Skip to content

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[string, ROBOFLOW_MANAGED_KEY, secret]): 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

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

  • output

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

  • output

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

  • output

    • parent_id (parent_id): Identifier of parent for step output.
    • root_parent_id (parent_id): Identifier of parent for step output.
    • image (image_metadata): Dictionary with image metadata required by supervision.
    • structured_output (dictionary): Dictionary.
    • raw_output (string): String value.
    • * (*): Equivalent of any element.
Example JSON definition of step OpenAI in version v1 
{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/open_ai@v1",
    "images": "$inputs.image",
    "prompt": "my prompt",
    "openai_api_key": "xxx-xxx",
    "openai_model": "gpt-4o",
    "json_output_format": {
        "count": "number of cats in the picture"
    },
    "image_detail": "auto",
    "max_tokens": 450
}