Week 11: Web Application Development Basics

Week 11: Web Application Development Basics#

Overview#

This week introduces students to the fundamentals of web application development, with a focus on building NLP-powered applications using Python web frameworks. Students will learn both Flask and Streamlit frameworks, starting from basic web concepts through to integrating LLM APIs in web applications. The course content progresses from understanding client-server architecture to implementing secure, production-ready applications. This week’s material bridges the gap between theoretical NLP knowledge and practical application development, preparing students for real-world AI engineering tasks.

Learning Objectives#

By the end of this week, you will be able to:

  1. Understand and implement basic web application architecture using Flask and Streamlit

  2. Create and handle web routes, forms, and HTTP requests in Flask applications

  3. Build interactive data-driven dashboards using Streamlit

  4. Integrate LLM APIs securely into web applications

  5. Deploy web applications with proper security measures and configuration

Key Topics#

1. Web Development Fundamentals#

  • Client-server architecture and HTTP protocols

  • Front-end vs. back-end development concepts

  • RESTful API principles

  • Basic HTML templating with Jinja2

2. Framework Implementation#

  • Flask application structure and routing

  • Streamlit components and interactivity

  • Form handling and user session management

  • Static file serving and file uploads

3. LLM Integration and Deployment#

  • API integration patterns and security

  • Environment configuration and key management

  • Error handling and rate limiting

  • Deployment strategies and monitoring

Practical Component#

In this week’s practical session, you will:

  • Set up Flask and Streamlit development environments

  • Create a basic web application with multiple routes and templates

  • Implement interactive dashboard features using Streamlit

  • Build and deploy a web application that integrates with LLM APIs

  • Practice secure API key management and error handling

Assignment#

Students will develop a web application that showcases NLP capabilities using either Flask or Streamlit. The application should integrate with at least one LLM API (e.g., OpenAI) to perform tasks such as text summarization, question answering, or code generation. Requirements include proper error handling, secure API key management, basic styling, and complete documentation. The assignment should be submitted as a GitHub repository with deployment instructions and a working demo.

Looking Ahead#

In Week 12, we’ll build upon these web development skills to focus on controlling and structuring LLM outputs. Students will learn advanced techniques for prompt engineering and output formatting, enabling more sophisticated and reliable AI applications. The focus will shift from basic web infrastructure to fine-tuned control over AI model interactions.