Package com.google.genai.types

Class GenerateContentConfig

java.lang.Object
com.google.genai.JsonSerializable
com.google.genai.types.GenerateContentConfig
public abstract class GenerateContentConfig extends JsonSerializable
Optional model configuration parameters.

For more information, see `Content generation parameters <https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/content-generation-parameters>`_.

  • Constructor Details

    • GenerateContentConfig

      public GenerateContentConfig()

  • Method Details

    • httpOptions

      public abstract Optional<HttpOptions> httpOptions()
      Used to override HTTP request options.

    • shouldReturnHttpResponse

      public abstract Optional<Boolean> shouldReturnHttpResponse()
      If true, the raw HTTP response will be returned in the 'sdk_http_response' field.

    • systemInstruction

      public abstract Optional<Content> systemInstruction()
      Instructions for the model to steer it toward better performance. For example, "Answer as concisely as possible" or "Don't use technical terms in your response".

    • temperature

      public abstract Optional<Float> temperature()
      Value that controls the degree of randomness in token selection. Lower temperatures are good for prompts that require a less open-ended or creative response, while higher temperatures can lead to more diverse or creative results.

    • topP

      public abstract Optional<Float> topP()
      Tokens are selected from the most to least probable until the sum of their probabilities equals this value. Use a lower value for less random responses and a higher value for more random responses.

    • topK

      public abstract Optional<Float> topK()
      For each token selection step, the ``top_k`` tokens with the highest probabilities are sampled. Then tokens are further filtered based on ``top_p`` with the final token selected using temperature sampling. Use a lower number for less random responses and a higher number for more random responses.

    • candidateCount

      public abstract Optional<Integer> candidateCount()
      Number of response variations to return.

    • maxOutputTokens

      public abstract Optional<Integer> maxOutputTokens()
      Maximum number of tokens that can be generated in the response.

    • stopSequences

      public abstract Optional<List<String>> stopSequences()
      List of strings that tells the model to stop generating text if one of the strings is encountered in the response.

    • responseLogprobs

      public abstract Optional<Boolean> responseLogprobs()
      Whether to return the log probabilities of the tokens that were chosen by the model at each step.

    • logprobs

      public abstract Optional<Integer> logprobs()
      Number of top candidate tokens to return the log probabilities for at each generation step.

    • presencePenalty

      public abstract Optional<Float> presencePenalty()
      Positive values penalize tokens that already appear in the generated text, increasing the probability of generating more diverse content.

    • frequencyPenalty

      public abstract Optional<Float> frequencyPenalty()
      Positive values penalize tokens that repeatedly appear in the generated text, increasing the probability of generating more diverse content.

    • seed

      public abstract Optional<Integer> seed()
      When ``seed`` is fixed to a specific number, the model makes a best effort to provide the same response for repeated requests. By default, a random number is used.

    • responseMimeType

      public abstract Optional<String> responseMimeType()
      Output response mimetype of the generated candidate text. Supported mimetype: - `text/plain`: (default) Text output. - `application/json`: JSON response in the candidates. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. This is a preview feature.

    • responseSchema

      public abstract Optional<Schema> responseSchema()
      The `Schema` object allows the definition of input and output data types. These types can be objects, but also primitives and arrays. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema). If set, a compatible response_mime_type must also be set. Compatible mimetypes: `application/json`: Schema for JSON response.

    • responseJsonSchema

      public abstract Optional<Object> responseJsonSchema()
      Optional. Output schema of the generated response. This is an alternative to `response_schema` that accepts [JSON Schema](https://json-schema.org/). If set, `response_schema` must be omitted, but `response_mime_type` is required. While the full JSON Schema may be sent, not all features are supported. Specifically, only the following properties are supported: - `$id` - `$defs` - `$ref` - `$anchor` - `type` - `format` - `title` - `description` - `enum` (for strings and numbers) - `items` - `prefixItems` - `minItems` - `maxItems` - `minimum` - `maximum` - `anyOf` - `oneOf` (interpreted the same as `anyOf`) - `properties` - `additionalProperties` - `required` The non-standard `propertyOrdering` property may also be set. Cyclic references are unrolled to a limited degree and, as such, may only be used within non-required properties. (Nullable properties are not sufficient.) If `$ref` is set on a sub-schema, no other properties, except for than those starting as a `$`, may be set.

    • routingConfig

      public abstract Optional<GenerationConfigRoutingConfig> routingConfig()
      Configuration for model router requests.

    • modelSelectionConfig

      public abstract Optional<ModelSelectionConfig> modelSelectionConfig()
      Configuration for model selection.

    • safetySettings

      public abstract Optional<List<SafetySetting>> safetySettings()
      Safety settings in the request to block unsafe content in the response.

    • tools

      public abstract Optional<List<Tool>> tools()
      Code that enables the system to interact with external systems to perform an action outside of the knowledge and scope of the model.

    • toolConfig

      public abstract Optional<ToolConfig> toolConfig()
      Associates model output to a specific function call.

    • labels

      public abstract Optional<Map<String,String>> labels()
      Labels with user-defined metadata to break down billed charges.

    • cachedContent

      public abstract Optional<String> cachedContent()
      Resource name of a context cache that can be used in subsequent requests.

    • responseModalities

      public abstract Optional<List<String>> responseModalities()
      The requested modalities of the response. Represents the set of modalities that the model can return.

    • mediaResolution

      public abstract Optional<MediaResolution> mediaResolution()
      If specified, the media resolution specified will be used.

    • speechConfig

      public abstract Optional<SpeechConfig> speechConfig()
      The speech generation configuration.

    • audioTimestamp

      public abstract Optional<Boolean> audioTimestamp()
      If enabled, audio timestamp will be included in the request to the model.

    • automaticFunctionCalling

      public abstract Optional<AutomaticFunctionCallingConfig> automaticFunctionCalling()
      The configuration for automatic function calling.

    • thinkingConfig

      public abstract Optional<ThinkingConfig> thinkingConfig()
      The thinking features configuration.

    • builder

      public static GenerateContentConfig.Builder builder()
      Instantiates a builder for GenerateContentConfig.

    • toBuilder

      public abstract GenerateContentConfig.Builder toBuilder()
      Creates a builder with the same values as this instance.

    • fromJson

      public static GenerateContentConfig fromJson(String jsonString)
      Deserializes a JSON string to a GenerateContentConfig object.