Getting Started with ChromaDB Install Build a Streamlit App Document Search | Python | Vector DB скачать в хорошем качестве

Getting Started with ChromaDB Install Build a Streamlit App Document Search | Python | Vector DB

Github repo: https://github.com/sharmasw/Library_e... This video delves deep into ChromaDB, an open-source embedding database designed for efficient vector storage and retrieval. Whether you're new to ChromaDB or just looking to enhance your knowledge, this video covers! You'll learn: ✅ How to install and set up ChromaDB. ✅ How to use ChromaDB to store and query embeddings. ✅ How to create a persistent database that stores your documents. ✅ How to build a Streamlit app that takes a user query and finds the closest matching document using embeddings. By the end of the video, you'll have a working example of an app that efficiently searches and retrieves the most relevant document based on user input! Perfect for data enthusiasts, machine learning practitioners, and anyone looking to incorporate embedding-based search into their projects. Don't forget to like, subscribe, and hit the bell icon to stay updated on more Python and machine learning tutorials! 00:00 Introduction 03:10 Install Chroma 04:40 Create Chroma client 08:30 Check Embeddings of stored documents 10:04 Query search in chromadb 15:40 Persist Chroma Client Instance 19:23 Setup different embedding models 25:33 Filter where 27:00 Add metadata in documents 28:00 Filter query using metadata 29:40 Operators in chromadb 32:20 Streamlit app using Chromadb