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AI Support Bot with Custom Knowledgebase Integration

A full-stack chatbot application that uses RAGS to interact intelligently with users based on custom-loaded knowledgebases. It supports dynamic dataset loading for seamless updates. The chatbot’s language model is evaluated on relevance, accuracy, coherence, completeness, creativity, tone, and alignment with intent, ensuring high-quality, user-focused interactions.

Techstack used

  • React
  • Tailwindcss
  • FastAPI
  • ChromaDB
  • Langchain
  • OpenAI
  • Docker

Flowchart

This diagram illustrates the high level components involved and thier interaction Flowchart

Demo

Chatbot

ai_support_bot_demo.mp4

Project Configuration

Before running the project, make sure to adjust the following configuration files:

Backend Configuration

  • Adjust the .env file located in the backend folder if any environment variables need modification.

Start Containers

To start the project, use Docker Compose to build and run the containers:

docker compose up --build

Frontend URL

Once the containers are running, you can access the frontend application at:

http://localhost:5173/

Backend URL

Once the containers are running, you can access the backend application at:

http://localhost:8081/

Pending Improvements

  • Add SQL/NoSQL DB to store the user queries and generated reponses

https://github.com/pixegami/langchain-rag-tutorial