ag2-testing
Skill252 starsChanged 6 months agoApache-2.0View on GitHub
Test AG2 beta agents and tools without hitting a real LLM provider. Pass `TestConfig(...)` from `autogen.beta.testing` as the agent's config (or per-`ask`) to mock LLM responses, inject `ToolCallEvent`s to simulate tool execution, and assert success / error paths. Use when the user is writing pytest tests for an Agent or Tool.
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We split this skill into the rules it gives an agent
3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 55
If a tool raises, the exception propagates to ask():
- Very specific: line 75
If the LLM calls a tool the agent doesn't have, the framework raises ToolNotFoundError:
- Very specific: line 133
Test markers / async config — repo pyproject.toml.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Testing agents and tools
When to use
Writing tests for code that builds AG2 beta Agents, custom @tool functions, middleware, or response schemas — anywhere you don't want to make real LLM API calls.
60-second recipe — mock an LLM response
import pytest
from autogen.beta import Agent
from autogen.beta.testing import TestConfig
@pytest.mark.asyncio
async def test_mocked_response():
agent = Agent("test_agent")
reply = await agent.ask("Hi!", config=TestConfig("This is a mocked response."))
assert reply.body == "This is a mocked response."TestConfig(*responses) replaces the model client. Each positional arg is the mocked response for the next sequential turn — strings for text replies, ToolCallEvent for tool dispatches.
Simulate a successful tool call
Pass a ToolCallEvent first (the model "decides" to call the tool), then the final answer:
import pytest
from autogen.beta import Agent
from autogen.beta.events import ToolCallEvent
from autogen.beta.testing import TestConfig
@pytest.mark.asyncio
async def test_tool_success():
def my_tool() -> str:
return "tool execution result"
agent = Agent("test_agent", tools=[my_tool])
config = TestConfig(
ToolCallEvent(name="my_tool"),
"final result",
)
reply = await agent.ask("Please use my_tool", config=config)
assert reply.body == "final result"Test tool error paths
If a tool raises, the exception propagates to ask():
@pytest.mark.asyncio
async def test_tool_raises():
def failing_tool() -> str:
raise ValueError("Something went wrong")
config = TestConfig(
ToolCallEvent(name="failing_tool"),
"result",
)
agent = Agent("test_agent", config=config, tools=[failing_tool])
with pytest.raises(ValueError, match="Something went wrong"):
await agent.ask("Hi!")Tool not found
If the LLM calls a tool the agent doesn't have, the framework raises ToolNotFoundError:
from autogen.beta.exceptions import ToolNotFoundError
@pytest.mark.asyncio
async def test_tool_not_found():
config = TestConfig(ToolCallEvent(name="unregistered_tool"))
agent = Agent("test_agent", config=config)
with pytest.raises(ToolNotFoundError, match="Tool `unregistered_tool` not found"):
await agent.ask("Hi!")Useful test patterns
Override Depends dependencies
def get_production_db():
raise Exception("Do not call in tests!")
@tool
def read_data(db: Annotated[object, Depends(get_production_db)]) -> str:
return "Data"
agent = Agent("test", tools=[read_data])
agent.dependency_provider.override(get_production_db, lambda: "mock_db")Override Inject dependencies
Just pass dependencies={...} to agent.ask(...):
await agent.ask("Read", dependencies={"database_pool": fake_pool})Capture stream events
from autogen.beta import MemoryStream
from autogen.beta.events import ToolCallEvent
stream = MemoryStream()
collected: list[ToolCallEvent] = []
stream.where(ToolCallEvent).subscribe(lambda e: collected.append(e))
await agent.ask("Test", stream=stream)
assert collected[0].name == "expected_tool"Multi-turn mock
Each positional arg in TestConfig(...) corresponds to one model response. For a multi-turn test, supply enough responses for each turn the test exercises.
Going deeper
- Source doc:
website/docs/beta/testing.mdx. - Test markers / async config — repo
pyproject.toml. Use@pytest.mark.asyncio(the project uses pytest-asyncio). - Streams (for asserting events):
website/docs/beta/advanced/stream.mdx.
Common pitfalls
- Forgetting
@pytest.mark.asyncio— the test will skip or fail oddly. - Mismatched response count —
TestConfigruns out of responses if the agent makes more LLM calls than you expect (e.g. tool error → another LLM call). Add more positional args or assert that the call sequence is what you intended. - Mocking the LLM but not the tool — your tool function still runs (and may hit real APIs / disk). Mock the tool if you're isolating LLM behaviour, or override its
Dependsto inject test doubles. - Asserting on
reply.bodywhen you set aresponse_schema—bodyis the raw text. Useawait reply.content()for the validated value. - Sharing
Agentinstances across async tests — agents carry mutable state (variables, dependencies). Construct fresh agents per test for isolation. - Using real provider clients in CI — wrap the provider config with
TestConfigper-test or via a fixture; never rely onOPENAI_API_KEYetc. being available in test environments.
In this repository15 other files it gives its agents.
- ag2-add-custom-toolSkill
- ag2-ag-uiSkill
- ag2-hitlSkill
- ag2-knowledge-and-memorySkill
- ag2-middlewareSkill
- ag2-multimodal-inputSkill
- ag2-observers-and-alertsSkill
- ag2-overviewSkill
- ag2-quickstartSkill
- ag2-shell-toolSkill
- ag2-structured-outputSkill
- ag2-subagent-delegationSkill
- ag2-telemetrySkill
- ag2-use-builtin-toolsSkill
- calculatorSkill
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