AI Chatbot for SMB Application

Many small businesses are eager to harness the power of AI, but the path from a simple idea to a reliable, production-grade application is often filled with unexpected challenges. An AI chatbot that works perfectly on a developer's laptop can easily fail in a real-world cloud environment.

I recently completed a project to build a production-ready Conversational AI (RAG) Chatbot, and the journey taught me that success isn't just about the AI model—it's about mastering the architecture that supports it.

Moving from a prototype to production is a tale of three critical domains: Robust Deployment, Code Resilience, and Interactive User Experience. It requires moving beyond simple scripts to containerized applications, writing defensive code that anticipates failure, and designing a user interface that is both intuitive and reliable.

I’ve distilled the key architectural decisions, deployment strategies, and solutions to the inevitable roadblocks into the interactive presentation below. I hope this visual summary of my learnings is useful for anyone else embarking on a similar journey.

Conversational RAG Chatbot

An interactive summary of the architecture and key learnings from building a production-ready AI application. Click on any component in the diagram below to explore the project's journey- By Amrish Menjoge.

Interactive Architecture Explorer

🖥️ Frontend: User Interface

⚙️ Backend: Logic & RAG Pipeline

🚀 Deployment: Infrastructure

Technology Stack

Streamlit

The core framework for building the interactive web user interface.

LangChain

The primary framework for orchestrating the entire RAG pipeline, from data processing to LLM interaction.

ChromaDB

The vector database used to store and retrieve document embeddings efficiently.

Koyeb

The cloud platform used for deploying and hosting the containerized application.

Docker

Used to containerize the application, defining a consistent and reproducible environment for deployment.

Nginx

Acts as a high-performance reverse proxy to improve the stability and connection handling of the Streamlit app.