Building AI-powered apps with Weaviate and Streamlit

In this video, JP shows how you can connect Streamlit to Weaviate, an AI-native database. JP will introduce you to the Streamlit Weaviate connection is, and how it helps you to build AI-powered Streamlit apps faster. He will walk through a Jupyter notebook and a demo Movie search app to demonstrate the connection and how to use it. Streamlit Weaviate Connection 🕹️ Demo app https://weaviate-movie-magic.streamlit.app/ 🐙 Weaviate recipe in Streamlit Cookbook https://github.com/streamlit/cookbook/tree/main/recipes/weaviate 📖 Weaviate recipe blog post https://blog.streamlit.io/how-to-recommendation-app-vector-database-weaviate/ 🐙 st-weaviate connection repo: https://github.com/weaviate/st-weaviate-connection 🐍 st-weaviate connection PyPI: https://pypi.org/project/st-weaviate-connection/0.1.0/ Documentation 📖 Weaviate https://weaviate.io/developers/weaviate 📖 Streamlit https://docs.streamlit.io/ ⏰ Timeline 0:00 About 0:16 About JP 0:22 Introduction and overview of Weaviate 0:52 Overview of the project and Streamlit-Weaviate connection 2:02 Introduction to Streamlit-Weaviate connection 4:36 Example: Movie Magic demo app 6:58 Walkthrough of demo app source code 8:39 Recap of building with Weaviate and Streamlit 9:30 Summary #weaviate #streamlit #python #llm #ai #app