Building an AI-Powered Chat App: Deep Dive into Request-Response & State Management | Part 3

Welcome to Part 3 of our series on building an AI-powered chat application! 🚀
In this video, we go beyond the basics and dive deep into the request-response flow, not only from the web page to the FastAPI backend server but also from the FastAPI backend server to the Ollama server. Using the Ollama 3.1, 70 billion parameter model LLM as an example, I explain how we manage state across these layers, despite REST APIs being stateless.
🔧 Key Concepts Covered:
Understanding stateful vs. stateless calls in web applications
Managing state between the web page and FastAPI backend using sessions
Constructing messages to manage state between FastAPI and Ollama server
A critical discussion on which endpoints to use and why
How system, user, assistant, and tool messages are constructed and managed
💡 Why Watch?:
This video is essential for anyone looking to understand the underlying architecture and state management in AI-driven web applications. Before diving into the code in the next video, it's crucial to grasp how data flows and how states are managed across different components of the system.
Missed the earlier parts?
👉Watch Full Playlist:
• Building a Real-Time A...
👉 Check out the code on GitHub:
github.com/Tea...
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[@ronwiltgen2698]

Thank you again to go in detail on how these endpoints work. The api documentation for OpenAI was pretty cool. Thank you.

[@MukulTripathi]

Glad it was helpful!