This is a web application that implements a question-answering system using the Retrieval-Augmented Generation (RAG) model. It combines GPT models with information retrieval techniques to generate appropriate responses to user queries.
Create a container from VSCode's Dev Containers.
-
Use the
.env.sample
file as a reference to create a.env
file and set your OpenAI API key and vector store type. -
Change the URL in the
process_webpage(url)
function inretrievers.py
. -
Run
python retrievers.py
to create indexes in thevectorstore
directory. -
Execute the following command to start the application:
streamlit run app.py
- After launching the application, enter a question on the web interface.
- The RAG model generates a response to your question and displays it on the interface.