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:
Absolute Static Crop,Qwen-VL,Gaze Detection,Triangle Visualization,EasyOCR,Model Comparison Visualization,Stitch OCR Detections,Llama 3.2 Vision,Heatmap Visualization,Stitch Images,Keypoint Visualization,Anthropic Claude,Webhook Sink,Google Gemini,GLM-OCR,QR Code Generator,VLM As Detector,Multi-Label Classification Model,Twilio SMS/MMS Notification,PLC ModbusTCP,Ellipse Visualization,Pixelate Visualization,Corner Visualization,Buffer,Llama 3.2 Vision,Qwen 3.5 API,LMM,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Dimension Collapse,Morphological Transformation,Camera Calibration,Motion Detection,Google Vision OCR,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,Identify Changes,Contrast Equalization,CSV Formatter,Model Monitoring Inference Aggregator,MQTT Writer,Image Threshold,Blur Visualization,Line Counter Visualization,Google Gemini,Background Color Visualization,Microsoft SQL Server Sink,Single-Label Classification Model,Background Subtraction,VLM As Classifier,Instance Segmentation Model,Twilio SMS Notification,Polygon Zone Visualization,OPC UA Writer Sink,Google Gemma API,Reference Path Visualization,Image Stack,Stability AI Inpainting,Crop Visualization,Anthropic Claude,Image Convert Grayscale,Dynamic Zone,Camera Focus,Image Slicer,Florence-2 Model,Polygon Visualization,MoonshotAI Kimi,Dynamic Crop,Qwen 3.6 API,Event Writer,Perspective Correction,Polygon Visualization,Clip Comparison,OCR Model,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,CogVLM,Contrast Enhancement,PLC EthernetIP,Grid Visualization,LMM For Classification,Florence-2 Model,OpenAI,Local File Sink,Roboflow Custom Metadata,Qwen3.5-VL,Image Blur,Label Visualization,Object Detection Model,Anthropic Claude,Cosine Similarity,Roboflow Vision Events,Image Preprocessing,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,Dot Visualization,Current Time,Keypoint Detection Model,Roboflow Asset Library Attributes,Halo Visualization,Classification Label Visualization,Mask Visualization,Image Contours,Camera Focus,OpenRouter,S3 Sink,Stability AI Image Generation,Google Gemma,Relative Static Crop,Roboflow Dataset Upload,OpenAI,Image Slicer,Stitch OCR Detections,Google Gemini,Email Notification,Text Display,Size Measurement,Depth Estimation,Icon Visualization,OpenAI,GeoTag Detection,SIFT,PLC Writer,Detections List Roll-Up,MoonshotAI Kimi - outputs:
VLM As Classifier,Qwen-VL,Cache Get,Triangle Visualization,Model Comparison Visualization,Stitch OCR Detections,YOLO-World Model,Llama 3.2 Vision,Anthropic Claude,Keypoint Visualization,Heatmap Visualization,Webhook Sink,Google Gemini,GLM-OCR,QR Code Generator,Instance Segmentation Model,VLM As Detector,MoonshotAI Kimi,Twilio SMS/MMS Notification,Line Counter,Distance Measurement,Ellipse Visualization,Single-Label Classification Model,Keypoint Detection Model,Corner Visualization,Buffer,Llama 3.2 Vision,JSON Parser,Qwen 3.5 API,LMM,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Morphological Transformation,Motion Detection,Google Vision OCR,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,SAM3 Video Tracker,Object Detection Model,Contrast Equalization,Detections Classes Replacement,Instance Segmentation Model,Model Monitoring Inference Aggregator,MQTT Writer,Multi-Label Classification Model,Cache Set,PLC Reader,Image Threshold,Line Counter Visualization,Google Gemini,Microsoft SQL Server Sink,VLM As Classifier,Object Detection Model,Path Deviation,Twilio SMS Notification,OPC UA Writer Sink,SAM 3,Instance Segmentation Model,Google Gemma API,Polygon Zone Visualization,Keypoint Detection Model,Reference Path Visualization,Stability AI Inpainting,Perception Encoder Embedding Model,Crop Visualization,Anthropic Claude,Florence-2 Model,Polygon Visualization,Time in Zone,MoonshotAI Kimi,Dynamic Crop,Qwen 3.6 API,Event Writer,Perspective Correction,Segment Anything 2 Model,Line Counter,Polygon Visualization,Clip Comparison,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,CogVLM,PLC EthernetIP,Grid Visualization,Time in Zone,LMM For Classification,Qwen3.5-VL,Florence-2 Model,OpenAI,Roboflow Custom Metadata,Local File Sink,Label Visualization,Image Blur,Seg Preview,Path Deviation,Object Detection Model,Anthropic Claude,Pixel Color Count,Roboflow Vision Events,Image Preprocessing,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,Detections Consensus,PTZ Tracking (ONVIF),Dot Visualization,Current Time,Roboflow Asset Library Attributes,Keypoint Detection Model,Halo Visualization,SAM 3,Classification Label Visualization,OpenRouter,Moondream2,S3 Sink,Stability AI Image Generation,VLM As Detector,Google Gemma,Roboflow Dataset Upload,CLIP Embedding Model,OpenAI,Stitch OCR Detections,Google Gemini,Email Notification,SAM 3,Detections Stitch,Text Display,Semantic Segmentation Model,Size Measurement,Depth Estimation,Icon Visualization,OpenAI,Time in Zone,Instance Segmentation Model,Background Color Visualization,Detections List Roll-Up,Mask Visualization
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[ROBOFLOW_MANAGED_KEY,secret,string]): 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:
Absolute Static Crop,Qwen-VL,Gaze Detection,Triangle Visualization,EasyOCR,Model Comparison Visualization,Stitch OCR Detections,Llama 3.2 Vision,Heatmap Visualization,Stitch Images,Keypoint Visualization,Anthropic Claude,Webhook Sink,Google Gemini,GLM-OCR,QR Code Generator,VLM As Detector,Multi-Label Classification Model,Twilio SMS/MMS Notification,PLC ModbusTCP,Ellipse Visualization,Pixelate Visualization,Corner Visualization,Buffer,Llama 3.2 Vision,Qwen 3.5 API,LMM,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Dimension Collapse,Morphological Transformation,Camera Calibration,Motion Detection,Google Vision OCR,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,Identify Changes,Contrast Equalization,CSV Formatter,Model Monitoring Inference Aggregator,MQTT Writer,Image Threshold,Blur Visualization,Line Counter Visualization,Google Gemini,Background Color Visualization,Microsoft SQL Server Sink,Single-Label Classification Model,Background Subtraction,VLM As Classifier,Instance Segmentation Model,Twilio SMS Notification,Polygon Zone Visualization,OPC UA Writer Sink,Google Gemma API,Reference Path Visualization,Image Stack,Stability AI Inpainting,Crop Visualization,Anthropic Claude,Image Convert Grayscale,Dynamic Zone,Camera Focus,Image Slicer,Florence-2 Model,Polygon Visualization,MoonshotAI Kimi,Dynamic Crop,Qwen 3.6 API,Event Writer,Perspective Correction,Polygon Visualization,Clip Comparison,OCR Model,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,CogVLM,Contrast Enhancement,PLC EthernetIP,Grid Visualization,LMM For Classification,Florence-2 Model,OpenAI,Local File Sink,Roboflow Custom Metadata,Qwen3.5-VL,Image Blur,Label Visualization,Object Detection Model,Anthropic Claude,Cosine Similarity,Roboflow Vision Events,Image Preprocessing,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,Dot Visualization,Current Time,Keypoint Detection Model,Roboflow Asset Library Attributes,Halo Visualization,Classification Label Visualization,Mask Visualization,Image Contours,Camera Focus,OpenRouter,S3 Sink,Stability AI Image Generation,Google Gemma,Relative Static Crop,Roboflow Dataset Upload,OpenAI,Image Slicer,Stitch OCR Detections,Google Gemini,Email Notification,Text Display,Size Measurement,Depth Estimation,Icon Visualization,OpenAI,GeoTag Detection,SIFT,PLC Writer,Detections List Roll-Up,MoonshotAI Kimi - outputs:
VLM As Classifier,Qwen-VL,Cache Get,Triangle Visualization,Model Comparison Visualization,Stitch OCR Detections,YOLO-World Model,Llama 3.2 Vision,Anthropic Claude,Keypoint Visualization,Heatmap Visualization,Webhook Sink,Google Gemini,GLM-OCR,QR Code Generator,Instance Segmentation Model,VLM As Detector,MoonshotAI Kimi,Twilio SMS/MMS Notification,Line Counter,Distance Measurement,Ellipse Visualization,Single-Label Classification Model,Keypoint Detection Model,Corner Visualization,Buffer,Llama 3.2 Vision,JSON Parser,Qwen 3.5 API,LMM,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Morphological Transformation,Motion Detection,Google Vision OCR,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,SAM3 Video Tracker,Object Detection Model,Contrast Equalization,Detections Classes Replacement,Instance Segmentation Model,Model Monitoring Inference Aggregator,MQTT Writer,Multi-Label Classification Model,Cache Set,PLC Reader,Image Threshold,Line Counter Visualization,Google Gemini,Microsoft SQL Server Sink,VLM As Classifier,Object Detection Model,Path Deviation,Twilio SMS Notification,OPC UA Writer Sink,SAM 3,Instance Segmentation Model,Google Gemma API,Polygon Zone Visualization,Keypoint Detection Model,Reference Path Visualization,Stability AI Inpainting,Perception Encoder Embedding Model,Crop Visualization,Anthropic Claude,Florence-2 Model,Polygon Visualization,Time in Zone,MoonshotAI Kimi,Dynamic Crop,Qwen 3.6 API,Event Writer,Perspective Correction,Segment Anything 2 Model,Line Counter,Polygon Visualization,Clip Comparison,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,CogVLM,PLC EthernetIP,Grid Visualization,Time in Zone,LMM For Classification,Qwen3.5-VL,Florence-2 Model,OpenAI,Roboflow Custom Metadata,Local File Sink,Label Visualization,Image Blur,Seg Preview,Path Deviation,Object Detection Model,Anthropic Claude,Pixel Color Count,Roboflow Vision Events,Image Preprocessing,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,Detections Consensus,PTZ Tracking (ONVIF),Dot Visualization,Current Time,Roboflow Asset Library Attributes,Keypoint Detection Model,Halo Visualization,SAM 3,Classification Label Visualization,OpenRouter,Moondream2,S3 Sink,Stability AI Image Generation,VLM As Detector,Google Gemma,Roboflow Dataset Upload,CLIP Embedding Model,OpenAI,Stitch OCR Detections,Google Gemini,Email Notification,SAM 3,Detections Stitch,Text Display,Semantic Segmentation Model,Size Measurement,Depth Estimation,Icon Visualization,OpenAI,Time in Zone,Instance Segmentation Model,Background Color Visualization,Detections List Roll-Up,Mask Visualization
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[ROBOFLOW_MANAGED_KEY,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 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:
Absolute Static Crop,Qwen-VL,Gaze Detection,Triangle Visualization,EasyOCR,Model Comparison Visualization,Stitch OCR Detections,Llama 3.2 Vision,Heatmap Visualization,Stitch Images,Keypoint Visualization,Anthropic Claude,Webhook Sink,Google Gemini,GLM-OCR,QR Code Generator,VLM As Detector,Multi-Label Classification Model,Twilio SMS/MMS Notification,PLC ModbusTCP,Ellipse Visualization,Pixelate Visualization,Corner Visualization,Buffer,Llama 3.2 Vision,Qwen 3.5 API,LMM,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Dimension Collapse,Morphological Transformation,Camera Calibration,Motion Detection,Google Vision OCR,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,Identify Changes,Contrast Equalization,CSV Formatter,Model Monitoring Inference Aggregator,MQTT Writer,Image Threshold,Blur Visualization,Line Counter Visualization,Google Gemini,Background Color Visualization,Microsoft SQL Server Sink,Single-Label Classification Model,Background Subtraction,VLM As Classifier,Instance Segmentation Model,Twilio SMS Notification,Polygon Zone Visualization,OPC UA Writer Sink,Google Gemma API,Reference Path Visualization,Image Stack,Stability AI Inpainting,Crop Visualization,Anthropic Claude,Image Convert Grayscale,Dynamic Zone,Camera Focus,Image Slicer,Florence-2 Model,Polygon Visualization,MoonshotAI Kimi,Dynamic Crop,Qwen 3.6 API,Event Writer,Perspective Correction,Polygon Visualization,Clip Comparison,OCR Model,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,CogVLM,Contrast Enhancement,PLC EthernetIP,Grid Visualization,LMM For Classification,Florence-2 Model,OpenAI,Local File Sink,Roboflow Custom Metadata,Qwen3.5-VL,Image Blur,Label Visualization,Object Detection Model,Anthropic Claude,Cosine Similarity,Roboflow Vision Events,Image Preprocessing,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,Dot Visualization,Current Time,Keypoint Detection Model,Roboflow Asset Library Attributes,Halo Visualization,Classification Label Visualization,Mask Visualization,Image Contours,Camera Focus,OpenRouter,S3 Sink,Stability AI Image Generation,Google Gemma,Relative Static Crop,Roboflow Dataset Upload,OpenAI,Image Slicer,Stitch OCR Detections,Google Gemini,Email Notification,Text Display,Size Measurement,Depth Estimation,Icon Visualization,OpenAI,GeoTag Detection,SIFT,PLC Writer,Detections List Roll-Up,MoonshotAI Kimi - outputs:
VLM As Classifier,Qwen-VL,Cache Get,Triangle Visualization,Model Comparison Visualization,Stitch OCR Detections,YOLO-World Model,Llama 3.2 Vision,Anthropic Claude,Keypoint Visualization,Heatmap Visualization,Webhook Sink,Google Gemini,GLM-OCR,QR Code Generator,Instance Segmentation Model,VLM As Detector,MoonshotAI Kimi,Twilio SMS/MMS Notification,Line Counter,Distance Measurement,Ellipse Visualization,Single-Label Classification Model,Keypoint Detection Model,Corner Visualization,Buffer,Llama 3.2 Vision,JSON Parser,Qwen 3.5 API,LMM,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Morphological Transformation,Motion Detection,Google Vision OCR,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,SAM3 Video Tracker,Object Detection Model,Contrast Equalization,Detections Classes Replacement,Instance Segmentation Model,Model Monitoring Inference Aggregator,MQTT Writer,Multi-Label Classification Model,Cache Set,PLC Reader,Image Threshold,Line Counter Visualization,Google Gemini,Microsoft SQL Server Sink,VLM As Classifier,Object Detection Model,Path Deviation,Twilio SMS Notification,OPC UA Writer Sink,SAM 3,Instance Segmentation Model,Google Gemma API,Polygon Zone Visualization,Keypoint Detection Model,Reference Path Visualization,Stability AI Inpainting,Perception Encoder Embedding Model,Crop Visualization,Anthropic Claude,Florence-2 Model,Polygon Visualization,Time in Zone,MoonshotAI Kimi,Dynamic Crop,Qwen 3.6 API,Event Writer,Perspective Correction,Segment Anything 2 Model,Line Counter,Polygon Visualization,Clip Comparison,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,CogVLM,PLC EthernetIP,Grid Visualization,Time in Zone,LMM For Classification,Qwen3.5-VL,Florence-2 Model,OpenAI,Roboflow Custom Metadata,Local File Sink,Label Visualization,Image Blur,Seg Preview,Path Deviation,Object Detection Model,Anthropic Claude,Pixel Color Count,Roboflow Vision Events,Image Preprocessing,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,Detections Consensus,PTZ Tracking (ONVIF),Dot Visualization,Current Time,Roboflow Asset Library Attributes,Keypoint Detection Model,Halo Visualization,SAM 3,Classification Label Visualization,OpenRouter,Moondream2,S3 Sink,Stability AI Image Generation,VLM As Detector,Google Gemma,Roboflow Dataset Upload,CLIP Embedding Model,OpenAI,Stitch OCR Detections,Google Gemini,Email Notification,SAM 3,Detections Stitch,Text Display,Semantic Segmentation Model,Size Measurement,Depth Estimation,Icon Visualization,OpenAI,Time in Zone,Instance Segmentation Model,Background Color Visualization,Detections List Roll-Up,Mask Visualization
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:
Absolute Static Crop,Qwen-VL,Triangle Visualization,EasyOCR,Model Comparison Visualization,Stitch OCR Detections,Llama 3.2 Vision,Heatmap Visualization,Stitch Images,Keypoint Visualization,Anthropic Claude,Webhook Sink,Google Gemini,GLM-OCR,QR Code Generator,VLM As Detector,Multi-Label Classification Model,Twilio SMS/MMS Notification,Ellipse Visualization,Pixelate Visualization,Corner Visualization,Llama 3.2 Vision,Qwen 3.5 API,LMM,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Morphological Transformation,Camera Calibration,Google Vision OCR,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,Contrast Equalization,CSV Formatter,Model Monitoring Inference Aggregator,MQTT Writer,Image Threshold,Blur Visualization,Line Counter Visualization,Google Gemini,Background Color Visualization,Microsoft SQL Server Sink,Single-Label Classification Model,Background Subtraction,VLM As Classifier,Instance Segmentation Model,Twilio SMS Notification,Polygon Zone Visualization,OPC UA Writer Sink,Google Gemma API,Reference Path Visualization,Stability AI Inpainting,Crop Visualization,Anthropic Claude,Image Convert Grayscale,Camera Focus,Image Slicer,Florence-2 Model,Polygon Visualization,MoonshotAI Kimi,Dynamic Crop,Qwen 3.6 API,Event Writer,Perspective Correction,Polygon Visualization,OCR Model,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,CogVLM,Contrast Enhancement,Grid Visualization,LMM For Classification,Florence-2 Model,OpenAI,Local File Sink,Roboflow Custom Metadata,Qwen3.5-VL,Image Blur,Label Visualization,Object Detection Model,Anthropic Claude,Roboflow Vision Events,Image Preprocessing,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,Dot Visualization,Current Time,Keypoint Detection Model,Roboflow Asset Library Attributes,Halo Visualization,Classification Label Visualization,Mask Visualization,Image Contours,Camera Focus,OpenRouter,S3 Sink,Stability AI Image Generation,Google Gemma,Relative Static Crop,Roboflow Dataset Upload,OpenAI,Image Slicer,Stitch OCR Detections,Google Gemini,Email Notification,Text Display,Depth Estimation,Icon Visualization,OpenAI,SIFT,PLC Writer,MoonshotAI Kimi - outputs:
Absolute Static Crop,Gaze Detection,Triangle Visualization,Byte Tracker,EasyOCR,Detection Event Log,Stitch OCR Detections,Track Class Lock,Llama 3.2 Vision,Heatmap Visualization,Keypoint Visualization,Webhook Sink,Detections Stabilizer,Continue If,Dominant Color,GLM-OCR,Instance Segmentation Model,VLM As Detector,SAM2 Video Tracker,PLC ModbusTCP,Twilio SMS/MMS Notification,Distance Measurement,SmolVLM2,Pixelate Visualization,Detections Transformation,Corner Visualization,Overlap Analysis,Buffer,Template Matching,Bounding Rectangle,Per-Class Confidence Filter,Velocity,Roboflow Visual Search,OpenAI-Compatible LLM,Morphological Transformation,Color Visualization,Roboflow Dataset Upload,Morphological Transformation,Camera Calibration,Clip Comparison,Bounding Box Visualization,OpenAI,Halo Visualization,Detections Combine,Contrast Equalization,CSV Formatter,Instance Segmentation Model,Model Monitoring Inference Aggregator,Multi-Label Classification Model,Cache Set,Delta Filter,Blur Visualization,Microsoft SQL Server Sink,Single-Label Classification Model,Background Subtraction,Object Detection Model,Path Deviation,Twilio SMS Notification,OPC UA Writer Sink,SAM 3,QR Code Detection,Keypoint Detection Model,Image Stack,SAM 3 Interactive,Qwen3-VL,Stability AI Inpainting,Multi-Label Classification Model,Perception Encoder Embedding Model,Image Convert Grayscale,Camera Focus,Florence-2 Model,Time in Zone,Dynamic Crop,Qwen 3.6 API,Perspective Correction,Segment Anything 2 Model,CogVLM,Mask Edge Snap,Byte Tracker,LMM For Classification,Florence-2 Model,Label Visualization,Image Blur,ByteTrack Tracker,Seg Preview,Path Deviation,Object Detection Model,Anthropic Claude,Pixel Color Count,Cosine Similarity,Trace Visualization,Email Notification,SIFT Comparison,Stability AI Outpainting,PTZ Tracking (ONVIF),Current Time,Property Definition,Image Contours,Camera Focus,Single-Label Classification Model,Moondream2,Data Aggregator,Stability AI Image Generation,VLM As Detector,Google Gemma,Detections Merge,Google Gemini,BoT-SORT Tracker,Email Notification,Byte Tracker,SAM 3,Detections Stitch,Text Display,Semantic Segmentation Model,Qwen3.5,OpenAI,Time in Zone,PLC Writer,SIFT Comparison,SIFT,Detections List Roll-Up,MoonshotAI Kimi,Mask Visualization,Detections Filter,VLM As Classifier,Qwen-VL,Cache Get,Model Comparison Visualization,OC-SORT Tracker,YOLO-World Model,Anthropic Claude,Stitch Images,Google Gemini,QR Code Generator,Multi-Label Classification Model,Line Counter,Ellipse Visualization,Single-Label Classification Model,Keypoint Detection Model,Rate Limiter,Switch Case,Llama 3.2 Vision,Qwen2.5-VL,JSON Parser,Qwen 3.5 API,LMM,Inner Workflow,Semantic Segmentation Model,Dimension Collapse,Motion Detection,Detection Offset,Google Vision OCR,SAM3 Video Tracker,Object Detection Model,Identify Changes,First Non Empty Or Default,Mask Area Measurement,Expression,Detections Classes Replacement,MQTT Writer,PLC Reader,Image Threshold,Line Counter Visualization,Google Gemini,Identify Outliers,Instance Segmentation Model,Polygon Zone Visualization,Google Gemma API,Reference Path Visualization,Crop Visualization,Anthropic Claude,Dynamic Zone,Image Slicer,Overlap Filter,Polygon Visualization,MoonshotAI Kimi,Event Writer,Line Counter,Polygon Visualization,Clip Comparison,OCR Model,Roboflow Visual Search Classifier,Circle Visualization,Slack Notification,PLC EthernetIP,Contrast Enhancement,Grid Visualization,Time in Zone,Barcode Detection,Local File Sink,Qwen3.5-VL,OpenAI,Roboflow Custom Metadata,SORT Tracker,Roboflow Vision Events,Image Preprocessing,Detections Consensus,Dot Visualization,Keypoint Detection Model,Roboflow Asset Library Attributes,Halo Visualization,SAM 3,Classification Label Visualization,OpenRouter,S3 Sink,CLIP Embedding Model,Roboflow Dataset Upload,Relative Static Crop,OpenAI,Image Slicer,Stitch OCR Detections,Size Measurement,Depth Estimation,Icon Visualization,GeoTag Detection,Instance Segmentation Model,Background Color Visualization,VLM As Classifier
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
}