Human-Robot Interaction (HRI)

This README provides a simple guide to set up and run a LLM-RAG system utilizing Ollama, an open-source platform for running large language models locally.

Prerequisites

Ensure that you have Ollama installed and running in the background before proceeding with the following steps.

As always, create a virtual environment, activate it, and pip install the requirements

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Step 1: Create Chroma Vectorstore

To initialize the Chroma vectorstore, run the following command in your terminal:

mkdir db
python vectorstore.py

This command generates the vectorstore from the data.

Step 2: Run Chatbot

Once the vectorstore is set up, launch the chatbot using the following command:

python chatbot.py

This command activates the LLM-RAG system, allowing users to engage with the chatbot. The chatbot leverages the capabilities of Mistral-7B model and the Chroma vectorstore to provide responsive and context-aware interactions.