• prompt (str): The prompt to send to the model. Defaults to "OCR the image.".
• enable_grounding (bool): Whether to enable grounding for bbox extraction. Defaults to False.
• mode (str): The inference mode. Options: "tiny", "small", "gundam", "base", "large". Defaults to "base".
• init_args (DeepSeekOCRInitArgs): Initialization arguments for the model including:
  • pretrained_model_name_or_path: Model identifier. Defaults to "deepseek-ai/DeepSeek-OCR".
  • torch_dtype: Model precision ("float16", "bfloat16", "auto"). Defaults to "auto".
  • attn_implementation: Attention implementation. Defaults to "flash_attention_2".
  • Note: This model requires CUDA. CPU inference is not supported.

agent:
  name: deepseek_ocr_agent
  description: Agent to run inference with DeepSeek OCR

templates:
- template_name: InputTemplate
  class_name: InputTemplate
  attributes: {}

- template_name: FolderImageDatasetCV2
  class_name: FolderImageDatasetCV2
  template_input: InputTemplate
  attributes:
    data_dir: dataset/input

- template_name: DeepSeekOCRInference
  class_name: DeepSeekOCRInference
  template_input: FolderImageDatasetCV2
  attributes:
    prompt: "Perform OCR."
    enable_grounding: false
    mode: base

agent:
  name: deepseek_ocr_grounding_agent
  description: Agent with grounding for bbox extraction

templates:
- template_name: InputTemplate
  class_name: InputTemplate
  attributes: {}

- template_name: FolderImageDatasetCV2
  class_name: FolderImageDatasetCV2
  template_input: InputTemplate
  attributes:
    data_dir: dataset/input

- template_name: DeepSeekOCRInference
  class_name: DeepSeekOCRInference
  template_input: FolderImageDatasetCV2
  attributes:
    prompt: "Convert the document to markdown."
    enable_grounding: true
    mode: base

- template_name: BBoxDrawer
  class_name: BBoxDrawer
  template_input: DeepSeekOCRInference
  attributes:
    draw_confidence: True
    draw_extra_labels: True

- template_name: ImageSaver
  class_name: ImageSaver
  template_input: BBoxDrawer
  attributes:
    save_dir: output
    root_dir: dataset

IMPORTANT This docker image depends on the sinapsis:base image. Please refer to the official sinapsis instructions to Build with Docker.

1. Build the sinapsis-ocr image:

docker compose -f docker/compose.yaml build

2. Start the app container:

docker compose -f docker/compose_app.yaml up

3. Check the status:

docker logs -f sinapsis-ocr-app

4. The logs will display the URL to access the webapp, e.g.:

NOTE: The url can be different, check the output of logs

Running on local URL:  http://127.0.0.1:7860

5. To stop the app:

docker compose -f docker/compose_app.yaml down

To run the webapp using the uv package manager, please:

1. Create the virtual environment and sync the dependencies:

uv sync --frozen

2. Install packages:

uv pip install sinapsis-deepseek-ocr[all] --extra-index-url https://pypi.sinapsis.tech

3. Run the webapp:

uv run webapps/gradio_ocr.py

4. The terminal will display the URL to access the webapp, e.g.:

Running on local URL:  http://127.0.0.1:7860

NOTE: The url can be different, check the output of the terminal

5. To stop the app press Control + C on the terminal