Selama Agentic Workflows, class AgentRunner dan antarmuka AgentSession memancarkan aliran peristiwa reaktif yang mewakili proses penalaran model, pemanggilan alat, dan respons tekstual. Halaman ini menunjukkan cara mengumpulkan peristiwa
dan menghubungkannya ke UI menggunakan Coroutine Kotlin dan Jetpack Compose.
Memahami antarmuka AgentEvent
Metode AgentSession.runAsync() dan AgentRunner.runSingleTurnAsync() menampilkan
aliran data Flow<AgentEvent>. Daripada menunggu seluruh reasoning loop selesai,
aplikasi Anda akan menerima update real-time saat agen mengeksekusi:
Event type |
Deskripsi |
Tindakan UI umum |
|
Memunculkan potongan teks inkremental ( |
Tambahkan |
|
Dipancarkan saat Gemini Nano memilih alat dan bersiap untuk menjalankannya (menyediakan |
Menampilkan indikator dalam proses (misalnya, "Memeriksa status pesanan..."). |
|
Dikeluarkan saat aplikasi selesai menjalankan fungsi alat (menyediakan
|
Ubah status alat menjadi selesai. |
Mengumpulkan peristiwa di class ViewModel
Gunakan class ViewModel Android untuk mengoordinasikan pengiriman perintah dan mengekspos status UI ke
layar Compose Anda:
package com.example.ai.agent.ui
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.google.mlkit.genai.agent.AgentEvent
import com.google.mlkit.genai.agent.AgentRunner
import com.google.mlkit.genai.agent.AgentSession
import com.google.mlkit.genai.common.GenAiException
import com.google.mlkit.genai.prompt.Content
import kotlinx.coroutines.flow.MutableStateFlow
import kotlinx.coroutines.flow.StateFlow
import kotlinx.coroutines.flow.asStateFlow
import kotlinx.coroutines.flow.catch
import kotlinx.coroutines.flow.update
import kotlinx.coroutines.launch
data class AgentUiState(
val messages: List<String> = emptyList(),
val currentResponse: String = "",
val activeToolStatus: String? = null,
val isLoading: Boolean = false,
val errorMessage: String? = null
)
class ChatViewModel(
private val runner: AgentRunner,
private val sessionId: String = "default_chat_session"
) : ViewModel() {
private val session: AgentSession = runner.getOrCreateSession(sessionId)
private val _uiState = MutableStateFlow(AgentUiState())
val uiState: StateFlow<AgentUiState> = _uiState.asStateFlow()
fun sendMessage(userText: String) {
_uiState.update {
it.copy(
messages = it.messages + userText,
currentResponse = "",
activeToolStatus = null,
isLoading = true,
errorMessage = null
)
}
viewModelScope.launch {
val content = Content.builder().text(userText).build()
session.runAsync(content)
.catch { e ->
val message = when {
e is GenAiException && e.errorCode == GenAiException.ErrorCode.MAX_TURNS_EXCEEDED ->
"Agent exceeded the maximum reasoning turns allowed."
e is GenAiException && e.errorCode == GenAiException.ErrorCode.NOT_AVAILABLE ->
"On-device AI is currently unavailable."
e is GenAiException && e.errorCode == GenAiException.ErrorCode.BUSY ->
"On-device AI is busy. Please try again."
else -> e.localizedMessage ?: "Agent error"
}
_uiState.update {
it.copy(
isLoading = false,
activeToolStatus = null,
errorMessage = message
)
}
}
.collect { event ->
when (event) {
is AgentEvent.TextMessage -> {
_uiState.update {
it.copy(
currentResponse = if (event.isPartial) {
it.currentResponse + event.text
} else {
event.text.ifEmpty { it.currentResponse }
},
activeToolStatus = null
)
}
}
is AgentEvent.FunctionCall -> {
_uiState.update {
it.copy(
activeToolStatus =
"Executing ${event.name}..."
)
}
}
is AgentEvent.FunctionResponse -> {
_uiState.update {
it.copy(
activeToolStatus =
"Received data from ${event.name}"
)
}
}
else -> {}
}
}
// Finalize message once stream completes
_uiState.update {
it.copy(
messages = it.messages + it.currentResponse,
currentResponse = "",
activeToolStatus = null,
isLoading = false
)
}
}
}
override fun onCleared() {
super.onCleared()
// Release session memory and cancel active coroutines
session.close()
}
}
Mengekstrak token teks secara langsung
Untuk antarmuka percakapan yang detail eksekusi alatnya tidak perlu
ditampilkan secara terpisah di UI, gunakan fungsi ekstensi textTokens() di
antarmuka Flow<AgentEvent>:
import com.google.mlkit.genai.agent.textTokens
import com.google.mlkit.genai.prompt.Content
val content = Content.builder().text(userText).build()
session.runAsync(content)
.textTokens()
.collect { token ->
appendTokenToChatBubble(token)
}
Merender di Jetpack Compose
Gunakan status AgentUiState dalam fungsi composable untuk merender teks yang di-streaming dan aktivitas alat langsung:
package com.example.ai.agent.ui
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyColumn
import androidx.compose.foundation.lazy.items
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Modifier
import androidx.compose.ui.unit.dp
@Composable
fun AgentChatScreen(
viewModel: ChatViewModel,
modifier: Modifier = Modifier
) {
val state by viewModel.uiState.collectAsState()
var inputText by remember { mutableStateOf("") }
Column(modifier = modifier.fillMaxSize().padding(16.dp)) {
LazyColumn(
modifier = Modifier.weight(1f).fillMaxWidth(),
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
items(state.messages) { message ->
Card(modifier = Modifier.fillMaxWidth()) {
Text(text = message, modifier = Modifier.padding(12.dp))
}
}
if (state.activeToolStatus != null) {
item {
Text(
text = state.activeToolStatus ?: "",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.secondary
)
}
}
if (state.currentResponse.isNotEmpty()) {
item {
Card(
colors = CardDefaults.cardColors(
containerColor =
MaterialTheme.colorScheme.surfaceVariant
),
modifier = Modifier.fillMaxWidth()
) {
Text(
text = state.currentResponse,
modifier = Modifier.padding(12.dp)
)
}
}
}
}
Row(
modifier = Modifier.fillMaxWidth().padding(top = 8.dp),
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
TextField(
value = inputText,
onValueChange = { inputText = it },
modifier = Modifier.weight(1f),
placeholder = { Text("Ask about an order...") }
)
Button(
onClick = {
if (inputText.isNotBlank()) {
viewModel.sendMessage(inputText)
inputText = ""
}
},
enabled = !state.isLoading
) {
Text("Send")
}
}
}
}
Langkah berikutnya
- Pelajari cara menentukan alat di Menentukan alat.
- Kelola memori sesi dan tangani rotasi di Mengelola sesi dan siklus proses.