Anthropic Claude

v3

Class: AnthropicClaudeBlockV3 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.anthropic_claude.v3.AnthropicClaudeBlockV3

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 Anthropic Claude model with vision capabilities.

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

API Key Options

This block supports two API key modes:

1. Roboflow Managed API Key (Default) - Use rf_key:account to proxy requests through Roboflow's API:
2. Simplified setup - no Anthropic API key required
3. Secure - your workflow API key is used for authentication

4. Usage-based billing - charged per token based on the model used

5. Custom Anthropic API Key - Provide your own Anthropic API key:

6. Full control over API usage
7. You pay Anthropic directly

Type identifier

Use the following identifier in step "type" field: roboflow_core/anthropic_claude@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 Claude 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 Anthropic API key or 'rf_key:account' to use Roboflow's managed API key.	✅
model_version	str	Model to be used.	✅
extended_thinking	bool	Enable extended thinking for deeper reasoning on complex tasks. Note: temperature cannot be used when extended thinking is enabled..	❌
thinking_budget_tokens	int	Maximum number of tokens for internal thinking when extended thinking is enabled. Higher values allow deeper reasoning but increase latency and cost. Must be less than max_tokens. Minimum: 1024..	❌
max_tokens	int	Maximum number of tokens the model can generate in its response..	❌
temperature	float	Temperature to sample from the model - value in range 0.0-1.0, the higher - the more random / "creative" the generations are. Cannot be used when extended_thinking is enabled..	✅
max_image_size	int	Maximum size of the image - if input has larger side, it will be downscaled, keeping aspect ratio.	✅
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 Anthropic API 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 Anthropic Claude in version v3.

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

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the Claude model.
  • classes (list_of_values): List of classes to be used.
  • api_key (Union[secret, string, ROBOFLOW_MANAGED_KEY]): Your Anthropic API key or 'rf_key:account' to use Roboflow's managed API key.
  • model_version (string): Model to be used.
  • temperature (float): Temperature to sample from the model - value in range 0.0-1.0, the higher - the more random / "creative" the generations are. Cannot be used when extended_thinking is enabled..
  • max_image_size (integer): Maximum size of the image - if input has larger side, it will be downscaled, keeping aspect ratio.

• 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 Anthropic Claude in version v3

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/anthropic_claude@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": "rf_key:account",
    "model_version": "claude-sonnet-4-5",
    "extended_thinking": "<block_does_not_provide_example>",
    "thinking_budget_tokens": "<block_does_not_provide_example>",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_image_size": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>"
}

v2

Class: AnthropicClaudeBlockV2 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.anthropic_claude.v2.AnthropicClaudeBlockV2

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 Anthropic Claude model with vision capabilities.

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

You need to provide your Anthropic API key to use the Claude model.

Type identifier

Use the following identifier in step "type" field: roboflow_core/anthropic_claude@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 Claude 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 Anthropic API key.	✅
model_version	str	Model to be used.	✅
extended_thinking	bool	Enable extended thinking for deeper reasoning on complex tasks. Note: temperature cannot be used when extended thinking is enabled..	❌
thinking_budget_tokens	int	Maximum number of tokens for internal thinking when extended thinking is enabled. Higher values allow deeper reasoning but increase latency and cost. Must be less than max_tokens. Minimum: 1024..	❌
max_tokens	int	Maximum number of tokens the model can generate in its response..	❌
temperature	float	Temperature to sample from the model - value in range 0.0-1.0, the higher - the more random / "creative" the generations are. Cannot be used when extended_thinking is enabled..	✅
max_image_size	int	Maximum size of the image - if input has larger side, it will be downscaled, keeping aspect ratio.	✅
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 Anthropic API 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 Anthropic Claude in version v2.

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

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the Claude model.
  • classes (list_of_values): List of classes to be used.
  • api_key (Union[secret, string]): Your Anthropic API key.
  • model_version (string): Model to be used.
  • temperature (float): Temperature to sample from the model - value in range 0.0-1.0, the higher - the more random / "creative" the generations are. Cannot be used when extended_thinking is enabled..
  • max_image_size (integer): Maximum size of the image - if input has larger side, it will be downscaled, keeping aspect ratio.

• 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 Anthropic Claude in version v2

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/anthropic_claude@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": "claude-sonnet-4-5",
    "extended_thinking": "<block_does_not_provide_example>",
    "thinking_budget_tokens": "<block_does_not_provide_example>",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_image_size": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>"
}

v1

Class: AnthropicClaudeBlockV1 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.foundation.anthropic_claude.v1.AnthropicClaudeBlockV1

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 Anthropic Claude model with vision capabilities.

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

You need to provide your Anthropic API key to use the Claude model.

Type identifier

Use the following identifier in step "type" field: roboflow_core/anthropic_claude@v1to 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 Claude 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 Anthropic API key.	✅
model_version	str	Model to be used.	✅
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_image_size	int	Maximum size of the image - if input has larger side, it will be downscaled, keeping aspect ratio.	✅
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 Anthropic API 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 Anthropic Claude in version v1.

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

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the Claude model.
  • classes (list_of_values): List of classes to be used.
  • api_key (Union[secret, string]): Your Anthropic API key.
  • model_version (string): Model to be used.
  • 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_image_size (integer): Maximum size of the image - if input has larger side, it will be downscaled, keeping aspect ratio.

• 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 Anthropic Claude in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/anthropic_claude@v1",
    "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": "claude-sonnet-4",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_image_size": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>"
}