In this repository, you will discover how Streamlit, a Python framework for developing interactive data applications, can work seamlessly with Azure OpenAI Service's Embedding and GPT 3.5 models. These tools make it possible to create a user-friendly web application that enables users to ask questions in natural language about a PDF file they have uploaded. It is a simple yet effective solution that allows users to retrieve valuable information from the document by semantic searching.
- app.py <-- Sample using FAISS (Facebook AI Similarity Search) as a Vector Database to store the embedding vectors and perform similar searches.
Architecture
To run this Streamlit web app
streamlit run app.py
Enjoy!