Google เปิดตัว ADK for Kotlin 1.0 ยกระดับการสร้าง AI Agent บน Android และ Server แบบมืออาชีพ

data class ServiceMetrics(
    val serviceName: String,
    val cpuUsagePercent: Double,
    val connectionPoolUsagePercent: Double,
    val activeConnections: Int,
    val maxConnections: Int,
    val p99LatencyMs: Int,
    val errorRatePercent: Double,
)
data class DeploymentInfo(
    val deploymentId: String,
    val serviceName: String,
    val gitCommit: String,
    val author: String,
    val deployedMinutesAgo: Int,
    val description: String,
)

class InfrastructureDiagnosticsService {
    @Tool
    suspend fun getServiceMetrics(
        @Param("Target service or database cluster") serviceName: String,
        @Param("Time window in minutes") windowMinutes: Int? = 15,
    ): ServiceMetrics {
        // Query monitoring backends (Datadog, Prometheus, Cloud Monitoring)
        return ServiceMetrics(
            serviceName = serviceName,
            cpuUsagePercent = 91.4,
            connectionPoolUsagePercent = 98.5,
            activeConnections = 492,
            maxConnections = 500,
            p99LatencyMs = 2450,
            errorRatePercent = 4.2,
        )
    }
    @Tool
    fun fetchRecentDeployments(
        @Param("Target service identifier") serviceName: String
    ): List<DeploymentInfo> {
        return listOf(
            DeploymentInfo(
                deploymentId = "deploy-9842",
                serviceName = serviceName,
                gitCommit = "a1b2c3d",
                author = "[email protected]",
                deployedMinutesAgo = 25,
                description = "Add unindexed batch query to user profile sync job",
            )
        )
    }
    @Tool
    fun notifyOnCall(
        @Param("Channel to notify, e.g. '#production-alerts'") channel: String,
        @Param("Diagnostic summary message") message: String,
        @Param("Severity: INFO, WARNING, CRITICAL") severity: String? = "WARNING",
    ): String {
        println(">>> [CHAT-OPS] Broadcasting [$severity] to $channel: $message")
        return "Notification posted successfully."
    }
}

---
name: database-incident-triage
description: Standard operating procedure for diagnosing database latency spikes and connection pool saturation.
allowed-tools: [getServiceMetrics, fetchRecentDeployments, notifyOnCall]
---
# Database Incident Triage SOP
1. **Telemetry**: Call `getServiceMetrics` to inspect CPU, latency, and pool saturation.
2. **Correlation**: Call `fetchRecentDeployments` to check for recent code/schema changes.
3. **Safety Rules**: Inspect `assets/mitigation_rules.txt` with `load_skill_resource` before taking action. Never restart primary nodes during peak hours.
4. **Notify**: Broadcast root-cause diagnosis to `#production-alerts` with `notifyOnCall`.

object IncidentTriageDemoAgent {
    val rootAgent = LlmAgent(
        name = "incident_triage_agent",
        model = Gemini(name = "gemini-3.8-flash"),
        instruction = Instruction(
            """
            You are an SRE on-call diagnostic assistant.
            When an alert is reported:
            1. Discover available triage playbooks and load the matching SOP using `load_skill`.
            2. Follow the playbook steps strictly, loading skill resources if needed.
            3. Use your diagnostics tools to inspect telemetry and notify the team.
            """.trimIndent()
        ),
        // 1. Compile-time generated function tools (zero reflection)
        tools = InfrastructureDiagnosticsService().generatedTools(),
        // 2. Dynamic skill toolset (provides list_skills, load_skill, load_skill_resource)
        toolsets = listOf(SkillToolset(NewFileSystemSource(resolveSkillsDir()))),
    )
}

fun main() = runBlocking {
    val runner = InMemoryRunner(
        agent = IncidentTriageDemoAgent.rootAgent,
        appName = "IncidentTriageApp"
    )
    val alert = "ALERT [P1]: Database latency spike detected on 'users-postgres-cluster'! "
              + "Active connections are surging and queries are timing out."
    val events = runner.runAsync(
        userId = "oncall-sre",
        sessionId = UUID.randomUUID().toString(),
        newMessage = Content.fromText(Role.USER, alert)
    ).toList()
    for (event in events) {
        event.content?.parts?.firstOrNull()?.text?.let { println("Agent: $it") }
    }
}

// 1. Sensitive Tool requiring human confirmation
class BankTransferTools {
    @Tool(
        name = "transferFunds",
        description = "Transfers money to another account. Requires explicit user approval.",
        requireConfirmation = true
    )
    fun transferFunds(
        @Param("Recipient account ID") recipientId: String,
        @Param("Amount in USD") amount: Double
    ): String {
        println(">>> [BANKING CORE] Executing transfer of \$$amount to $recipientId...")
        return "Successfully scheduled transfer of \$$amount to $recipientId. Ref: TX-${System.currentTimeMillis()}"
    }
}

// 2. Define the Agent backed by Firebase AI (Gemini 3.8 Flash)
fun createFinancialAgent(): LlmAgent {
    val firebaseAi = FirebaseAI.getInstance(FirebaseApp.getInstance())
    return LlmAgent(
        name = "FinancialAgent",
        description = "Handles banking inquiries and scheduled fund transfers",
        model = Firebase.create("gemini-3.8-flash", firebaseAi),
        instruction = Instruction(
            "You are a secure banking assistant. Help users manage their accounts and transfer funds."
        ),
        tools = BankTransferTools().generatedTools()
    )
}

// 3. Configure the Runner with Persistent Android Storage Services
fun createAndroidRunner(applicationContext: Context, agent: LlmAgent): InMemoryRunner {
    return InMemoryRunner(
        agent = agent,
        appName = "AndroidFinancialApp",
        // SQLite persistence for chat history across reboots / process death
        sessionService = RoomSessionService.fromContext(applicationContext),
        // On-device full-text indexed memory with AndroidX AppSearch
        memoryService = AppSearchMemoryService.fromContext(applicationContext),
        // App-private file storage for generated statements/receipts
        artifactService = FileArtifactService.fromExternalFilesDir(applicationContext)
    )
}

// 4. Multi-turn Human-in-the-Loop Execution
suspend fun runFinancialDemo(runner: InMemoryRunner) {
    val userId = "user-123"
    val sessionId = "session-${UUID.randomUUID()}"
    suspend fun sendTurn(message: Content): List<Event> {
        val events = runner.runAsync(userId = userId, sessionId = sessionId, newMessage = message).toList()
        for (event in events) {
            event.content?.parts?.firstOrNull()?.text?.let { println("Agent: $it") }
        }
        return events
    }
    // --- Turn 1: User requests transfer (Agent pauses execution)
    println("User: Please transfer $50 to account ACCT-9876.\n")
    val turn1Events = sendTurn(
            Content.fromText(Role.USER, "Please transfer $50 to account ACCT-9876."))
    // Intercept the synthetic confirmation request emitted by ADK
    val confirmationRequestId = turn1Events
        .flatMap { it.functionCalls() }
        .firstOrNull { it.name == FunctionCall.REQUEST_CONFIRMATION_FUNCTION_CALL_NAME }
        ?.id ?: return
    println("\n[UI]: Sensitive action detected. User tapped [Confirm Transfer].\n")
    // --- Turn 2: User confirms in the Android UI (Resumes & executes transferFunds)
    val approvalMessage = Content(
        role = Role.USER,
        parts = listOf(
            Part(
                functionResponse = FunctionResponse(
                    name = FunctionCall.REQUEST_CONFIRMATION_FUNCTION_CALL_NAME,
                    id = confirmationRequestId,
                    response = mapOf(ToolConfirmation.CONFIRMED_KEY to true)
                )
            )
        )
    )
    sendTurn(approvalMessage)
}

dependencies {
    // ADK Kotlin Core Engine + KSP Processor
    implementation("com.google.adk:google-adk-kotlin-core:1.0.0")
    ksp("com.google.adk:google-adk-kotlin-processor:1.0.0")
    // Optional Android-first extensions:
    implementation("com.google.adk:google-adk-kotlin-mlkit-android:1.0.0-beta")
    implementation("com.google.adk:google-adk-kotlin-litertlm:1.0.0")
    implementation("com.google.adk:google-adk-kotlin-firebase-android:1.0.0")
}