OpenAI¶
v4¶
Class: OpenAIBlockV4 (there are multiple versions of this block)
Source: inference.core.workflows.core_steps.models.foundation.openai.v4.OpenAIBlockV4
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 -
Unprompted Object Detection (
object-detection) - Model detects and returns the bounding boxes for prominent objects in the image -
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@v4to 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. | ✅ |
reasoning_effort |
str |
Controls reasoning. Reducing can result in faster responses and fewer tokens. GPT-5.1 and higher models default to 'none' (no reasoning) and support 'none', 'low', 'medium', 'high'. GPT-5.2 also supports 'xhigh'. GPT-5 models default to 'medium' and support 'minimal', 'low', 'medium', 'high'.. | ✅ |
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 its response. If not specified, the model will use its default limit. Minimum value is 16.. | ❌ |
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.
Runtime compatibility¶
-
requires_internet— air-gapped / offline deployments - This block depends on a service that is not reachable from fully offline / air-gapped deployments.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to OpenAI in version v4.
- inputs:
Google Gemma API,Camera Focus,Event Writer,Google Gemini,Current Time,Ellipse Visualization,Camera Focus,Image Contours,Image Preprocessing,Background Subtraction,Color Visualization,Crop Visualization,Mask Visualization,Multi-Label Classification Model,Relative Static Crop,Google Vision OCR,SIFT Comparison,Google Gemini,EasyOCR,Llama 3.2 Vision,VLM As Detector,Contrast Enhancement,Image Convert Grayscale,Google Gemma,Google Gemini,Image Blur,Keypoint Visualization,Identify Changes,MQTT Writer,Buffer,Anthropic Claude,Camera Calibration,Twilio SMS Notification,LMM For Classification,Qwen 3.6 API,Perspective Correction,OpenAI-Compatible LLM,Contrast Equalization,Clip Comparison,Qwen-VL,Image Stack,Model Comparison Visualization,Single-Label Classification Model,PLC EthernetIP,Dot Visualization,OpenAI,Dynamic Zone,Reference Path Visualization,Polygon Visualization,Size Measurement,Microsoft SQL Server Sink,Webhook Sink,SIFT,Image Slicer,Stability AI Outpainting,Halo Visualization,Dimension Collapse,Email Notification,QR Code Generator,Local File Sink,Classification Label Visualization,Bounding Box Visualization,MoonshotAI Kimi,Pixelate Visualization,Image Slicer,Depth Estimation,Text Display,Roboflow Vision Events,Object Detection Model,Icon Visualization,Motion Detection,Blur Visualization,VLM As Classifier,Anthropic Claude,Grid Visualization,Cosine Similarity,OpenRouter,MoonshotAI Kimi,Anthropic Claude,Detections List Roll-Up,LMM,Stability AI Inpainting,Roboflow Dataset Upload,PLC ModbusTCP,Model Monitoring Inference Aggregator,Image Threshold,Qwen3.5-VL,Trace Visualization,Circle Visualization,Instance Segmentation Model,Label Visualization,Morphological Transformation,Morphological Transformation,Polygon Zone Visualization,Keypoint Detection Model,Dynamic Crop,Polygon Visualization,Florence-2 Model,OpenAI,CSV Formatter,Stability AI Image Generation,Gaze Detection,Qwen 3.5 API,Absolute Static Crop,CogVLM,Roboflow Dataset Upload,Stitch Images,Florence-2 Model,Twilio SMS/MMS Notification,Clip Comparison,Triangle Visualization,Roboflow Asset Library Attributes,Background Color Visualization,Corner Visualization,Stitch OCR Detections,Line Counter Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Custom Metadata,OCR Model,OpenAI,Email Notification,Slack Notification,S3 Sink,GLM-OCR,OpenAI,Llama 3.2 Vision,Heatmap Visualization,OPC UA Writer Sink - outputs:
Google Gemma API,Event Writer,Google Gemini,Current Time,Ellipse Visualization,SAM 3,Image Preprocessing,YOLO-World Model,Mask Visualization,Crop Visualization,Segment Anything 2 Model,Color Visualization,Seg Preview,Perception Encoder Embedding Model,JSON Parser,Cache Set,Google Vision OCR,Single-Label Classification Model,SIFT Comparison,Object Detection Model,Google Gemini,Instance Segmentation Model,Llama 3.2 Vision,VLM As Detector,SAM 3,Google Gemma,Google Gemini,Keypoint Detection Model,Image Blur,Keypoint Visualization,MQTT Writer,Buffer,Anthropic Claude,VLM As Detector,PTZ Tracking (ONVIF),Twilio SMS Notification,Detections Stitch,LMM For Classification,Qwen 3.6 API,Semantic Segmentation Model,Perspective Correction,Cache Get,Detections Classes Replacement,SAM 3,Time in Zone,CLIP Embedding Model,OpenAI-Compatible LLM,Contrast Equalization,Clip Comparison,Qwen-VL,Model Comparison Visualization,PLC EthernetIP,Dot Visualization,OpenAI,Moondream2,Reference Path Visualization,Polygon Visualization,Size Measurement,Microsoft SQL Server Sink,Path Deviation,Webhook Sink,Instance Segmentation Model,Stability AI Outpainting,Halo Visualization,Email Notification,QR Code Generator,Local File Sink,Classification Label Visualization,Bounding Box Visualization,MoonshotAI Kimi,Object Detection Model,Path Deviation,Depth Estimation,Roboflow Vision Events,Text Display,Time in Zone,Distance Measurement,Object Detection Model,Icon Visualization,Motion Detection,VLM As Classifier,Anthropic Claude,Grid Visualization,OpenRouter,MoonshotAI Kimi,Anthropic Claude,Detections List Roll-Up,LMM,Stability AI Inpainting,Roboflow Dataset Upload,Qwen3.5-VL,Image Threshold,Model Monitoring Inference Aggregator,Trace Visualization,Circle Visualization,Instance Segmentation Model,Label Visualization,Pixel Color Count,Morphological Transformation,Morphological Transformation,Polygon Zone Visualization,Keypoint Detection Model,VLM As Classifier,Dynamic Crop,Polygon Visualization,Florence-2 Model,OpenAI,Stability AI Image Generation,Qwen 3.5 API,CogVLM,Roboflow Dataset Upload,Multi-Label Classification Model,Florence-2 Model,Twilio SMS/MMS Notification,Line Counter,Time in Zone,Clip Comparison,Triangle Visualization,Roboflow Asset Library Attributes,Background Color Visualization,Detections Consensus,Keypoint Detection Model,Corner Visualization,Stitch OCR Detections,Line Counter Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Custom Metadata,Line Counter,OpenAI,Email Notification,Slack Notification,S3 Sink,GLM-OCR,OpenAI,Llama 3.2 Vision,Heatmap Visualization,Instance Segmentation Model,OPC UA Writer Sink
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
OpenAI in version v4 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[secret,string,ROBOFLOW_MANAGED_KEY]): Your OpenAI API key.model_version(string): Model to be used.reasoning_effort(string): Controls reasoning. Reducing can result in faster responses and fewer tokens. GPT-5.1 and higher models default to 'none' (no reasoning) and support 'none', 'low', 'medium', 'high'. GPT-5.2 also supports 'xhigh'. GPT-5 models default to 'medium' and support 'minimal', 'low', 'medium', 'high'..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 ifstringor LLM / VLM output iflanguage_model_output.classes(list_of_values): List of values of any type.
Example JSON definition of step OpenAI in version v4
{
"name": "<your_step_name_here>",
"type": "roboflow_core/open_ai@v4",
"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-5.1",
"reasoning_effort": "<block_does_not_provide_example>",
"image_detail": "auto",
"max_tokens": "<block_does_not_provide_example>",
"temperature": "<block_does_not_provide_example>",
"max_concurrent_requests": "<block_does_not_provide_example>"
}
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.
Runtime compatibility¶
-
requires_internet— air-gapped / offline deployments - This block depends on a service that is not reachable from fully offline / air-gapped deployments.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to OpenAI in version v3.
- inputs:
Google Gemma API,Camera Focus,Event Writer,Google Gemini,Current Time,Ellipse Visualization,Camera Focus,Image Contours,Image Preprocessing,Background Subtraction,Color Visualization,Crop Visualization,Mask Visualization,Multi-Label Classification Model,Relative Static Crop,Google Vision OCR,SIFT Comparison,Google Gemini,EasyOCR,Llama 3.2 Vision,VLM As Detector,Contrast Enhancement,Image Convert Grayscale,Google Gemma,Google Gemini,Image Blur,Keypoint Visualization,Identify Changes,MQTT Writer,Buffer,Anthropic Claude,Camera Calibration,Twilio SMS Notification,LMM For Classification,Qwen 3.6 API,Perspective Correction,OpenAI-Compatible LLM,Contrast Equalization,Clip Comparison,Qwen-VL,Image Stack,Model Comparison Visualization,Single-Label Classification Model,PLC EthernetIP,Dot Visualization,OpenAI,Dynamic Zone,Reference Path Visualization,Polygon Visualization,Size Measurement,Microsoft SQL Server Sink,Webhook Sink,SIFT,Image Slicer,Stability AI Outpainting,Halo Visualization,Dimension Collapse,Email Notification,QR Code Generator,Local File Sink,Classification Label Visualization,Bounding Box Visualization,MoonshotAI Kimi,Pixelate Visualization,Image Slicer,Depth Estimation,Text Display,Roboflow Vision Events,Object Detection Model,Icon Visualization,Motion Detection,Blur Visualization,VLM As Classifier,Anthropic Claude,Grid Visualization,Cosine Similarity,OpenRouter,MoonshotAI Kimi,Anthropic Claude,Detections List Roll-Up,LMM,Stability AI Inpainting,Roboflow Dataset Upload,PLC ModbusTCP,Model Monitoring Inference Aggregator,Image Threshold,Qwen3.5-VL,Trace Visualization,Circle Visualization,Instance Segmentation Model,Label Visualization,Morphological Transformation,Morphological Transformation,Polygon Zone Visualization,Keypoint Detection Model,Dynamic Crop,Polygon Visualization,Florence-2 Model,OpenAI,CSV Formatter,Stability AI Image Generation,Gaze Detection,Qwen 3.5 API,Absolute Static Crop,CogVLM,Roboflow Dataset Upload,Stitch Images,Florence-2 Model,Twilio SMS/MMS Notification,Clip Comparison,Triangle Visualization,Roboflow Asset Library Attributes,Background Color Visualization,Corner Visualization,Stitch OCR Detections,Line Counter Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Custom Metadata,OCR Model,OpenAI,Email Notification,Slack Notification,S3 Sink,GLM-OCR,OpenAI,Llama 3.2 Vision,Heatmap Visualization,OPC UA Writer Sink - outputs:
Google Gemma API,Event Writer,Google Gemini,Current Time,Ellipse Visualization,SAM 3,Image Preprocessing,YOLO-World Model,Mask Visualization,Crop Visualization,Segment Anything 2 Model,Color Visualization,Seg Preview,Perception Encoder Embedding Model,JSON Parser,Cache Set,Google Vision OCR,Single-Label Classification Model,SIFT Comparison,Object Detection Model,Google Gemini,Instance Segmentation Model,Llama 3.2 Vision,VLM As Detector,SAM 3,Google Gemma,Google Gemini,Keypoint Detection Model,Image Blur,Keypoint Visualization,MQTT Writer,Buffer,Anthropic Claude,VLM As Detector,PTZ Tracking (ONVIF),Twilio SMS Notification,Detections Stitch,LMM For Classification,Qwen 3.6 API,Semantic Segmentation Model,Perspective Correction,Cache Get,Detections Classes Replacement,SAM 3,Time in Zone,CLIP Embedding Model,OpenAI-Compatible LLM,Contrast Equalization,Clip Comparison,Qwen-VL,Model Comparison Visualization,PLC EthernetIP,Dot Visualization,OpenAI,Moondream2,Reference Path Visualization,Polygon Visualization,Size Measurement,Microsoft SQL Server Sink,Path Deviation,Webhook Sink,Instance Segmentation Model,Stability AI Outpainting,Halo Visualization,Email Notification,QR Code Generator,Local File Sink,Classification Label Visualization,Bounding Box Visualization,MoonshotAI Kimi,Object Detection Model,Path Deviation,Depth Estimation,Roboflow Vision Events,Text Display,Time in Zone,Distance Measurement,Object Detection Model,Icon Visualization,Motion Detection,VLM As Classifier,Anthropic Claude,Grid Visualization,OpenRouter,MoonshotAI Kimi,Anthropic Claude,Detections List Roll-Up,LMM,Stability AI Inpainting,Roboflow Dataset Upload,Qwen3.5-VL,Image Threshold,Model Monitoring Inference Aggregator,Trace Visualization,Circle Visualization,Instance Segmentation Model,Label Visualization,Pixel Color Count,Morphological Transformation,Morphological Transformation,Polygon Zone Visualization,Keypoint Detection Model,VLM As Classifier,Dynamic Crop,Polygon Visualization,Florence-2 Model,OpenAI,Stability AI Image Generation,Qwen 3.5 API,CogVLM,Roboflow Dataset Upload,Multi-Label Classification Model,Florence-2 Model,Twilio SMS/MMS Notification,Line Counter,Time in Zone,Clip Comparison,Triangle Visualization,Roboflow Asset Library Attributes,Background Color Visualization,Detections Consensus,Keypoint Detection Model,Corner Visualization,Stitch OCR Detections,Line Counter Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Custom Metadata,Line Counter,OpenAI,Email Notification,Slack Notification,S3 Sink,GLM-OCR,OpenAI,Llama 3.2 Vision,Heatmap Visualization,Instance Segmentation Model,OPC UA Writer Sink
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[secret,string,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 ifstringor LLM / VLM output iflanguage_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.
Runtime compatibility¶
-
requires_internet— air-gapped / offline deployments - This block depends on a service that is not reachable from fully offline / air-gapped deployments.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to OpenAI in version v2.
- inputs:
Google Gemma API,Camera Focus,Event Writer,Google Gemini,Current Time,Ellipse Visualization,Camera Focus,Image Contours,Image Preprocessing,Background Subtraction,Color Visualization,Crop Visualization,Mask Visualization,Multi-Label Classification Model,Relative Static Crop,Google Vision OCR,SIFT Comparison,Google Gemini,EasyOCR,Llama 3.2 Vision,VLM As Detector,Contrast Enhancement,Image Convert Grayscale,Google Gemma,Google Gemini,Image Blur,Keypoint Visualization,Identify Changes,MQTT Writer,Buffer,Anthropic Claude,Camera Calibration,Twilio SMS Notification,LMM For Classification,Qwen 3.6 API,Perspective Correction,OpenAI-Compatible LLM,Contrast Equalization,Clip Comparison,Qwen-VL,Image Stack,Model Comparison Visualization,Single-Label Classification Model,PLC EthernetIP,Dot Visualization,OpenAI,Dynamic Zone,Reference Path Visualization,Polygon Visualization,Size Measurement,Microsoft SQL Server Sink,Webhook Sink,SIFT,Image Slicer,Stability AI Outpainting,Halo Visualization,Dimension Collapse,Email Notification,QR Code Generator,Local File Sink,Classification Label Visualization,Bounding Box Visualization,MoonshotAI Kimi,Pixelate Visualization,Image Slicer,Depth Estimation,Text Display,Roboflow Vision Events,Object Detection Model,Icon Visualization,Motion Detection,Blur Visualization,VLM As Classifier,Anthropic Claude,Grid Visualization,Cosine Similarity,OpenRouter,MoonshotAI Kimi,Anthropic Claude,Detections List Roll-Up,LMM,Stability AI Inpainting,Roboflow Dataset Upload,PLC ModbusTCP,Model Monitoring Inference Aggregator,Image Threshold,Qwen3.5-VL,Trace Visualization,Circle Visualization,Instance Segmentation Model,Label Visualization,Morphological Transformation,Morphological Transformation,Polygon Zone Visualization,Keypoint Detection Model,Dynamic Crop,Polygon Visualization,Florence-2 Model,OpenAI,CSV Formatter,Stability AI Image Generation,Gaze Detection,Qwen 3.5 API,Absolute Static Crop,CogVLM,Roboflow Dataset Upload,Stitch Images,Florence-2 Model,Twilio SMS/MMS Notification,Clip Comparison,Triangle Visualization,Roboflow Asset Library Attributes,Background Color Visualization,Corner Visualization,Stitch OCR Detections,Line Counter Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Custom Metadata,OCR Model,OpenAI,Email Notification,Slack Notification,S3 Sink,GLM-OCR,OpenAI,Llama 3.2 Vision,Heatmap Visualization,OPC UA Writer Sink - outputs:
Google Gemma API,Event Writer,Google Gemini,Current Time,Ellipse Visualization,SAM 3,Image Preprocessing,YOLO-World Model,Mask Visualization,Crop Visualization,Segment Anything 2 Model,Color Visualization,Seg Preview,Perception Encoder Embedding Model,JSON Parser,Cache Set,Google Vision OCR,Single-Label Classification Model,SIFT Comparison,Object Detection Model,Google Gemini,Instance Segmentation Model,Llama 3.2 Vision,VLM As Detector,SAM 3,Google Gemma,Google Gemini,Keypoint Detection Model,Image Blur,Keypoint Visualization,MQTT Writer,Buffer,Anthropic Claude,VLM As Detector,PTZ Tracking (ONVIF),Twilio SMS Notification,Detections Stitch,LMM For Classification,Qwen 3.6 API,Semantic Segmentation Model,Perspective Correction,Cache Get,Detections Classes Replacement,SAM 3,Time in Zone,CLIP Embedding Model,OpenAI-Compatible LLM,Contrast Equalization,Clip Comparison,Qwen-VL,Model Comparison Visualization,PLC EthernetIP,Dot Visualization,OpenAI,Moondream2,Reference Path Visualization,Polygon Visualization,Size Measurement,Microsoft SQL Server Sink,Path Deviation,Webhook Sink,Instance Segmentation Model,Stability AI Outpainting,Halo Visualization,Email Notification,QR Code Generator,Local File Sink,Classification Label Visualization,Bounding Box Visualization,MoonshotAI Kimi,Object Detection Model,Path Deviation,Depth Estimation,Roboflow Vision Events,Text Display,Time in Zone,Distance Measurement,Object Detection Model,Icon Visualization,Motion Detection,VLM As Classifier,Anthropic Claude,Grid Visualization,OpenRouter,MoonshotAI Kimi,Anthropic Claude,Detections List Roll-Up,LMM,Stability AI Inpainting,Roboflow Dataset Upload,Qwen3.5-VL,Image Threshold,Model Monitoring Inference Aggregator,Trace Visualization,Circle Visualization,Instance Segmentation Model,Label Visualization,Pixel Color Count,Morphological Transformation,Morphological Transformation,Polygon Zone Visualization,Keypoint Detection Model,VLM As Classifier,Dynamic Crop,Polygon Visualization,Florence-2 Model,OpenAI,Stability AI Image Generation,Qwen 3.5 API,CogVLM,Roboflow Dataset Upload,Multi-Label Classification Model,Florence-2 Model,Twilio SMS/MMS Notification,Line Counter,Time in Zone,Clip Comparison,Triangle Visualization,Roboflow Asset Library Attributes,Background Color Visualization,Detections Consensus,Keypoint Detection Model,Corner Visualization,Stitch OCR Detections,Line Counter Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Custom Metadata,Line Counter,OpenAI,Email Notification,Slack Notification,S3 Sink,GLM-OCR,OpenAI,Llama 3.2 Vision,Heatmap Visualization,Instance Segmentation Model,OPC UA Writer Sink
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[secret,string]): 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 ifstringor LLM / VLM output iflanguage_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.
Runtime compatibility¶
-
requires_internet— air-gapped / offline deployments - This block depends on a service that is not reachable from fully offline / air-gapped deployments.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to OpenAI in version v1.
- inputs:
Google Gemma API,Camera Focus,Event Writer,Google Gemini,Current Time,Ellipse Visualization,Camera Focus,Image Contours,Image Preprocessing,Background Subtraction,Color Visualization,Crop Visualization,Mask Visualization,Multi-Label Classification Model,Relative Static Crop,Google Vision OCR,SIFT Comparison,Google Gemini,EasyOCR,Llama 3.2 Vision,VLM As Detector,Contrast Enhancement,Image Convert Grayscale,Google Gemma,Google Gemini,Image Blur,Keypoint Visualization,MQTT Writer,Anthropic Claude,Camera Calibration,Twilio SMS Notification,LMM For Classification,Qwen 3.6 API,Perspective Correction,OpenAI-Compatible LLM,Contrast Equalization,Clip Comparison,Qwen-VL,Model Comparison Visualization,Single-Label Classification Model,Dot Visualization,OpenAI,Reference Path Visualization,Polygon Visualization,Microsoft SQL Server Sink,Webhook Sink,SIFT,Image Slicer,Stability AI Outpainting,Halo Visualization,Email Notification,QR Code Generator,Local File Sink,Classification Label Visualization,Bounding Box Visualization,MoonshotAI Kimi,Pixelate Visualization,Image Slicer,Depth Estimation,Text Display,Roboflow Vision Events,Object Detection Model,Icon Visualization,Blur Visualization,VLM As Classifier,Anthropic Claude,Grid Visualization,OpenRouter,MoonshotAI Kimi,Anthropic Claude,LMM,Stability AI Inpainting,Roboflow Dataset Upload,Model Monitoring Inference Aggregator,Image Threshold,Qwen3.5-VL,Trace Visualization,Circle Visualization,Instance Segmentation Model,Label Visualization,Morphological Transformation,Morphological Transformation,Polygon Zone Visualization,Keypoint Detection Model,Dynamic Crop,Polygon Visualization,Florence-2 Model,OpenAI,CSV Formatter,Stability AI Image Generation,Qwen 3.5 API,Absolute Static Crop,CogVLM,Roboflow Dataset Upload,Stitch Images,Florence-2 Model,Twilio SMS/MMS Notification,Triangle Visualization,Roboflow Asset Library Attributes,Background Color Visualization,Corner Visualization,Stitch OCR Detections,Line Counter Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Custom Metadata,OCR Model,OpenAI,Email Notification,Slack Notification,S3 Sink,GLM-OCR,OpenAI,Llama 3.2 Vision,Heatmap Visualization,OPC UA Writer Sink - outputs:
Camera Focus,Current Time,Camera Focus,Image Preprocessing,Background Subtraction,Multi-Label Classification Model,Color Visualization,Mask Visualization,Segment Anything 2 Model,Seg Preview,Multi-Label Classification Model,JSON Parser,Cache Set,Google Vision OCR,Single-Label Classification Model,SIFT Comparison,Google Gemini,Instance Segmentation Model,Llama 3.2 Vision,Contrast Enhancement,Keypoint Detection Model,Keypoint Visualization,First Non Empty Or Default,Camera Calibration,VLM As Detector,Twilio SMS Notification,Expression,LMM For Classification,Barcode Detection,Perspective Correction,Cache Get,Detection Offset,CLIP Embedding Model,OpenAI-Compatible LLM,Clip Comparison,Qwen-VL,PLC EthernetIP,Model Comparison Visualization,Dot Visualization,OpenAI,Moondream2,Size Measurement,Detections Stabilizer,Dominant Color,Microsoft SQL Server Sink,SIFT,Stability AI Outpainting,Dimension Collapse,Email Notification,ByteTrack Tracker,Classification Label Visualization,Bounding Box Visualization,Object Detection Model,Pixelate Visualization,Template Matching,Image Slicer,Roboflow Vision Events,Text Display,Time in Zone,Distance Measurement,Blur Visualization,Qwen3-VL,MoonshotAI Kimi,Detections List Roll-Up,LMM,Stability AI Inpainting,Roboflow Dataset Upload,PLC ModbusTCP,Qwen3.5-VL,Circle Visualization,Instance Segmentation Model,Label Visualization,Morphological Transformation,Polygon Zone Visualization,VLM As Classifier,OpenAI,CSV Formatter,Stability AI Image Generation,CogVLM,Roboflow Dataset Upload,Detections Merge,Clip Comparison,Triangle Visualization,Detections Consensus,Background Color Visualization,Stitch OCR Detections,Delta Filter,Line Counter Visualization,Halo Visualization,Roboflow Custom Metadata,OpenAI,Email Notification,Slack Notification,Llama 3.2 Vision,Detections Filter,Bounding Rectangle,Google Gemma API,Event Writer,Google Gemini,Rate Limiter,Ellipse Visualization,Inner Workflow,SAM 3,Image Contours,YOLO-World Model,Crop Visualization,Perception Encoder Embedding Model,SAM2 Video Tracker,Relative Static Crop,Object Detection Model,Semantic Segmentation Model,EasyOCR,VLM As Detector,SAM 3,Image Convert Grayscale,Qwen3.5,Google Gemma,Google Gemini,Image Blur,Identify Changes,MQTT Writer,Buffer,Anthropic Claude,OC-SORT Tracker,PTZ Tracking (ONVIF),SIFT Comparison,Detections Stitch,Overlap Analysis,Qwen 3.6 API,Semantic Segmentation Model,Detections Classes Replacement,SAM 3,Time in Zone,Mask Edge Snap,Contrast Equalization,SORT Tracker,Image Stack,Single-Label Classification Model,Identify Outliers,Dynamic Zone,Continue If,Reference Path Visualization,Polygon Visualization,QR Code Detection,Path Deviation,Property Definition,Webhook Sink,Instance Segmentation Model,Image Slicer,Halo Visualization,QR Code Generator,Local File Sink,MoonshotAI Kimi,SmolVLM2,Path Deviation,Depth Estimation,Byte Tracker,Object Detection Model,Icon Visualization,Motion Detection,VLM As Classifier,Anthropic Claude,Grid Visualization,Cosine Similarity,OpenRouter,Anthropic Claude,Model Monitoring Inference Aggregator,Image Threshold,Overlap Filter,Data Aggregator,Trace Visualization,Pixel Color Count,Morphological Transformation,Keypoint Detection Model,Dynamic Crop,Polygon Visualization,Florence-2 Model,Detections Transformation,Single-Label Classification Model,Gaze Detection,Qwen 3.5 API,Byte Tracker,Mask Area Measurement,Absolute Static Crop,Multi-Label Classification Model,Stitch Images,Florence-2 Model,Twilio SMS/MMS Notification,Line Counter,Time in Zone,Byte Tracker,Roboflow Asset Library Attributes,Keypoint Detection Model,Corner Visualization,Detections Combine,Stitch OCR Detections,BoT-SORT Tracker,Line Counter,OCR Model,S3 Sink,GLM-OCR,Detection Event Log,OpenAI,Qwen2.5-VL,Heatmap Visualization,Instance Segmentation Model,OPC UA Writer Sink,Per-Class Confidence Filter,Velocity
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[secret,string]): 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
}