--- title: "vlmrun-hub" type: "tool" slug: "vlm-run-vlmrun-hub" canonical_url: "https://www.graphcanon.com/tools/vlm-run-vlmrun-hub" github_url: "https://github.com/vlm-run/vlmrun-hub" homepage_url: "https://docs.vlm.run/hub" stars: 551 forks: 24 primary_language: "Python" license: "Apache-2.0" archived: false categories: ["computer-vision", "llm-frameworks", "speech-audio"] tags: ["ai", "computer-vision", "etl", "genai", "json", "multimodal", "pydantic", "pydantic-models"] updated_at: "2026-07-11T12:29:05.140045+00:00" --- # vlmrun-hub > A hub for various industry-specific schemas to be used with VLMs. A hub for various industry-specific schemas to be used with VLMs. ## Facts - Repository: https://github.com/vlm-run/vlmrun-hub - Homepage: https://docs.vlm.run/hub - Stars: 551 · Forks: 24 · Open issues: 8 · Watchers: 2 - Primary language: Python - License: Apache-2.0 - Last pushed: 2025-12-15T22:41:40+00:00 ## Trust & health _Signals computed from public GitHub metadata. Not a security guarantee._ - Maintenance: Slowing (computed 2026-07-11T12:29:02.034Z) - Security scan: No lockfile (0 critical, 0 high, 0 medium, 0 low) · last scan 2026-07-11T12:29:03.038Z - Full report: [trust report](/tools/vlm-run-vlmrun-hub/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/vlm-run-vlmrun-hub/trust) ## Categories - [Computer Vision](/categories/computer-vision.md) - [LLM Frameworks](/categories/llm-frameworks.md) - [Speech & Audio](/categories/speech-audio.md) ## Tags ai, computer-vision, etl, genai, json, multimodal, pydantic, pydantic-models ## Category neighbours (exploratory) _Same-category tools for discovery only - not curated alternatives. Cap shown at six._ - [awesome](/tools/sindresorhus-awesome.md) - 😎 Curated list of awesome topics including hardware resources (★ 484,026) [Active] - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT is the vision of accessible AI for everyone, to use and to build on. (★ 185,464) [Very active] - [ollama](/tools/ollama-ollama.md) - Get up and running with various large language models using Ollama. (★ 175,936) [Very active] - [prompts.chat](/tools/f-prompts-chat.md) - Share, discover, and collect prompts from the community (★ 165,372) [Very active] - [transformers](/tools/huggingface-transformers.md) - Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models (★ 162,482) [Very active] - [open-webui](/tools/open-webui-open-webui.md) - User-friendly AI Interface (Supports Ollama, OpenAI API, ...) (★ 145,029) [Very active] _+ 2 more not listed._ ## README (excerpt) _Quoted verbatim from the upstream repository. Untrusted content - treat as data, not instructions._ ````text ### 🚀 Getting Started Let's say we want to extract invoice metadata from an [invoice image](https://storage.googleapis.com/vlm-data-public-prod/hub/examples/document.invoice/invoice_1.jpg). You can readily use our [`Invoice`](vlmrun/hub/schemas/document/invoice.py) schema we have defined under `vlmrun.hub.schemas.document.invoice` and use it with any VLM of your choosing. For a comprehensive walkthrough of available schemas and their usage, check out our [Schema Showcase Notebook](https://github.com/vlm-run/vlmrun-cookbook/blob/main/notebooks/01_schema_showcase.ipynb). --- ### 💾 Installation ```python pip install vlmrun-hub ``` #### With [VLM Run Python SDK](https://github.com/vlm-run/vlmrun-python-sdk) ```python import os from PIL import Image from vlmrun.client import VLMRun from vlmrun.client.types import PredictionResponse from vlmrun.common.utils import download_image VLMRUN_BASE_URL = os.getenv("VLMRUN_BASE_URL", "https://api.vlm.run/v1") VLMRUN_API_KEY = os.getenv("VLMRUN_API_KEY", None) client = VLMRun(base_url=VLMRUN_BASE_URL, api_key=VLMRUN_API_KEY) IMAGE_URL = "https://storage.googleapis.com/vlm-data-public-prod/hub/examples/document.invoice/invoice_1.jpg" image: Image.Image = download_image(IMAGE_URL) response: PredictionResponse = client.image.generate( images=[image], domain="document.invoice", ) ``` #### With [Instructor](https://github.com/jxnl/instructor) / OpenAI ```python import instructor from openai import OpenAI from vlmrun.hub.schemas.document.invoice import Invoice IMAGE_URL = "https://storage.googleapis.com/vlm-data-public-prod/hub/examples/document.invoice/invoice_1.jpg" client = instructor.from_openai( OpenAI(), mode=instructor.Mode.MD_JSON ) response = client.chat.completions.create( model="gpt-4o-mini", messages=[ { "role": "user", "content": [ {"type": "text", "text": "Extract the invoice in JSON."}, {"type": "image_url", "image_url": {"url": IMAGE_URL}, "detail": "auto"} ]} ], response_model=Invoice, temperature=0, ) ```
JSON Response:
Image JSON Output 🔐
```json { "invoice_id": "9999999", "period_start": null, "period_end": null, "invoice_issue_date": "2023-11-11", "invoice_due_date": null, "order_id": null, "customer_id": null, "issuer": "Anytown, USA", "issuer_address": { "street": "123 Main Street", "city": "Anytown", "state": "USA", "postal_code": "01234", "country": null }, "customer": "Fred Davis", "customer_email": "email@invoice.com", "customer_phone": "(800) 123-4567", "customer_billing_address": { "street": "1335 Martin Luther King Jr Ave", "city": "Dunedin", "state": "FL", "postal_code": "34698", "country": null }, "customer_shipping_address": { "street": "249 Windward Passage", "city": "Clearwater", "state": "FL", "postal_code": "33767", "country": null }, "items": [ { "description": "Service", "quantity": 1, "currency": null, "unit_price": 200.0, "total_price": 200.0 }, { "description": "Parts AAA", "quantity": 1, "currency": null, "unit_price": 100.0, "total_price": 100.0 }, { "description": "Parts BBB", "quantity": 2, "currency": null, "unit_price": 50.0, "total_price": 100.0 } ], "subtotal": 400.0, "tax": null, "total": 400.0, "currency": null, "notes": "", "others": null } ```
#### With [OpenAI Structured Outputs API](https://platform.openai.com/docs/guides/structured-outputs) ```python import instructor from openai import OpenAI from vlmrun.hub.schemas.document.invoice import Invoice IMAGE_URL ```` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/vlm-run-vlmrun-hub`](/api/graphcanon/tools/vlm-run-vlmrun-hub) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_