ライフサイクル・フック
ライフサイクル・フックを使用したエージェント実行の監視およびデバッグ。
ライフサイクル・フックを使用したエージェント実行の監視
ライフサイクル・フックを使用すると、ファンクション・コールやリモート・サービス相互作用などのagent.run()メソッド中に、主要なライフサイクル・イベントにカスタム・ロギングまたは処理ステップをプラグインできます。
この機能は、これらのイベントの詳細を人間が読める形式でWebアプリケーションのエンド・ユーザーに表示する場合や、顧客がエージェントを構築および監視するためのプラットフォームを提供している場合はエージェント開発者に特に役立ちます。
Python
lifecycle_hook.py
import json
from rich.console import Console
from oci.addons.adk import Agent, AgentClient
from oci.addons.adk.tool.prebuilt import CalculatorToolkit
from oci.addons.adk.run.types import RequiredAction, PerformedAction
# A callback function that is called when a required action is fulfilled
def handle_fulfilled_required_action(required_action: RequiredAction, performed_action: PerformedAction):
# Implement your custom logging or processing here
# Access the required action and performed action objects to get the details
pass
# A callback function that is called when a remote service is invoked
def handle_invoked_remote_service(chat_request, chat_response):
# Implement your custom logging or processing here
# Access the chat request and response objects to get the details
pass
def main():
client = AgentClient(
auth_type="api_key",
profile="DEFAULT",
region="us-chicago-1"
)
agent = Agent(
client=client,
agent_endpoint_id="ocid1.genaiagentendpoint...",
instructions="You're a helpful assistant that can perform calculations.",
tools=[CalculatorToolkit()]
)
agent.setup()
input = "What's the square root of 475695037565?"
response = agent.run(
input,
max_steps=6,
on_fulfilled_required_action=handle_fulfilled_required_action,
on_invoked_remote_service=handle_invoked_remote_service,
)
response.pretty_print()
if __name__ == "__main__":
main()
Java
LifecycleHookAgent.java
package demos;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.oracle.bmc.ConfigFileReader;
import com.oracle.bmc.auth.BasicAuthenticationDetailsProvider;
import com.oracle.bmc.auth.SessionTokenAuthenticationDetailsProvider;
import com.oracle.bmc.generativeaiagentruntime.model.FunctionCallingPerformedAction;
import com.oracle.bmc.generativeaiagentruntime.model.FunctionCallingRequiredAction;
import com.oracle.bmc.generativeaiagentruntime.model.PerformedAction;
import com.oracle.bmc.generativeaiagentruntime.model.RequiredAction;
import com.oracle.bmc.generativeaiagentruntime.responses.ChatResponse;
import com.oracle.bmc.adk.agent.Agent;
import com.oracle.bmc.adk.agent.RunOptions;
import com.oracle.bmc.adk.client.AgentClient;
import com.oracle.bmc.adk.tools.prebuilt.CalculatorToolkit;
import com.oracle.bmc.adk.run.RunResponse;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
public class LifecycleHookAgent {
private static final ObjectMapper objectMapper = new ObjectMapper();
public static void main(String[] args) throws Exception {
final String AGENT_ENDPOINT_ID =
"ocid1.genaiagentendpoint.oc1.us-chicago-1...";
final String configLocation = "~/.oci/config";
final String configProfile = "DEFAULT";
BasicAuthenticationDetailsProvider authProvider =
new SessionTokenAuthenticationDetailsProvider(
ConfigFileReader.parse(configLocation, configProfile));
AgentClient agentClient = AgentClient.builder()
.authProvider(authProvider)
.region("us-chicago-1")
.build();
// Instantiate the local agent object (with the client, instructions, and tools to be
// registered)
Agent agent = Agent.builder()
.client(agentClient)
.agentEndpointId(WRITER_AGENT_ENDPOINT_ID)
.instructions("You are a helpful assistant that can perform calculations.")
.tools(List.of(new CalculatorToolkit()))
.build();
// Set up the agent (configures the instructions and tools in the remote agent resource)
agent.setup();
// Use the agent to process the end user request (automatically handles function calling)
final String input = "What is the square root of 16?";
final Integer maxStep = 6;
final RunOptions runOptions = RunOptions.builder()
.maxSteps(maxStep)
.onFulfilledRequiredAction(LifecycleHookAgent::handleFulfilledRequiredAction)
.onInvokedRemoteService(LifecycleHookAgent::handleInvokedRemoteService)
.build();
RunResponse response = agent.run(input, runOptions);
response.prettyPrint();
}
public static void handleFulfilledRequiredAction(
RequiredAction requiredAction, PerformedAction performedAction) {
String toolCallName =
((FunctionCallingRequiredAction) requiredAction).getFunctionCall().getName();
String toolCallArgs =
((FunctionCallingRequiredAction) requiredAction).getFunctionCall().getArguments();
String toolCallOutput =
((FunctionCallingPerformedAction) performedAction).getFunctionCallOutput();
// Format JSON strings with proper indentation
String formattedArgs = formatJson(toolCallArgs);
String formattedOutput = formatJson(toolCallOutput);
String baseMessage = "Executed client-side function tool: **" + toolCallName + "**";
String details =
"Function Tool call arguments:\n```json\n"
+ formattedArgs
+ "\n```\nFunction Tool call output:\n```json\n"
+ formattedOutput
+ "\n```";
System.out.println(baseMessage);
System.out.println(details);
}
public static void handleInvokedRemoteService(
Map<String, Object> chatRequest, ChatResponse chatResponse) {
String label = "Invoked Agent Service API: ";
if (chatResponse.getChatResult().getRequiredActions() != null) {
List<RequiredAction> actions = chatResponse.getChatResult().getRequiredActions();
label += " received " + actions.size() + " action(s) for client to take";
} else {
label += " received agent text message";
}
String content =
"Agent Service call request:\n```json\n"
+ formatJson(chatRequest)
+ "\n```\nAgent Service call response:\n```json\n"
+ formatJson(chatResponse)
+ "\n```";
System.out.println(label);
System.out.println(content);
}
private static String formatJson(Object obj) {
try {
return objectMapper.writerWithDefaultPrettyPrinter().writeValueAsString(obj);
} catch (JsonProcessingException e) {
return obj.toString();
}
}
}
現在、ADKは2つのライフサイクル・フックをサポートしています。
on_fulfilled_required_action: このフックは、ファンクション・ツールの起動など、必要なアクションの実行後にコールされます。on_invoked_remote_service: このフックは、リモート・エージェント・サービスAPIが呼び出されたときにコールされます。