순차 에이전트¶

`SequentialAgent`¶

SequentialAgent는 목록에 지정된 순서대로 하위 에이전트를 실행하는 워크플로 에이전트입니다.

실행이 고정되고 엄격한 순서로 이루어지기를 원할 때 SequentialAgent를 사용하세요.

예제¶

두 가지 도구, 즉 페이지 내용 가져오기와 페이지 요약하기를 사용하여 모든 웹페이지를 요약할 수 있는 에이전트를 만들고 싶다고 가정해 봅시다. 에이전트는 항상 페이지 요약하기를 호출하기 전에 페이지 내용 가져오기를 호출해야 하므로(아무것도 없는 것을 요약할 수는 없으므로!), SequentialAgent를 사용하여 에이전트를 구축해야 합니다.

다른 워크플로 에이전트와 마찬가지로 SequentialAgent는 LLM으로 구동되지 않으므로 실행 방식이 결정적입니다. 즉, 워크플로 에이전트는 실행(즉, 순차적으로)에만 관련이 있고 내부 로직에는 관련이 없습니다. 워크플로 에이전트의 도구나 하위 에이전트는 LLM을 활용할 수도 있고 그렇지 않을 수도 있습니다.

작동 방식¶

SequentialAgent의 Run Async 메서드가 호출되면 다음 작업을 수행합니다:

반복: 제공된 순서대로 하위 에이전트 목록을 반복합니다.
하위 에이전트 실행: 목록의 각 하위 에이전트에 대해 하위 에이전트의 Run Async 메서드를 호출합니다.

순차 에이전트

전체 예제: 코드 개발 파이프라인¶

간소화된 코드 개발 파이프라인을 생각해 보세요:

코드 작성자 에이전트: 사양에 따라 초기 코드를 생성하는 LLM 에이전트입니다.
코드 검토자 에이전트: 생성된 코드의 오류, 스타일 문제 및 모범 사례 준수 여부를 검토하는 LLM 에이전트입니다. 코드 작성자 에이전트의 출력을 받습니다.
코드 리팩터러 에이전트: 검토된 코드(및 검토자의 의견)를 가져와 품질을 개선하고 문제를 해결하기 위해 리팩터링하는 LLM 에이전트입니다.

SequentialAgent는 이에 완벽합니다:

SequentialAgent(sub_agents=[CodeWriterAgent, CodeReviewerAgent, CodeRefactorerAgent])

이렇게 하면 코드가 작성된 후 검토되고 마지막으로 리팩터링되는 것이 엄격하고 신뢰할 수 있는 순서로 보장됩니다. 각 하위 에이전트의 출력은 출력 키를 통해 상태에 저장되어 다음 에이전트로 전달됩니다.

코드

PythonJava

# Part of agent.py --> Follow https://google.github.io/adk-docs/get-started/quickstart/ to learn the setup

# --- 1. Define Sub-Agents for Each Pipeline Stage ---

# Code Writer Agent
# Takes the initial specification (from user query) and writes code.
code_writer_agent = LlmAgent(
    name="CodeWriterAgent",
    model=GEMINI_MODEL,
    # Change 3: Improved instruction
    instruction="""You are a Python Code Generator.
Based *only* on the user's request, write Python code that fulfills the requirement.
Output *only* the complete Python code block, enclosed in triple backticks (```python ... ```). 
Do not add any other text before or after the code block.
""",
    description="Writes initial Python code based on a specification.",
    output_key="generated_code" # Stores output in state['generated_code']
)

# Code Reviewer Agent
# Takes the code generated by the previous agent (read from state) and provides feedback.
code_reviewer_agent = LlmAgent(
    name="CodeReviewerAgent",
    model=GEMINI_MODEL,
    # Change 3: Improved instruction, correctly using state key injection
    instruction="""You are an expert Python Code Reviewer. 
    Your task is to provide constructive feedback on the provided code.

    **Code to Review:**
    ```python
    {generated_code}
    ```

**Review Criteria:**
1.  **Correctness:** Does the code work as intended? Are there logic errors?
2.  **Readability:** Is the code clear and easy to understand? Follows PEP 8 style guidelines?
3.  **Efficiency:** Is the code reasonably efficient? Any obvious performance bottlenecks?
4.  **Edge Cases:** Does the code handle potential edge cases or invalid inputs gracefully?
5.  **Best Practices:** Does the code follow common Python best practices?

**Output:**
Provide your feedback as a concise, bulleted list. Focus on the most important points for improvement.
If the code is excellent and requires no changes, simply state: "No major issues found."
Output *only* the review comments or the "No major issues" statement.
""",
    description="Reviews code and provides feedback.",
    output_key="review_comments", # Stores output in state['review_comments']
)


# Code Refactorer Agent
# Takes the original code and the review comments (read from state) and refactors the code.
code_refactorer_agent = LlmAgent(
    name="CodeRefactorerAgent",
    model=GEMINI_MODEL,
    # Change 3: Improved instruction, correctly using state key injection
    instruction="""You are a Python Code Refactoring AI.
Your goal is to improve the given Python code based on the provided review comments.

  **Original Code:**
  ```python
  {generated_code}
  ```

  **Review Comments:**
  {review_comments}

**Task:**
Carefully apply the suggestions from the review comments to refactor the original code.
If the review comments state "No major issues found," return the original code unchanged.
Ensure the final code is complete, functional, and includes necessary imports and docstrings.

**Output:**
Output *only* the final, refactored Python code block, enclosed in triple backticks (```python ... ```). 
Do not add any other text before or after the code block.
""",
    description="Refactors code based on review comments.",
    output_key="refactored_code", # Stores output in state['refactored_code']
)


# --- 2. Create the SequentialAgent ---
# This agent orchestrates the pipeline by running the sub_agents in order.
code_pipeline_agent = SequentialAgent(
    name="CodePipelineAgent",
    sub_agents=[code_writer_agent, code_reviewer_agent, code_refactorer_agent],
    description="Executes a sequence of code writing, reviewing, and refactoring.",
    # The agents will run in the order provided: Writer -> Reviewer -> Refactorer
)

# For ADK tools compatibility, the root agent must be named `root_agent`
root_agent = code_pipeline_agent

import com.google.adk.agents.LlmAgent;
import com.google.adk.agents.SequentialAgent;
import com.google.adk.events.Event;
import com.google.adk.runner.InMemoryRunner;
import com.google.adk.sessions.Session;
import com.google.genai.types.Content;
import com.google.genai.types.Part;
import io.reactivex.rxjava3.core.Flowable;

public class SequentialAgentExample {

  private static final String APP_NAME = "CodePipelineAgent";
  private static final String USER_ID = "test_user_456";
  private static final String MODEL_NAME = "gemini-2.0-flash";

  public static void main(String[] args) {
    SequentialAgentExample sequentialAgentExample = new SequentialAgentExample();
    sequentialAgentExample.runAgent(
        "Write a Java function to calculate the factorial of a number.");
  }

  public void runAgent(String prompt) {

    LlmAgent codeWriterAgent =
        LlmAgent.builder()
            .model(MODEL_NAME)
            .name("CodeWriterAgent")
            .description("Writes initial Java code based on a specification.")
            .instruction(
                """
                You are a Java Code Generator.
                Based *only* on the user's request, write Java code that fulfills the requirement.
                Output *only* the complete Java code block, enclosed in triple backticks (```java ... ```).
                Do not add any other text before or after the code block.
                """)
            .outputKey("generated_code")
            .build();

    LlmAgent codeReviewerAgent =
        LlmAgent.builder()
            .model(MODEL_NAME)
            .name("CodeReviewerAgent")
            .description("Reviews code and provides feedback.")
            .instruction(
                """
                    You are an expert Java Code Reviewer.
                    Your task is to provide constructive feedback on the provided code.

                    **Code to Review:**
                    ```java
                    {generated_code}
                    ```

                    **Review Criteria:**
                    1.  **Correctness:** Does the code work as intended? Are there logic errors?
                    2.  **Readability:** Is the code clear and easy to understand? Follows Java style guidelines?
                    3.  **Efficiency:** Is the code reasonably efficient? Any obvious performance bottlenecks?
                    4.  **Edge Cases:** Does the code handle potential edge cases or invalid inputs gracefully?
                    5.  **Best Practices:** Does the code follow common Java best practices?

                    **Output:**
                    Provide your feedback as a concise, bulleted list. Focus on the most important points for improvement.
                    If the code is excellent and requires no changes, simply state: "No major issues found."
                    Output *only* the review comments or the "No major issues" statement.
                """)
            .outputKey("review_comments")
            .build();

    LlmAgent codeRefactorerAgent =
        LlmAgent.builder()
            .model(MODEL_NAME)
            .name("CodeRefactorerAgent")
            .description("Refactors code based on review comments.")
            .instruction(
                """
                You are a Java Code Refactoring AI.
                Your goal is to improve the given Java code based on the provided review comments.

                  **Original Code:**
                  ```java
                  {generated_code}
                  ```

                  **Review Comments:**
                  {review_comments}

                **Task:**
                Carefully apply the suggestions from the review comments to refactor the original code.
                If the review comments state "No major issues found," return the original code unchanged.
                Ensure the final code is complete, functional, and includes necessary imports and docstrings.

                **Output:**
                Output *only* the final, refactored Java code block, enclosed in triple backticks (```java ... ```).
                Do not add any other text before or after the code block.
                """)
            .outputKey("refactored_code")
            .build();

    SequentialAgent codePipelineAgent =
        SequentialAgent.builder()
            .name(APP_NAME)
            .description("Executes a sequence of code writing, reviewing, and refactoring.")
            // The agents will run in the order provided: Writer -> Reviewer -> Refactorer
            .subAgents(codeWriterAgent, codeReviewerAgent, codeRefactorerAgent)
            .build();

    // Create an InMemoryRunner
    InMemoryRunner runner = new InMemoryRunner(codePipelineAgent, APP_NAME);
    // InMemoryRunner automatically creates a session service. Create a session using the service
    Session session = runner.sessionService().createSession(APP_NAME, USER_ID).blockingGet();
    Content userMessage = Content.fromParts(Part.fromText(prompt));

    // Run the agent
    Flowable<Event> eventStream = runner.runAsync(USER_ID, session.id(), userMessage);

    // Stream event response
    eventStream.blockingForEach(
        event -> {
          if (event.finalResponse()) {
            System.out.println(event.stringifyContent());
          }
        });
  }
}

순차 에이전트¶

SequentialAgent¶

예제¶

작동 방식¶

전체 예제: 코드 개발 파이프라인¶

`SequentialAgent`¶