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.

Available Connections¶

Compatible Blocks

Check what blocks you can connect to OpenAI in version v4.

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 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 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.

Available Connections¶

Compatible Blocks

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

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 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.

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 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.

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
}