Anthropic Claude¶
Class: AnthropicClaudeBlockV1
Source: inference.core.workflows.core_steps.models.foundation.anthropic_claude.v1.AnthropicClaudeBlockV1
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:
Stitch Images,Pixelate Visualization,Multi-Label Classification Model,LMM For Classification,Gaze Detection,Line Counter,Blur Visualization,Single-Label Classification Model,Mask Visualization,OCR Model,Object Detection Model,SIFT,Line Counter,Model Monitoring Inference Aggregator,Polygon Visualization,Halo Visualization,Grid Visualization,Google Vision OCR,Model Comparison Visualization,Email Notification,Camera Focus,CogVLM,Image Threshold,Keypoint Visualization,Template Matching,Image Preprocessing,Roboflow Dataset Upload,Slack Notification,Stitch OCR Detections,Identify Changes,Relative Static Crop,Background Color Visualization,Clip Comparison,Bounding Box Visualization,Ellipse Visualization,Image Contours,Label Visualization,Classification Label Visualization,Line Counter Visualization,LMM,Stability AI Inpainting,Reference Path Visualization,VLM as Detector,Dynamic Crop,Triangle Visualization,Absolute Static Crop,Distance Measurement,Florence-2 Model,SIFT Comparison,Keypoint Detection Model,Corner Visualization,Perspective Correction,Cosine Similarity,Local File Sink,Polygon Zone Visualization,VLM as Classifier,Dimension Collapse,Image Slicer,Trace Visualization,Webhook Sink,OpenAI,Twilio SMS Notification,Roboflow Custom Metadata,Size Measurement,Crop Visualization,Instance Segmentation Model,Buffer,Roboflow Dataset Upload,Clip Comparison,Anthropic Claude,Dynamic Zone,Image Blur,Circle Visualization,Image Convert Grayscale,Dot Visualization,Google Gemini,SIFT Comparison,Florence-2 Model,OpenAI,Color Visualization,Pixel Color Count,CSV Formatter,Llama 3.2 Vision - outputs:
Path Deviation,LMM For Classification,Keypoint Detection Model,Line Counter,Instance Segmentation Model,CLIP Embedding Model,Mask Visualization,Object Detection Model,Line Counter,YOLO-World Model,Model Monitoring Inference Aggregator,Cache Get,Polygon Visualization,Halo Visualization,VLM as Detector,Grid Visualization,Google Vision OCR,Model Comparison Visualization,Email Notification,CogVLM,Image Threshold,Keypoint Visualization,Image Preprocessing,Roboflow Dataset Upload,Slack Notification,Background Color Visualization,Clip Comparison,Bounding Box Visualization,Ellipse Visualization,Classification Label Visualization,Label Visualization,Line Counter Visualization,LMM,Stability AI Inpainting,Reference Path Visualization,VLM as Detector,Dynamic Crop,Triangle Visualization,Object Detection Model,Distance Measurement,Time in Zone,Detections Stitch,Florence-2 Model,SIFT Comparison,Keypoint Detection Model,Corner Visualization,Perspective Correction,Local File Sink,Polygon Zone Visualization,VLM as Classifier,Twilio SMS Notification,Trace Visualization,Webhook Sink,Size Measurement,OpenAI,Roboflow Custom Metadata,Detections Consensus,Cache Set,Crop Visualization,Instance Segmentation Model,Buffer,Roboflow Dataset Upload,Clip Comparison,VLM as Classifier,Anthropic Claude,Image Blur,Circle Visualization,Dot Visualization,Google Gemini,Segment Anything 2 Model,JSON Parser,Florence-2 Model,Time in Zone,Path Deviation,OpenAI,Color Visualization,Pixel Color Count,Llama 3.2 Vision
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-3-5-sonnet",
"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>"
}