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StarVector

StarVector is a multimodal vision-language foundation model that generates Scalable Vector Graphics code from images or text instructions.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

StarVector — OpenViST project profile in AI Models.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use StarVector when a workflow calls for generating SVG code from a visual reference or text instruction, or when exploring model-based vectorization rather than curve-only tracing.

Who it is for

  • Developers exploring vision-language models for vector graphics generation.
  • Design and research practitioners investigating image-to-SVG or text-to-SVG workflows.
  • Python users who want to inspect or install the model's public repository.

Documented uses

  • Generate SVG illustrations from text prompts.
  • Convert raster images into SVG code.
  • Prototype a vision-language workflow for vector graphics generation.
  • Explore diagram generation as an SVG task.
Before you choose

Requirements & limits

The GitHub repository is public and specifies an Apache-2.0 license. Its installation instructions use Conda and Python 3.11.3.

  • The model accepts either visual input for image-to-SVG generation or text alone for text-to-SVG generation.
  • The project treats vectorization as code generation and describes using primitives such as ellipses, polygons and text.
  • The repository documents a Python package setup; training dependencies are installed separately.
  • Linked resources include 1B and 8B model repositories, plus SVG-Stack and SVG-Bench datasets.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the StarVector Python package

Install the repository package in the documented Conda environment.

Before you start

  • Git
  • Conda
  • Python 3.11.3

Steps

  1. Clone the GitHub repository and change into the star-vector directory.

  2. Create and activate a Conda environment using Python 3.11.3.

  3. Upgrade pip, then install the package in editable mode with pip install -e .

Expected outcome

The StarVector repository package is installed in the active environment.

Guide limitations

  • These steps cover package setup only; they do not document a complete generation run.
  • Training dependencies are separate and require installing the [train] extra.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
7 October 2026
Original website title
joanrod/star-vector · Official homepage title · retained in its source language
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