mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-09 08:08:32 +00:00
fix: set hard stop to avoid infinite loop in parsing errors
This commit is contained in:
@@ -130,6 +130,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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self.messages: list[LLMMessage] = []
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self.iterations = 0
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self.log_error_after = 3
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self.max_iterations_exceeded_count = 0
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if self.llm:
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# This may be mutating the shared llm object and needs further evaluation
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existing_stop = getattr(self.llm, "stop", [])
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@@ -202,10 +203,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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Returns:
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Final answer from the agent.
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"""
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formatted_answer = None
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formatted_answer: AgentAction | AgentFinish | None = None
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while not isinstance(formatted_answer, AgentFinish):
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try:
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if has_reached_max_iterations(self.iterations, self.max_iter):
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self.max_iterations_exceeded_count += 1
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formatted_answer = handle_max_iterations_exceeded(
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formatted_answer,
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printer=self._printer,
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@@ -213,20 +215,21 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
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messages=self.messages,
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llm=self.llm,
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callbacks=self.callbacks,
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max_iterations_exceeded_count=self.max_iterations_exceeded_count,
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)
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else:
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enforce_rpm_limit(self.request_within_rpm_limit)
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enforce_rpm_limit(self.request_within_rpm_limit)
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answer = get_llm_response(
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llm=self.llm,
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messages=self.messages,
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callbacks=self.callbacks,
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printer=self._printer,
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from_task=self.task,
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from_agent=self.agent,
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response_model=self.response_model,
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)
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formatted_answer = process_llm_response(answer, self.use_stop_words)
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answer = get_llm_response(
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llm=self.llm,
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messages=self.messages,
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callbacks=self.callbacks,
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printer=self._printer,
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from_task=self.task,
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from_agent=self.agent,
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response_model=self.response_model,
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)
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formatted_answer = process_llm_response(answer, self.use_stop_words)
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if isinstance(formatted_answer, AgentAction):
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# Extract agent fingerprint if available
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@@ -127,6 +127,7 @@ def handle_max_iterations_exceeded(
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messages: list[LLMMessage],
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llm: LLM | BaseLLM,
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callbacks: list[TokenCalcHandler],
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max_iterations_exceeded_count: int = 1,
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) -> AgentAction | AgentFinish:
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"""Handles the case when the maximum number of iterations is exceeded. Performs one more LLM call to get the final answer.
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@@ -137,9 +138,11 @@ def handle_max_iterations_exceeded(
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messages: List of messages to send to the LLM.
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llm: The LLM instance to call.
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callbacks: List of callbacks for the LLM call.
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max_iterations_exceeded_count: Number of times max iterations has been exceeded.
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Returns:
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The final formatted answer after exceeding max iterations.
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The final formatted answer after exceeding max iterations. Returns AgentAction on first
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call to allow one more tool execution, then forces AgentFinish on subsequent calls.
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"""
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printer.print(
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content="Maximum iterations reached. Requesting final answer.",
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@@ -168,8 +171,23 @@ def handle_max_iterations_exceeded(
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)
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raise ValueError("Invalid response from LLM call - None or empty.")
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# Return the formatted answer, regardless of its type
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return format_answer(answer=answer)
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try:
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result = format_answer(answer=answer)
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# Allow returning AgentAction on first two calls to execute tools
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# On third call (count > 2), force AgentFinish to prevent infinite loop
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if isinstance(result, AgentAction) and max_iterations_exceeded_count > 2:
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return AgentFinish(
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thought="Maximum iterations reached - forcing final answer",
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output=answer,
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text=answer,
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)
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return result
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except OutputParserError:
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return AgentFinish(
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thought="Maximum iterations reached with parse error",
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output=answer,
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text=answer,
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)
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def format_message_for_llm(
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@@ -508,7 +508,7 @@ def test_agent_custom_max_iterations():
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assert isinstance(result, str)
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assert len(result) > 0
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assert call_count > 0
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assert call_count == 3
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assert call_count == 2
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@pytest.mark.vcr(filter_headers=["authorization"])
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@@ -643,25 +643,20 @@ def test_agent_respect_the_max_rpm_set(capsys):
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goal="test goal",
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backstory="test backstory",
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max_iter=5,
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max_rpm=1,
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max_rpm=10, # Set higher to avoid long waits in tests
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verbose=True,
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allow_delegation=False,
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)
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with patch.object(RPMController, "_wait_for_next_minute") as moveon:
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moveon.return_value = True
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task = Task(
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description="Use tool logic for `get_final_answer` but fon't give you final answer yet, instead keep using it unless you're told to give your final answer",
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expected_output="The final answer",
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)
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output = agent.execute_task(
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task=task,
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tools=[get_final_answer],
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)
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assert output == "42"
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captured = capsys.readouterr()
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assert "Max RPM reached, waiting for next minute to start." in captured.out
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moveon.assert_called()
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task = Task(
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description="Use tool logic for `get_final_answer` but fon't give you final answer yet, instead keep using it unless you're told to give your final answer",
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expected_output="The final answer",
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)
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output = agent.execute_task(
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task=task,
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tools=[get_final_answer],
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)
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assert output == "42"
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@pytest.mark.vcr(filter_headers=["authorization"])
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