# 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 import pytest from agents.agent_types import AgentText from agents.agents import ( AgentMaxIterationsError, ManagedAgent, CodeAgent, JsonAgent, Toolbox, ) from agents.default_tools import PythonInterpreterTool def get_new_path(suffix="") -> str: directory = tempfile.mkdtemp() return os.path.join(directory, str(uuid.uuid4()) + suffix) def fake_react_json_llm(messages, stop_sequences=None, grammar=None) -> str: prompt = str(messages) if "special_marker" not in prompt: return """ Thought: I should multiply 2 by 3.6452. special_marker Action: { "action": "python_interpreter", "action_input": {"code": "2*3.6452"} } """ else: # We're at step 2 return """ Thought: I can now answer the initial question Action: { "action": "final_answer", "action_input": {"answer": "7.2904"} } """ def fake_react_code_llm(messages, stop_sequences=None, grammar=None) -> str: prompt = str(messages) if "special_marker" not in prompt: return """ Thought: I should multiply 2 by 3.6452. special_marker Code: ```py result = 2**3.6452 ``` """ else: # We're at step 2 return """ Thought: I can now answer the initial question Code: ```py final_answer(7.2904) ``` """ def fake_react_code_llm_error(messages, stop_sequences=None) -> str: prompt = str(messages) if "special_marker" not in prompt: return """ Thought: I should multiply 2 by 3.6452. special_marker Code: ```py print = 2 ``` """ else: # We're at step 2 return """ Thought: I can now answer the initial question Code: ```py final_answer("got an error") ``` """ def fake_react_code_functiondef(messages, stop_sequences=None) -> str: prompt = str(messages) if "special_marker" not in prompt: return """ 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 ``` """ else: # We're at step 2 return """ 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) ``` """ def fake_code_llm_oneshot(messages, stop_sequences=None, grammar=None) -> str: return """ 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_llm_no_return(messages, stop_sequences=None, grammar=None) -> str: return """ 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_code_agent(self): agent = CodeAgent( tools=[PythonInterpreterTool()], llm_engine=fake_code_llm_oneshot ) output = agent.run("What is 2 multiplied by 3.6452?") assert isinstance(output, str) assert output == "7.2904" def test_fake_react_json_agent(self): agent = JsonAgent( tools=[PythonInterpreterTool()], llm_engine=fake_react_json_llm ) output = agent.run("What is 2 multiplied by 3.6452?") assert isinstance(output, str) assert output == "7.2904" assert agent.logs[1].task == "What is 2 multiplied by 3.6452?" assert agent.logs[2].observation == "7.2904" assert ( agent.logs[2].rationale.strip() == "Thought: I should multiply 2 by 3.6452. special_marker" ) assert ( agent.logs[3].llm_output == """ Thought: I can now answer the initial question Action: { "action": "final_answer", "action_input": {"answer": "7.2904"} } """ ) def test_fake_react_code_agent(self): agent = CodeAgent( tools=[PythonInterpreterTool()], llm_engine=fake_react_code_llm ) output = agent.run("What is 2 multiplied by 3.6452?") assert isinstance(output, float) assert output == 7.2904 assert agent.logs[1].task == "What is 2 multiplied by 3.6452?" assert agent.logs[3].tool_call == { "tool_arguments": "final_answer(7.2904)", "tool_name": "code interpreter", } def test_react_code_agent_code_errors_show_offending_lines(self): agent = CodeAgent( tools=[PythonInterpreterTool()], llm_engine=fake_react_code_llm_error ) output = agent.run("What is 2 multiplied by 3.6452?") assert isinstance(output, AgentText) assert output == "got an error" assert "Evaluation stopped at line 'print = 2' because of" in str(agent.logs) def test_setup_agent_with_empty_toolbox(self): JsonAgent(llm_engine=fake_react_json_llm, tools=[]) def test_react_fails_max_iterations(self): agent = CodeAgent( tools=[PythonInterpreterTool()], llm_engine=fake_code_llm_no_return, # use this callable because it never ends max_iterations=5, ) agent.run("What is 2 multiplied by 3.6452?") assert len(agent.logs) == 8 assert type(agent.logs[-1].error) is AgentMaxIterationsError def test_init_agent_with_different_toolsets(self): toolset_1 = [] agent = CodeAgent(tools=toolset_1, llm_engine=fake_react_code_llm) assert ( len(agent.toolbox.tools) == 1 ) # when no tools are provided, only the final_answer tool is added by default toolset_2 = [PythonInterpreterTool(), PythonInterpreterTool()] agent = CodeAgent(tools=toolset_2, llm_engine=fake_react_code_llm) assert ( len(agent.toolbox.tools) == 2 ) # deduplication of tools, so only one python_interpreter tool is added in addition to final_answer toolset_3 = Toolbox(toolset_2) agent = CodeAgent(tools=toolset_3, llm_engine=fake_react_code_llm) assert ( len(agent.toolbox.tools) == 2 ) # same as previous one, where toolset_3 is an instantiation of previous one # check that add_base_tools will not interfere with existing tools with pytest.raises(KeyError) as e: agent = JsonAgent( tools=toolset_3, llm_engine=fake_react_json_llm, add_base_tools=True ) assert "already exists in the toolbox" in str(e) # check that python_interpreter base tool does not get added to code agents agent = CodeAgent(tools=[], llm_engine=fake_react_code_llm, add_base_tools=True) assert ( len(agent.toolbox.tools) == 2 ) # added final_answer tool + search def test_function_persistence_across_steps(self): agent = CodeAgent( tools=[], llm_engine=fake_react_code_functiondef, max_iterations=2, additional_authorized_imports=["numpy"], ) res = agent.run("ok") assert res[0] == 0.5 def test_init_managed_agent(self): agent = CodeAgent(tools=[], llm_engine=fake_react_code_functiondef) managed_agent = ManagedAgent(agent, name="managed_agent", description="Empty") assert managed_agent.name == "managed_agent" assert managed_agent.description == "Empty" def test_agent_description_gets_correctly_inserted_in_system_prompt(self): agent = CodeAgent(tools=[], llm_engine=fake_react_code_functiondef) managed_agent = ManagedAgent(agent, name="managed_agent", description="Empty") manager_agent = CodeAgent( tools=[], llm_engine=fake_react_code_functiondef, managed_agents=[managed_agent], ) assert "You can also give requests to team members." not in agent.system_prompt print("ok1") assert "{{managed_agents_descriptions}}" not in agent.system_prompt assert ( "You can also give requests to team members." in manager_agent.system_prompt )