You can use safety settings to adjust the likelihood of getting responses that may be considered harmful. By default, safety settings block content with medium and/or high probability of being unsafe content across all dimensions.
Gemini safety settings Jump to Imagen safety settings Jump to
Safety settings for Gemini models
Click your Gemini API provider to view provider-specific content and code on this page. |
Swift
You configure
SafetySettings
when you create a GenerativeModel
instance.
Example with one safety setting:
import FirebaseAI
// Initialize the Gemini Developer API backend service
// Create an `GenerativeModel` instance and add safety settings to its config
let model = FirebaseAI.firebaseAI(backend: .googleAI()).generativeModel(
modelName: "GEMINI_MODEL_NAME",
safetySettings: [
SafetySetting(harmCategory: .harassment, threshold: .blockOnlyHigh)
]
)
// ...
Example with multiple safety settings:
import FirebaseAI
let harassmentSafety = SafetySetting(harmCategory: .harassment, threshold: .blockOnlyHigh)
let hateSpeechSafety = SafetySetting(harmCategory: .hateSpeech, threshold: .blockMediumAndAbove)
// Initialize the Gemini Developer API backend service
// Create an `GenerativeModel` instance and add safety settings to its config
let model = FirebaseAI.firebaseAI(backend: .googleAI()).generativeModel(
modelName: "GEMINI_MODEL_NAME",
safetySettings: [harassmentSafety, hateSpeechSafety]
)
// ...
Kotlin
You configure
SafetySettings
when you create a GenerativeModel
instance.
Example with one safety setting:
import com.google.firebase.vertexai.type.HarmBlockThreshold
import com.google.firebase.vertexai.type.HarmCategory
import com.google.firebase.vertexai.type.SafetySetting
// Create a `GenerativeModel` instance and add safety settings to its config
val model = Firebase.ai(backend = GenerativeBackend.googleAI()).generativeModel(
modelName = "GEMINI_MODEL_NAME",
safetySettings = listOf(
SafetySetting(HarmCategory.HARASSMENT, HarmBlockThreshold.ONLY_HIGH)
)
)
// ...
Example with multiple safety settings:
import com.google.firebase.vertexai.type.HarmBlockThreshold
import com.google.firebase.vertexai.type.HarmCategory
import com.google.firebase.vertexai.type.SafetySetting
val harassmentSafety = SafetySetting(HarmCategory.HARASSMENT, HarmBlockThreshold.ONLY_HIGH)
val hateSpeechSafety = SafetySetting(HarmCategory.HATE_SPEECH, HarmBlockThreshold.MEDIUM_AND_ABOVE)
// Create a `GenerativeModel` instance and add safety settings to its config
val model = Firebase.ai(backend = GenerativeBackend.googleAI()).generativeModel(
modelName = "GEMINI_MODEL_NAME",
safetySettings = listOf(harassmentSafety, hateSpeechSafety)
)
// ...
Java
You configure
SafetySettings
when you create a GenerativeModel
instance.
SafetySetting harassmentSafety = new SafetySetting(HarmCategory.HARASSMENT,
HarmBlockThreshold.ONLY_HIGH);
// Create an `GenerativeModel` instance and add safety settings to its config
GenerativeModelFutures model = GenerativeModelFutures.from(
FirebaseAI.getInstance(GenerativeBackend.googleAI())
.generativeModel(
/* modelName */ "IMAGEN_MODEL_NAME",
/* generationConfig is optional */ null,
Collections.singletonList(harassmentSafety)
);
);
// ...
Example with multiple safety settings:
SafetySetting harassmentSafety = new SafetySetting(HarmCategory.HARASSMENT,
HarmBlockThreshold.ONLY_HIGH);
SafetySetting hateSpeechSafety = new SafetySetting(HarmCategory.HATE_SPEECH,
HarmBlockThreshold.MEDIUM_AND_ABOVE);
// Create an `GenerativeModel` instance and add safety settings to its config
GenerativeModelFutures model = GenerativeModelFutures.from(
FirebaseAI.getInstance(GenerativeBackend.googleAI())
.generativeModel(
/* modelName */ "IMAGEN_MODEL_NAME",
/* generationConfig is optional */ null,
List.of(harassmentSafety, hateSpeechSafety)
);
);
// ...
Web
You configure
SafetySettings
when you create a GenerativeModel
instance.
Example with one safety setting:
import { HarmBlockThreshold, HarmCategory, getAI, getGenerativeModel, GoogleAIBackend } from "firebase/ai";
// ...
// Initialize the Gemini Developer API backend service
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });
const safetySettings = [
{
category: HarmCategory.HARM_CATEGORY_HARASSMENT,
threshold: HarmBlockThreshold.BLOCK_ONLY_HIGH,
},
];
// Create a `GenerativeModel` instance and add safety settings to its config
const model = getGenerativeModel(ai, { model: "GEMINI_MODEL_NAME", safetySettings });
// ...
Example with multiple safety settings:
import { HarmBlockThreshold, HarmCategory, getAI, getGenerativeModel, GoogleAIBackend } from "firebase/ai";
// ...
// Initialize the Gemini Developer API backend service
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });
const safetySettings = [
{
category: HarmCategory.HARM_CATEGORY_HARASSMENT,
threshold: HarmBlockThreshold.BLOCK_ONLY_HIGH,
},
{
category: HarmCategory.HARM_CATEGORY_HATE_SPEECH,
threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
},
];
// Create a `GenerativeModel` instance and add safety settings to its config
const model = getGenerativeModel(ai, { model: "GEMINI_MODEL_NAME", safetySettings });
// ...
Dart
You configure
SafetySettings
when you create a GenerativeModel
instance.
Example with one safety setting:
// ...
final safetySettings = [
SafetySetting(HarmCategory.harassment, HarmBlockThreshold.high)
];
// Initialize the Gemini Developer API backend service
// Create a `GenerativeModel` instance and add safety settings to its config
final model = FirebaseAI.googleAI().generativeModel(
model: 'GEMINI_MODEL_NAME',
safetySettings: safetySettings,
);
// ...
Example with multiple safety settings:
// ...
final safetySettings = [
SafetySetting(HarmCategory.harassment, HarmBlockThreshold.high),
SafetySetting(HarmCategory.hateSpeech, HarmBlockThreshold.high),
];
// Initialize the Gemini Developer API backend service
// Create a `GenerativeModel` instance and add safety settings to its config
final model = FirebaseAI.googleAI().generativeModel(
model: 'GEMINI_MODEL_NAME',
safetySettings: safetySettings,
);
// ...
Unity
You configure
SafetySettings
when you create a GenerativeModel
instance.
Example with one safety setting:
// ...
// Initialize the Gemini Developer API backend service
// Create a `GenerativeModel` instance and add safety settings to its config
var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());
var model = ai.GetGenerativeModel(
modelName: "GEMINI_MODEL_NAME",
safetySettings: new SafetySetting[] {
new SafetySetting(HarmCategory.Harassment, SafetySetting.HarmBlockThreshold.OnlyHigh)
}
);
// ...
Example with multiple safety settings:
// ...
var harassmentSafety = new SafetySetting(HarmCategory.Harassment, SafetySetting.HarmBlockThreshold.OnlyHigh);
var hateSpeechSafety = new SafetySetting(HarmCategory.HateSpeech, SafetySetting.HarmBlockThreshold.MediumAndAbove);
// Initialize the Vertex AI Gemini API backend service
// Create a `GenerativeModel` instance and add safety settings to its config
var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());
var model = ai.GetGenerativeModel(
modelName: "GEMINI_MODEL_NAME",
safetySettings: new SafetySetting[] { harassmentSafety, hateSpeechSafety }
);
// ...
Safety settings for Imagen models
Click your Gemini API provider to view provider-specific content and code on this page. |
Learn about all the supported safety settings and their available values for Imagen models in the Google Cloud documentation.
Swift
You configure
ImagenSafetySettings
when you create an ImagenModel
instance.
import FirebaseAI
// Initialize the Gemini Developer API backend service
// Create an `ImagenModel` instance and add safety settings to its config
let model = FirebaseAI.firebaseAI(backend: .googleAI()).imagenModel(
modelName: "IMAGEN_MODEL_NAME",
safetySettings: ImagenSafetySettings(
safetyFilterLevel: .blockLowAndAbove,
personFilterLevel: .allowAdult
)
)
// ...
Kotlin
You configure
ImagenSafetySettings
when you create an ImagenModel
instance.
// Initialize the Vertex AI Gemini API backend service
// Create an `ImagenModel` instance and add safety settings to its config
val model = Firebase.ai(backend = GenerativeBackend.googleAI()).imagenModel(
modelName = "IMAGEN_MODEL_NAME",
safetySettings = ImagenSafetySettings(
safetyFilterLevel = ImagenSafetyFilterLevel.BLOCK_LOW_AND_ABOVE,
personFilterLevel = ImagenPersonFilterLevel.BLOCK_ALL
)
)
// ...
Java
You configure
ImagenSafetySettings
when you create an ImagenModel
instance.
// Create an `ImagenModel` instance and add safety settings to its config
ImagenModelFutures model = ImagenModelFutures.from(
FirebaseAI.getInstance(GenerativeBackend.googleAI())
.imagenModel(
/* modelName */ "IMAGEN_MODEL_NAME",
/* imageGenerationConfig */ null);
);
// ...
Web
You configure
ImagenSafetySettings
when you create an ImagenModel
instance.
// ...
// Initialize the Gemini Developer API backend service
const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() });
// Create an `ImagenModel` instance and add safety settings to its config
const model = getImagenModel(
ai,
{
model: "IMAGEN_MODEL_NAME",
safetySettings: {
safetyFilterLevel: ImagenSafetyFilterLevel.BLOCK_LOW_AND_ABOVE,
personFilterLevel: ImagenPersonFilterLevel.ALLOW_ADULT,
}
}
);
// ...
Dart
You configure
ImagenSafetySettings
when you create an ImagenModel
instance.
// ...
// Initialize the Gemini Developer API backend service
// Create an `ImagenModel` instance and add safety settings to its config
final model = FirebaseAI.googleAI().imagenModel(
model: 'IMAGEN_MODEL_NAME',
safetySettings: ImagenSafetySettings(
ImagenSafetyFilterLevel.blockLowAndAbove,
ImagenPersonFilterLevel.allowAdult,
),
);
// ...
Unity
Using Imagen is not yet supported for Unity, but check back soon!
Other options to control content generation
- Learn more about prompt design so that you can influence the model to generate output specific to your needs.
- Configure model parameters to control how the model generates a response. For Gemini models, these parameters include max output tokens, temperature, topK, and topP. For Imagen models, these include aspect ratio, person generation, watermarking, etc.
- Set system instructions to steer the behavior of the model. This feature is like a preamble that you add before the model gets exposed to any further instructions from the end user.
- Pass a response schema along with the prompt to specify a specific output schema. This feature is most commonly used when generating JSON output, but it can also be used for classification tasks (like when you want the model to use specific labels or tags).