AI-Powered Content Generation and Template Automation for E‑commerce

As a new form of product presentation, AIGC‑generated content now appears throughout the entire Taobao user journey, from discovery feeds to detail pages. Over the past year the team has tackled core technologies such as video generation and multimodal text‑image synthesis, achieving large‑scale deployment across multiple scenarios.

The series "Taobao AIGC Content Generation Technology Summary" collects ten technical articles that explore these advances, including image‑driven generation, multimodal video driving, and large‑model applications.

Traditional graphic‑rich guides require designers to create templates and front‑end engineers to manually annotate slots, a process that is time‑consuming and inflexible. Large models can automatically extract key information and generate image‑text guides, reducing cost and speeding up production.

We built an automated template‑generation tool that ingests designer mock‑ups, lets a large model produce HTML code, renders the result, and iteratively refines it via natural‑language feedback. This loop improves efficiency while ensuring the output matches design intent.

For template filling, the model parses an input HTML template, identifies slots (title, image, paragraph, etc.), and populates them with product data. It can handle both non‑tabular and tabular templates, accurately inserting text and images, and supports natural‑language edits to adjust colors, fonts, and layout.

Experiments show that the approach dramatically cuts manual effort, enables rapid visual iteration (e.g., quick color‑scheme testing), and supports personalized, “one‑size‑fits‑all” shopping guides. The team envisions broader adoption of large‑model‑driven content creation to further enhance e‑commerce experiences.