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Fix #3242: Add reasoning parameter to LLM class to disable reasoning mode
- Add reasoning parameter to LLM.__init__() method - Implement logic in _prepare_completion_params to handle reasoning=False - Add comprehensive tests for reasoning parameter functionality - Ensure reasoning=False overrides reasoning_effort parameter - Add integration test with Agent class The fix ensures that when reasoning=False is set, the reasoning_effort parameter is not included in the LLM completion call, effectively disabling reasoning mode for models like Qwen and Cogito with Ollama. Co-Authored-By: João <joao@crewai.com>
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@@ -2,6 +2,7 @@
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import json
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import pytest
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from unittest.mock import patch
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from crewai import Agent, Task
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from crewai.llm import LLM
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@@ -259,3 +260,31 @@ def test_agent_with_function_calling_fallback():
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assert result == "4"
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assert "Reasoning Plan:" in task.description
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assert "Invalid JSON that will trigger fallback" in task.description
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def test_agent_with_llm_reasoning_disabled():
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"""Test agent with LLM reasoning disabled."""
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llm = LLM("gpt-3.5-turbo", reasoning=False)
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agent = Agent(
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role="Test Agent",
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goal="To test the LLM reasoning parameter",
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backstory="I am a test agent created to verify the LLM reasoning parameter works correctly.",
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llm=llm,
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reasoning=False,
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verbose=True
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)
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task = Task(
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description="Simple math task: What's 3+3?",
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expected_output="The answer should be a number.",
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agent=agent
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)
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with patch.object(agent.llm, 'call') as mock_call:
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mock_call.return_value = "6"
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result = agent.execute_task(task)
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assert result == "6"
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assert "Reasoning Plan:" not in task.description
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@@ -711,3 +711,99 @@ def test_ollama_does_not_modify_when_last_is_user(ollama_llm):
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formatted = ollama_llm._format_messages_for_provider(original_messages)
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assert formatted == original_messages
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def test_llm_reasoning_parameter_false():
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"""Test that reasoning=False disables reasoning mode."""
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llm = LLM(model="ollama/qwen", reasoning=False)
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with patch("litellm.completion") as mock_completion:
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mock_message = MagicMock()
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mock_message.content = "Test response"
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mock_choice = MagicMock()
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mock_choice.message = mock_message
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mock_response = MagicMock()
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mock_response.choices = [mock_choice]
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mock_response.usage = {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10}
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mock_completion.return_value = mock_response
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llm.call("Test message")
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_, kwargs = mock_completion.call_args
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assert "reasoning_effort" not in kwargs
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def test_llm_reasoning_parameter_true():
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"""Test that reasoning=True enables reasoning mode."""
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llm = LLM(model="ollama/qwen", reasoning=True, reasoning_effort="medium")
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with patch("litellm.completion") as mock_completion:
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mock_message = MagicMock()
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mock_message.content = "Test response"
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mock_choice = MagicMock()
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mock_choice.message = mock_message
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mock_response = MagicMock()
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mock_response.choices = [mock_choice]
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mock_response.usage = {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10}
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mock_completion.return_value = mock_response
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llm.call("Test message")
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_, kwargs = mock_completion.call_args
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assert kwargs["reasoning_effort"] == "medium"
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def test_llm_reasoning_parameter_none_with_reasoning_effort():
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"""Test that reasoning=None with reasoning_effort still includes reasoning_effort."""
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llm = LLM(model="ollama/qwen", reasoning=None, reasoning_effort="high")
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with patch("litellm.completion") as mock_completion:
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mock_message = MagicMock()
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mock_message.content = "Test response"
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mock_choice = MagicMock()
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mock_choice.message = mock_message
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mock_response = MagicMock()
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mock_response.choices = [mock_choice]
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mock_response.usage = {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10}
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mock_completion.return_value = mock_response
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llm.call("Test message")
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_, kwargs = mock_completion.call_args
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assert kwargs["reasoning_effort"] == "high"
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def test_llm_reasoning_false_overrides_reasoning_effort():
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"""Test that reasoning=False overrides reasoning_effort."""
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llm = LLM(model="ollama/qwen", reasoning=False, reasoning_effort="high")
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with patch("litellm.completion") as mock_completion:
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mock_message = MagicMock()
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mock_message.content = "Test response"
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mock_choice = MagicMock()
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mock_choice.message = mock_message
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mock_response = MagicMock()
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mock_response.choices = [mock_choice]
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mock_response.usage = {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10}
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mock_completion.return_value = mock_response
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llm.call("Test message")
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_, kwargs = mock_completion.call_args
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assert "reasoning_effort" not in kwargs
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_ollama_qwen_with_reasoning_disabled():
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"""Test Ollama Qwen model with reasoning disabled."""
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if not os.getenv("OLLAMA_BASE_URL"):
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pytest.skip("OLLAMA_BASE_URL not set; skipping test.")
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llm = LLM(
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model="ollama/qwen",
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base_url=os.getenv("OLLAMA_BASE_URL", "http://localhost:11434"),
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reasoning=False
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)
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result = llm.call("What is 2+2?")
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assert isinstance(result, str)
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assert len(result.strip()) > 0
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