A starting point for a RAG AI Chatbot that acts as a sales agent for any website by scraping its data. This project has a Flask backend and a React frontend.
Make a copy of .env.backend.template and .env.frontend.template and modify them according to your configuration and place them as .env. in their respective folders.
Both the backend and frontend provide Dockerfiles to build docker images locally.
Use docker build -t rag-chat-backend . and docker build -t rag-chat-frontend . to build images.
Make a copy of .env.backend.template and .env.frontend.template and modify them according to your configuration and place them as .env.backend and .env.frontend next to the docker-compose.yml file.
The provided docker-compose.yml file runs a complete working example from the created docker images. Use dannycarrera/rag-ai-chatbot-backend and dannycarrera/rag-ai-chatbot-frontend to pull from the published repos instead.