Build an LLM Web App in Python from Scratch: Part 2 (Streamlit & FSM)

This tutorial demonstrates building an AI-powered image generator web application. The application uses a human-in-the-loop (HITL) system, allowing users to iterate on image generation. Streamlit simplifies web app development by eliminating the need for HTML/CSS. PocketFlow manages the AI workflow, dividing tasks into nodes for efficient processing. A Finite State Machine (FSM) handles user interactions and manages the application's state. The application's core functionality includes prompt input, image generation, user review, and approval or regeneration. `st.session_state` acts as a memory bank, storing data between Streamlit reruns. The tutorial breaks down the process into four parts, focusing on web app implementation in part two. The complete code example is available for reference, illustrating the concepts discussed. Finally, the tutorial highlights the integration of Streamlit, PocketFlow, and the FSM for a seamless user experience.