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Adding overall usage_metrics to crew and not adding delegation tools if there no agents the allow delegation

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João Moura
2024-02-28 02:12:12 -03:00
parent 5d682a5d6c
commit ed22fdd993
5 changed files with 1360 additions and 9 deletions
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36
src/crewai/crew.py
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@@ -53,6 +53,10 @@ class Crew(BaseModel):
agents: List[Agent] = Field(default_factory=list) agents: List[Agent] = Field(default_factory=list)
process: Process = Field(default=Process.sequential) process: Process = Field(default=Process.sequential)
verbose: Union[int, bool] = Field(default=0) verbose: Union[int, bool] = Field(default=0)
usage_metrics: Optional[dict] = Field(
default=None,
description="Metrics for the LLM usage during all tasks execution.",
)
full_output: Optional[bool] = Field( full_output: Optional[bool] = Field(
default=False, default=False,
description="Whether the crew should return the full output with all tasks outputs or just the final output.", description="Whether the crew should return the full output with all tasks outputs or just the final output.",
@@ -187,14 +191,27 @@ class Crew(BaseModel):
agent.step_callback = self.step_callback agent.step_callback = self.step_callback
agent.create_agent_executor() agent.create_agent_executor()
if self.process == Process.sequential: metrics = []
return self._run_sequential_process()
if self.process == Process.hierarchical:
return self._run_hierarchical_process()
raise NotImplementedError( if self.process == Process.sequential:
f"The process '{self.process}' is not implemented yet." result = self._run_sequential_process()
) elif self.process == Process.hierarchical:
result, manager_metrics = self._run_hierarchical_process()
metrics.append(manager_metrics)
else:
raise NotImplementedError(
f"The process '{self.process}' is not implemented yet."
)
metrics = metrics + [
agent._token_process.get_summary() for agent in self.agents
]
self.usage_metrics = {
key: sum([m[key] for m in metrics if m is not None]) for key in metrics[0]
}
return result
def _run_sequential_process(self) -> str: def _run_sequential_process(self) -> str:
"""Executes tasks sequentially and returns the final output.""" """Executes tasks sequentially and returns the final output."""
@@ -204,7 +221,8 @@ class Crew(BaseModel):
agents_for_delegation = [ agents_for_delegation = [
agent for agent in self.agents if agent != task.agent agent for agent in self.agents if agent != task.agent
] ]
task.tools += AgentTools(agents=agents_for_delegation).tools() if len(agents_for_delegation) > 0:
task.tools += AgentTools(agents=agents_for_delegation).tools()
role = task.agent.role if task.agent is not None else "None" role = task.agent.role if task.agent is not None else "None"
self._logger.log("debug", f"Working Agent: {role}") self._logger.log("debug", f"Working Agent: {role}")
@@ -247,7 +265,7 @@ class Crew(BaseModel):
) )
self._finish_execution(task_output) self._finish_execution(task_output)
return self._format_output(task_output) return self._format_output(task_output), manager._token_process.get_summary()
def _format_output(self, output: str) -> str: def _format_output(self, output: str) -> str:
"""Formats the output of the crew execution.""" """Formats the output of the crew execution."""

983
tests/cassettes/test_agent_usage_metrics_are_captured_for_hierarchical_process.yaml Normal file
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@@ -0,0 +1,983 @@
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are also known for your ability to delegate work to the right people, and to
ask the right questions to get the best out of your team.\nEven though you don''t
perform tasks by yourself, you have a lot of experience in the field, which
allows you to properly evaluate the work of your team members.\n\nYour personal
goal is: Manage the team to complete the task in the best way possible.I have
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answer goes here]\n```\nI MUST use these formats, my jobs depends on it!\n\nCurrent
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tests/cassettes/test_agents_do_not_get_delegation_tools_with_there_is_only_one_agent.yaml Normal file
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94
tests/crew_test.py
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@@ -556,3 +556,97 @@ def test_task_with_no_arguments():
result = crew.kickoff() result = crew.kickoff()
assert result == "The total number of sales from January to May is 75." assert result == "The total number of sales from January to May is 75."
def test_delegation_is_not_enabled_if_there_are_only_one_agent():
from unittest.mock import patch
researcher = Agent(
role="Researcher",
goal="Make the best research and analysis on content about AI and AI agents",
backstory="You're an expert researcher, specialized in technology, software engineering, AI and startups. You work as a freelancer and is now working on doing research and analysis for a new customer.",
allow_delegation=True,
)
task = Task(
description="Look at the available data nd give me a sense on the total number of sales.",
agent=researcher,
)
crew = Crew(agents=[researcher], tasks=[task])
with patch.object(Task, "execute") as execute:
execute.return_value = "ok"
crew.kickoff()
assert task.tools == []
@pytest.mark.vcr(filter_headers=["authorization"])
def test_agents_do_not_get_delegation_tools_with_there_is_only_one_agent():
agent = Agent(
role="Researcher",
goal="Be super empathetic.",
backstory="You're love to sey howdy.",
allow_delegation=False,
)
task = Task(description="say howdy", expected_output="Howdy!", agent=agent)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
assert result == "Howdy!"
assert len(agent.tools) == 0
@pytest.mark.vcr(filter_headers=["authorization"])
def test_agent_usage_metrics_are_captured_for_sequential_process():
agent = Agent(
role="Researcher",
goal="Be super empathetic.",
backstory="You're love to sey howdy.",
allow_delegation=False,
)
task = Task(description="say howdy", expected_output="Howdy!", agent=agent)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
assert result == "Howdy!"
assert crew.usage_metrics == {
"completion_tokens": 8,
"prompt_tokens": 103,
"successful_requests": 1,
"total_tokens": 111,
}
@pytest.mark.vcr(filter_headers=["authorization"])
def test_agent_usage_metrics_are_captured_for_hierarchical_process():
from langchain_openai import ChatOpenAI
agent = Agent(
role="Researcher",
goal="Be super empathetic.",
backstory="You're love to sey howdy.",
allow_delegation=False,
)
task = Task(description="say howdy", expected_output="Howdy!")
crew = Crew(
agents=[agent],
tasks=[task],
process=Process.hierarchical,
manager_llm=ChatOpenAI(temperature=0, model="gpt-4"),
)
result = crew.kickoff()
assert result == "Howdy!"
assert crew.usage_metrics == {
"total_tokens": 1365,
"prompt_tokens": 1256,
"completion_tokens": 109,
"successful_requests": 3,
}