This project implements a chatbot designed to answer questions about your resume and work experience conversationally. Using RAG (Retrieval-Augmented Generation), the bot leverages a knowledge base to respond with accurate, context-aware information about your professional background.
- Frontend: React
- Backend: Flask
- Reverse Proxy: Nginx
- Containerization & Orchestration: Docker & Docker Compose
- Language Model: Llama 3.2:3B (Meta)
Make sure the following are installed before proceeding:
- Docker: for containerization
- Docker Compose: to run and orchestrate the containers
- Ollama: required for interacting with the Llama 3.2:3B model
Follow these steps to set up and run the application locally:
-
Clone this repository: Download the project to your local machine.
git clone https://github.com/Mateorovere/My_ChatBot.git cd My_ChatBot -
Build and Run with Docker Compose:
docker-compose up --build
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Access the Chatbot: Open your web browser and go to http://localhost:3000/.
This chatbot integrates a Llama 3.2:3B model, using Ollama to interact with a custom knowledge base of your resume and professional experience. This setup enables thebot to provide factual, in-depth responses to user queries about your skills, projects, and work history.
- Contextual Responses: The chatbot can handle various questions about your background by retrieving relevant information and generating appropriate responses.
- Retrieval-Augmented Generation (RAG): Uses RAG to improve response accuracy by drawing from a curated knowledge base of your resume data.
- Interactive UI: The React frontend provides a user-friendly interface, allowing users to engage conversationally with the chatbot.