mirror of
https://github.com/google/adk-docs.git
synced 2026-09-14 16:16:59 +08:00
Juan Carlos Radillo Diaz
89 lines
4.0 KiB
Markdown
89 lines
4.0 KiB
Markdown
# Sequential template workflow agent
|
|
|
|
<div class="language-support-tag">
|
|
<span class="lst-supported">Supported in ADK</span><span class="lst-python">Python v0.1.0</span><span class="lst-typescript">TypeScript v0.2.0</span><span class="lst-go">Go v0.1.0</span><span class="lst-java">Java v0.2.0</span>
|
|
</div>
|
|
|
|
The ***SequentialAgent*** class is a [template workflow](/agents/workflow-agents/)
|
|
agent that executes its sub-agents in the order they are specified in a list.
|
|
Use ***SequentialAgent*** when you want execution to occur in a fixed, strict
|
|
order. As with other templated workflows, the execution of a
|
|
***SequentialAgent*** object is not controlled by an AI model, and is
|
|
deterministic in how it executes its sub-agents. The sub-agents specified in the
|
|
sequential execution set may or may not utilize AI models, but the overall
|
|
execution of those sub-agents is ultimately managed by the ***SequentialAgent***
|
|
object you define.
|
|
|
|
!!! note "Alternative: graph-based workflows"
|
|
|
|
Starting in ADK 2.0 for Python and Go, templated workflows have been superseded
|
|
|
|
by more flexible workflow structures, including
|
|
[graph-based workflows](/graphs/) and
|
|
[dynamic workflows](/graphs/dynamic/).
|
|
|
|
### Example scenario
|
|
|
|
You want to build an agent that can summarize any webpage, using two tools:
|
|
**Get Page Contents** and **Summarize Page**. Since the agent must always call
|
|
**Get Page Contents** before calling **Summarize Page**, you can build your
|
|
agent using the ***SequentialAgent*** class.
|
|
|
|
### How it works
|
|
|
|
When the `SequentialAgent`'s `Run Async` method is called, it performs the following actions:
|
|
|
|
1. **Iteration:** It iterates through the sub agents list in the order they were provided.
|
|
2. **Sub-Agent Execution:** For each sub-agent in the list, it calls the sub-agent's `Run Async` method.
|
|
|
|
{: width="600"}
|
|
|
|
!!! note "Shared Invocation Context"
|
|
The `SequentialAgent` passes the same `InvocationContext` to each of its
|
|
sub-agents. This means they all share the same session state, including the
|
|
temporary (`temp:`) namespace, making it easy to pass data between steps within
|
|
a single turn.
|
|
|
|
### Full Example: Code Development Pipeline
|
|
|
|
Consider a simplified code development pipeline:
|
|
|
|
* **Code Writer Agent:** An LLM Agent that generates initial code based on a specification.
|
|
* **Code Reviewer Agent:** An LLM Agent that reviews the generated code for errors, style issues, and adherence to best practices. It receives the output of the Code Writer Agent.
|
|
* **Code Refactorer Agent:** An LLM Agent that takes the reviewed code, and the reviewer's comments, and refactors it to improve quality and address issues.
|
|
|
|
Using a `SequentialAgent` makes it simple to define this exection flow, as shown
|
|
in the following code snippet:
|
|
|
|
```py
|
|
SequentialAgent(sub_agents=[CodeWriterAgent, CodeReviewerAgent, CodeRefactorerAgent])
|
|
```
|
|
|
|
This ensures the code is written, *then* reviewed, and *finally* refactored, in a strict, dependable order. **The output from each sub-agent is passed to the next by storing them in state via [Output Key](/agents/llm-agents/##data-handling)**.
|
|
|
|
???+ "Code"
|
|
|
|
=== "Python"
|
|
```py
|
|
--8<-- "examples/python/snippets/agents/workflow-agents/sequential_agent_code_development_agent.py:init"
|
|
```
|
|
|
|
=== "TypeScript"
|
|
```typescript
|
|
--8<-- "examples/typescript/snippets/agents/workflow-agents/sequential_agent_code_development_agent.ts:init"
|
|
```
|
|
|
|
=== "Go"
|
|
```go
|
|
--8<-- "examples/go/snippets/agents/workflow-agents/sequential/main.go:init"
|
|
```
|
|
|
|
=== "Java"
|
|
```java
|
|
--8<-- "examples/java/snippets/src/main/java/agents/workflow/SequentialAgentExample.java:init"
|
|
```
|
|
|
|
!!! tip "Global instructions for all agents"
|
|
|
|
Apply consistent rules or identity across all agents in your workflow using `GlobalInstructionPlugin` registered on your `App` or `Runner` object. Do not use the `global_instruction` parameter on `Agent` which is deprecated since ADK Python v1.16.0.
|