Build a QA Retrieval Chatbot with FastAPI & Vector Database
In this tutorial, I'll show you how to build a QA retrieval chatbot using FastAPI and a vector database! You'll see in the code how to upload PDFs, store them in a vector database, and create a chatbot that can answer questions based on the content of the uploaded documents. Whether you're a beginner or an experienced Python developer, code will guide you step-by-step to create an intelligent chatbot that retrieves answers directly from PDF files.
Topics covered:
FastAPI for building a RESTful API
Vector database integration for document storage
PDF document upload and processing
Implementing a question-answer retrieval system
By the end, you'll have a fully functional QA chatbot capable of understanding and responding to content from your uploaded documents!
#Python #FastAPI #AI #VectorDB #Chatbot #PDF #DocumentProcessing #codewithalighori