ec2b666284
Continuous Integration / Pre-commit Linter (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.10) (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.11) (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.12) (push) Has been cancelled
Continuous Integration / Mypy Check (Python 3.13) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.10) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.11) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.12) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.13) (push) Has been cancelled
Continuous Integration / Unit Tests (Python 3.14) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.10) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.11) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.12) (push) Has been cancelled
Copybara PR Handler / close-imported-pr (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.13) (push) Has been cancelled
Continuous Integration / A2A v0.3 Tests (Python 3.14) (push) Has been cancelled
435 lines
13 KiB
Python
435 lines
13 KiB
Python
# Copyright 2026 Google LLC
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
"""Unit tests for LlmAgent include_contents field behavior."""
|
|
|
|
from google.adk.agents.llm_agent import LlmAgent
|
|
from google.adk.agents.run_config import RunConfig
|
|
from google.adk.agents.sequential_agent import SequentialAgent
|
|
from google.genai import types
|
|
import pytest
|
|
|
|
from .. import testing_utils
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_include_contents_default_behavior():
|
|
"""Test that include_contents='default' preserves conversation history including tool interactions."""
|
|
|
|
def simple_tool(message: str) -> dict:
|
|
return {"result": f"Tool processed: {message}"}
|
|
|
|
mock_model = testing_utils.MockModel.create(
|
|
responses=[
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "first"}
|
|
),
|
|
"First response",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "second"}
|
|
),
|
|
"Second response",
|
|
]
|
|
)
|
|
|
|
agent = LlmAgent(
|
|
name="test_agent",
|
|
model=mock_model,
|
|
include_contents="default",
|
|
instruction="You are a helpful assistant",
|
|
tools=[simple_tool],
|
|
)
|
|
|
|
runner = testing_utils.InMemoryRunner(agent)
|
|
runner.run("First message")
|
|
runner.run("Second message")
|
|
|
|
# First turn requests
|
|
assert testing_utils.simplify_contents(mock_model.requests[0].contents) == [
|
|
("user", "First message")
|
|
]
|
|
|
|
assert testing_utils.simplify_contents(mock_model.requests[1].contents) == [
|
|
("user", "First message"),
|
|
(
|
|
"model",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "first"}
|
|
),
|
|
),
|
|
(
|
|
"user",
|
|
types.Part.from_function_response(
|
|
name="simple_tool", response={"result": "Tool processed: first"}
|
|
),
|
|
),
|
|
]
|
|
|
|
# Second turn should include full conversation history
|
|
assert testing_utils.simplify_contents(mock_model.requests[2].contents) == [
|
|
("user", "First message"),
|
|
(
|
|
"model",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "first"}
|
|
),
|
|
),
|
|
(
|
|
"user",
|
|
types.Part.from_function_response(
|
|
name="simple_tool", response={"result": "Tool processed: first"}
|
|
),
|
|
),
|
|
("model", "First response"),
|
|
("user", "Second message"),
|
|
]
|
|
|
|
# Second turn with tool should include full history + current tool interaction
|
|
assert testing_utils.simplify_contents(mock_model.requests[3].contents) == [
|
|
("user", "First message"),
|
|
(
|
|
"model",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "first"}
|
|
),
|
|
),
|
|
(
|
|
"user",
|
|
types.Part.from_function_response(
|
|
name="simple_tool", response={"result": "Tool processed: first"}
|
|
),
|
|
),
|
|
("model", "First response"),
|
|
("user", "Second message"),
|
|
(
|
|
"model",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "second"}
|
|
),
|
|
),
|
|
(
|
|
"user",
|
|
types.Part.from_function_response(
|
|
name="simple_tool", response={"result": "Tool processed: second"}
|
|
),
|
|
),
|
|
]
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_include_contents_none_behavior():
|
|
"""Test that include_contents='none' excludes conversation history but includes current input."""
|
|
|
|
def simple_tool(message: str) -> dict:
|
|
return {"result": f"Tool processed: {message}"}
|
|
|
|
mock_model = testing_utils.MockModel.create(
|
|
responses=[
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "first"}
|
|
),
|
|
"First response",
|
|
"Second response",
|
|
]
|
|
)
|
|
|
|
agent = LlmAgent(
|
|
name="test_agent",
|
|
model=mock_model,
|
|
include_contents="none",
|
|
instruction="You are a helpful assistant",
|
|
tools=[simple_tool],
|
|
)
|
|
|
|
runner = testing_utils.InMemoryRunner(agent)
|
|
runner.run("First message")
|
|
runner.run("Second message")
|
|
|
|
# First turn behavior
|
|
assert testing_utils.simplify_contents(mock_model.requests[0].contents) == [
|
|
("user", "First message")
|
|
]
|
|
|
|
assert testing_utils.simplify_contents(mock_model.requests[1].contents) == [
|
|
("user", "First message"),
|
|
(
|
|
"model",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "first"}
|
|
),
|
|
),
|
|
(
|
|
"user",
|
|
types.Part.from_function_response(
|
|
name="simple_tool", response={"result": "Tool processed: first"}
|
|
),
|
|
),
|
|
]
|
|
|
|
# Second turn should only have current input, no history
|
|
assert testing_utils.simplify_contents(mock_model.requests[2].contents) == [
|
|
("user", "Second message")
|
|
]
|
|
|
|
# System instruction and tools should be preserved
|
|
assert (
|
|
"You are a helpful assistant"
|
|
in mock_model.requests[0].config.system_instruction
|
|
)
|
|
assert len(mock_model.requests[0].config.tools) > 0
|
|
|
|
|
|
def test_model_input_context_is_sent_to_model_without_persisting_to_session():
|
|
mock_model = testing_utils.MockModel.create(responses=["Answer"])
|
|
agent = LlmAgent(name="test_agent", model=mock_model)
|
|
runner = testing_utils.InMemoryRunner(agent)
|
|
session = runner.session
|
|
|
|
list(
|
|
runner.runner.run(
|
|
user_id=session.user_id,
|
|
session_id=session.id,
|
|
new_message=testing_utils.get_user_content("Question"),
|
|
run_config=RunConfig(
|
|
model_input_context=[
|
|
types.UserContent("Relevant context for this turn")
|
|
]
|
|
),
|
|
)
|
|
)
|
|
|
|
assert testing_utils.simplify_contents(mock_model.requests[0].contents) == [
|
|
("user", "Relevant context for this turn"),
|
|
("user", "Question"),
|
|
]
|
|
assert testing_utils.simplify_events(runner.session.events) == [
|
|
("user", "Question"),
|
|
("test_agent", "Answer"),
|
|
]
|
|
|
|
|
|
def test_model_input_context_stays_before_user_message_after_tool_call():
|
|
def simple_tool(message: str) -> dict:
|
|
return {"result": f"Tool processed: {message}"}
|
|
|
|
mock_model = testing_utils.MockModel.create(
|
|
responses=[
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "payload"}
|
|
),
|
|
"Answer",
|
|
]
|
|
)
|
|
agent = LlmAgent(name="test_agent", model=mock_model, tools=[simple_tool])
|
|
runner = testing_utils.InMemoryRunner(agent)
|
|
session = runner.session
|
|
|
|
list(
|
|
runner.runner.run(
|
|
user_id=session.user_id,
|
|
session_id=session.id,
|
|
new_message=testing_utils.get_user_content("Question"),
|
|
run_config=RunConfig(
|
|
model_input_context=[
|
|
types.UserContent("Relevant context for this turn")
|
|
]
|
|
),
|
|
)
|
|
)
|
|
|
|
assert testing_utils.simplify_contents(mock_model.requests[0].contents) == [
|
|
("user", "Relevant context for this turn"),
|
|
("user", "Question"),
|
|
]
|
|
assert testing_utils.simplify_contents(mock_model.requests[1].contents) == [
|
|
("user", "Relevant context for this turn"),
|
|
("user", "Question"),
|
|
(
|
|
"model",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "payload"}
|
|
),
|
|
),
|
|
(
|
|
"user",
|
|
types.Part.from_function_response(
|
|
name="simple_tool",
|
|
response={"result": "Tool processed: payload"},
|
|
),
|
|
),
|
|
]
|
|
assert testing_utils.simplify_events(runner.session.events) == [
|
|
("user", "Question"),
|
|
(
|
|
"test_agent",
|
|
types.Part.from_function_call(
|
|
name="simple_tool", args={"message": "payload"}
|
|
),
|
|
),
|
|
(
|
|
"test_agent",
|
|
types.Part.from_function_response(
|
|
name="simple_tool",
|
|
response={"result": "Tool processed: payload"},
|
|
),
|
|
),
|
|
("test_agent", "Answer"),
|
|
]
|
|
|
|
|
|
def test_model_input_context_with_include_contents_none_sub_agent():
|
|
agent1_model = testing_utils.MockModel.create(
|
|
responses=["Agent1 response: XYZ"]
|
|
)
|
|
agent1 = LlmAgent(name="agent1", model=agent1_model)
|
|
|
|
agent2_model = testing_utils.MockModel.create(
|
|
responses=["Agent2 final response"]
|
|
)
|
|
agent2 = LlmAgent(
|
|
name="agent2",
|
|
model=agent2_model,
|
|
include_contents="none",
|
|
)
|
|
sequential_agent = SequentialAgent(
|
|
name="sequential_test_agent", sub_agents=[agent1, agent2]
|
|
)
|
|
runner = testing_utils.InMemoryRunner(sequential_agent)
|
|
session = runner.session
|
|
|
|
list(
|
|
runner.runner.run(
|
|
user_id=session.user_id,
|
|
session_id=session.id,
|
|
new_message=testing_utils.get_user_content("Original user request"),
|
|
run_config=RunConfig(
|
|
model_input_context=[
|
|
types.UserContent("Relevant context for this turn")
|
|
]
|
|
),
|
|
)
|
|
)
|
|
|
|
assert testing_utils.simplify_contents(agent1_model.requests[0].contents) == [
|
|
("user", "Relevant context for this turn"),
|
|
("user", "Original user request"),
|
|
]
|
|
assert testing_utils.simplify_contents(agent2_model.requests[0].contents) == [
|
|
("user", "Relevant context for this turn"),
|
|
(
|
|
"user",
|
|
[
|
|
types.Part(text="For context:"),
|
|
types.Part(text="[agent1] said: Agent1 response: XYZ"),
|
|
],
|
|
),
|
|
]
|
|
|
|
|
|
def test_model_input_context_without_user_message_is_prepended_before_history():
|
|
mock_model = testing_utils.MockModel.create(
|
|
responses=["First answer", "Second answer"]
|
|
)
|
|
agent = LlmAgent(name="test_agent", model=mock_model)
|
|
runner = testing_utils.InMemoryRunner(agent)
|
|
session = runner.session
|
|
|
|
list(
|
|
runner.runner.run(
|
|
user_id=session.user_id,
|
|
session_id=session.id,
|
|
new_message=testing_utils.get_user_content("First question"),
|
|
)
|
|
)
|
|
# No new_message, so the invocation has no user content to anchor before
|
|
# (e.g. live mode or a re-run over existing history). The transient context
|
|
# falls back to the front of the request, before all prior history.
|
|
list(
|
|
runner.runner.run(
|
|
user_id=session.user_id,
|
|
session_id=session.id,
|
|
new_message=None,
|
|
run_config=RunConfig(
|
|
model_input_context=[
|
|
types.UserContent("Relevant context for this turn")
|
|
]
|
|
),
|
|
)
|
|
)
|
|
|
|
assert testing_utils.simplify_contents(mock_model.requests[1].contents) == [
|
|
("user", "Relevant context for this turn"),
|
|
("user", "First question"),
|
|
("model", "First answer"),
|
|
]
|
|
assert testing_utils.simplify_events(runner.session.events) == [
|
|
("user", "First question"),
|
|
("test_agent", "First answer"),
|
|
("test_agent", "Second answer"),
|
|
]
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_include_contents_none_sequential_agents():
|
|
"""Test include_contents='none' with sequential agents."""
|
|
|
|
agent1_model = testing_utils.MockModel.create(
|
|
responses=["Agent1 response: XYZ"]
|
|
)
|
|
agent1 = LlmAgent(
|
|
name="agent1",
|
|
model=agent1_model,
|
|
instruction="You are Agent1",
|
|
)
|
|
|
|
agent2_model = testing_utils.MockModel.create(
|
|
responses=["Agent2 final response"]
|
|
)
|
|
agent2 = LlmAgent(
|
|
name="agent2",
|
|
model=agent2_model,
|
|
include_contents="none",
|
|
instruction="You are Agent2",
|
|
)
|
|
|
|
sequential_agent = SequentialAgent(
|
|
name="sequential_test_agent", sub_agents=[agent1, agent2]
|
|
)
|
|
|
|
runner = testing_utils.InMemoryRunner(sequential_agent)
|
|
events = runner.run("Original user request")
|
|
|
|
simplified_events = [event for event in events if event.content]
|
|
assert len(simplified_events) == 2
|
|
assert "Agent1 response" in str(simplified_events[0].content)
|
|
assert "Agent2 final response" in str(simplified_events[1].content)
|
|
|
|
# Agent1 sees original user request
|
|
agent1_contents = testing_utils.simplify_contents(
|
|
agent1_model.requests[0].contents
|
|
)
|
|
assert ("user", "Original user request") in agent1_contents
|
|
|
|
# Agent2 with include_contents='none' should not see original request
|
|
agent2_contents = testing_utils.simplify_contents(
|
|
agent2_model.requests[0].contents
|
|
)
|
|
|
|
assert not any(
|
|
"Original user request" in str(content) for _, content in agent2_contents
|
|
)
|
|
assert any(
|
|
"Agent1 response" in str(content) for _, content in agent2_contents
|
|
)
|