for rapid development

REST API Backend

Spring Boot for scalable service architecture

AI/ML Processing

Python Flask service with Langchain integration

Vector Search

FAISS integration for efficient similarity search

Inside the Project

AI Chat Screenshot 1 AI Chat Screenshot 2 AI Chat Screenshot 3

Screenshots from the AI Chat application

Built with modern stack

See full dependencies
Java 17 •
Spring Boot 3.2 •
Maven •
Java Swing •
Python 3.11+ •
Flask •
Langchain •
FAISS •
OpenAI •
H2 Database

Interested in this project?

Let's discuss how I can bring similar solutions to your team.

Let's connect
or check out the source code on GitHub