FastAPI and Chatbot Integration for Water Quality Prediction Model
Augmented Startups via YouTube
Overview
Learn to integrate a water potability prediction model with FastAPI and create an intelligent chatbot in this 15-minute tutorial video. Master the process of setting up a virtual environment using conda, implement FastAPI backend integration, and develop an interactive chat module powered by GPT-3.5 Turbo through LangChain. Explore essential FastAPI concepts including endpoint creation, static file handling, and Jinja2 templating while structuring payloads with Pydantic. Follow along with step-by-step demonstrations covering environment setup, library imports, API endpoint definition, prediction functionality implementation, and chatbot feature development using OpenAI's language model. Perfect for machine learning enthusiasts and full-stack developers looking to enhance their applications with AI-powered features and robust API integration.
Syllabus
– Introduction
– Setting Up Virtual Environment
– Importing Libraries for FastAPI
– Structuring Payload with Pydantic
– Defining API Endpoints
– Setting Up Predict Functionality
– Adding Chatbot Feature
– Using LangChain for ChatGPT Integration
– Next Steps: HTML UI Development
Taught by
Augmented Startups