firebase-ios-sdk/GeminiLanguageModel/Sources/GeminiAPIDataModels/GenerateContent/CountTokensRequest.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.

import Foundation

/// An internal data model for `CountTokensRequest`.
///
/// ### Gemini Developer API
///
/// Type: `GoogleAiGenerativelanguageV1betaCountTokensRequest`
///
/// Counts the number of tokens in the `prompt` sent to a model.
///
/// Models may tokenize text differently, so each model may return a different
/// `token_count`.
///
/// ### Gemini Enterprise API
///
/// Type: `GoogleCloudAiplatformV1beta1CountTokensRequest`
///
/// Request message for PredictionService.CountTokens.
package struct CountTokensRequest: Codable, Sendable, Equatable, Hashable {
  /// Optional. The input given to the model as a prompt. This field is ignored when
  ///
  /// ### Gemini Developer API
  ///
  /// Optional. The input given to the model as a prompt. This field is ignored when
  /// `generate_content_request` is set.
  ///
  /// ### Gemini Enterprise API
  ///
  /// Optional. Input content.
  package let contents: [Content]?

  /// Optional. The overall input given to the `Model`. This includes the prompt as well as
  ///
  /// ### Gemini Developer API
  ///
  /// Optional. The overall input given to the `Model`. This includes the prompt as well as
  /// other model steering information like [system
  /// instructions](https://ai.google.dev/gemini-api/docs/system-instructions),
  /// and/or function declarations for [function
  /// calling](https://ai.google.dev/gemini-api/docs/function-calling).
  /// `Model`s/`Content`s and `generate_content_request`s are mutually
  /// exclusive. You can either send `Model` + `Content`s or a
  /// `generate_content_request`, but never both.
  ///
  /// ### Gemini Enterprise API
  ///
  /// > Important: This property is not supported in the Gemini Enterprise API.
  package let generateContentRequest: GenerateContentRequest?

  /// Optional. The name of the publisher model requested to serve the prediction.
  ///
  /// ### Gemini Developer API
  ///
  /// > Important: This property is not supported in the Gemini Developer API.
  ///
  /// ### Gemini Enterprise API
  ///
  /// Optional. The name of the publisher model requested to serve the prediction.
  /// Format:
  /// `projects/{project}/locations/{location}/publishers/*/models/*`
  package let model: String?

  /// Optional. The instances that are the input to token counting call.
  ///
  /// ### Gemini Developer API
  ///
  /// > Important: This property is not supported in the Gemini Developer API.
  ///
  /// ### Gemini Enterprise API
  ///
  /// Optional. The instances that are the input to token counting call.
  /// Schema is identical to the prediction schema of the underlying model.
  package let instances: [JSONValue]?

  /// Optional. The user provided system instructions for the model.
  ///
  /// ### Gemini Developer API
  ///
  /// > Important: This property is not supported in the Gemini Developer API.
  ///
  /// ### Gemini Enterprise API
  ///
  /// Optional. The user provided system instructions for the model.
  /// Note: only text should be used in parts and content in each part will be in
  /// a separate paragraph.
  package let systemInstruction: Content?

  /// Optional. A list of `Tools` the model may use to generate the next response.
  ///
  /// ### Gemini Developer API
  ///
  /// > Important: This property is not supported in the Gemini Developer API.
  ///
  /// ### Gemini Enterprise API
  ///
  /// Optional. A list of `Tools` the model may use to generate the next response.
  ///
  /// A `Tool` is a piece of code that enables the system to interact with
  /// external systems to perform an action, or set of actions, outside of
  /// knowledge and scope of the model.
  package let tools: [Tool]?

  /// Optional. Generation config that the model will use to generate the response.
  ///
  /// ### Gemini Developer API
  ///
  /// > Important: This property is not supported in the Gemini Developer API.
  ///
  /// ### Gemini Enterprise API
  ///
  /// Optional. Generation config that the model will use to generate the response.
  package let generationConfig: GenerationConfig?

  /// Creates a new `CountTokensRequest`.
  ///
  /// - Parameters:
  ///   - contents: Optional. The input given to the model as a prompt. This field is ignored when (behavior varies by backend). For more details, see ``contents``.
  ///   - generateContentRequest: Optional. The overall input given to the `Model`. This includes the prompt as well as (Gemini Developer API only). For more details, see ``generateContentRequest``.
  ///   - model: Optional. The name of the publisher model requested to serve the prediction. (Gemini Enterprise API only). For more details, see ``model``.
  ///   - instances: Optional. The instances that are the input to token counting call. (Gemini Enterprise API only). For more details, see ``instances``.
  ///   - systemInstruction: Optional. The user provided system instructions for the model. (Gemini Enterprise API only). For more details, see ``systemInstruction``.
  ///   - tools: Optional. A list of `Tools` the model may use to generate the next response. (Gemini Enterprise API only). For more details, see ``tools``.
  ///   - generationConfig: Optional. Generation config that the model will use to generate the response. (Gemini Enterprise API only). For more details, see ``generationConfig``.
  package init(
    contents: [Content]? = nil,
    generateContentRequest: GenerateContentRequest? = nil,
    model: String? = nil,
    instances: [JSONValue]? = nil,
    systemInstruction: Content? = nil,
    tools: [Tool]? = nil,
    generationConfig: GenerationConfig? = nil
  ) {
    self.contents = contents
    self.generateContentRequest = generateContentRequest
    self.model = model
    self.instances = instances
    self.systemInstruction = systemInstruction
    self.tools = tools
    self.generationConfig = generationConfig
  }
  enum CodingKeys: String, CodingKey {
    case contents = "contents"
    case generateContentRequest = "generateContentRequest"
    case model = "model"
    case instances = "instances"
    case systemInstruction = "systemInstruction"
    case tools = "tools"
    case generationConfig = "generationConfig"
  }
}