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:
- Roboflow Managed API Key (Default) - Use
rf_key:accountto proxy requests through Roboflow's API: - Simplified setup - no Anthropic API key required
- Secure - your workflow API key is used for authentication
-
Usage-based billing - charged per token based on the model used
-
Custom Anthropic API Key - Provide your own Anthropic API key:
- Full control over API usage
- 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:
Distance Measurement,Anthropic Claude,Instance Segmentation Model,SIFT Comparison,Google Vision OCR,Circle Visualization,Image Slicer,Google Gemini,Image Contours,Qwen 3.6 API,Single-Label Classification Model,Roboflow Vision Events,Depth Estimation,Line Counter Visualization,Stitch Images,Morphological Transformation,LMM,Model Comparison Visualization,Buffer,MoonshotAI Kimi,Grid Visualization,Twilio SMS/MMS Notification,OpenAI,Clip Comparison,Twilio SMS Notification,Qwen-VL,S3 Sink,Halo Visualization,Camera Focus,SIFT Comparison,Keypoint Detection Model,Local File Sink,Mask Visualization,SIFT,Anthropic Claude,MoonshotAI Kimi,Roboflow Dataset Upload,Text Display,Image Slicer,Multi-Label Classification Model,Absolute Static Crop,Llama 3.2 Vision,GLM-OCR,Object Detection Model,Roboflow Custom Metadata,Email Notification,Dynamic Crop,OpenRouter,Cosine Similarity,Model Monitoring Inference Aggregator,Contrast Enhancement,Motion Detection,Webhook Sink,Google Gemma API,Stability AI Image Generation,Color Visualization,Heatmap Visualization,Contrast Equalization,Google Gemini,Roboflow Dataset Upload,Slack Notification,Anthropic Claude,QR Code Generator,Clip Comparison,OpenAI,Bounding Box Visualization,Florence-2 Model,VLM As Classifier,Image Blur,Dot Visualization,Polygon Zone Visualization,Label Visualization,Icon Visualization,Image Threshold,LMM For Classification,Blur Visualization,Line Counter,Relative Static Crop,Dimension Collapse,Trace Visualization,Qwen3.5-VL,Size Measurement,Dynamic Zone,Florence-2 Model,Camera Focus,CogVLM,Pixelate Visualization,Llama 3.2 Vision,Image Convert Grayscale,Keypoint Visualization,Polygon Visualization,Line Counter,Google Gemma,Classification Label Visualization,Image Stack,Morphological Transformation,Gaze Detection,Camera Calibration,Google Gemini,Email Notification,Image Preprocessing,Corner Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Asset Library Attributes,Reference Path Visualization,OpenAI,Background Color Visualization,Identify Changes,Ellipse Visualization,CSV Formatter,Stability AI Outpainting,VLM As Detector,EasyOCR,Triangle Visualization,OCR Model,Crop Visualization,Perspective Correction,Qwen 3.5 API,Detection Event Log,Stitch OCR Detections,OpenAI-Compatible LLM,Detections List Roll-Up,Polygon Visualization,Background Subtraction,Template Matching,Pixel Color Count,OpenAI,Stability AI Inpainting - outputs:
Distance Measurement,Keypoint Detection Model,Instance Segmentation Model,Anthropic Claude,Google Vision OCR,Circle Visualization,Google Gemini,Qwen 3.6 API,CLIP Embedding Model,Roboflow Vision Events,Depth Estimation,Line Counter Visualization,VLM As Detector,Morphological Transformation,LMM,Model Comparison Visualization,Buffer,MoonshotAI Kimi,Segment Anything 2 Model,Grid Visualization,Cache Set,Instance Segmentation Model,Twilio SMS/MMS Notification,OpenAI,Detections Classes Replacement,Clip Comparison,Twilio SMS Notification,SAM 3,Qwen-VL,S3 Sink,SAM 3,Halo Visualization,Local File Sink,Semantic Segmentation Model,SIFT Comparison,Multi-Label Classification Model,Keypoint Detection Model,Mask Visualization,Path Deviation,Anthropic Claude,MoonshotAI Kimi,Roboflow Dataset Upload,Text Display,Llama 3.2 Vision,VLM As Classifier,PTZ Tracking (ONVIF),Path Deviation,GLM-OCR,Object Detection Model,Email Notification,Seg Preview,Dynamic Crop,Roboflow Custom Metadata,Instance Segmentation Model,Time in Zone,OpenRouter,Model Monitoring Inference Aggregator,Motion Detection,Webhook Sink,Google Gemma API,Stability AI Image Generation,Color Visualization,Heatmap Visualization,Contrast Equalization,Object Detection Model,YOLO-World Model,Google Gemini,Roboflow Dataset Upload,Slack Notification,Anthropic Claude,QR Code Generator,Clip Comparison,OpenAI,Bounding Box Visualization,SAM 3,Florence-2 Model,VLM As Classifier,Image Blur,Keypoint Detection Model,Detections Consensus,Dot Visualization,Polygon Zone Visualization,Label Visualization,Icon Visualization,Image Threshold,Cache Get,LMM For Classification,Object Detection Model,Line Counter,Trace Visualization,Moondream2,Size Measurement,Perception Encoder Embedding Model,Florence-2 Model,CogVLM,Llama 3.2 Vision,Time in Zone,Keypoint Visualization,Polygon Visualization,Line Counter,Google Gemma,Classification Label Visualization,Morphological Transformation,Email Notification,Google Gemini,Image Preprocessing,Corner Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Asset Library Attributes,OpenAI,Reference Path Visualization,Detections Stitch,Background Color Visualization,Single-Label Classification Model,JSON Parser,Ellipse Visualization,Stability AI Outpainting,VLM As Detector,Triangle Visualization,Crop Visualization,Qwen 3.5 API,Perspective Correction,Stitch OCR Detections,OpenAI-Compatible LLM,Detections List Roll-Up,Instance Segmentation Model,Time in Zone,Polygon Visualization,Pixel Color Count,OpenAI,Stability AI Inpainting
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,ROBOFLOW_MANAGED_KEY,string]): 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 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 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:
Distance Measurement,Anthropic Claude,Instance Segmentation Model,SIFT Comparison,Google Vision OCR,Circle Visualization,Image Slicer,Google Gemini,Image Contours,Qwen 3.6 API,Single-Label Classification Model,Roboflow Vision Events,Depth Estimation,Line Counter Visualization,Stitch Images,Morphological Transformation,LMM,Model Comparison Visualization,Buffer,MoonshotAI Kimi,Grid Visualization,Twilio SMS/MMS Notification,OpenAI,Clip Comparison,Twilio SMS Notification,Qwen-VL,S3 Sink,Halo Visualization,Camera Focus,SIFT Comparison,Keypoint Detection Model,Local File Sink,Mask Visualization,SIFT,Anthropic Claude,MoonshotAI Kimi,Roboflow Dataset Upload,Text Display,Image Slicer,Multi-Label Classification Model,Absolute Static Crop,Llama 3.2 Vision,GLM-OCR,Object Detection Model,Roboflow Custom Metadata,Email Notification,Dynamic Crop,OpenRouter,Cosine Similarity,Model Monitoring Inference Aggregator,Contrast Enhancement,Motion Detection,Webhook Sink,Google Gemma API,Stability AI Image Generation,Color Visualization,Heatmap Visualization,Contrast Equalization,Google Gemini,Roboflow Dataset Upload,Slack Notification,Anthropic Claude,QR Code Generator,Clip Comparison,OpenAI,Bounding Box Visualization,Florence-2 Model,VLM As Classifier,Image Blur,Dot Visualization,Polygon Zone Visualization,Label Visualization,Icon Visualization,Image Threshold,LMM For Classification,Blur Visualization,Line Counter,Relative Static Crop,Dimension Collapse,Trace Visualization,Qwen3.5-VL,Size Measurement,Dynamic Zone,Florence-2 Model,Camera Focus,CogVLM,Pixelate Visualization,Llama 3.2 Vision,Image Convert Grayscale,Keypoint Visualization,Polygon Visualization,Line Counter,Google Gemma,Classification Label Visualization,Image Stack,Morphological Transformation,Gaze Detection,Camera Calibration,Google Gemini,Email Notification,Image Preprocessing,Corner Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Asset Library Attributes,Reference Path Visualization,OpenAI,Background Color Visualization,Identify Changes,Ellipse Visualization,CSV Formatter,Stability AI Outpainting,VLM As Detector,EasyOCR,Triangle Visualization,OCR Model,Crop Visualization,Perspective Correction,Qwen 3.5 API,Detection Event Log,Stitch OCR Detections,OpenAI-Compatible LLM,Detections List Roll-Up,Polygon Visualization,Background Subtraction,Template Matching,Pixel Color Count,OpenAI,Stability AI Inpainting - outputs:
Distance Measurement,Keypoint Detection Model,Instance Segmentation Model,Anthropic Claude,Google Vision OCR,Circle Visualization,Google Gemini,Qwen 3.6 API,CLIP Embedding Model,Roboflow Vision Events,Depth Estimation,Line Counter Visualization,VLM As Detector,Morphological Transformation,LMM,Model Comparison Visualization,Buffer,MoonshotAI Kimi,Segment Anything 2 Model,Grid Visualization,Cache Set,Instance Segmentation Model,Twilio SMS/MMS Notification,OpenAI,Detections Classes Replacement,Clip Comparison,Twilio SMS Notification,SAM 3,Qwen-VL,S3 Sink,SAM 3,Halo Visualization,Local File Sink,Semantic Segmentation Model,SIFT Comparison,Multi-Label Classification Model,Keypoint Detection Model,Mask Visualization,Path Deviation,Anthropic Claude,MoonshotAI Kimi,Roboflow Dataset Upload,Text Display,Llama 3.2 Vision,VLM As Classifier,PTZ Tracking (ONVIF),Path Deviation,GLM-OCR,Object Detection Model,Email Notification,Seg Preview,Dynamic Crop,Roboflow Custom Metadata,Instance Segmentation Model,Time in Zone,OpenRouter,Model Monitoring Inference Aggregator,Motion Detection,Webhook Sink,Google Gemma API,Stability AI Image Generation,Color Visualization,Heatmap Visualization,Contrast Equalization,Object Detection Model,YOLO-World Model,Google Gemini,Roboflow Dataset Upload,Slack Notification,Anthropic Claude,QR Code Generator,Clip Comparison,OpenAI,Bounding Box Visualization,SAM 3,Florence-2 Model,VLM As Classifier,Image Blur,Keypoint Detection Model,Detections Consensus,Dot Visualization,Polygon Zone Visualization,Label Visualization,Icon Visualization,Image Threshold,Cache Get,LMM For Classification,Object Detection Model,Line Counter,Trace Visualization,Moondream2,Size Measurement,Perception Encoder Embedding Model,Florence-2 Model,CogVLM,Llama 3.2 Vision,Time in Zone,Keypoint Visualization,Polygon Visualization,Line Counter,Google Gemma,Classification Label Visualization,Morphological Transformation,Email Notification,Google Gemini,Image Preprocessing,Corner Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Asset Library Attributes,OpenAI,Reference Path Visualization,Detections Stitch,Background Color Visualization,Single-Label Classification Model,JSON Parser,Ellipse Visualization,Stability AI Outpainting,VLM As Detector,Triangle Visualization,Crop Visualization,Qwen 3.5 API,Perspective Correction,Stitch OCR Detections,OpenAI-Compatible LLM,Detections List Roll-Up,Instance Segmentation Model,Time in Zone,Polygon Visualization,Pixel Color Count,OpenAI,Stability AI Inpainting
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 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:
Distance Measurement,Anthropic Claude,Instance Segmentation Model,SIFT Comparison,Google Vision OCR,Circle Visualization,Image Slicer,Google Gemini,Image Contours,Qwen 3.6 API,Single-Label Classification Model,Roboflow Vision Events,Depth Estimation,Line Counter Visualization,Stitch Images,Morphological Transformation,LMM,Model Comparison Visualization,Buffer,MoonshotAI Kimi,Grid Visualization,Twilio SMS/MMS Notification,OpenAI,Clip Comparison,Twilio SMS Notification,Qwen-VL,S3 Sink,Halo Visualization,Camera Focus,SIFT Comparison,Keypoint Detection Model,Local File Sink,Mask Visualization,SIFT,Anthropic Claude,MoonshotAI Kimi,Roboflow Dataset Upload,Text Display,Image Slicer,Multi-Label Classification Model,Absolute Static Crop,Llama 3.2 Vision,GLM-OCR,Object Detection Model,Roboflow Custom Metadata,Email Notification,Dynamic Crop,OpenRouter,Cosine Similarity,Model Monitoring Inference Aggregator,Contrast Enhancement,Motion Detection,Webhook Sink,Google Gemma API,Stability AI Image Generation,Color Visualization,Heatmap Visualization,Contrast Equalization,Google Gemini,Roboflow Dataset Upload,Slack Notification,Anthropic Claude,QR Code Generator,Clip Comparison,OpenAI,Bounding Box Visualization,Florence-2 Model,VLM As Classifier,Image Blur,Dot Visualization,Polygon Zone Visualization,Label Visualization,Icon Visualization,Image Threshold,LMM For Classification,Blur Visualization,Line Counter,Relative Static Crop,Dimension Collapse,Trace Visualization,Qwen3.5-VL,Size Measurement,Dynamic Zone,Florence-2 Model,Camera Focus,CogVLM,Pixelate Visualization,Llama 3.2 Vision,Image Convert Grayscale,Keypoint Visualization,Polygon Visualization,Line Counter,Google Gemma,Classification Label Visualization,Image Stack,Morphological Transformation,Gaze Detection,Camera Calibration,Google Gemini,Email Notification,Image Preprocessing,Corner Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Asset Library Attributes,Reference Path Visualization,OpenAI,Background Color Visualization,Identify Changes,Ellipse Visualization,CSV Formatter,Stability AI Outpainting,VLM As Detector,EasyOCR,Triangle Visualization,OCR Model,Crop Visualization,Perspective Correction,Qwen 3.5 API,Detection Event Log,Stitch OCR Detections,OpenAI-Compatible LLM,Detections List Roll-Up,Polygon Visualization,Background Subtraction,Template Matching,Pixel Color Count,OpenAI,Stability AI Inpainting - outputs:
Distance Measurement,Keypoint Detection Model,Instance Segmentation Model,Anthropic Claude,Google Vision OCR,Circle Visualization,Google Gemini,Qwen 3.6 API,CLIP Embedding Model,Roboflow Vision Events,Depth Estimation,Line Counter Visualization,VLM As Detector,Morphological Transformation,LMM,Model Comparison Visualization,Buffer,MoonshotAI Kimi,Segment Anything 2 Model,Grid Visualization,Cache Set,Instance Segmentation Model,Twilio SMS/MMS Notification,OpenAI,Detections Classes Replacement,Clip Comparison,Twilio SMS Notification,SAM 3,Qwen-VL,S3 Sink,SAM 3,Halo Visualization,Local File Sink,Semantic Segmentation Model,SIFT Comparison,Multi-Label Classification Model,Keypoint Detection Model,Mask Visualization,Path Deviation,Anthropic Claude,MoonshotAI Kimi,Roboflow Dataset Upload,Text Display,Llama 3.2 Vision,VLM As Classifier,PTZ Tracking (ONVIF),Path Deviation,GLM-OCR,Object Detection Model,Email Notification,Seg Preview,Dynamic Crop,Roboflow Custom Metadata,Instance Segmentation Model,Time in Zone,OpenRouter,Model Monitoring Inference Aggregator,Motion Detection,Webhook Sink,Google Gemma API,Stability AI Image Generation,Color Visualization,Heatmap Visualization,Contrast Equalization,Object Detection Model,YOLO-World Model,Google Gemini,Roboflow Dataset Upload,Slack Notification,Anthropic Claude,QR Code Generator,Clip Comparison,OpenAI,Bounding Box Visualization,SAM 3,Florence-2 Model,VLM As Classifier,Image Blur,Keypoint Detection Model,Detections Consensus,Dot Visualization,Polygon Zone Visualization,Label Visualization,Icon Visualization,Image Threshold,Cache Get,LMM For Classification,Object Detection Model,Line Counter,Trace Visualization,Moondream2,Size Measurement,Perception Encoder Embedding Model,Florence-2 Model,CogVLM,Llama 3.2 Vision,Time in Zone,Keypoint Visualization,Polygon Visualization,Line Counter,Google Gemma,Classification Label Visualization,Morphological Transformation,Email Notification,Google Gemini,Image Preprocessing,Corner Visualization,Stitch OCR Detections,Halo Visualization,Roboflow Asset Library Attributes,OpenAI,Reference Path Visualization,Detections Stitch,Background Color Visualization,Single-Label Classification Model,JSON Parser,Ellipse Visualization,Stability AI Outpainting,VLM As Detector,Triangle Visualization,Crop Visualization,Qwen 3.5 API,Perspective Correction,Stitch OCR Detections,OpenAI-Compatible LLM,Detections List Roll-Up,Instance Segmentation Model,Time in Zone,Polygon Visualization,Pixel Color Count,OpenAI,Stability AI Inpainting
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 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>"
}