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