OpenAI¶

Version v2¶

Ask a question to OpenAI's GPT-4 with Vision model.

You can specify arbitrary text prompts or predefined ones, the block supports the following types of prompt:

• unconstrained - any arbitrary prompt you like

• ocr- predefined prompt to recognise text from image

• visual-question-answering - your prompt is supposed to provide question and will be wrapped into structure that is suited for VQA task

• caption - predefined prompt to generate short caption of the image

• detailed-caption - predefined prompt to generate elaborated caption of the image

• classification - predefined prompt to generate multi-class classification output (that can be parsed with VLM as Classifier block)

• multi-label-classification - predefined prompt to generate multi-label classification output (that can be parsed with VLM as Classifier block)

• structured-answering - your input defines expected JSON output fields that can be parsed with JSON Parser block.

You need to provide your OpenAI API key to use the GPT-4 with Vision model.

Type identifier¶

Use the following identifier in step "type" field: roboflow_core/open_ai@v2to add the block as as step in your workflow.

Properties¶

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections¶

Check what blocks you can connect to OpenAI in version v2.

• inputs: Label Visualization, Crop Visualization, Mask Visualization, Blur Visualization, Image Contours, Bounding Box Visualization, Image Convert Grayscale, Camera Focus, Dot Visualization, Color Visualization, Corner Visualization, Circle Visualization, Perspective Correction, Image Slicer, Triangle Visualization, Relative Static Crop, Absolute Static Crop, Halo Visualization, Background Color Visualization, SIFT, Pixelate Visualization, Polygon Visualization, Dynamic Crop, Image Blur, Ellipse Visualization, Image Threshold
• outputs: JSON Parser, VLM as Detector, Roboflow Custom Metadata, VLM as Classifier, Perspective Correction

The available connections depend on its binding kinds. Check what binding kinds OpenAI in version v2 has.

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/open_ai@v2",
    "images": "$inputs.image",
    "task_type": "<block_does_not_provide_example>",
    "prompt": "my prompt",
    "output_structure": {
        "my_key": "description"
    },
    "classes": [
        "class-a",
        "class-b"
    ],
    "api_key": "xxx-xxx",
    "model_version": "gpt-4o",
    "image_detail": "auto",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>"
}

Version v1¶

Ask a question to OpenAI's GPT-4 with Vision model.

You can specify arbitrary text prompts to the OpenAIBlock.

You need to provide your OpenAI API key to use the GPT-4 with Vision model.

This model was previously part of the LMM block.

Type identifier¶

Use the following identifier in step "type" field: roboflow_core/open_ai@v1to add the block as as step in your workflow.

Properties¶

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections¶

Check what blocks you can connect to OpenAI in version v1.

• inputs: Label Visualization, Crop Visualization, Mask Visualization, Blur Visualization, Image Contours, Bounding Box Visualization, Image Convert Grayscale, Camera Focus, Dot Visualization, Color Visualization, Corner Visualization, Circle Visualization, Perspective Correction, Image Slicer, Triangle Visualization, Relative Static Crop, Absolute Static Crop, Halo Visualization, Background Color Visualization, SIFT, Pixelate Visualization, Polygon Visualization, Dynamic Crop, Image Blur, Ellipse Visualization, Image Threshold
• outputs: Template Matching, Segment Anything 2 Model, Blur Visualization, Image Convert Grayscale, VLM as Detector, Circle Visualization, CogVLM, Absolute Static Crop, LMM For Classification, Background Color Visualization, YOLO-World Model, Detections Transformation, Polygon Visualization, Image Threshold, OCR Model, Detections Classes Replacement, Image Contours, Bounding Box Visualization, Object Detection Model, Roboflow Custom Metadata, Dimension Collapse, Clip Comparison, First Non Empty Or Default, Detections Filter, Instance Segmentation Model, Halo Visualization, SIFT, Roboflow Dataset Upload, Google Gemini, Dynamic Crop, Image Slicer, Detection Offset, Roboflow Dataset Upload, Detections Stitch, Multi-Label Classification Model, Barcode Detection, Camera Focus, Dot Visualization, Corner Visualization, OpenAI, Triangle Visualization, Relative Static Crop, Pixel Color Count, Pixelate Visualization, JSON Parser, Dynamic Zone, Detections Consensus, Label Visualization, Crop Visualization, Mask Visualization, LMM, Property Definition, QR Code Detection, Color Visualization, VLM as Classifier, Perspective Correction, OpenAI, Keypoint Detection Model, Clip Comparison, Anthropic Claude, Dominant Color, Continue If, Expression, SIFT Comparison, Image Blur, Ellipse Visualization, Single-Label Classification Model

The available connections depend on its binding kinds. Check what binding kinds OpenAI in version v1 has.

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/open_ai@v1",
    "images": "$inputs.image",
    "prompt": "my prompt",
    "openai_api_key": "xxx-xxx",
    "openai_model": "gpt-4o",
    "json_output_format": {
        "count": "number of cats in the picture"
    },
    "image_detail": "auto",
    "max_tokens": 450
}