Lona Kiragu
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huggingface/InferenceSupport upvoted an article 6 days ago
VLM Run Gateway: Run GLM-OCR, DeepSeek-OCR-2, dots.mocr with an OpenAI Compatible API reacted to nwaughachukwuma's post with ❤️ about 1 month ago
# One API for Every Visual & OCR Models.
The VLM Run Gateway is a fully compatible API for OpenAI chat completions for visual intelligence. If you’re building document extraction or visual understanding, the Gateway exposes OCR, VQA, and detection behind a single interface you already know.
Read the docs: https://docs.vlm.run/gateway/introduction.
We actively support the following recent OCR and VQA models, which you can try today at no cost:
* zai-org/glm-ocr
* rednote-hilab/dots.mocr
* paddleocr/pp-ocrv6
* qwen/qwen3.5-0.8b
## Quickstart
### CLI
```bash
uvx vlmrun gw models
uvx vlmrun config set --api-key '<VLMRUN_API_KEY>' # anon-user, rate-limited
uvx vlmrun gw chat <doc>.pdf -m zai-org/glm-ocr
uvx vlmrun gw chat <doc>.pdf -m zai-org/glm-ocr --json-mode
uvx vlmrun gw chat <doc>.pdf -m deepseek-ai/deepseek-ocr-2
uvx vlmrun gw chat <doc>.pdf -m rednote-hilab/dots.mocr
uvx vlmrun gw chat <doc>.pdf -m paddleocr/pp-ocrv6
```
### OpenAI SDK
```
from openai import OpenAI
client = OpenAI(
base_url="https://gateway.vlm.run/v1/openai",
api_key="<VLMRUN_API_KEY>",
)
response = client.chat.completions.create(
model="zai-org/glm-ocr",
messages=[
{
"role": "user",
"content": [
{
"type": "document_url",
"document_url": {
"url": "https://storage.googleapis.com/vlm-data-public-prod/hub/examples/finance.sec-filings/tsla-8k.pdf"
},
},
],
}
],
extra_body={"method": "markdown", "document_dpi": 150},
)
print(response.choices[0].message.content)
```
## Auth and limits
Anonymous auth is enabled, so you can omit the authorization header entirely, or send Bearer "" or Bearer vlmrun. Rate limits are 60 req/min and 1000 req/hr.Organizations
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