Build an LLM Chatbot

This chatbot interfaces with a agent designed to answer questions about the hospitals, patients, visits, physicians, and insurance payers in a fake hospital system.The agent uses retrieval-augment generation (RAG) over both structured and unstructured data that has been synthetically generated.

Flowchart

Files Explaination

Running Instructions

Create a .env file in the root directory and add the following environment variables:

NEO4J_URI=<YOUR_NEO4J_URI>
NEO4J_USERNAME=<YOUR_NEO4J_USERNAME>
NEO4J_PASSWORD=<YOUR_NEO4J_PASSWORD>

OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>

HOSPITALS_CSV_PATH=https://raw.githubusercontent.com/hfhoffman1144/langchain_neo4j_rag_app/main/data/hospitals.csv
PAYERS_CSV_PATH=https://raw.githubusercontent.com/hfhoffman1144/langchain_neo4j_rag_app/main/data/payers.csv
PHYSICIANS_CSV_PATH=https://raw.githubusercontent.com/hfhoffman1144/langchain_neo4j_rag_app/main/data/physicians.csv
PATIENTS_CSV_PATH=https://raw.githubusercontent.com/hfhoffman1144/langchain_neo4j_rag_app/main/data/patients.csv
VISITS_CSV_PATH=https://raw.githubusercontent.com/hfhoffman1144/langchain_neo4j_rag_app/main/data/visits.csv
REVIEWS_CSV_PATH=https://raw.githubusercontent.com/hfhoffman1144/langchain_neo4j_rag_app/main/data/reviews.csv

CHATBOT_URL=http://host.docker.internal:8000/hospital-rag-agent

HOSPITAL_AGENT_MODEL=llama3  # your model. I used my fine tunned model from ollama
HOSPITAL_CYPHER_MODEL=llama3
HOSPITAL_QA_MODEL=llama3

The three NEO4J_ variables are used to connect to your Neo4j AuraDB instance. Follow the directions here to create a free instance.

Once you have a running Neo4j instance, and have filled out all the environment variables in .env, you can run the entire project with Docker Compose. You can install Docker Compose by following these directions.

Once you've filled in all of the environment variables, set up a Neo4j AuraDB instance, and installed Docker Compose, open a terminal and run:

$ docker-compose up --build

After each container finishes building, you'll be able to access the chatbot api at http://localhost:8000/docs and the Streamlit app at http://localhost:8501/.