# DocTR

[DocTR](https://github.com/mindee/doctr) is a document OCR model deployable via our [Serverless Hosted API](/deploy/serverless-hosted-api-v2.md).

## Code sample

Call the `/doctr/ocr` endpoint directly with `curl`:

```bash
curl --location 'https://serverless.roboflow.com/doctr/ocr' \
  --header 'Content-Type: application/json' \
  --data '{
    "api_key": "YOUR_API_KEY",
    "image": {"type": "url", "value": "https://media.roboflow.com/inference/license_plate_1.jpg"}
  }'
```

The same call through the SDK. Pass your [Roboflow API Key](https://app.roboflow.com/settings/api) via the `API_KEY` env variable.

```bash
pip install inference-sdk
```

```python
import os
import urllib.request
from inference_sdk import InferenceHTTPClient

# Sample image containing text
urllib.request.urlretrieve(
    "https://media.roboflow.com/inference/license_plate_1.jpg",
    "./sample.jpg",
)

client = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key=os.getenv("API_KEY"),
)

result = client.ocr_image(inference_input="./sample.jpg", model="doctr")

print(result["result"]) # Extracted text
```

The code above prints inference results to the terminal:

```
Mr
AUTPMATIC
280SE
34 T6511
```

{% hint style="info" %}
Set `api_url` to match your deployment target:

* `https://serverless.roboflow.com` for the Serverless Hosted API.
* `http://localhost:9001` for a local [Inference](https://inference.roboflow.com/) server.
* Your [Dedicated Deployment](/deploy/dedicated-deployments.md) URL for a private endpoint.
  {% endhint %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.roboflow.com/deploy/supported-models/doctr.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.