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Google Gemma API

Class: GoogleGemmaBlockV1

Source: inference.core.workflows.core_steps.models.foundation.google_gemma.v1.GoogleGemmaBlockV1

Ask a question to Google's Gemma 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 providers and model variants

Gemma is exposed via OpenRouter API and we require passing an OpenRouter API Key to run.

Pick a specific model version from the model_version dropdown - new Gemma releases will be added to this list as they become available on OpenRouter.

API Usage Charges

OpenRouter is an external third party providing access to the model and incurring charges on the usage. Please check pricing on openrouter.ai before use.

💡 Further reading and Acceptable Use Policy

Model license

Check the Gemma Terms of Use before use.

Type identifier

Use the following identifier in step "type" field: roboflow_core/google_gemma@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 Gemma 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 OpenRouter 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 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 Gemma API in version v1.

Input and Output Bindings

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

Bindings

  • input

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

Example JSON definition of step Google Gemma API in version v1 
{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/google_gemma@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": "Gemma 4 31B - OpenRouter",
    "max_tokens": "<block_does_not_provide_example>",
    "temperature": "<block_does_not_provide_example>",
    "max_concurrent_requests": "<block_does_not_provide_example>"
}