firebase-ios-sdk/GeminiLanguageModel/Sources/GeminiAPIDataModels/GenerateContent/GenerationConfig.swift

// Copyright 2026 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

// DO NOT EDIT. This file is generated by GeminiLanguageModel/scripts/typegen;
// see its README.md for how to regenerate it.

import Foundation

/// Configuration for content generation. This message contains all the parameters that control how
/// the model generates content. It allows you to influence the randomness, length, and structure of
/// the output.
package struct GenerationConfig: Codable, Sendable, Equatable, Hashable, Buildable {
  /// If enabled, audio timestamps will be included in the request to the model. This can be useful
  /// for synchronizing audio with other modalities in the response.
  ///
  /// > Important: This property is not supported in the Gemini Developer API.
  package var audioTimestamp: Bool?

  /// Configuration for audio transcription (speech recognition).
  package var audioTranscriptionConfig: AudioTranscriptionConfig?

  /// The number of candidate responses to generate. A higher `candidate_count` can provide more
  /// options to choose from, but it also consumes more resources. This can be useful for generating
  /// a variety of responses and selecting the best one.
  package var candidateCount: Int?

  /// If enabled, the model will detect emotions and adapt its responses accordingly. For example,
  /// if the model detects that the user is frustrated, it may provide a more empathetic response.
  package var enableAffectiveDialog: Bool?

  /// Enables enhanced civic answers. It may not be available for all models.
  ///
  /// > Important: This property is not supported in the Gemini Enterprise Agent Platform.
  package var enableEnhancedCivicAnswers: Bool?

  /// Penalizes tokens based on their frequency in the generated text. A positive value helps to
  /// reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
  package var frequencyPenalty: Double?

  /// Config for image generation features. Deprecated: Use `response_format.image` instead.
  package var imageConfig: ImageConfig?

  /// The number of top log probabilities to return for each token. This can be used to see which
  /// other tokens were considered likely candidates for a given position. A higher value will
  /// return more options, but it will also increase the size of the response.
  package var logprobs: Int?

  /// The maximum number of tokens to generate in the response. A token is approximately four
  /// characters. The default value varies by model. This parameter can be used to control the
  /// length of the generated text and prevent overly long responses.
  package var maxOutputTokens: Int?

  /// The token resolution at which input media content is sampled. This is used to control the
  /// trade-off between the quality of the response and the number of tokens used to represent the
  /// media. A higher resolution allows the model to perceive more detail, which can lead to a more
  /// nuanced response, but it will also use more tokens. This does not affect the image dimensions
  /// sent to the model.
  package var mediaResolution: MediaResolution?

  /// Penalizes tokens that have already appeared in the generated text. A positive value encourages
  /// the model to generate more diverse and less repetitive text. Valid values can range from
  /// [-2.0, 2.0].
  package var presencePenalty: Double?

  /// New response format field for the model to configure output formatting and delivery.
  package var responseFormat: ResponseFormatConfig?

  /// When this field is set, response_schema must be omitted and response_mime_type must be set to
  /// `application/json`. Deprecated: Use `response_format` instead.
  package var responseJSONSchema: JSONObject?

  /// If set to true, the log probabilities of the output tokens are returned. Log probabilities are
  /// the logarithm of the probability of a token appearing in the output. A higher log probability
  /// means the token is more likely to be generated. This can be useful for analyzing the model's
  /// confidence in its own output and for debugging.
  package var responseLogprobs: Bool?

  /// The IANA standard MIME type of the response. The model will generate output that conforms to
  /// this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The
  /// model needs to be prompted to output the appropriate response type, otherwise the behavior is
  /// undefined. Deprecated: Use `response_format` instead.
  package var responseMIMEType: String?

  /// The modalities of the response. The model will generate a response that includes all the
  /// specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will
  /// include both text and an image.
  package var responseModalities: [Modality]?

  /// A seed for the random number generator. By setting a seed, you can make the model's output
  /// mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the
  /// model will produce the same response every time. However, it's not a guaranteed absolute
  /// deterministic behavior. This is different from parameters like `temperature`, which control
  /// the *level* of randomness. `seed` ensures that the "random" choices the model makes are the
  /// same on every run, making it essential for testing and ensuring reproducible results.
  package var seed: Int?

  /// The speech generation config.
  package var speechConfig: SpeechConfig?

  /// A list of character sequences that will stop the model from generating further tokens. If a
  /// stop sequence is generated, the output will end at that point. This is useful for controlling
  /// the length and structure of the output. For example, you can use ["\n", "###"] to stop
  /// generation at a new line or a specific marker.
  package var stopSequences: [String]?

  /// Controls the randomness of the output. A higher temperature results in more creative and
  /// diverse responses, while a lower temperature makes the output more predictable and focused.
  /// The valid range is (0.0, 2.0].
  package var temperature: Double?

  /// Configuration for thinking features. An error will be returned if this field is set for models
  /// that don't support thinking.
  package var thinkingConfig: ThinkingConfig?

  /// Specifies the top-k sampling threshold. The model considers only the top k most probable
  /// tokens for the next token. This can be useful for generating more coherent and less random
  /// text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most
  /// likely words.
  package var topK: Int?

  /// Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens
  /// whose cumulative probability is at least `top_p`. This helps generate more diverse and less
  /// repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the
  /// cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust
  /// either temperature or `top_p`, but not both.
  package var topP: Double?

  /// Initializes a new `GenerationConfig`.
  package init() {}

  enum CodingKeys: String, CodingKey {
    case audioTimestamp
    case audioTranscriptionConfig
    case candidateCount
    case enableAffectiveDialog
    case enableEnhancedCivicAnswers
    case frequencyPenalty
    case imageConfig
    case logprobs
    case maxOutputTokens
    case mediaResolution
    case presencePenalty
    case responseFormat
    case responseJSONSchema = "responseJsonSchema"
    case responseLogprobs
    case responseMIMEType = "responseMimeType"
    case responseModalities
    case seed
    case speechConfig
    case stopSequences
    case temperature
    case thinkingConfig
    case topK
    case topP
  }
}