Sample chatbot using advanced RAG and a SQL database

This example demonstrates how to create a chatbot with RAG using quarkus-langchain4j. This chatbot internally uses LLM-generated SQL queries to retrieve the relevant information from a PostgreSQL database.

Running the example

A prerequisite to running this example is to provide your OpenAI API key.

export QUARKUS_LANGCHAIN4J_OPENAI_API_KEY=<your-openai-api-key>

Then, simply run the project in Dev mode:

mvn quarkus:dev

Using the example

Open your browser and navigate to http://localhost:8080. Click the orange robot in the bottom right corner to open the chat window.

The chatbot uses a SQL database with information about movies with their basic metadata (the database is populated with data from src/main/resources/data/movies.csv at startup). When you ask a question, an LLM is used to generate SQL queries necessary for answering your question. Check the application's log, the SQL queries and the retrieved data will be printed there.