FastAPI & Qdrant: Building a Semantic Search & CRUD Backend with Streamlit Frontend
This video demonstrates a powerful backend service built with FastAPI, integrating a PostgreSQL (or SQLite) database for structured data and Qdrant for blazing-fast semantic search. We'll explore how to perform CRUD (Create, Read, Update, Delete) operations on AI/ML tools and leverage vector embeddings for intelligent, context-aware search. The project also features a user-friendly Streamlit frontend for easy interaction and visualization of the backend's capabilities.
Key topics covered:
FastAPI for building robust and asynchronous APIs
SQLAlchemy for efficient database interactions
Qdrant as a high-performance vector database
SentenceTransformers for generating text embeddings
Streamlit for creating interactive web applications
Implementing semantic search for AI/ML tools
Designing a microservice architecture with dual data storage
Perfect for developers interested in FastAPI, vector databases, semantic search, and building full-stack AI applications!