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# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# 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.
import os
import tempfile
import unittest
import uuid
from contextlib import nullcontext as does_not_raise
from pathlib import Path
from unittest.mock import MagicMock
import pytest
from transformers.testing_utils import get_tests_dir
from smolagents.agent_types import AgentImage, AgentText
from smolagents.agents import (
AgentMaxStepsError,
CodeAgent,
MultiStepAgent,
ToolCall,
ToolCallingAgent,
populate_template,
)
from smolagents.default_tools import DuckDuckGoSearchTool, FinalAnswerTool, PythonInterpreterTool, VisitWebpageTool
from smolagents.memory import PlanningStep
from smolagents.models import (
ChatMessage,
ChatMessageToolCall,
ChatMessageToolCallDefinition,
HfApiModel,
MessageRole,
TransformersModel,
)
from smolagents.tools import Tool, tool
from smolagents.utils import BASE_BUILTIN_MODULES
def get_new_path(suffix="") -> str:
directory = tempfile.mkdtemp()
return os.path.join(directory, str(uuid.uuid4()) + suffix)
class FakeToolCallModel:
def __call__(self, messages, tools_to_call_from=None, stop_sequences=None, grammar=None):
if len(messages) < 3:
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_0",
type="function",
function=ChatMessageToolCallDefinition(
name="python_interpreter", arguments={"code": "2*3.6452"}
),
)
],
)
else:
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_1",
type="function",
function=ChatMessageToolCallDefinition(name="final_answer", arguments={"answer": "7.2904"}),
)
],
)
class FakeToolCallModelImage:
def __call__(self, messages, tools_to_call_from=None, stop_sequences=None, grammar=None):
if len(messages) < 3:
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_0",
type="function",
function=ChatMessageToolCallDefinition(
name="fake_image_generation_tool",
arguments={"prompt": "An image of a cat"},
),
)
],
)
else:
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_1",
type="function",
function=ChatMessageToolCallDefinition(name="final_answer", arguments="image.png"),
)
],
)
class FakeToolCallModelVL:
def __call__(self, messages, tools_to_call_from=None, stop_sequences=None, grammar=None):
if len(messages) < 3:
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_0",
type="function",
function=ChatMessageToolCallDefinition(
name="fake_image_understanding_tool",
arguments={
"prompt": "What is in this image?",
"image": "image.png",
},
),
)
],
)
else:
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_1",
type="function",
function=ChatMessageToolCallDefinition(name="final_answer", arguments="The image is a cat."),
)
],
)
def fake_code_model(messages, stop_sequences=None, grammar=None) -> str:
prompt = str(messages)
if "special_marker" not in prompt:
return ChatMessage(
role="assistant",
content="""
Thought: I should multiply 2 by 3.6452. special_marker
Code:
```py
result = 2**3.6452
```<end_code>
""",
)
else: # We're at step 2
return ChatMessage(
role="assistant",
content="""
Thought: I can now answer the initial question
Code:
```py
final_answer(7.2904)
```<end_code>
""",
)
def fake_code_model_error(messages, stop_sequences=None) -> str:
prompt = str(messages)
if "special_marker" not in prompt:
return ChatMessage(
role="assistant",
content="""
Thought: I should multiply 2 by 3.6452. special_marker
Code:
```py
print("Flag!")
def error_function():
raise ValueError("error")
error_function()
```<end_code>
""",
)
else: # We're at step 2
return ChatMessage(
role="assistant",
content="""
Thought: I faced an error in the previous step.
Code:
```py
final_answer("got an error")
```<end_code>
""",
)
def fake_code_model_syntax_error(messages, stop_sequences=None) -> str:
prompt = str(messages)
if "special_marker" not in prompt:
return ChatMessage(
role="assistant",
content="""
Thought: I should multiply 2 by 3.6452. special_marker
Code:
```py
a = 2
b = a * 2
print("Failing due to unexpected indent")
print("Ok, calculation done!")
```<end_code>
""",
)
else: # We're at step 2
return ChatMessage(
role="assistant",
content="""
Thought: I can now answer the initial question
Code:
```py
final_answer("got an error")
```<end_code>
""",
)
def fake_code_model_import(messages, stop_sequences=None) -> str:
return ChatMessage(
role="assistant",
content="""
Thought: I can answer the question
Code:
```py
import numpy as np
final_answer("got an error")
```<end_code>
""",
)
def fake_code_functiondef(messages, stop_sequences=None) -> str:
prompt = str(messages)
if "special_marker" not in prompt:
return ChatMessage(
role="assistant",
content="""
Thought: Let's define the function. special_marker
Code:
```py
import numpy as np
def moving_average(x, w):
return np.convolve(x, np.ones(w), 'valid') / w
```<end_code>
""",
)
else: # We're at step 2
return ChatMessage(
role="assistant",
content="""
Thought: I can now answer the initial question
Code:
```py
x, w = [0, 1, 2, 3, 4, 5], 2
res = moving_average(x, w)
final_answer(res)
```<end_code>
""",
)
def fake_code_model_single_step(messages, stop_sequences=None, grammar=None) -> str:
return ChatMessage(
role="assistant",
content="""
Thought: I should multiply 2 by 3.6452. special_marker
Code:
```py
result = python_interpreter(code="2*3.6452")
final_answer(result)
```
""",
)
def fake_code_model_no_return(messages, stop_sequences=None, grammar=None) -> str:
return ChatMessage(
role="assistant",
content="""
Thought: I should multiply 2 by 3.6452. special_marker
Code:
```py
result = python_interpreter(code="2*3.6452")
print(result)
```
""",
)
class AgentTests(unittest.TestCase):
def test_fake_toolcalling_agent(self):
agent = ToolCallingAgent(tools=[PythonInterpreterTool()], model=FakeToolCallModel())
output = agent.run("What is 2 multiplied by 3.6452?")
assert isinstance(output, str)
assert "7.2904" in output
assert agent.memory.steps[0].task == "What is 2 multiplied by 3.6452?"
assert "7.2904" in agent.memory.steps[1].observations
assert agent.memory.steps[2].model_output is None
def test_toolcalling_agent_handles_image_tool_outputs(self):
from PIL import Image
@tool
def fake_image_generation_tool(prompt: str) -> Image.Image:
"""Tool that generates an image.
Args:
prompt: The prompt
"""
return Image.open(Path(get_tests_dir("fixtures")) / "000000039769.png")
agent = ToolCallingAgent(tools=[fake_image_generation_tool], model=FakeToolCallModelImage())
output = agent.run("Make me an image.")
assert isinstance(output, AgentImage)
assert isinstance(agent.state["image.png"], Image.Image)
def test_toolcalling_agent_handles_image_inputs(self):
from PIL import Image
image = Image.open(Path(get_tests_dir("fixtures")) / "000000039769.png") # dummy input
@tool
def fake_image_understanding_tool(prompt: str, image: Image.Image) -> str:
"""Tool that creates a caption for an image.
Args:
prompt: The prompt
image: The image
"""
return "The image is a cat."
agent = ToolCallingAgent(tools=[fake_image_understanding_tool], model=FakeToolCallModelVL())
output = agent.run("Caption this image.", images=[image])
assert output == "The image is a cat."
def test_fake_code_agent(self):
agent = CodeAgent(tools=[PythonInterpreterTool()], model=fake_code_model)
output = agent.run("What is 2 multiplied by 3.6452?")
assert isinstance(output, float)
assert output == 7.2904
assert agent.memory.steps[0].task == "What is 2 multiplied by 3.6452?"
assert agent.memory.steps[2].tool_calls == [
ToolCall(name="python_interpreter", arguments="final_answer(7.2904)", id="call_2")
]
def test_additional_args_added_to_task(self):
agent = CodeAgent(tools=[], model=fake_code_model)
agent.run(
"What is 2 multiplied by 3.6452?",
additional_args={"instruction": "Remember this."},
)
assert "Remember this" in agent.task
assert "Remember this" in str(agent.input_messages)
def test_reset_conversations(self):
agent = CodeAgent(tools=[PythonInterpreterTool()], model=fake_code_model)
output = agent.run("What is 2 multiplied by 3.6452?", reset=True)
assert output == 7.2904
assert len(agent.memory.steps) == 3
output = agent.run("What is 2 multiplied by 3.6452?", reset=False)
assert output == 7.2904
assert len(agent.memory.steps) == 5
output = agent.run("What is 2 multiplied by 3.6452?", reset=True)
assert output == 7.2904
assert len(agent.memory.steps) == 3
def test_code_agent_code_errors_show_offending_line_and_error(self):
agent = CodeAgent(tools=[PythonInterpreterTool()], model=fake_code_model_error)
output = agent.run("What is 2 multiplied by 3.6452?")
assert isinstance(output, AgentText)
assert output == "got an error"
assert "Code execution failed at line 'error_function()'" in str(agent.memory.steps[1].error)
assert "ValueError" in str(agent.memory.steps)
def test_code_agent_code_error_saves_previous_print_outputs(self):
agent = CodeAgent(tools=[PythonInterpreterTool()], model=fake_code_model_error, verbosity_level=10)
agent.run("What is 2 multiplied by 3.6452?")
assert "Flag!" in str(agent.memory.steps[1].observations)
def test_code_agent_syntax_error_show_offending_lines(self):
agent = CodeAgent(tools=[PythonInterpreterTool()], model=fake_code_model_syntax_error)
output = agent.run("What is 2 multiplied by 3.6452?")
assert isinstance(output, AgentText)
assert output == "got an error"
assert ' print("Failing due to unexpected indent")' in str(agent.memory.steps)
def test_setup_agent_with_empty_toolbox(self):
ToolCallingAgent(model=FakeToolCallModel(), tools=[])
def test_fails_max_steps(self):
agent = CodeAgent(
tools=[PythonInterpreterTool()],
model=fake_code_model_no_return, # use this callable because it never ends
max_steps=5,
)
answer = agent.run("What is 2 multiplied by 3.6452?")
assert len(agent.memory.steps) == 7 # Task step + 5 action steps + Final answer
assert type(agent.memory.steps[-1].error) is AgentMaxStepsError
assert isinstance(answer, str)
agent = CodeAgent(
tools=[PythonInterpreterTool()],
model=fake_code_model_no_return, # use this callable because it never ends
max_steps=5,
)
answer = agent.run("What is 2 multiplied by 3.6452?", max_steps=3)
assert len(agent.memory.steps) == 5 # Task step + 3 action steps + Final answer
assert type(agent.memory.steps[-1].error) is AgentMaxStepsError
assert isinstance(answer, str)
def test_tool_descriptions_get_baked_in_system_prompt(self):
tool = PythonInterpreterTool()
tool.name = "fake_tool_name"
tool.description = "fake_tool_description"
agent = CodeAgent(tools=[tool], model=fake_code_model)
agent.run("Empty task")
assert tool.name in agent.system_prompt
assert tool.description in agent.system_prompt
def test_module_imports_get_baked_in_system_prompt(self):
agent = CodeAgent(tools=[], model=fake_code_model)
agent.run("Empty task")
for module in BASE_BUILTIN_MODULES:
assert module in agent.system_prompt
def test_init_agent_with_different_toolsets(self):
toolset_1 = []
agent = CodeAgent(tools=toolset_1, model=fake_code_model)
assert len(agent.tools) == 1 # when no tools are provided, only the final_answer tool is added by default
toolset_2 = [PythonInterpreterTool(), PythonInterpreterTool()]
with pytest.raises(ValueError) as e:
agent = CodeAgent(tools=toolset_2, model=fake_code_model)
assert "Each tool or managed_agent should have a unique name!" in str(e)
with pytest.raises(ValueError) as e:
agent.name = "python_interpreter"
agent.description = "empty"
CodeAgent(tools=[PythonInterpreterTool()], model=fake_code_model, managed_agents=[agent])
assert "Each tool or managed_agent should have a unique name!" in str(e)
# check that python_interpreter base tool does not get added to CodeAgent
agent = CodeAgent(tools=[], model=fake_code_model, add_base_tools=True)
assert len(agent.tools) == 3 # added final_answer tool + search + visit_webpage
# check that python_interpreter base tool gets added to ToolCallingAgent
agent = ToolCallingAgent(tools=[], model=fake_code_model, add_base_tools=True)
assert len(agent.tools) == 4 # added final_answer tool + search + visit_webpage
def test_function_persistence_across_steps(self):
agent = CodeAgent(
tools=[],
model=fake_code_functiondef,
max_steps=2,
additional_authorized_imports=["numpy"],
)
res = agent.run("ok")
assert res[0] == 0.5
def test_init_managed_agent(self):
agent = CodeAgent(tools=[], model=fake_code_functiondef, name="managed_agent", description="Empty")
assert agent.name == "managed_agent"
assert agent.description == "Empty"
def test_agent_description_gets_correctly_inserted_in_system_prompt(self):
managed_agent = CodeAgent(tools=[], model=fake_code_functiondef, name="managed_agent", description="Empty")
manager_agent = CodeAgent(
tools=[],
model=fake_code_functiondef,
managed_agents=[managed_agent],
)
assert "You can also give tasks to team members." not in managed_agent.system_prompt
assert "{{managed_agents_descriptions}}" not in managed_agent.system_prompt
assert "You can also give tasks to team members." in manager_agent.system_prompt
def test_code_agent_missing_import_triggers_advice_in_error_log(self):
# Set explicit verbosity level to 1 to override the default verbosity level of -1 set in CI fixture
agent = CodeAgent(tools=[], model=fake_code_model_import, verbosity_level=1)
with agent.logger.console.capture() as capture:
agent.run("Count to 3")
str_output = capture.get()
assert "`additional_authorized_imports`" in str_output.replace("\n", "")
def test_replay_shows_logs(self):
agent = CodeAgent(
tools=[], model=fake_code_model_import, verbosity_level=0, additional_authorized_imports=["numpy"]
)
agent.run("Count to 3")
with agent.logger.console.capture() as capture:
agent.replay()
str_output = capture.get().replace("\n", "")
assert "New run" in str_output
assert "Agent output:" in str_output
assert 'final_answer("got' in str_output
assert "```<end_code>" in str_output
def test_code_nontrivial_final_answer_works(self):
def fake_code_model_final_answer(messages, stop_sequences=None, grammar=None):
return ChatMessage(
role="assistant",
content="""Code:
```py
def nested_answer():
final_answer("Correct!")
nested_answer()
```<end_code>""",
)
agent = CodeAgent(tools=[], model=fake_code_model_final_answer)
output = agent.run("Count to 3")
assert output == "Correct!"
def test_transformers_toolcalling_agent(self):
@tool
def weather_api(location: str, celsius: bool = False) -> str:
"""
Gets the weather in the next days at given location.
Secretly this tool does not care about the location, it hates the weather everywhere.
Args:
location: the location
celsius: the temperature type
"""
return "The weather is UNGODLY with torrential rains and temperatures below -10°C"
model = TransformersModel(
model_id="HuggingFaceTB/SmolLM2-360M-Instruct",
max_new_tokens=100,
device_map="auto",
do_sample=False,
)
agent = ToolCallingAgent(model=model, tools=[weather_api], max_steps=1)
agent.run("What's the weather in Paris?")
assert agent.memory.steps[0].task == "What's the weather in Paris?"
assert agent.memory.steps[1].tool_calls[0].name == "weather_api"
step_memory_dict = agent.memory.get_succinct_steps()[1]
assert step_memory_dict["model_output_message"].tool_calls[0].function.name == "weather_api"
assert step_memory_dict["model_output_message"].raw["completion_kwargs"]["max_new_tokens"] == 100
assert "model_input_messages" in agent.memory.get_full_steps()[1]
def test_final_answer_checks(self):
def check_always_fails(final_answer, agent_memory):
assert False, "Error raised in check"
agent = CodeAgent(model=fake_code_model, tools=[], final_answer_checks=[check_always_fails])
agent.run("Dummy task.")
assert "Error raised in check" in str(agent.write_memory_to_messages())
class CustomFinalAnswerTool(FinalAnswerTool):
def forward(self, answer) -> str:
return answer + "CUSTOM"
class MockTool(Tool):
def __init__(self, name):
self.name = name
self.description = "Mock tool description"
self.inputs = {}
self.output_type = "string"
def forward(self):
return "Mock tool output"
class MockAgent:
def __init__(self, name, tools, description="Mock agent description"):
self.name = name
self.tools = {t.name: t for t in tools}
self.description = description
class TestMultiStepAgent:
def test_instantiation_disables_logging_to_terminal(self):
fake_model = MagicMock()
agent = MultiStepAgent(tools=[], model=fake_model)
assert agent.logger.level == -1, "logging to terminal should be disabled for testing using a fixture"
def test_instantiation_with_prompt_templates(self, prompt_templates):
agent = MultiStepAgent(tools=[], model=MagicMock(), prompt_templates=prompt_templates)
assert agent.prompt_templates == prompt_templates
assert agent.prompt_templates["system_prompt"] == "This is a test system prompt."
assert "managed_agent" in agent.prompt_templates
assert agent.prompt_templates["managed_agent"]["task"] == "Task for {{name}}: {{task}}"
assert agent.prompt_templates["managed_agent"]["report"] == "Report for {{name}}: {{final_answer}}"
@pytest.mark.parametrize(
"tools, expected_final_answer_tool",
[([], FinalAnswerTool), ([CustomFinalAnswerTool()], CustomFinalAnswerTool)],
)
def test_instantiation_with_final_answer_tool(self, tools, expected_final_answer_tool):
agent = MultiStepAgent(tools=tools, model=MagicMock())
assert "final_answer" in agent.tools
assert isinstance(agent.tools["final_answer"], expected_final_answer_tool)
def test_step_number(self):
fake_model = MagicMock()
fake_model.last_input_token_count = 10
fake_model.last_output_token_count = 20
max_steps = 2
agent = MultiStepAgent(tools=[], model=fake_model, max_steps=max_steps)
assert hasattr(agent, "step_number"), "step_number attribute should be defined"
assert agent.step_number == 0, "step_number should be initialized to 0"
agent.run("Test task")
assert hasattr(agent, "step_number"), "step_number attribute should be defined"
assert agent.step_number == max_steps + 1, "step_number should be max_steps + 1 after run method is called"
@pytest.mark.parametrize(
"step, expected_messages_list",
[
(
1,
[
[{"role": MessageRole.USER, "content": [{"type": "text", "text": "INITIAL_FACTS_USER_PROMPT"}]}],
[{"role": MessageRole.USER, "content": [{"type": "text", "text": "INITIAL_PLAN_USER_PROMPT"}]}],
],
),
(
2,
[
[
{
"role": MessageRole.SYSTEM,
"content": [{"type": "text", "text": "UPDATE_FACTS_SYSTEM_PROMPT"}],
},
{"role": MessageRole.USER, "content": [{"type": "text", "text": "UPDATE_FACTS_USER_PROMPT"}]},
],
[
{
"role": MessageRole.SYSTEM,
"content": [{"type": "text", "text": "UPDATE_PLAN_SYSTEM_PROMPT"}],
},
{"role": MessageRole.USER, "content": [{"type": "text", "text": "UPDATE_PLAN_USER_PROMPT"}]},
],
],
),
],
)
def test_planning_step(self, step, expected_messages_list):
fake_model = MagicMock()
agent = CodeAgent(
tools=[],
model=fake_model,
)
task = "Test task"
agent.planning_step(task, is_first_step=(step == 1), step=step)
expected_message_texts = {
"INITIAL_FACTS_USER_PROMPT": populate_template(
agent.prompt_templates["planning"]["initial_facts"], variables=dict(task=task)
),
"INITIAL_PLAN_USER_PROMPT": populate_template(
agent.prompt_templates["planning"]["initial_plan"],
variables=dict(
task=task,
tools=agent.tools,
managed_agents=agent.managed_agents,
answer_facts=agent.memory.steps[0].model_output_message_facts.content,
),
),
"UPDATE_FACTS_SYSTEM_PROMPT": agent.prompt_templates["planning"]["update_facts_pre_messages"],
"UPDATE_FACTS_USER_PROMPT": agent.prompt_templates["planning"]["update_facts_post_messages"],
"UPDATE_PLAN_SYSTEM_PROMPT": populate_template(
agent.prompt_templates["planning"]["update_plan_pre_messages"], variables=dict(task=task)
),
"UPDATE_PLAN_USER_PROMPT": populate_template(
agent.prompt_templates["planning"]["update_plan_post_messages"],
variables=dict(
task=task,
tools=agent.tools,
managed_agents=agent.managed_agents,
facts_update=agent.memory.steps[0].model_output_message_facts.content,
remaining_steps=agent.max_steps - step,
),
),
}
for expected_messages in expected_messages_list:
for expected_message in expected_messages:
for expected_content in expected_message["content"]:
expected_content["text"] = expected_message_texts[expected_content["text"]]
assert len(agent.memory.steps) == 1
planning_step = agent.memory.steps[0]
assert isinstance(planning_step, PlanningStep)
expected_model_input_messages = expected_messages_list[0]
model_input_messages = planning_step.model_input_messages
assert isinstance(model_input_messages, list)
assert len(model_input_messages) == len(expected_model_input_messages) # 2
for message, expected_message in zip(model_input_messages, expected_model_input_messages):
assert isinstance(message, dict)
assert "role" in message
assert "content" in message
assert message["role"] in MessageRole.__members__.values()
assert message["role"] == expected_message["role"]
assert isinstance(message["content"], list)
assert len(message["content"]) == 1
for content, expected_content in zip(message["content"], expected_message["content"]):
assert content == expected_content
# Test calls to model
assert len(fake_model.call_args_list) == 2
for call_args, expected_messages in zip(fake_model.call_args_list, expected_messages_list):
assert len(call_args.args) == 1
messages = call_args.args[0]
assert isinstance(messages, list)
assert len(messages) == len(expected_messages)
for message, expected_message in zip(messages, expected_messages):
assert isinstance(message, dict)
assert "role" in message
assert "content" in message
assert message["role"] in MessageRole.__members__.values()
assert message["role"] == expected_message["role"]
assert isinstance(message["content"], list)
assert len(message["content"]) == 1
for content, expected_content in zip(message["content"], expected_message["content"]):
assert content == expected_content
@pytest.mark.parametrize(
"images, expected_messages_list",
[
(
None,
[
[
{
"role": MessageRole.SYSTEM,
"content": [{"type": "text", "text": "FINAL_ANSWER_SYSTEM_PROMPT"}],
},
{"role": MessageRole.USER, "content": [{"type": "text", "text": "FINAL_ANSWER_USER_PROMPT"}]},
]
],
),
(
["image1.png"],
[
[
{
"role": MessageRole.SYSTEM,
"content": [{"type": "text", "text": "FINAL_ANSWER_SYSTEM_PROMPT"}, {"type": "image"}],
},
{"role": MessageRole.USER, "content": [{"type": "text", "text": "FINAL_ANSWER_USER_PROMPT"}]},
]
],
),
],
)
def test_provide_final_answer(self, images, expected_messages_list):
fake_model = MagicMock()
fake_model.return_value.content = "Final answer."
agent = CodeAgent(
tools=[],
model=fake_model,
)
task = "Test task"
final_answer = agent.provide_final_answer(task, images=images)
expected_message_texts = {
"FINAL_ANSWER_SYSTEM_PROMPT": agent.prompt_templates["final_answer"]["pre_messages"],
"FINAL_ANSWER_USER_PROMPT": populate_template(
agent.prompt_templates["final_answer"]["post_messages"], variables=dict(task=task)
),
}
for expected_messages in expected_messages_list:
for expected_message in expected_messages:
for expected_content in expected_message["content"]:
if "text" in expected_content:
expected_content["text"] = expected_message_texts[expected_content["text"]]
assert final_answer == "Final answer."
# Test calls to model
assert len(fake_model.call_args_list) == 1
for call_args, expected_messages in zip(fake_model.call_args_list, expected_messages_list):
assert len(call_args.args) == 1
messages = call_args.args[0]
assert isinstance(messages, list)
assert len(messages) == len(expected_messages)
for message, expected_message in zip(messages, expected_messages):
assert isinstance(message, dict)
assert "role" in message
assert "content" in message
assert message["role"] in MessageRole.__members__.values()
assert message["role"] == expected_message["role"]
assert isinstance(message["content"], list)
assert len(message["content"]) == len(expected_message["content"])
for content, expected_content in zip(message["content"], expected_message["content"]):
assert content == expected_content
@pytest.mark.parametrize(
"tools, managed_agents, name, expectation",
[
# Valid case: no duplicates
(
[MockTool("tool1"), MockTool("tool2")],
[MockAgent("agent1", [MockTool("tool3")])],
"test_agent",
does_not_raise(),
),
# Invalid case: duplicate tool names
([MockTool("tool1"), MockTool("tool1")], [], "test_agent", pytest.raises(ValueError)),
# Invalid case: tool name same as managed agent name
(
[MockTool("tool1")],
[MockAgent("tool1", [MockTool("final_answer")])],
"test_agent",
pytest.raises(ValueError),
),
# Valid case: tool name same as managed agent's tool name
([MockTool("tool1")], [MockAgent("agent1", [MockTool("tool1")])], "test_agent", does_not_raise()),
# Invalid case: duplicate managed agent name and managed agent tool name
([MockTool("tool1")], [], "tool1", pytest.raises(ValueError)),
# Valid case: duplicate tool names across managed agents
(
[MockTool("tool1")],
[
MockAgent("agent1", [MockTool("tool2"), MockTool("final_answer")]),
MockAgent("agent2", [MockTool("tool2"), MockTool("final_answer")]),
],
"test_agent",
does_not_raise(),
),
],
)
def test_validate_tools_and_managed_agents(self, tools, managed_agents, name, expectation):
fake_model = MagicMock()
with expectation:
MultiStepAgent(
tools=tools,
model=fake_model,
name=name,
managed_agents=managed_agents,
)
class TestCodeAgent:
@pytest.mark.parametrize("provide_run_summary", [False, True])
def test_call_with_provide_run_summary(self, provide_run_summary):
agent = CodeAgent(tools=[], model=MagicMock(), provide_run_summary=provide_run_summary)
assert agent.provide_run_summary is provide_run_summary
agent.managed_agent_prompt = "Task: {task}"
agent.name = "test_agent"
agent.run = MagicMock(return_value="Test output")
agent.write_memory_to_messages = MagicMock(return_value=[{"content": "Test summary"}])
result = agent("Test request")
expected_summary = "Here is the final answer from your managed agent 'test_agent':\nTest output"
if provide_run_summary:
expected_summary += (
"\n\nFor more detail, find below a summary of this agent's work:\n"
"<summary_of_work>\n\nTest summary\n---\n</summary_of_work>"
)
assert result == expected_summary
def test_errors_logging(self):
def fake_code_model(messages, stop_sequences=None, grammar=None) -> str:
return ChatMessage(role="assistant", content="Code:\n```py\nsecret=3;['1', '2'][secret]\n```")
agent = CodeAgent(tools=[], model=fake_code_model, verbosity_level=1)
with agent.logger.console.capture() as capture:
agent.run("Test request")
assert "secret\\\\" in repr(capture.get())
def test_change_tools_after_init(self):
from smolagents import tool
@tool
def fake_tool_1() -> str:
"""Fake tool"""
return "1"
@tool
def fake_tool_2() -> str:
"""Fake tool"""
return "2"
def fake_code_model(messages, stop_sequences=None, grammar=None) -> str:
return ChatMessage(role="assistant", content="Code:\n```py\nfinal_answer(fake_tool_1())\n```")
agent = CodeAgent(tools=[fake_tool_1], model=fake_code_model)
agent.tools["final_answer"] = CustomFinalAnswerTool()
agent.tools["fake_tool_1"] = fake_tool_2
answer = agent.run("Fake task.")
assert answer == "2CUSTOM"
class MultiAgentsTests(unittest.TestCase):
def test_multiagents_save(self):
model = HfApiModel("Qwen/Qwen2.5-Coder-32B-Instruct", max_tokens=2096, temperature=0.5)
web_agent = ToolCallingAgent(
model=model,
tools=[DuckDuckGoSearchTool(max_results=2), VisitWebpageTool()],
name="web_agent",
description="does web searches",
)
code_agent = CodeAgent(model=model, tools=[], name="useless", description="does nothing in particular")
agent = CodeAgent(
model=model,
tools=[],
additional_authorized_imports=["pandas", "datetime"],
managed_agents=[web_agent, code_agent],
max_print_outputs_length=1000,
executor_type="local",
executor_kwargs={"max_workers": 2},
)
agent.save("agent_export")
expected_structure = {
"managed_agents": {
"useless": {"tools": {"files": ["final_answer.py"]}, "files": ["agent.json", "prompts.yaml"]},
"web_agent": {
"tools": {"files": ["final_answer.py", "visit_webpage.py", "web_search.py"]},
"files": ["agent.json", "prompts.yaml"],
},
},
"tools": {"files": ["final_answer.py"]},
"files": ["app.py", "requirements.txt", "agent.json", "prompts.yaml"],
}
def verify_structure(current_path: Path, structure: dict):
for dir_name, contents in structure.items():
if dir_name != "files":
# For directories, verify they exist and recurse into them
dir_path = current_path / dir_name
assert dir_path.exists(), f"Directory {dir_path} does not exist"
assert dir_path.is_dir(), f"{dir_path} is not a directory"
verify_structure(dir_path, contents)
else:
# For files, verify each exists in the current path
for file_name in contents:
file_path = current_path / file_name
assert file_path.exists(), f"File {file_path} does not exist"
assert file_path.is_file(), f"{file_path} is not a file"
verify_structure(Path("agent_export"), expected_structure)
# Test that re-loaded agents work as expected.
agent2 = CodeAgent.from_folder("agent_export", planning_interval=5)
assert agent2.planning_interval == 5 # Check that kwargs are used
assert set(agent2.authorized_imports) == set(["pandas", "datetime"] + BASE_BUILTIN_MODULES)
assert agent2.max_print_outputs_length == 1000
assert agent2.executor_type == "local"
assert agent2.executor_kwargs == {"max_workers": 2}
assert (
agent2.managed_agents["web_agent"].tools["web_search"].max_results == 10
) # For now tool init parameters are forgotten
assert agent2.model.kwargs["temperature"] == pytest.approx(0.5)
def test_multiagents(self):
class FakeModelMultiagentsManagerAgent:
model_id = "fake_model"
def __call__(
self,
messages,
stop_sequences=None,
grammar=None,
tools_to_call_from=None,
):
if tools_to_call_from is not None:
if len(messages) < 3:
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_0",
type="function",
function=ChatMessageToolCallDefinition(
name="search_agent",
arguments="Who is the current US president?",
),
)
],
)
else:
assert "Report on the current US president" in str(messages)
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_0",
type="function",
function=ChatMessageToolCallDefinition(
name="final_answer", arguments="Final report."
),
)
],
)
else:
if len(messages) < 3:
return ChatMessage(
role="assistant",
content="""
Thought: Let's call our search agent.
Code:
```py
result = search_agent("Who is the current US president?")
```<end_code>
""",
)
else:
assert "Report on the current US president" in str(messages)
return ChatMessage(
role="assistant",
content="""
Thought: Let's return the report.
Code:
```py
final_answer("Final report.")
```<end_code>
""",
)
manager_model = FakeModelMultiagentsManagerAgent()
class FakeModelMultiagentsManagedAgent:
model_id = "fake_model"
def __call__(
self,
messages,
tools_to_call_from=None,
stop_sequences=None,
grammar=None,
):
return ChatMessage(
role="assistant",
content="",
tool_calls=[
ChatMessageToolCall(
id="call_0",
type="function",
function=ChatMessageToolCallDefinition(
name="final_answer",
arguments="Report on the current US president",
),
)
],
)
managed_model = FakeModelMultiagentsManagedAgent()
web_agent = ToolCallingAgent(
tools=[],
model=managed_model,
max_steps=10,
name="search_agent",
description="Runs web searches for you. Give it your request as an argument. Make the request as detailed as needed, you can ask for thorough reports",
)
manager_code_agent = CodeAgent(
tools=[],
model=manager_model,
managed_agents=[web_agent],
additional_authorized_imports=["time", "numpy", "pandas"],
)
report = manager_code_agent.run("Fake question.")
assert report == "Final report."
manager_toolcalling_agent = ToolCallingAgent(
tools=[],
model=manager_model,
managed_agents=[web_agent],
)
report = manager_toolcalling_agent.run("Fake question.")
assert report == "Final report."
# Test that visualization works
with manager_toolcalling_agent.logger.console.capture() as capture:
manager_toolcalling_agent.visualize()
assert "├──" in capture.get()
@pytest.fixture
def prompt_templates():
return {
"system_prompt": "This is a test system prompt.",
"managed_agent": {"task": "Task for {{name}}: {{task}}", "report": "Report for {{name}}: {{final_answer}}"},
}
|