How to Visualize Your Codebase Using ChatGPT Projects

And Why the New GPT-4o Image Generator Changes Everything

“You never really understand a system until you can draw it.”
— Me, after visualizing a OpenAlgo – Python Flask app login flow in 60 seconds using GPT-4o latest image model.

Understanding how your app works internally is one thing. Explaining it visually — to yourself, your team, or the world — is another. That’s why I’m excited to share how I used ChatGPT Projects + GPT‑4o’s image generation to dissect and visualize the login architecture of my OpenAlgo codebase.

This wasn’t just “make a chart.”

It was more like:
Upload my whole project → Let GPT trace the logic → Generate a high-res diagram — with precision, style, and actual meaning.

Let’s break down how you can do this too.

The Evolution: GPT-4o’s Image Generation (March 25, 2025 Release)

At OpenAI, the March 25 release of GPT‑4o introduced something that developers and product teams have been dreaming of:

Text + structure + visual context → beautifully rendered, purposeful diagrams.

These are not your average clipart visuals or gimmicky infographics.
We’re talking about:

• Crystal-clear block diagrams
• Precise label positioning
• Natural language guidance → accurate visuals
• Multiple layout support (vertical, horizontal, rectangular, etc.)
• Rich styling options (neon blocks, dark background, comic-style humor, notebook POV)

This makes image generation useful — not just decorative.

My Goal: Understand the Login Flow of OpenAlgo

I maintain an open-source trading platform called OpenAlgo, which has a complex login flow:

• Frontend form (login.html)
• Flask-based route handling
• Session setup
• Broker-specific OAuth/token exchange (e.g., Zerodha)
• DB persistence
• Asynchronous contract downloads

Instead of mapping this by hand (ugh), I turned to ChatGPT Projects.

Step-by-Step: How I Used ChatGPT to Visualize the Flow

1. Upload the Full Codebase

I zipped my project (openalgo-main.zip) and uploaded it directly into ChatGPT in “Projects” mode.

2. Ask a Natural Question

I typed:

It analyzed the relevant files:

• login.html, auth.py, brlogin.py
• Broker-specific API handlers like zerodha/auth_api.py
• Utility modules like auth_utils.py and session.py

Then it constructed a high-level login process explanation, identifying every key step from form submission to broker callback.

3. Diagram Generated Instantly

Without needing to explain HTML forms or Flask decorators, GPT‑4o generated this:

A horizontal flowchart, styled cleanly with:

• Logical groupings: UI → Backend → Broker API → Database
• Color-coded boxes with readable white text
• Arrows guiding the logical sequence
• Labels like “Request Access Token”, “Store Broker Token”, and “Redirect to Dashboard”

4. Refine with Natural Commands

I wasn’t happy with the initial look, so I asked:

• “Make the image rectangular and text centered”
• “Use neon-colored blocks with white text on a black background”

Each time, GPT‑4o redrew the diagram from scratch, respecting my layout and style preferences — no manual tools, no drawing apps, just smart visual language rendering.

The Quality of the Visualization (Why It’s a Big Deal)

GPT‑4o’s latest visual engine delivers supreme quality:

• ✅ Accurate block alignment — You’ll never see wonky arrows again.
• ✅ Symbolically correct — Shapes like diamonds for conditionals (“Success?”).
• ✅ Style matching your tone — From minimalist tech blog to playful comic strip.
• ✅ Responsive re-rendering — Add a new step? It reflows the layout.
• ✅ Readable text rendering — Labels are sharp and render as intended, even across languages.

It’s like having a product designer with system architecture knowledge built into your terminal.

Why Developers Should Use This for Architecture Docs

If you’re:

• A solo dev explaining your repo to contributors
• A startup pitching product flow to investors
• A backend engineer explaining API routes to frontend
• A product team onboarding new engineers
• A maintainer of open source projects

Stop drawing manually.
Let GPT-4o:

• Parse your repo
• Visualize the architecture
• Style it your way
• Iterate with you in real-time

This works not only for login flows, but:

• Signup/registration flows
• Data pipelines (ETL)
• Microservices call graphs
• Cron job orchestration
• CI/CD pipeline maps

Final Login Flow I Generated

This is what I ended up with — a stunning dark-themed, neon-highlighted login flow, breaking down how OpenAlgo authenticates users and brokers:

(You’ll see how every arrow and label actually helps explain the flow. This isn’t just pretty — it’s explanatory.)

Recap: How You Can Do This Too

1. Go to ChatGPT (Pro account required)
2. Enter “Projects” mode
3. Upload your full source code
4. Ask: “Visualize the login flow of this app”
5. Tweak styling, structure, and labels with natural prompts
6. Export or embed your final diagram

Final Thought

As devs, we’ve always visualized in our heads. Now we can share that vision — clearly, beautifully, and instantly.