refactor(ai-logic): use vertexAI() for samples that use Cloud Storage (#2675)

Author: thatfiredev

firebase-ai/app/build.gradle.kts

@@ -2,7 +2,7 @@ plugins {
  id("com.android.application")
  id("org.jetbrains.kotlin.android")
  id("org.jetbrains.kotlin.plugin.compose")
- kotlin("plugin.serialization") version "2.1.20"
+ kotlin("plugin.serialization") version "2.1.21"
  id("com.google.gms.google-services")
 }
 

firebase-ai/app/src/main/java/com/google/firebase/quickstart/ai/FirebaseAISamples.kt

@@ -1,5 +1,6 @@
 package com.google.firebase.quickstart.ai
 
+import com.google.firebase.ai.type.GenerativeBackend
 import com.google.firebase.ai.type.ResponseModality
 import com.google.firebase.ai.type.content
 import com.google.firebase.ai.type.generationConfig
@@ -86,10 +87,11 @@ val FIREBASE_AI_SAMPLES = listOf(
  }
  ),
  Sample(
- title = "Translation from audio",
- description = "Translate an audio file",
+ title = "Translation from audio (Vertex AI)",
+ description = "Translate an audio file stored in Cloud Storage",
  navRoute = "chat",
  categories = listOf(Category.AUDIO),
+ backend = GenerativeBackend.vertexAI(),
  initialPrompt = content {
  fileData(
  "https://storage.googleapis.com/cloud-samples-data/generative-ai/audio/" +
@@ -100,10 +102,11 @@ val FIREBASE_AI_SAMPLES = listOf(
  }
  ),
  Sample(
- title = "Blog post creator",
- description = "Create a blog post from an image file.",
+ title = "Blog post creator (Vertex AI)",
+ description = "Create a blog post from an image file stored in Cloud Storage.",
  navRoute = "chat",
  categories = listOf(Category.IMAGE),
+ backend = GenerativeBackend.vertexAI(),
  initialPrompt = content {
  fileData(
  "https://storage.googleapis.com/cloud-samples-data/generative-ai/image/meal-prep.jpeg",
@@ -145,10 +148,12 @@ val FIREBASE_AI_SAMPLES = listOf(
  }
  ),
  Sample(
- title = "Document comparison",
- description = "Compare the contents of 2 documents",
+ title = "Document comparison (Vertex AI)",
+ description = "Compare the contents of 2 documents." +
+ " Only supported by the Vertex AI Gemini API because the documents are stored in Cloud Storage",
  navRoute = "chat",
  categories = listOf(Category.DOCUMENT),
+ backend = GenerativeBackend.vertexAI(),
  initialPrompt = content {
  fileData(
  "https://storage.googleapis.com/cloud-samples-data/generative-ai/pdf/form_1040_2013.pdf",
@@ -165,10 +170,11 @@ val FIREBASE_AI_SAMPLES = listOf(
  }
  ),
  Sample(
- title = "Hashtags for a video",
- description = "Generate hashtags for a video ad",
+ title = "Hashtags for a video (Vertex AI)",
+ description = "Generate hashtags for a video ad stored in Cloud Storage",
  navRoute = "chat",
  categories = listOf(Category.VIDEO),
+ backend = GenerativeBackend.vertexAI(),
  initialPrompt = content {
  fileData(
  "https://storage.googleapis.com/cloud-samples-data/generative-ai/video/google_home_celebrity_ad.mp4",

firebase-ai/app/src/main/java/com/google/firebase/quickstart/ai/feature/text/ChatViewModel.kt

@@ -57,7 +57,7 @@ class ChatViewModel(
 
  init {
  val generativeModel = Firebase.ai(
- backend = GenerativeBackend.googleAI()
+ backend = sample.backend // GenerativeBackend.googleAI() by default
  ).generativeModel(
  modelName = sample.modelName ?: "gemini-2.0-flash",
  systemInstruction = sample.systemInstructions,

firebase-ai/app/src/main/java/com/google/firebase/quickstart/ai/ui/navigation/Sample.kt

@@ -2,6 +2,7 @@ package com.google.firebase.quickstart.ai.ui.navigation
 
 import com.google.firebase.ai.type.Content
 import com.google.firebase.ai.type.GenerationConfig
+import com.google.firebase.ai.type.GenerativeBackend
 import java.util.UUID
 
 enum class Category(
@@ -22,6 +23,7 @@ data class Sample(
  val categories: List<Category>,
  // Optional parameters
  val modelName: String? = null,
+ val backend: GenerativeBackend = GenerativeBackend.googleAI(),
  val initialPrompt: Content? = null,
  val systemInstructions: Content? = null,
  val generationConfig: GenerationConfig? = null,

gradle/libs.versions.toml

@@ -2,7 +2,7 @@
 agp = "8.10.1"
 coilCompose = "2.7.0"
 firebaseBom = "33.15.0"
-kotlin = "2.1.20"
+kotlin = "2.1.21"
 coreKtx = "1.16.0"
 junit = "4.13.2"
 junitVersion = "1.2.1"