Google Gemini

Class: GoogleGeminiBlockV1

Source: inference.core.workflows.core_steps.models.foundation.google_gemini.v1.GoogleGeminiBlockV1

Ask a question to Google's Gemini 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 Google AI API key to use the Gemini model.

WARNING!

This block makes use of /v1beta API of Google Gemini model - the implementation may change in the future, without guarantee of backward compatibility.

Type identifier

Use the following identifier in step "type" field: roboflow_core/google_gemini@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 Gemini 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 Google AI 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_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 Google Gemini 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 Google Gemini in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Google Gemini in version v1 has.

Bindings

• input

  • images (image): The image to infer on..
  • prompt (string): Text prompt to the Gemini model.
  • classes (list_of_values): List of classes to be used.
  • api_key (Union[string, secret]): Your Google AI 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..

• 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 Google Gemini in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/google_gemini@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": "gemini-2.5-pro",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>"
}