Auto-update dependencies.

gradle/libs.versions.toml

@@ -6,11 +6,12 @@ coreKtx = "1.15.0"
 junit = "4.13.2"
 junitVersion = "1.2.1"
 espressoCore = "3.6.1"
+kotlinxSerializationJson = "1.7.3"
 lifecycleRuntimeKtx = "2.8.7"
 activityCompose = "1.9.3"
 composeBom = "2024.10.01"
 reactiveStreams = "1.0.4"
-vertexAI = "16.0.0-beta06"
+vertexAI = "16.0.1"
 
 [libraries]
 androidx-core-ktx = { group = "androidx.core", name = "core-ktx", version.ref = "coreKtx" }
@@ -31,6 +32,7 @@ androidx-material3 = { group = "androidx.compose.material3", name = "material3"
 
 # Vertex AI SDKs in Firebase
 firebase-vertex-ai ={ group = "com.google.firebase", name = "firebase-vertexai", version.ref = "vertexAI" }
+kotlinx-serialization-json = { module = "org.jetbrains.kotlinx:kotlinx-serialization-json", version.ref = "kotlinxSerializationJson" }
 reactive-streams = { module = "org.reactivestreams:reactive-streams", version.ref = "reactiveStreams" }
 
 [plugins]

storage/app/build.gradle.kts

@@ -2,7 +2,7 @@ plugins {
     id("com.android.application")
     id("kotlin-android")
     id("com.google.gms.google-services")
-    id("com.google.devtools.ksp") version "2.0.21-1.0.26"
+    id("com.google.devtools.ksp") version "2.0.21-1.0.27"
 }
 
 android {

vertexai/app/build.gradle.kts

@@ -59,6 +59,7 @@ dependencies {
     implementation(libs.androidx.material3)
 
     implementation(libs.firebase.vertex.ai)
+    implementation(libs.kotlinx.serialization.json)
 
     // Required for one-shot operations (to use `ListenableFuture` from Reactive Streams)
     implementation(libs.reactive.streams)

vertexai/app/src/main/java/com/google/firebase/example/vertexai/java/ChatViewModel.java

@@ -169,10 +169,10 @@ void systemInstructionsText() {
                 /* modelName */ "gemini-1.5-pro-preview-0409",
                 /* generationConfig (optional) */ null,
                 /* safetySettings (optional) */ null,
-                /* requestOptions (optional) */ new RequestOptions(),
                 /* tools (optional) */ null,
                 /* toolsConfig (optional) */ null,
-                /* systemInstruction (optional) */ systemInstruction
+                /* systemInstruction (optional) */ systemInstruction,
+                /* requestOptions (optional) */ new RequestOptions()
         );
         // [END vertexai_si_text]
     }

vertexai/app/src/main/java/com/google/firebase/example/vertexai/java/ConfigurationViewModel.java

@@ -5,7 +5,7 @@
 import com.google.firebase.vertexai.FirebaseVertexAI;
 import com.google.firebase.vertexai.GenerativeModel;
 import com.google.firebase.vertexai.java.GenerativeModelFutures;
-import com.google.firebase.vertexai.type.BlockThreshold;
+import com.google.firebase.vertexai.type.HarmBlockThreshold;
 import com.google.firebase.vertexai.type.GenerationConfig;
 import com.google.firebase.vertexai.type.HarmCategory;
 import com.google.firebase.vertexai.type.RequestOptions;
@@ -39,7 +39,7 @@ void configModelParams() {
 
     void configSafetySettings() {
         SafetySetting harassmentSafety1 = new SafetySetting(HarmCategory.HARASSMENT,
-                BlockThreshold.ONLY_HIGH);
+                HarmBlockThreshold.ONLY_HIGH, null);
 
         GenerativeModel gm1 = FirebaseVertexAI.Companion.getInstance().generativeModel(
                 "MODEL_NAME",
@@ -51,10 +51,10 @@ void configSafetySettings() {
 
         // [START vertexai_safety_settings]
         SafetySetting harassmentSafety = new SafetySetting(HarmCategory.HARASSMENT,
-                BlockThreshold.ONLY_HIGH);
+                HarmBlockThreshold.ONLY_HIGH, null);
 
         SafetySetting hateSpeechSafety = new SafetySetting(HarmCategory.HATE_SPEECH,
-                BlockThreshold.MEDIUM_AND_ABOVE);
+                HarmBlockThreshold.MEDIUM_AND_ABOVE, null);
 
         GenerativeModel gm = FirebaseVertexAI.Companion.getInstance().generativeModel(
                 "MODEL_NAME",

vertexai/app/src/main/java/com/google/firebase/example/vertexai/java/GenerateContentViewModel.java

@@ -258,7 +258,7 @@ void generateContentWithVideo(Executor executor, Uri videoUri) {
                 stream.close();
 
                 Content prompt = new Content.Builder()
-                        .addBlob("video/mp4", videoBytes)
+                        .addInlineData(videoBytes, "video/mp4")
                         .addText("What is in the video?")
                         .build();
 
@@ -298,7 +298,7 @@ void generateContentWithVideoStream(
                 stream.close();
 
                 Content prompt = new Content.Builder()
-                        .addBlob("video/mp4", videoBytes)
+                        .addInlineData(videoBytes, "video/mp4")
                         .addText("What is in the video?")
                         .build();
 

vertexai/app/src/main/java/com/google/firebase/example/vertexai/kotlin/ConfigurationViewModel.kt

@@ -2,7 +2,7 @@ package com.google.firebase.example.vertexai.kotlin
 
 import androidx.lifecycle.ViewModel
 import com.google.firebase.Firebase
-import com.google.firebase.vertexai.type.BlockThreshold
+import com.google.firebase.vertexai.type.HarmBlockThreshold
 import com.google.firebase.vertexai.type.HarmCategory
 import com.google.firebase.vertexai.type.SafetySetting
 import com.google.firebase.vertexai.type.generationConfig
@@ -30,13 +30,13 @@ class ConfigurationViewModel : ViewModel() {
         val generativeModel1 = Firebase.vertexAI.generativeModel(
             modelName = "MODEL_NAME",
             safetySettings = listOf(
-                SafetySetting(HarmCategory.HARASSMENT, BlockThreshold.ONLY_HIGH)
+                SafetySetting(HarmCategory.HARASSMENT, HarmBlockThreshold.ONLY_HIGH)
             )
         )
 
         // [START vertexai_safety_settings]
-        val harassmentSafety = SafetySetting(HarmCategory.HARASSMENT, BlockThreshold.ONLY_HIGH)
-        val hateSpeechSafety = SafetySetting(HarmCategory.HATE_SPEECH, BlockThreshold.MEDIUM_AND_ABOVE)
+        val harassmentSafety = SafetySetting(HarmCategory.HARASSMENT, HarmBlockThreshold.ONLY_HIGH)
+        val hateSpeechSafety = SafetySetting(HarmCategory.HATE_SPEECH, HarmBlockThreshold.MEDIUM_AND_ABOVE)
 
         val generativeModel = Firebase.vertexAI.generativeModel(
             modelName = "MODEL_NAME",

vertexai/app/src/main/java/com/google/firebase/example/vertexai/kotlin/FunctionCallViewModel.kt

@@ -3,90 +3,93 @@ package com.google.firebase.example.vertexai.kotlin
 import androidx.lifecycle.ViewModel
 import androidx.lifecycle.viewModelScope
 import com.google.firebase.Firebase
-import com.google.firebase.vertexai.GenerativeModel
-import com.google.firebase.vertexai.type.FunctionResponsePart
-import com.google.firebase.vertexai.type.InvalidStateException
+import com.google.firebase.vertexai.type.FunctionDeclaration
 import com.google.firebase.vertexai.type.Schema
 import com.google.firebase.vertexai.type.Tool
-import com.google.firebase.vertexai.type.content
-import com.google.firebase.vertexai.type.defineFunction
 import com.google.firebase.vertexai.vertexAI
 import kotlinx.coroutines.launch
-import org.json.JSONObject
+import kotlinx.serialization.json.JsonObject
+import kotlinx.serialization.json.JsonPrimitive
+import kotlinx.serialization.json.jsonObject
+import kotlinx.serialization.json.jsonPrimitive
 
 class FunctionCallViewModel : ViewModel() {
 
     // [START vertexai_fc_create_function]
-    suspend fun makeApiRequest(
-        currencyFrom: String,
-        currencyTo: String
-    ): JSONObject {
-        // This hypothetical API returns a JSON such as:
-        // {"base":"USD","rates":{"SEK": 10.99}}
-        return JSONObject().apply {
-            put("base", currencyFrom)
-            put("rates", hashMapOf(currencyTo to 10.99))
-        }
+    // This function calls a hypothetical external API that returns
+    // a collection of weather information for a given location on a given date.
+    // `location` is an object of the form { city: string, state: string }
+    data class Location(val city: String, val state: String)
+
+    suspend fun fetchWeather(location: Location, date: String): JsonObject {
+
+        // TODO(developer): Write a standard function that would call to an external weather API.
+
+        // For demo purposes, this hypothetical response is hardcoded here in the expected format.
+        return JsonObject(mapOf(
+            "temperature" to JsonPrimitive(38),
+            "chancePrecipitation" to JsonPrimitive("56%"),
+            "cloudConditions" to JsonPrimitive("partlyCloudy")
+        ))
     }
     // [END vertexai_fc_create_function]
 
     // [START vertexai_fc_func_declaration]
-    val getExchangeRate = defineFunction(
-        name = "getExchangeRate",
-        description = "Get the exchange rate for currencies between countries",
-        Schema.str("currencyFrom", "The currency to convert from."),
-        Schema.str("currencyTo", "The currency to convert to.")
-    ) { from, to ->
-        // Call the function that you declared above
-        makeApiRequest(from, to)
-    }
+    val fetchWeatherTool = FunctionDeclaration(
+        "fetchWeather",
+        "Get the weather conditions for a specific city on a specific date.",
+        mapOf(
+            "location" to Schema.obj(
+                mapOf(
+                    "city" to Schema.string("The city of the location."),
+                    "state" to Schema.string("The US state of the location."),
+                ),
+                description = "The name of the city and its state for which " +
+                        "to get the weather. Only cities in the " +
+                        "USA are supported."
+            ),
+            "date" to Schema.string("The date for which to get the weather." +
+                    " Date must be in the format: YYYY-MM-DD."
+            ),
+        ),
+    )
     // [END vertexai_fc_func_declaration]
 
     // [START vertexai_fc_init]
     // Initialize the Vertex AI service and the generative model
-    // Use a model that supports function calling, like Gemini 1.0 Pro.
-    val generativeModel = Firebase.vertexAI.generativeModel(
-        modelName = "gemini-1.0-pro",
-        // Specify the function declaration.
-        tools = listOf(Tool(listOf(getExchangeRate)))
+    // Use a model that supports function calling, like a Gemini 1.5 model
+    val model = Firebase.vertexAI.generativeModel(
+        modelName = "gemini-1.5-flash",
+        // Provide the function declaration to the model.
+        tools = listOf(Tool.functionDeclarations(listOf(fetchWeatherTool)))
     )
     // [END vertexai_fc_init]
 
     // [START vertexai_fc_generate]
     fun generateFunctionCall() {
         viewModelScope.launch {
-            val chat = generativeModel.startChat()
+            val prompt = "What was the weather in Boston on October 17, 2024?"
+            val chat = model.startChat()
+            // Send the user's question (the prompt) to the model using multi-turn chat.
+            val result = chat.sendMessage(prompt)
 
-            val prompt = "How much is 50 US dollars worth in Swedish krona?"
+            val functionCalls = result.functionCalls
+            // When the model responds with one or more function calls, invoke the function(s).
+            val fetchWeatherCall = functionCalls.find { it.name == "fetchWeather" }
 
-            // Send the message to the generative model
-            var response = chat.sendMessage(prompt)
-
-            // Check if the model responded with a function call
-            response.functionCalls.firstOrNull()?.let { functionCall ->
-                // Try to retrieve the stored lambda from the model's tools and
-                // throw an exception if the returned function was not declared
-                val matchedFunction = generativeModel.tools?.flatMap { it.functionDeclarations }
-                    ?.first { it.name == functionCall.name }
-                    ?: throw InvalidStateException("Function not found: ${functionCall.name}")
-
-                // Call the lambda retrieved above
-                val apiResponse: JSONObject = matchedFunction.execute(functionCall)
-
-                // Send the API response back to the generative model
-                // so that it generates a text response that can be displayed to the user
-                response = chat.sendMessage(
-                    content(role = "function") {
-                        part(FunctionResponsePart(functionCall.name, apiResponse))
-                    }
+            // Forward the structured input data prepared by the model
+            // to the hypothetical external API.
+            val functionResponse = fetchWeatherCall?.let {
+                // Alternatively, if your `Location` class is marked as @Serializable, you can use
+                // val location = Json.decodeFromJsonElement<Location>(it.args["location"]!!)
+                val location = Location(
+                    it.args["location"]!!.jsonObject["city"]!!.jsonPrimitive.content,
+                    it.args["location"]!!.jsonObject["state"]!!.jsonPrimitive.content
                 )
-            }
-
-            // Whenever the model responds with text, show it in the UI
-            response.text?.let { modelResponse ->
-                println(modelResponse)
+                val date = it.args["date"]!!.jsonPrimitive.content
+                fetchWeather(location, date)
             }
         }
     }
     // [END vertexai_fc_generate]
-}
+}

vertexai/app/src/main/java/com/google/firebase/example/vertexai/kotlin/GenerateContentViewModel.kt

@@ -154,7 +154,7 @@ class GenerateContentViewModel : ViewModel() {
                     val bytes = stream.readBytes()
 
                     val prompt = content {
-                        blob("video/mp4", bytes)
+                        inlineData(bytes, "video/mp4")
                         text("What is in the video?")
                     }
 
@@ -181,7 +181,7 @@ class GenerateContentViewModel : ViewModel() {
                     val bytes = stream.readBytes()
 
                     val prompt = content {
-                        blob("video/mp4", bytes)
+                        inlineData(bytes, "video/mp4")
                         text("What is in the video?")
                     }