OpenAI

v3

Class: OpenAIBlockV3 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.openai.v3.OpenAIBlockV3

Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning

Ask a question to OpenAI's GPT models with vision capabilities (including GPT-5 and GPT-4o).

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

• Open Prompt (unconstrained) - Use any prompt to generate a raw response

• Text Recognition (OCR) (ocr) - Model recognizes text in the image

• Visual Question Answering (visual-question-answering) - Model answers the question you submit in the prompt

• Captioning (short) (caption) - Model provides a short description of the image

• Captioning (detailed-caption) - Model provides a long description of the image

• Single-Label Classification (classification) - Model classifies the image content as one of the provided classes

• Multi-Label Classification (multi-label-classification) - Model classifies the image content as one or more of the provided classes

• Structured Output Generation (structured-answering) - Model returns a JSON response with the specified fields

Provide your OpenAI API key or set the value to rf_key:account (or rf_key:user:<id>) to proxy requests through Roboflow's API.

Type identifier

Use the following identifier in step "type" field: roboflow_core/open_ai@v3to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
task_type	str	Task type to be performed by model. Value determines required parameters and output response..	❌
prompt	str	Text prompt to the OpenAI model.	✅
output_structure	Dict[str, str]	Dictionary with structure of expected JSON response.	❌
classes	List[str]	List of classes to be used.	✅
api_key	str	Your OpenAI API key.	✅
model_version	str	Model to be used.	✅
image_detail	str	Indicates the image's quality, with 'high' suggesting it is of high resolution and should be processed or displayed with high fidelity..	✅
max_tokens	int	Maximum number of tokens the model can generate in it's response..	❌
temperature	float	Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..	✅
max_concurrent_requests	int	Number of concurrent requests that can be executed by block when batch of input images provided. If not given - block defaults to value configured globally in Workflows Execution Engine. Please restrict if you hit OpenAI limits..	❌

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

Available Connections

Compatible Blocks

Check what blocks you can connect to OpenAI in version v3.

• inputs: VLM as Detector, Google Vision OCR, Classification Label Visualization, Circle Visualization, Image Contours, Relative Static Crop, Image Preprocessing, LMM For Classification, VLM as Classifier, Ellipse Visualization, Stitch Images, Triangle Visualization, Stability AI Inpainting, QR Code Generator, Image Slicer, Background Color Visualization, Model Monitoring Inference Aggregator, OCR Model, Dot Visualization, Florence-2 Model, SIFT, Morphological Transformation, EasyOCR, Reference Path Visualization, Halo Visualization, SIFT Comparison, Gaze Detection, Buffer, Polygon Visualization, Image Slicer, Florence-2 Model, Slack Notification, Clip Comparison, Image Convert Grayscale, Instance Segmentation Model, OpenAI, Color Visualization, Keypoint Detection Model, Google Gemini, Label Visualization, Email Notification, Llama 3.2 Vision, Trace Visualization, Dynamic Zone, Size Measurement, Email Notification, Corner Visualization, Mask Visualization, CogVLM, Stability AI Outpainting, OpenAI, Roboflow Custom Metadata, Stitch OCR Detections, Blur Visualization, CSV Formatter, Crop Visualization, OpenAI, Grid Visualization, Perspective Correction, Twilio SMS Notification, Absolute Static Crop, Single-Label Classification Model, Clip Comparison, Contrast Equalization, Roboflow Dataset Upload, Roboflow Dataset Upload, Polygon Zone Visualization, Stability AI Image Generation, Webhook Sink, Depth Estimation, Dimension Collapse, Bounding Box Visualization, Camera Focus, Line Counter Visualization, Multi-Label Classification Model, Icon Visualization, Image Blur, Pixelate Visualization, Image Threshold, Anthropic Claude, LMM, Google Gemini, Cosine Similarity, Dynamic Crop, Model Comparison Visualization, Camera Calibration, Local File Sink, Keypoint Visualization, Identify Changes, Object Detection Model
• outputs: VLM as Detector, Google Vision OCR, SAM 3, Classification Label Visualization, Circle Visualization, Image Preprocessing, LMM For Classification, VLM as Classifier, Ellipse Visualization, Triangle Visualization, Stability AI Inpainting, QR Code Generator, VLM as Classifier, Background Color Visualization, Model Monitoring Inference Aggregator, Segment Anything 2 Model, Moondream2, Distance Measurement, Dot Visualization, Florence-2 Model, Morphological Transformation, Reference Path Visualization, Halo Visualization, SIFT Comparison, Buffer, Polygon Visualization, Florence-2 Model, Slack Notification, Clip Comparison, Perception Encoder Embedding Model, Instance Segmentation Model, OpenAI, Color Visualization, Line Counter, PTZ Tracking (ONVIF).md), Keypoint Detection Model, Object Detection Model, Google Gemini, JSON Parser, Label Visualization, Email Notification, Llama 3.2 Vision, Trace Visualization, Line Counter, YOLO-World Model, Size Measurement, Email Notification, Corner Visualization, Mask Visualization, Time in Zone, OpenAI, Roboflow Custom Metadata, Stability AI Outpainting, CogVLM, Stitch OCR Detections, Detections Stitch, Cache Set, Time in Zone, Crop Visualization, VLM as Detector, OpenAI, Grid Visualization, Detections Classes Replacement, Perspective Correction, Twilio SMS Notification, Clip Comparison, Seg Preview, Contrast Equalization, Roboflow Dataset Upload, Roboflow Dataset Upload, Polygon Zone Visualization, CLIP Embedding Model, Stability AI Image Generation, Webhook Sink, Bounding Box Visualization, Line Counter Visualization, Instance Segmentation Model, Icon Visualization, Image Blur, Time in Zone, Image Threshold, Path Deviation, Keypoint Detection Model, Anthropic Claude, LMM, Google Gemini, Pixel Color Count, Dynamic Crop, Path Deviation, Detections Consensus, Model Comparison Visualization, Cache Get, Local File Sink, Keypoint Visualization, Object Detection Model

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds OpenAI in version v3 has.

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the OpenAI model.
  • classes (list_of_values): List of classes to be used.
  • api_key (Union[string, secret, ROBOFLOW_MANAGED_KEY]): Your OpenAI API key.
  • model_version (string): Model to be used.
  • image_detail (string): Indicates the image's quality, with 'high' suggesting it is of high resolution and should be processed or displayed with high fidelity..
  • temperature (float): Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..

• output

  • output (Union[string, language_model_output]): String value if string or LLM / VLM output if language_model_output.
  • classes (list_of_values): List of values of any type.

Example JSON definition of step OpenAI in version v3

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/open_ai@v3",
    "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-5",
    "image_detail": "auto",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>"
}

v2

Class: OpenAIBlockV2 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.openai.v2.OpenAIBlockV2

Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning

Ask a question to OpenAI's GPT models with vision capabilities (including GPT-4o and GPT-5).

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

• Open Prompt (unconstrained) - Use any prompt to generate a raw response

• Text Recognition (OCR) (ocr) - Model recognizes text in the image

• Visual Question Answering (visual-question-answering) - Model answers the question you submit in the prompt

• Captioning (short) (caption) - Model provides a short description of the image

• Captioning (detailed-caption) - Model provides a long description of the image

• Single-Label Classification (classification) - Model classifies the image content as one of the provided classes

• Multi-Label Classification (multi-label-classification) - Model classifies the image content as one or more of the provided classes

• Structured Output Generation (structured-answering) - Model returns a JSON response with the specified fields

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

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
task_type	str	Task type to be performed by model. Value determines required parameters and output response..	❌
prompt	str	Text prompt to the OpenAI model.	✅
output_structure	Dict[str, str]	Dictionary with structure of expected JSON response.	❌
classes	List[str]	List of classes to be used.	✅
api_key	str	Your OpenAI API key.	✅
model_version	str	Model to be used.	✅
image_detail	str	Indicates the image's quality, with 'high' suggesting it is of high resolution and should be processed or displayed with high fidelity..	✅
max_tokens	int	Maximum number of tokens the model can generate in it's response..	❌
temperature	float	Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..	✅
max_concurrent_requests	int	Number of concurrent requests that can be executed by block when batch of input images provided. If not given - block defaults to value configured globally in Workflows Execution Engine. Please restrict if you hit OpenAI limits..	❌

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

Available Connections

Compatible Blocks

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

• inputs: VLM as Detector, Google Vision OCR, Classification Label Visualization, Circle Visualization, Image Contours, Relative Static Crop, Image Preprocessing, LMM For Classification, VLM as Classifier, Ellipse Visualization, Stitch Images, Triangle Visualization, Stability AI Inpainting, QR Code Generator, Image Slicer, Background Color Visualization, Model Monitoring Inference Aggregator, OCR Model, Dot Visualization, Florence-2 Model, SIFT, Morphological Transformation, EasyOCR, Reference Path Visualization, Halo Visualization, SIFT Comparison, Gaze Detection, Buffer, Polygon Visualization, Image Slicer, Florence-2 Model, Slack Notification, Clip Comparison, Image Convert Grayscale, Instance Segmentation Model, OpenAI, Color Visualization, Keypoint Detection Model, Google Gemini, Label Visualization, Email Notification, Llama 3.2 Vision, Trace Visualization, Dynamic Zone, Size Measurement, Email Notification, Corner Visualization, Mask Visualization, CogVLM, Stability AI Outpainting, OpenAI, Roboflow Custom Metadata, Stitch OCR Detections, Blur Visualization, CSV Formatter, Crop Visualization, OpenAI, Grid Visualization, Perspective Correction, Twilio SMS Notification, Absolute Static Crop, Single-Label Classification Model, Clip Comparison, Contrast Equalization, Roboflow Dataset Upload, Roboflow Dataset Upload, Polygon Zone Visualization, Stability AI Image Generation, Webhook Sink, Depth Estimation, Dimension Collapse, Bounding Box Visualization, Camera Focus, Line Counter Visualization, Multi-Label Classification Model, Icon Visualization, Image Blur, Pixelate Visualization, Image Threshold, Anthropic Claude, LMM, Google Gemini, Cosine Similarity, Dynamic Crop, Model Comparison Visualization, Camera Calibration, Local File Sink, Keypoint Visualization, Identify Changes, Object Detection Model
• outputs: VLM as Detector, Google Vision OCR, SAM 3, Classification Label Visualization, Circle Visualization, Image Preprocessing, LMM For Classification, VLM as Classifier, Ellipse Visualization, Triangle Visualization, Stability AI Inpainting, QR Code Generator, VLM as Classifier, Background Color Visualization, Model Monitoring Inference Aggregator, Segment Anything 2 Model, Moondream2, Distance Measurement, Dot Visualization, Florence-2 Model, Morphological Transformation, Reference Path Visualization, Halo Visualization, SIFT Comparison, Buffer, Polygon Visualization, Florence-2 Model, Slack Notification, Clip Comparison, Perception Encoder Embedding Model, Instance Segmentation Model, OpenAI, Color Visualization, Line Counter, PTZ Tracking (ONVIF).md), Keypoint Detection Model, Object Detection Model, Google Gemini, JSON Parser, Label Visualization, Email Notification, Llama 3.2 Vision, Trace Visualization, Line Counter, YOLO-World Model, Size Measurement, Email Notification, Corner Visualization, Mask Visualization, Time in Zone, OpenAI, Roboflow Custom Metadata, Stability AI Outpainting, CogVLM, Stitch OCR Detections, Detections Stitch, Cache Set, Time in Zone, Crop Visualization, VLM as Detector, OpenAI, Grid Visualization, Detections Classes Replacement, Perspective Correction, Twilio SMS Notification, Clip Comparison, Seg Preview, Contrast Equalization, Roboflow Dataset Upload, Roboflow Dataset Upload, Polygon Zone Visualization, CLIP Embedding Model, Stability AI Image Generation, Webhook Sink, Bounding Box Visualization, Line Counter Visualization, Instance Segmentation Model, Icon Visualization, Image Blur, Time in Zone, Image Threshold, Path Deviation, Keypoint Detection Model, Anthropic Claude, LMM, Google Gemini, Pixel Color Count, Dynamic Crop, Path Deviation, Detections Consensus, Model Comparison Visualization, Cache Get, Local File Sink, Keypoint Visualization, Object Detection Model

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the OpenAI model.
  • classes (list_of_values): List of classes to be used.
  • api_key (Union[string, secret]): Your OpenAI API key.
  • model_version (string): Model to be used.
  • image_detail (string): Indicates the image's quality, with 'high' suggesting it is of high resolution and should be processed or displayed with high fidelity..
  • temperature (float): Temperature to sample from the model - value in range 0.0-2.0, the higher - the more random / "creative" the generations are..

• output

  • output (Union[string, language_model_output]): String value if string or LLM / VLM output if language_model_output.
  • classes (list_of_values): List of values of any type.

Example JSON definition of step OpenAI in version v2

{
    "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>"
}

v1

Class: OpenAIBlockV1 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.openai.v1.OpenAIBlockV1

Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning

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

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
prompt	str	Text prompt to the OpenAI model.	✅
openai_api_key	str	Your OpenAI API key.	✅
openai_model	str	Model to be used.	✅
json_output_format	Dict[str, str]	Holds dictionary that maps name of requested output field into its description.	❌
image_detail	str	Indicates the image's quality, with 'high' suggesting it is of high resolution and should be processed or displayed with high fidelity..	✅
max_tokens	int	Maximum number of tokens the model can generate in it's response..	❌

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

Available Connections

Compatible Blocks

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

• inputs: VLM as Detector, Google Vision OCR, Classification Label Visualization, Circle Visualization, Image Contours, Relative Static Crop, Image Preprocessing, LMM For Classification, VLM as Classifier, Ellipse Visualization, Stitch Images, Triangle Visualization, Stability AI Inpainting, QR Code Generator, Image Slicer, Background Color Visualization, Model Monitoring Inference Aggregator, OCR Model, Dot Visualization, Florence-2 Model, SIFT, Morphological Transformation, EasyOCR, Reference Path Visualization, Halo Visualization, SIFT Comparison, Polygon Visualization, Image Slicer, Florence-2 Model, Slack Notification, Clip Comparison, Image Convert Grayscale, Instance Segmentation Model, OpenAI, Color Visualization, Keypoint Detection Model, Google Gemini, Label Visualization, Email Notification, Llama 3.2 Vision, Trace Visualization, Email Notification, Corner Visualization, Mask Visualization, CogVLM, Stability AI Outpainting, OpenAI, Roboflow Custom Metadata, Stitch OCR Detections, Blur Visualization, CSV Formatter, Crop Visualization, OpenAI, Grid Visualization, Perspective Correction, Twilio SMS Notification, Absolute Static Crop, Single-Label Classification Model, Contrast Equalization, Roboflow Dataset Upload, Roboflow Dataset Upload, Polygon Zone Visualization, Stability AI Image Generation, Webhook Sink, Depth Estimation, Bounding Box Visualization, Camera Focus, Line Counter Visualization, Multi-Label Classification Model, Icon Visualization, Image Blur, Pixelate Visualization, Image Threshold, Anthropic Claude, LMM, Google Gemini, Dynamic Crop, Model Comparison Visualization, Camera Calibration, Local File Sink, Keypoint Visualization, Object Detection Model
• outputs: VLM as Detector, Byte Tracker, Google Vision OCR, SAM 3, Overlap Filter, Detections Stabilizer, Image Preprocessing, LMM For Classification, Ellipse Visualization, Triangle Visualization, Stitch Images, Detections Combine, QR Code Generator, Image Slicer, VLM as Classifier, Background Color Visualization, Model Monitoring Inference Aggregator, Segment Anything 2 Model, Template Matching, Distance Measurement, Dot Visualization, EasyOCR, Halo Visualization, Data Aggregator, Slack Notification, Byte Tracker, Color Visualization, JSON Parser, Llama 3.2 Vision, QR Code Detection, Expression, Line Counter, Size Measurement, Email Notification, Delta Filter, Corner Visualization, Mask Visualization, Continue If, Time in Zone, Roboflow Custom Metadata, Stability AI Outpainting, Barcode Detection, Dominant Color, Time in Zone, Crop Visualization, VLM as Detector, Grid Visualization, Perspective Correction, Clip Comparison, Single-Label Classification Model, Contrast Equalization, Polygon Zone Visualization, CLIP Embedding Model, Bounding Box Visualization, Camera Focus, Icon Visualization, Image Blur, Time in Zone, Path Deviation, Anthropic Claude, Cosine Similarity, Multi-Label Classification Model, Dynamic Crop, Bounding Rectangle, Path Deviation, Detections Consensus, Model Comparison Visualization, Cache Get, Local File Sink, Rate Limiter, Identify Changes, Classification Label Visualization, Circle Visualization, SIFT Comparison, Image Contours, Relative Static Crop, Detections Filter, VLM as Classifier, Stability AI Inpainting, Moondream2, Velocity, OCR Model, Florence-2 Model, SIFT, Morphological Transformation, Detections Transformation, Reference Path Visualization, Gaze Detection, SIFT Comparison, Buffer, Polygon Visualization, Florence-2 Model, Image Slicer, Detection Offset, Clip Comparison, Perception Encoder Embedding Model, Instance Segmentation Model, OpenAI, Image Convert Grayscale, Line Counter, PTZ Tracking (ONVIF).md), Object Detection Model, Keypoint Detection Model, Google Gemini, Label Visualization, Email Notification, Trace Visualization, Byte Tracker, Dynamic Zone, YOLO-World Model, OpenAI, CogVLM, Stitch OCR Detections, Detections Stitch, Cache Set, Blur Visualization, CSV Formatter, Single-Label Classification Model, OpenAI, Detections Classes Replacement, Twilio SMS Notification, Absolute Static Crop, Seg Preview, Roboflow Dataset Upload, Roboflow Dataset Upload, Property Definition, Stability AI Image Generation, Webhook Sink, Depth Estimation, Dimension Collapse, Line Counter Visualization, Instance Segmentation Model, Multi-Label Classification Model, Pixelate Visualization, Image Threshold, Detections Merge, Keypoint Detection Model, LMM, Google Gemini, Identify Outliers, Pixel Color Count, SmolVLM2, Qwen2.5-VL, First Non Empty Or Default, Camera Calibration, Keypoint Visualization, Object Detection Model

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the OpenAI model.
  • openai_api_key (Union[string, secret]): Your OpenAI API key.
  • openai_model (string): Model to be used.
  • image_detail (string): Indicates the image's quality, with 'high' suggesting it is of high resolution and should be processed or displayed with high fidelity..

• output

  • parent_id (parent_id): Identifier of parent for step output.
  • root_parent_id (parent_id): Identifier of parent for step output.
  • image (image_metadata): Dictionary with image metadata required by supervision.
  • structured_output (dictionary): Dictionary.
  • raw_output (string): String value.
  • * (*): Equivalent of any element.

Example JSON definition of step OpenAI in version v1

{
    "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
}