GraphCanon updated Sep 24, 2026 · GitHub synced Sep 24, 2026
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Decision brief
vlmrun-hub offers predefined schemas for VLM tasks like invoice metadata extraction, integrated with popular vision-language models.
Good fit when
- When you need to quickly implement invoice metadata extraction from images using preset schemas and any chosen VLM.
- Suitable for developers working on computer vision projects that require integration of industry-standard document schema understanding.
Avoid when
- Avoid if you are looking for a general-purpose library without predefined domain-specific schemas like invoices or documents.
- Not ideal for projects requiring real-time, low-latency VLM processing as it may introduce additional API call overhead.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (282d since push)
- As of Sep 24, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 24, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install vlmrun-hubSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides predefined schemas like Invoice for use with various Vision Language Models (VLMs) in tasks such as invoice metadata extraction from images.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Sep 24, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 24, 2026)
```python pip install vlmrun-hubSource link
Tags
README
🚀 Getting Started Let's say we want to extract invoice metadata from an invoice image. You can readily use our schema we have defined under and use it with any VLM of your choosing. For a comprehensive walkthrough of available schemas and their usage, check out our Schema Showca...
For agents
This page has a .md twin and JSON over the API.