Descriptions:
Fahd Mirza walks through a complete integration of WeasyPrint — a lightweight Python-based HTML-to-PDF rendering engine — with Ollama, the popular local model runner, to create an AI-powered document generation pipeline. The tutorial is hands-on throughout, running on an Ubuntu system equipped with an NVIDIA RTX 6000 GPU (48GB VRAM) and using the OpenAI-compatible GPT OSS model served through Ollama.
Mirza begins by explaining what WeasyPrint is and why it stands apart from browser-based PDF solutions like those relying on WebKit or Gecko: it uses a pure Python CSS layout engine optimized for pagination, making it far lighter and easier to embed in server-side workflows. The installation walkthrough covers prerequisites including Python 3.10+, Pango (a text rendering library), and the WeasyPrint pip package. He then demonstrates converting a live website to PDF in seconds before moving to the AI integration.
The core of the tutorial shows how to prompt Ollama to generate HTML content — first a basic AI-topic report, then a realistic five-item IT consulting invoice complete with CSS formatting — and pipe that output directly into WeasyPrint for PDF rendering. The result is a clean, fully formatted PDF document produced without any manual HTML authoring. Mirza frames the pattern as a general template for embedding local AI into traditional document workflows, with obvious extensions to invoicing systems, report automation, and any use case requiring programmatic PDF generation.
📺 Source: Fahd Mirza · Published May 31, 2026
🏷️ Format: Tutorial Demo
