Vibe Coding a Production-Ready FastAPI Speech-to-Text API with Whisper, Redis & PostgreSQL

In this video, we build a production-style Speech-to-Text API using Python FastAPI, Whisper/Faster Whisper, PostgreSQL, SQLAlchemy, Alembic, Redis queue, MinIO, and Docker. #FastAPI #Python #BackendDevelopment #VibeCoding #OpenAI #Whisper #AIEngineering #SoftwareEngineering #Redis #PostgreSQL #Docker #PythonDeveloper #AICoding #Codex But this is not a “single prompt generated my full app” type of vibe coding tutorial. Instead, I show a more realistic workflow: First, we plan the backend architecture. Then we discuss the structure with AI. Then we use Codex to help implement the project step by step. After that, we run the app locally, set up database migrations, test the API using Insomnia, handle API key validation, start the worker, process an audio file, and finally get the transcription result. The goal of this video is to show how vibe coding can actually be useful when you combine it with proper software engineering thinking. In this tutorial, you will learn: How to plan a FastAPI backend before coding How to structure a production-style Python API How to use Redis queue and worker for long-running STT jobs How to store uploaded audio using MinIO like S3 How to use PostgreSQL with SQLAlchemy and Alembic How to run migrations locally How to use Whisper/Faster Whisper for speech-to-text How to test upload and job status APIs Why real vibe coding is not just one big prompt This is a practical backend development tutorial for developers who want to use AI coding assistants properly while still building usable and scalable applications. Chapters 00:00 Introduction: Real Vibe Coding vs One-Prompt Apps 01:28 Planning the Speech-to-Text API Architecture 03:12 Tools and Local Services Required 05:45 Initializing the FastAPI Project with uv 07:55 Using Codex Plan Mode to Design the Backend 10:30 Choosing and Managing the Whisper Model 14:10 Queue Worker Flow: Upload, Process, Store Result 17:42 Codex Implementation and Project Structure Review 30:20 Running the App and Setting Up Alembic Migrations 35:20 Testing Health, Upload, API Key and Job Status APIs 42:30 Running the Worker and Processing the STT Job 48:20 Final Thoughts: Why Vibe Coding Needs a Process GitHub Repository: https://github.com/RajKKapadia/YouTube-Vibe-Coded-Backend-Development 🚀 Join My Free Community! 👇 🌐 Nas.io - [Learn Everything About Chatbots](https://nas.io/learn-everything-about-chatbots) 📚 Master Google Dialogflow & Build Smart Chatbots! ES: [Enroll Now](https://www.udemy.com/course/master-google-dialogflow-build-smart-chatbots/) CX: [Enroll Now](https://www.udemy.com/course/master-dialogflow-cx-build-engaging-chatbots-2025) 💬 Join Our Discord Group & Connect with Like-Minded People! 🔗 [Discord Community](https://discord.gg/dKruft7Kqs) 🔥 Get Exclusive Perks & Behind-the-Scenes Content! 🎥 [Join This Channel](https://www.youtube.com/channel/UCOT01XvBSj12xQsANtTeAcQ/join) 💡 Need a Custom Chatbot or AI/ML/DL Solution? 📩 Contact me for: 🤖 Chatbot Development | 🧠 AI/ML/DL Projects 🎯 Hire Me on Freelance Platforms! 💼 [Fiverr Profile](https://www.fiverr.com/rajkkapadia) 💼 [Upwork Profile](https://www.upwork.com/freelancers/~0176aeacfcff7f1fc2) 💼 [LinkedIn Profile](https://www.linkedin.com/in/rajkkapadia/) 📢 Share Your Thoughts! 💬 Drop a comment below & let me know what you think about this video! 📌 Don't Forget to: 👍 LIKE | 🔔 SUBSCRIBE | 💬 COMMENT 🎶 Enjoy Life, Feel the Music. ✌️ Peace.