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* Adding tool caching a loop execution prevention. This adds some guardrails, to both prevent the same tool to be used consecutively and also caching tool's results across the entire crew so it cuts down execution time and eventual LLM calls. This plays a huge role for smaller opensource models that usually fall into those behaviors patterns. It also includes some smaller improvements around the tool prompt and agent tools, all with the same intention of guiding models into better conform with agent instructions.
198 lines
5.9 KiB
Python
198 lines
5.9 KiB
Python
"""Test Agent creation and execution basic functionality."""
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import pytest
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from langchain.chat_models import ChatOpenAI as OpenAI
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from crewai.agent import Agent
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from crewai.agents import CacheHandler
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def test_agent_creation():
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agent = Agent(role="test role", goal="test goal", backstory="test backstory")
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assert agent.role == "test role"
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assert agent.goal == "test goal"
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assert agent.backstory == "test backstory"
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assert agent.tools == []
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def test_agent_default_values():
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agent = Agent(role="test role", goal="test goal", backstory="test backstory")
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assert isinstance(agent.llm, OpenAI)
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assert agent.llm.model_name == "gpt-4"
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assert agent.llm.temperature == 0.7
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assert agent.llm.verbose == False
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assert agent.allow_delegation == True
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def test_custom_llm():
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agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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llm=OpenAI(temperature=0, model="gpt-4"),
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)
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assert isinstance(agent.llm, OpenAI)
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assert agent.llm.model_name == "gpt-4"
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assert agent.llm.temperature == 0
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_agent_without_memory():
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no_memory_agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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memory=False,
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llm=OpenAI(temperature=0, model="gpt-4"),
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)
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memory_agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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memory=True,
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llm=OpenAI(temperature=0, model="gpt-4"),
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)
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result = no_memory_agent.execute_task("How much is 1 + 1?")
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assert result == "1 + 1 equals 2."
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assert no_memory_agent.agent_executor.memory is None
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assert memory_agent.agent_executor.memory is not None
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_agent_execution():
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agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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allow_delegation=False,
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)
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output = agent.execute_task("How much is 1 + 1?")
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assert output == "2"
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_agent_execution_with_tools():
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from langchain.tools import tool
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@tool
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def multiplier(numbers) -> float:
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"""Useful for when you need to multiply two numbers together.
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The input to this tool should be a comma separated list of numbers of
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length two, representing the two numbers you want to multiply together.
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For example, `1,2` would be the input if you wanted to multiply 1 by 2."""
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a, b = numbers.split(",")
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return int(a) * int(b)
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agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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tools=[multiplier],
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allow_delegation=False,
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)
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output = agent.execute_task("What is 3 times 4")
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assert output == "12"
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_logging_tool_usage():
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from langchain.tools import tool
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@tool
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def multiplier(numbers) -> float:
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"""Useful for when you need to multiply two numbers together.
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The input to this tool should be a comma separated list of numbers of
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length two, representing the two numbers you want to multiply together.
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For example, `1,2` would be the input if you wanted to multiply 1 by 2."""
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a, b = numbers.split(",")
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return int(a) * int(b)
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agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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tools=[multiplier],
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allow_delegation=False,
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verbose=True,
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)
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assert agent.tools_handler.last_used_tool == {}
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output = agent.execute_task("What is 3 times 5?")
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tool_usage = {
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"tool": "multiplier",
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"input": "3,5",
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}
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assert output == "3 times 5 is 15."
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assert agent.tools_handler.last_used_tool == tool_usage
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_cache_hitting():
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from unittest.mock import patch
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from langchain.tools import tool
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@tool
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def multiplier(numbers) -> float:
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"""Useful for when you need to multiply two numbers together.
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The input to this tool should be a comma separated list of numbers of
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length two, representing the two numbers you want to multiply together.
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For example, `1,2` would be the input if you wanted to multiply 1 by 2."""
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a, b = numbers.split(",")
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return int(a) * int(b)
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cache_handler = CacheHandler()
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agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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tools=[multiplier],
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allow_delegation=False,
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cache_handler=cache_handler,
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verbose=True,
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)
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output = agent.execute_task("What is 2 times 6?")
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output = agent.execute_task("What is 3 times 3?")
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assert cache_handler._cache == {"multiplier-2,6": "12", "multiplier-3,3": "9"}
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with patch.object(CacheHandler, "read") as read:
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read.return_value = "0"
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output = agent.execute_task("What is 2 times 6?")
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assert output == "0"
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read.assert_called_once_with("multiplier", "2,6")
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_agent_execution_with_specific_tools():
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from langchain.tools import tool
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@tool
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def multiplier(numbers) -> float:
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"""Useful for when you need to multiply two numbers together.
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The input to this tool should be a comma separated list of numbers of
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length two, representing the two numbers you want to multiply together.
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For example, `1,2` would be the input if you wanted to multiply 1 by 2."""
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a, b = numbers.split(",")
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return int(a) * int(b)
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agent = Agent(
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role="test role",
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goal="test goal",
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backstory="test backstory",
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allow_delegation=False,
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)
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output = agent.execute_task(task="What is 3 times 4", tools=[multiplier])
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assert output == "12"
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