Build a Website Analyzer with GPT-5 & FastAPI

8/11/2025

How to Build a Website Analyzer with GPT-5 & FastAPI: An Insider's Guide

Hey everyone, hope you're doing awesome. I've been deep in the world of large language models & Python lately, & I wanted to share a pretty cool project I've been experimenting with: building a website analyzer using GPT-5 & FastAPI. It’s one of those projects that sounds complicated, but honestly, once you break it down, it's totally doable & SUPER powerful.

The basic idea is to create a tool that takes any website URL, scrapes its content, & then uses an LLM like the much-anticipated GPT-5 to generate a detailed analysis. Think business model, target audience, marketing strategies, UX feedback, the whole nine yards. This is the kind of tool that can provide some serious value, whether you're a marketer, a developer, or just a curious tech enthusiast.

We're going to walk through this step-by-step. I'll cover setting up a solid FastAPI backend, the nitty-gritty of web scraping, how to talk to GPT-5 to get what you want, & even how to handle the tricky bits like getting reliable JSON output. This is gonna be a long one, but trust me, it’s packed with practical stuff.

Why Even Bother Building This?

Before we dive into the code, let's talk about why this is a worthwhile project. A tool like this has a ton of applications:

Competitive Analysis: Quickly get a deep understanding of what your competitors are doing, what their messaging is, & who they're targeting.
Lead Generation & Qualification: If you're in B2B sales, you could run this on a potential client's website to understand their business inside & out before you even make the first call.
Content & SEO Strategy: Analyze top-ranking websites in your niche to deconstruct their content strategy, keywords, & overall approach.
UX & UI Insights: Get an AI-powered "first impression" of a website's user experience, identifying potential points of friction or confusion.

Honestly, the possibilities are pretty endless. You could even productize this into a service. And with the power of something like GPT-5, the depth of analysis you can get is just incredible. The recently released GPT-5 models, like

gpt-5-mini

and

gpt-5-chat

, are designed for these kinds of complex, multi-step workflows & have shown a significant reduction in hallucinations, which is KEY for a tool like this.

The Tech Stack: FastAPI, GPT-5, & More

Here’s what we’ll be using to build our website analyzer:

FastAPI: A modern, fast (hence the name) Python web framework for building APIs. It's incredibly intuitive & has automatic interactive documentation, which is a lifesaver.
GPT-5 (or another powerful LLM): The brains of our operation. We'll be using the OpenAI API to access its advanced reasoning capabilities.
BeautifulSoup & Requests/Selenium: For scraping the content from the target website. We'll need to be smart about this to handle different types of websites.
Pydantic: This is a data validation library that FastAPI is built on. We’ll use it to define the structure of our API requests & responses, & more importantly, to get reliable JSON output from our LLM.
Celery: For running our analysis tasks in the background. Scraping & analyzing a website can take time, & we don't want our users waiting around with a frozen screen. Celery is perfect for this.

Let's Get Building: The FastAPI Backend

First things first, we need a solid foundation. A well-structured FastAPI project is going to make our lives a whole lot easier as we add more functionality. Forget throwing everything into a single

main.py

file; that gets messy, fast.

A good project structure separates concerns. Here’s a structure that I’ve found works well for larger applications, inspired by best practices from startups & the FastAPI community: