diff --git a/FirebaseVertexAI/Sources/FunctionCalling.swift b/FirebaseVertexAI/Sources/FunctionCalling.swift
index 7bf366a7132..69c90b18e10 100644
--- a/FirebaseVertexAI/Sources/FunctionCalling.swift
+++ b/FirebaseVertexAI/Sources/FunctionCalling.swift
@@ -35,6 +35,8 @@ public struct FunctionDeclaration {
   ///   with a maximum length of 63.
   ///   - description: A brief description of the function.
   ///   - parameters: Describes the parameters to this function.
+  ///   - optionalParameters: The names of parameters that may be omitted by the model in function
+  ///   calls; by default, all parameters are considered required.
   public init(name: String, description: String, parameters: [String: Schema],
               optionalParameters: [String] = []) {
     self.name = name
diff --git a/FirebaseVertexAI/Sources/GenerativeModel.swift b/FirebaseVertexAI/Sources/GenerativeModel.swift
index 0ac58732e11..c920a0daa88 100644
--- a/FirebaseVertexAI/Sources/GenerativeModel.swift
+++ b/FirebaseVertexAI/Sources/GenerativeModel.swift
@@ -97,17 +97,17 @@ public final class GenerativeModel {
   }
 
   /// Generates content from String and/or image inputs, given to the model as a prompt, that are
-  /// representable as one or more ``ModelContent/Part``s.
+  /// representable as one or more ``Part``s.
   ///
-  /// Since ``ModelContent/Part``s do not specify a role, this method is intended for generating
-  /// content from
+  /// Since ``Part``s do not specify a role, this method is intended for generating content from
   /// [zero-shot](https://developers.google.com/machine-learning/glossary/generative#zero-shot-prompting)
   /// or "direct" prompts. For
   /// [few-shot](https://developers.google.com/machine-learning/glossary/generative#few-shot-prompting)
-  /// prompts, see `generateContent(_ content: @autoclosure () throws -> [ModelContent])`.
+  /// prompts, see `generateContent(_ content: [ModelContent])`.
   ///
-  /// - Parameter content: The input(s) given to the model as a prompt (see ``PartsRepresentable``
-  /// for conforming types).
+  /// - Parameters:
+  ///   - parts: The input(s) given to the model as a prompt (see ``PartsRepresentable`` for
+  ///   conforming types).
   /// - Returns: The content generated by the model.
   /// - Throws: A ``GenerateContentError`` if the request failed.
   public func generateContent(_ parts: any PartsRepresentable...)
@@ -153,17 +153,17 @@ public final class GenerativeModel {
   }
 
   /// Generates content from String and/or image inputs, given to the model as a prompt, that are
-  /// representable as one or more ``ModelContent/Part``s.
+  /// representable as one or more ``Part``s.
   ///
-  /// Since ``ModelContent/Part``s do not specify a role, this method is intended for generating
-  /// content from
+  /// Since ``Part``s do not specify a role, this method is intended for generating content from
   /// [zero-shot](https://developers.google.com/machine-learning/glossary/generative#zero-shot-prompting)
   /// or "direct" prompts. For
   /// [few-shot](https://developers.google.com/machine-learning/glossary/generative#few-shot-prompting)
   /// prompts, see `generateContentStream(_ content: @autoclosure () throws -> [ModelContent])`.
   ///
-  /// - Parameter content: The input(s) given to the model as a prompt (see
-  /// ``PartsRepresentable`` for conforming types).
+  /// - Parameters:
+  ///   - parts: The input(s) given to the model as a prompt (see ``PartsRepresentable`` for
+  ///   conforming types).
   /// - Returns: A stream wrapping content generated by the model or a ``GenerateContentError``
   ///     error if an error occurred.
   @available(macOS 12.0, *)
@@ -228,21 +228,20 @@ public final class GenerativeModel {
   }
 
   /// Runs the model's tokenizer on String and/or image inputs that are representable as one or more
-  /// ``ModelContent/Part``s.
+  /// ``Part``s.
   ///
-  /// Since ``ModelContent/Part``s do not specify a role, this method is intended for tokenizing
+  /// Since ``Part``s do not specify a role, this method is intended for tokenizing
   /// [zero-shot](https://developers.google.com/machine-learning/glossary/generative#zero-shot-prompting)
   /// or "direct" prompts. For
   /// [few-shot](https://developers.google.com/machine-learning/glossary/generative#few-shot-prompting)
   /// input, see `countTokens(_ content: @autoclosure () throws -> [ModelContent])`.
   ///
-  /// - Parameter content: The input(s) given to the model as a prompt (see ``PartsRepresentable``
-  /// for conforming types).
+  /// - Parameters:
+  ///   - parts: The input(s) given to the model as a prompt (see ``PartsRepresentable`` for
+  ///   conforming types).
   /// - Returns: The results of running the model's tokenizer on the input; contains
   /// ``CountTokensResponse/totalTokens``.
-  /// - Throws: A ``CountTokensError`` if the tokenization request failed.
-  public func countTokens(_ parts: any PartsRepresentable...) async throws
-    -> CountTokensResponse {
+  public func countTokens(_ parts: any PartsRepresentable...) async throws -> CountTokensResponse {
     return try await countTokens([ModelContent(parts: parts)])
   }
 
@@ -251,10 +250,7 @@ public final class GenerativeModel {
   /// - Parameter content: The input given to the model as a prompt.
   /// - Returns: The results of running the model's tokenizer on the input; contains
   /// ``CountTokensResponse/totalTokens``.
-  /// - Throws: A ``CountTokensError`` if the tokenization request failed or the input content was
-  /// invalid.
-  public func countTokens(_ content: [ModelContent]) async throws
-    -> CountTokensResponse {
+  public func countTokens(_ content: [ModelContent]) async throws -> CountTokensResponse {
     let countTokensRequest = CountTokensRequest(
       model: modelResourceName,
       contents: content,
diff --git a/FirebaseVertexAI/Sources/ModelContent.swift b/FirebaseVertexAI/Sources/ModelContent.swift
index 9697a97a5bf..885d209e0a1 100644
--- a/FirebaseVertexAI/Sources/ModelContent.swift
+++ b/FirebaseVertexAI/Sources/ModelContent.swift
@@ -33,7 +33,7 @@ extension [ModelContent] {
 
 /// A type describing data in media formats interpretable by an AI model. Each generative AI
 /// request or response contains an `Array` of ``ModelContent``s, and each ``ModelContent`` value
-/// may comprise multiple heterogeneous ``ModelContent/Part``s.
+/// may comprise multiple heterogeneous ``Part``s.
 @available(iOS 15.0, macOS 11.0, macCatalyst 15.0, tvOS 15.0, watchOS 8.0, *)
 public struct ModelContent: Equatable, Sendable {
   enum InternalPart: Equatable, Sendable {
diff --git a/FirebaseVertexAI/Sources/Types/Public/Part.swift b/FirebaseVertexAI/Sources/Types/Public/Part.swift
index 1eba33ae018..8cc25de1db2 100644
--- a/FirebaseVertexAI/Sources/Types/Public/Part.swift
+++ b/FirebaseVertexAI/Sources/Types/Public/Part.swift
@@ -104,11 +104,11 @@ public struct FunctionCallPart: Part {
   }
 }
 
-/// Result output from a ``FunctionCall``.
+/// Result output from a function call.
 ///
 /// Contains a string representing the `FunctionDeclaration.name` and a structured JSON object
 /// containing any output from the function is used as context to the model. This should contain the
-/// result of a ``FunctionCall`` made based on model prediction.
+/// result of a ``FunctionCallPart`` made based on model prediction.
 @available(iOS 15.0, macOS 11.0, macCatalyst 15.0, tvOS 15.0, watchOS 8.0, *)
 public struct FunctionResponsePart: Part {
   let functionResponse: FunctionResponse