Testing Workflow Agents Reference

Write unit tests for workflow agents using pytest with async support and the public InMemoryRunner from google.adk.runners.

Setup

bash

# Install ADK + pytest + pytest-asyncio
pip install "google-adk>=2.0" pytest pytest-asyncio

# Or with uv
uv add "google-adk>=2.0" pytest pytest-asyncio

pyproject.toml:

toml

[tool.pytest.ini_options]
asyncio_mode = "auto"

asyncio_mode = "auto" removes the need to mark every test with @pytest.mark.asyncio; if you'd rather mark each test explicitly, omit it.

Imports

All imports below are from the published google-adk package — no test-internal helpers required.

python

import pytest
from google.genai import types
from google.adk import Workflow
from google.adk.agents import LlmAgent
from google.adk.apps import App
from google.adk.apps.app import ResumabilityConfig
from google.adk.events import Event, RequestInput
from google.adk.runners import InMemoryRunner

A small `run` helper

Tests are tidier with a helper that drives one turn and collects events:

python

async def run(agent, text="hi", app_name="test_app"):
    runner = InMemoryRunner(agent=agent, app_name=app_name)
    session = await runner.session_service.create_session(
        app_name=app_name, user_id="u1"
    )
    msg = types.Content(role="user", parts=[types.Part(text=text)])
    events = []
    async for event in runner.run_async(
        user_id="u1", session_id=session.id, new_message=msg,
    ):
        events.append(event)
    return runner, session, events


def node_name(event):
    """Extract the node name from event.node_info.path.

    e.g. 'workflow@1/step@1' -> 'step'.
    """
    if not event.node_info:
        return None
    return event.node_info.path.split("/")[-1].split("@")[0]

In ADK 2.x, event.author is the enclosing workflow's name; the per-node identifier lives in event.node_info.path. Use node_name(event) to filter by the node that emitted an event.

Basic Workflow Test

python

async def test_simple_workflow():
    def step_one(node_input: str) -> str:
        return "step 1 done"

    def step_two(node_input: str) -> str:
        return "step 2 done"

    agent = Workflow(
        name="test_workflow",
        edges=[
            ("START", step_one),
            (step_one, step_two),
        ],
    )

    _, _, events = await run(agent)
    final = [e for e in events if node_name(e) == "step_two" and e.output][-1]
    assert final.output == "step 2 done"

Testing Conditional Routing

python

async def test_routing():
    def router(node_input: str):
        if "error" in node_input:
            return Event(output=node_input, route="error")
        return Event(output=node_input, route="success")

    def success_handler(node_input: str) -> str:
        return f"OK: {node_input}"

    def error_handler(node_input: str) -> str:
        return f"ERR: {node_input}"

    agent = Workflow(
        name="routing_test",
        edges=[
            ("START", router),
            (router, {"success": success_handler, "error": error_handler}),
        ],
    )

    _, _, evs_ok = await run(agent, text="all good")
    assert any(node_name(e) == "success_handler" for e in evs_ok)

    _, _, evs_err = await run(agent, text="error case")
    assert any(node_name(e) == "error_handler" for e in evs_err)

Testing HITL (Pause and Resume)

python

async def test_hitl_workflow():
    async def ask_user(ctx, node_input: str):
        yield RequestInput(message="Approve?", interrupt_id="ask")

    def after_approval(node_input) -> str:
        return f"Approved: {node_input}"

    agent = Workflow(
        name="hitl_test",
        edges=[
            ("START", ask_user),
            (ask_user, after_approval),
        ],
    )

    app = App(
        name="hitl_test_app",
        root_agent=agent,
        resumability_config=ResumabilityConfig(is_resumable=True),
    )
    runner = InMemoryRunner(app=app)
    session = await runner.session_service.create_session(
        app_name="hitl_test_app", user_id="u1"
    )

    # First turn: should pause with a RequestInput function call
    msg = types.Content(role="user", parts=[types.Part(text="start")])
    pause_events = []
    async for event in runner.run_async(
        user_id="u1", session_id=session.id, new_message=msg,
    ):
        pause_events.append(event)

    fc_events = [e for e in pause_events if e.get_function_calls()]
    assert fc_events, "expected an interrupt function call"
    fc = fc_events[-1].get_function_calls()[0]

    # Resume by responding to the function call
    response = types.Content(
        role="user",
        parts=[types.Part(function_response=types.FunctionResponse(
            id=fc.id, name=fc.name, response={"result": "yes"},
        ))],
    )
    resumed = []
    async for event in runner.run_async(
        user_id="u1", session_id=session.id, new_message=response,
    ):
        resumed.append(event)

    final = [e for e in resumed if node_name(e) == "after_approval"][-1]
    assert final.output == "Approved: yes"

Testing State Updates

Prefer asserting on the post-run session's state rather than reading state mid-flight:

python

async def test_state_management():
    def writer(node_input: str):
        return Event(output=node_input, state={"counter": 1})

    def reader(ctx, node_input):
        return f"counter={ctx.state['counter']}"

    agent = Workflow(
        name="state_test",
        edges=[("START", writer, reader)],
    )

    runner, session, events = await run(agent)
    final = [e for e in events if node_name(e) == "reader" and e.output][-1]
    assert final.output == "counter=1"

    # Or read state directly off the session after the run
    final_session = await runner.session_service.get_session(
        app_name="test_app", user_id="u1", session_id=session.id
    )
    assert final_session.state["counter"] == 1

Testing Parallel Execution

python

from google.adk.workflow import node

async def test_parallel_worker():
    def produce(node_input: str) -> list:
        return [1, 2, 3]

    @node(parallel_worker=True)
    def double(node_input: int) -> int:
        return node_input * 2

    def collect(node_input: list) -> str:
        return f"results: {node_input}"

    agent = Workflow(
        name="parallel_test",
        edges=[("START", produce, double, collect)],
    )

    _, _, events = await run(agent)
    final = [e for e in events if node_name(e) == "collect" and e.output][-1]
    assert final.output == "results: [2, 4, 6]"

Mocking LLM Agents

For unit tests that don't hit the real API, pass a fake BaseLlm to the LlmAgent constructor. The framework only requires the abstract generate_content_async method.

python

from google.adk.models.base_llm import BaseLlm
from google.adk.models.llm_response import LlmResponse
from google.genai import types


class FakeLlm(BaseLlm):
    def __init__(self, *, responses: list[str]):
        super().__init__(model="fake")
        self._responses = list(responses)

    async def generate_content_async(self, llm_request, stream=False):
        text = self._responses.pop(0)
        yield LlmResponse(content=types.Content(
            role="model", parts=[types.Part(text=text)],
        ))


async def test_llm_agent_with_fake():
    agent = LlmAgent(
        name="x",
        model=FakeLlm(responses=["ok"]),
        instruction="Help.",
    )
    _, _, events = await run(agent, text="hi")
    final = events[-1]
    assert final.content and final.content.parts[0].text == "ok"

If you only need to assert call shapes, monkeypatch the agent's canonical_model.generate_content_async with a mock instead.

Integration tests with a real model

Tag tests that hit a real model and skip them by default:

python

import os
import pytest

@pytest.fixture(scope="session", autouse=True)
def adk_env():
    if "GOOGLE_API_KEY" not in os.environ:
        pytest.skip("GOOGLE_API_KEY not set; skipping integration tests")
    os.environ.setdefault("GOOGLE_GENAI_USE_VERTEXAI", "FALSE")

@pytest.mark.integration
async def test_real_model():
    ...

Then pytest -m integration to run them, or pytest -m "not integration" to skip.

Testing Tips

Create a fresh InMemoryRunner and session per test — runners hold state and reuse causes cross-test interference.
Use a unique app_name per test (e.g. request.node.name) to avoid collisions across parallel pytest workers.
Assert on event.node_info.path, not event.author. event.author is the enclosing workflow's name; event.node_info.path identifies the exact node that emitted the event.
Use event.is_final_response() to filter for "the agent's final message" events.
For workflows with a JoinNode, make sure every LLM agent feeding into it has output_schema= set — otherwise the join buffer fails JSON serialization in tests that use DatabaseSessionService.
Run with pytest -xvs while iterating (-x stop on first failure, -v verbose, -s show prints) to debug event flow.

Testing Workflow Agents Reference

Testing Workflow Agents Reference

Setup

Imports

A small run helper

Basic Workflow Test

Testing Conditional Routing

Testing HITL (Pause and Resume)

Testing State Updates

Testing Parallel Execution

Mocking LLM Agents

Integration tests with a real model

Testing Tips

A small `run` helper