GenerativeModel

abstract @ FeatureStatus 
int  checkStatus 
()

Checks the current availability status of the content generation feature.

abstract void  clearImplicitCaches 
()

Clears all caches created by implicit prefix caching.

This experimental method clears all caches created by implicit prefix caching. When promptPrefix is provided in generateContent or generateContentStream , the system caches its processing implicitly to reduce inference time for subsequent requests sharing the same prefix. This method clears all such created caches.

abstract void  close 
()

Releases resources associated with the content generation engine.

This should be called when the GenerativeModel is no longer needed. Can be safely called multiple times.

abstract @ NonNull 
 CountTokensResponse 
 countTokens 
(@ NonNull 
 GenerateContentRequest 
 request)

Counts the number of tokens in the request.

The number of tokens counted includes only input request tokens. The result can be compared with getTokenLimit to check if the request is within the token limit.

abstract @ NonNull 
 Flow 
<@ NonNull 
 DownloadStatus 
>  download 
()

Downloads the required model assets for the content generation feature if they are not already available.

Use this method to proactively download models before inference. The returned Flow emits DownloadStatus to report progress and completion status.

default @ NonNull 
 GenerateContentResponse 
 generateContent 
(@ NonNull 
 String 
 prompt)

Performs asynchronous content generation on the provided input prompt.

This is a convenience method that wraps the input prompt in a GenerateContentRequest with default generation parameters.

abstract @ NonNull 
 GenerateContentResponse 
 generateContent 
(@ NonNull 
 GenerateContentRequest 
 request)

Performs asynchronous content generation on the provided input request.

This is the standard, non-streaming version of inference. The full generation suggestions are returned once the model completes processing.

This method is non-blocking. To handle the result, callers should use try / catch to handle the returned GenerateContentResponse or a potential GenAiException.

The coroutine that runs generateContent is cancellable. If the inference is no longer needed (e.g., the user navigates away or input changes), the coroutine can be cancelled.

Note that inference requests may fail under certain conditions such as:

• Invalid or malformed input in the GenerateContentRequest .

• Exceeded usage quota or failed safety checks.

default @ NonNull 
 GenerateContentResponse 
 generateContent 
(
    @ NonNull 
 String 
 prompt,
    @ NonNull 
 StreamingCallback 
 streamingCallback
)

Performs streaming content generation inference on the provided input prompt.

This is a convenience method that wraps the input prompt in a GenerateContentRequest with default generation parameters.

abstract @ NonNull 
 GenerateContentResponse 
 generateContent 
(
    @ NonNull 
 GenerateContentRequest 
 request,
    @ NonNull 
 StreamingCallback 
 streamingCallback
)

Performs streaming content generation inference on the provided input request.

Partial results are delivered incrementally through the provided StreamingCallback . The function suspends until all results are received and returns the complete, final GenerateContentResponse . If streaming is interrupted by a GenAiException, consider removing any already streamed partial output from the UI.

The coroutine that runs generateContent is cancellable. If the inference is no longer needed (e.g., the user navigates away or input changes), the coroutine can be cancelled.

Note that inference requests may fail under certain conditions such as:

• Invalid or malformed input in the GenerateContentRequest .

• Exceeded usage quota or failed safety checks.

default @ NonNull 
 Flow 
<@ NonNull 
 GenerateContentResponse 
>  generateContentStream 
(@ NonNull 
 String 
 prompt)

Performs streaming content generation inference on the provided input prompt.

This is a convenience method that wraps the input prompt in a GenerateContentRequest with default generation parameters.

abstract @ NonNull 
 Flow 
<@ NonNull 
 GenerateContentResponse 
>  generateContentStream 
(@ NonNull 
 GenerateContentRequest 
 request)

Performs streaming content generation inference on the provided input request.

Partial results are delivered incrementally through the returned Flow . Each GenerateContentResponse contains a single Candidate . The last emitted value contains a Candidate with a FinishReason that is a non-null FinishReason (e.g., FinishReason.STOP or FinishReason.MAX_TOKENS)

This streaming mode is useful to build a more responsive UI. Streaming can be interrupted by a GenAiException. In that case, consider removing any already streamed partial output from the UI.

The coroutine collecting the Flow is cancellable. If the inference is no longer needed (e.g., the user navigates away or input changes), the coroutine can be cancelled

Note that inference requests may fail under certain conditions such as:

• Invalid or malformed input in the GenerateContentRequest .

• Exceeded usage quota or failed safety checks.

Important: This function currently only supports a candidateCount of 1 in the GenerateContentRequest . Providing a candidateCount greater than 1 will result in an IllegalArgumentException . If you need to receive multiple candidates in the final result, please use the generateContent(request: GenerateContentRequest, streamingCallback: StreamingCallback) method instead.

abstract @ NonNull 
 String 
 getBaseModelName 
()

Returns the name of the base model used by this generator instance.

The model name may be used for logging, debugging, or feature gating purposes.

abstract @ NonNull 
 Caches 
 getCaches 
()

Provides explicit management of cached contexts.

This experimental property offers direct control over cached contexts to accelerate inference.

The GenerativeModel supports two types of caching:

1. Implicit Caching: Automatically created when a promptPrefix is provided in generateContent or generateContentStream . The system manages their lifecycle. These caches cannot be accessed directly but can be cleared using clearImplicitCaches .

2. Explicit Caching: Managed via this caches property. Users can explicitly create, retrieve, and manage the lifecycle of cache entries.

Use isCachingFeatureAvailable to check if the caching feature is available. Attempting to use the caches property when the feature is not available will result in an exception.

abstract int  getTokenLimit 
()

Returns total token limit for the API including both input and output tokens.

This limit can be used with countTokens to check if a request is within limits before running inference. The input size returned by countTokens plusing the output size specified by GenerateContentRequest.maxOutputTokens should be no larger than the limit returned by this method.

abstract boolean  isCachingFeatureAvailable 
()

Checks if the caching feature is available.

abstract void  warmup 
()

Warms up the inference engine for use by loading necessary models and initializing runtime components.

While calling this method is optional, we recommend invoking it well before the first inference call to reduce the latency of the initial inference.