Building PasteDB: A Bulletproof Code-Sharing Platform Powered by FastAPI and OpenAI's gpt-oss-20b

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

I built PasteDB, a lightweight code-sharing platform designed to make sharing code blocks seamless. To take it a step further for this challenge, I integrated an "Explain This Code" AI assistant layer.

Who I built it for: I built this feature specifically for my developer friends and peers who are learning to code. Often, when we share raw code snippets over chat platforms, beginners struggle to understand the core logic without context. PasteDB now automatically analyzes any shared snippet at the click of a button, acting as an on-demand mentor.

Demo

• Live Link: https://pastedb.netlify.app

• Backend API: https://pastedb-rw62.onrender.com

Code

Here is the official open-source repository for PasteDB:
https://github.com/sorathiya903/pastedb

How I Built It

PasteDB is engineered using a robust, free-tier distributed stack:

• Frontend: Vanilla JavaScript, HTML and CSS hosted on Netlify
• Backend: FastAPI (Python) hosted on a free-tier Render instance
• Database: MongoDB Atlas

Overcoming Infrastructure Limits with Open-Weight AI

The biggest engineering hurdle was Render's strict 512MB RAM constraint on the free tier. Running even a small 350MB model locally on the backend would trigger an Out-of-Memory (OOM) crash once the Python dependencies and KV caches loaded.

To solve this, I decoupled the compute by making outbound streaming requests to Groq's cloud infrastructure to tap into the official open-weight OpenAI Model model. This leaves a 0MB memory footprint on Render while generating lightning-fast, structured Markdown explanations for the user.

Bulletproof Quota Protection

To protect my public API quota from malicious spam or heavy judging traffic, I engineered a zero-RAM, custom in-memory IP Rate Limiter directly inside the FastAPI routing layer. It limits users to 3 requests per minute per IP, protecting the app against HTTP 429 exhaustion while keeping the experience completely smooth and available for the judges.

# A snippet of my custom rate-limiter guarding the open-weight pipeline

Why Does Open Innovation Matter?

Open innovation was the entire foundation of this project. Relying on premium, closed-source corporate APIs forces developers into commercial paywalls, rigid token meters, and strict monetization loops from day one.

By utilizing open-weight ecosystem components like Llama 3.1, I was able to build a completely free, highly scalable utility tool for my friends. Open innovation democratizes AI execution, proving that independent developers can ship fully secured AI tools without a massive corporate budget.

Prize Categories

I am entering PasteDB into the following categories:

• Grand Prize Category
• Open-Source AI / Open-Weight Model Integration: I successfully deployed a 21B open-weight reasoning model pipeline (gpt-oss-20b) across a modern full-stack ecosystem consisting of Netlify (Frontend), FastAPI on Render (Backend), and MongoDB Atlas (Database). Offloading the inference compute allowed me to seamlessly integrate this open-weight powerhouse while staying perfectly within Render’s free-tier memory constraints.