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Part of the accelerator
Streaming LLM Applications with FastAPI is one workshop inside AI Engineer Career Accelerator Program.
See the full path with mentor reviews and a portfolio outcome.
Stop copying ChatGPT prompts and hoping for the best. Build a real FastAPI application that streams LLM responses in real-time, with structured prompts, parameter control, and safety guardrails you actually understand.
Engineers are learning here from
Build an AI application that streams responses in real-time. Learn prompt engineering, LLM parameter control, Server-Sent Events, content safety guardrails, and the provider pattern for multi-model support.
Stream LLM responses in real-time and master prompt engineering fundamentals.
What you'll ship
What you'll learn
Curriculum
Getting started
Set up your environment, make your first LLM call, and learn structured prompt engineering
Parameters and streaming
Control creativity with LLM parameters and stream responses in real-time with Server-Sent Events
Advanced patterns
Apply advanced prompting techniques, add observability, and build pre/post-processing pipelines for production quality
Who it's for
who want to build their first AI application without framework overhead
curious about LLMs but unsure where to start beyond ChatGPT
looking for a practical, hands-on introduction to AI engineering
FAQ
No. This is a beginner course. You should know basic Python (functions, variables, async/await) but no AI or ML background is needed.
The project supports Fireworks, OpenRouter, Gemini, and OpenAI. You only need one API key. OpenRouter has a free tier to get started.
No. You build a real FastAPI application with streaming endpoints, input validation, and a processing pipeline. Prompt engineering is one piece of the full picture.