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Build an LLM Web App in Python from Scratch: Part 3 (FastAPI & WebSockets)
- The article discusses building a real-time AI chatbot web app using FastAPI for backends and WebSockets for live chat.
- Streaming AI in web apps creates a more engaging user experience with instant responses flowing in.
- FastAPI, a high-speed Python web framework, is used for the backend of the chatbot.
- WebSockets enable live, two-way communication between the server and the browser for real-time interactions.
- Async programming is crucial for integrating AI tasks into web apps without freezing the entire application.
- PocketFlow, in its async version, helps manage complex AI tasks by allowing multiple operations to run concurrently.
- The StreamingChatNode class streams AI responses word by word through WebSockets to provide a more dynamic chatbot experience.
- The article provides code snippets and explanations for implementing FastAPI, WebSockets, and asynchronous AI tasks in web apps.
- By combining FastAPI, WebSockets, and PocketFlow, developers can create a seamless real-time AI chatbot with interactive streaming capabilities.
- The tutorial guides developers through creating a live chat experience where AI responses are displayed word by word for a more natural conversation flow.
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