53 Streaming LLM Output in Python: Using an Accumulator for Real-Time Text Rendering PYTH 10.9

All the code used in this video is free and downloadable at https://industry-python.thinkific.com - Free registration required.

In this lesson, we improve how streamed responses from a local LLM (via Ollama) are displayed in Python. Instead of printing one chunk per line as the stream arrives, we introduce an accumulator pattern that collects streamed text into a single string and renders it cleanly on one line.

You’ll learn how to:

Consume streamed responses using an HTTPX client

Accumulate incremental text chunks into a Python string

Control console output with print(..., end="") and flush=True

Simulate UI-style redraw behavior by clearing the screen and reprinting accumulated text

Understand why this accumulator approach maps directly to how UI frameworks like Flet redraw the screen during streaming updates

This video bridges the gap between simple console-based streaming and real UI-driven applications, showing why accumulation is essential when re-rendering views instead of printing diffs.

Ideal for developers working with:

Python streaming responses

Local LLMs and Ollama

Preparing backend logic for UI frameworks like Flet

Understanding real-time rendering vs. incremental console output

This pattern will be reused in future videos when we move fully into UI-based streaming.