improving test

2026-01-08 23:58:34 +00:00 · 2025-05-27 01:27:25 -07:00
parent e636f1dc17
commit 88721788e9
14 changed files with 3606 additions and 68 deletions
--- a/score.json
+++ b/score.json
@@ -0,0 +1,3 @@
+{
+  "score": 4
+}
--- a/tests/cassettes/test_agent_error_on_parsing_tool.yaml
+++ b/tests/cassettes/test_agent_error_on_parsing_tool.yaml
--- a/tests/cassettes/test_agent_with_knowledge_sources.yaml
+++ b/tests/cassettes/test_agent_with_knowledge_sources.yaml
--- a/tests/cassettes/test_agent_with_knowledge_sources_with_query_limit_and_score_threshold.yaml
+++ b/tests/cassettes/test_agent_with_knowledge_sources_with_query_limit_and_score_threshold.yaml
--- a/tests/cassettes/test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default.yaml
+++ b/tests/cassettes/test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default.yaml
--- a/tests/cassettes/test_agent_with_ollama_llama3.yaml
+++ b/tests/cassettes/test_agent_with_ollama_llama3.yaml
--- a/tests/cassettes/test_agent_without_max_rpm_respects_crew_rpm.yaml
+++ b/tests/cassettes/test_agent_without_max_rpm_respects_crew_rpm.yaml
--- a/tests/cassettes/test_cache_hitting.yaml
+++ b/tests/cassettes/test_cache_hitting.yaml
@@ -1020,4 +1020,63 @@ interactions:
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    http_version: HTTP/1.1
    status_code: 200
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+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '1626'
+      Content-Type:
+      - application/x-protobuf
+      User-Agent:
+      - OTel-OTLP-Exporter-Python/1.31.1
+    method: POST
+    uri: https://telemetry.crewai.com:4319/v1/traces
+  response:
+    body:
+      string: "\n\0"
+    headers:
+      Content-Length:
+      - '2'
+      Content-Type:
+      - application/x-protobuf
+      Date:
+      - Tue, 27 May 2025 08:13:05 GMT
+    status:
+      code: 200
+      message: OK
 version: 1
--- a/tests/cassettes/test_increment_tool_errors.yaml
+++ b/tests/cassettes/test_increment_tool_errors.yaml
--- a/tests/cassettes/test_llm_callback_replacement.yaml
+++ b/tests/cassettes/test_llm_callback_replacement.yaml
@@ -202,4 +202,389 @@ interactions:
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+      N3oCGAGFAQABAAA=
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '20189'
+      Content-Type:
+      - application/x-protobuf
+      User-Agent:
+      - OTel-OTLP-Exporter-Python/1.31.1
+    method: POST
+    uri: https://telemetry.crewai.com:4319/v1/traces
+  response:
+    body:
+      string: "\n\0"
+    headers:
+      Content-Length:
+      - '2'
+      Content-Type:
+      - application/x-protobuf
+      Date:
+      - Tue, 27 May 2025 08:13:25 GMT
+    status:
+      code: 200
+      message: OK
 version: 1
--- a/tests/cassettes/test_tool_result_as_answer_is_the_final_answer_for_the_agent.yaml
+++ b/tests/cassettes/test_tool_result_as_answer_is_the_final_answer_for_the_agent.yaml
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+      pieces of a puzzle to see the whole picture. When we add, we take two or more
+      groups of things and count them all together.  **Angle**: Use relatable and
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+      do you have in total?    - You start with 2 apples.    - Your friend gives you
+      3 more apples.    - Now, you count all the apples together: 2 + 3 = 5.    -
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+      1 finger on the other hand.    - Put them together and count: 3 + 1 = 4.    -
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 version: 1
--- a/tests/crew_test.py
+++ b/tests/crew_test.py
@@ -4418,7 +4418,7 @@ def test_reset_knowledge_with_no_crew_knowledge(researcher,writer):

    with pytest.raises(RuntimeError) as excinfo:
        crew.reset_memories(command_type='knowledge')
-        
+
        # Optionally, you can also check the error message
    assert "Crew Knowledge and Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message

@@ -4497,7 +4497,7 @@ def test_reset_agent_knowledge_with_no_agent_knowledge(researcher,writer):

    with pytest.raises(RuntimeError) as excinfo:
        crew.reset_memories(command_type='agent_knowledge')
-    
+
    # Optionally, you can also check the error message
    assert "Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message

@@ -4517,7 +4517,7 @@ def test_reset_agent_knowledge_with_only_crew_knowledge(researcher,writer):

    with pytest.raises(RuntimeError) as excinfo:
        crew.reset_memories(command_type='agent_knowledge')
-    
+
    # Optionally, you can also check the error message
    assert "Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message

--- a/tests/reasoning_interval_test.py
+++ b/tests/reasoning_interval_test.py
@@ -8,62 +8,58 @@ from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.utilities.reasoning_handler import AgentReasoning


-@pytest.fixture
-def mock_llm_responses():
-    """Fixture for mock LLM responses."""
-    return {
-        "initial_reasoning": "I'll solve this task step by step.\n\nREADY: I am ready to execute the task.\n\n",
-        "mid_execution_reasoning": "Based on progress so far, I'll adjust my approach.\n\nREADY: I am ready to continue executing the task.",
-        "execution_step": "I'm working on the task...",
-        "final_result": "Task completed successfully."
-    }
+def test_agent_with_reasoning_interval():
+    """Ensure that the agent triggers mid-execution reasoning based on the fixed interval."""

+    # Use a mock LLM to avoid real network calls
+    llm = MagicMock()
+
+    agent = Agent(
+        role="Test Agent",
+        goal="To test the reasoning interval feature",
+        backstory="I am a test agent created to verify the reasoning interval feature works correctly.",
+        llm=llm,
+        reasoning=True,
+        reasoning_interval=2,  # Reason every 2 steps
+        verbose=True,
+    )

-def test_agent_with_reasoning_interval(mock_llm_responses):
-    """Test agent with reasoning interval."""
-    with patch('crewai.llm.LLM.call') as mock_llm_call:
-        mock_llm_call.return_value = mock_llm_responses["initial_reasoning"]
-        
-        llm = MagicMock()
-        llm.call.return_value = mock_llm_responses["initial_reasoning"]
-        
-        agent = Agent(
-            role="Test Agent",
-            goal="To test the reasoning interval feature",
-            backstory="I am a test agent created to verify the reasoning interval feature works correctly.",
-            llm=llm,
-            reasoning=True,
-            reasoning_interval=2,  # Reason every 2 steps
-            verbose=True
-        )
-    
    task = Task(
        description="Multi-step task that requires periodic reasoning.",
        expected_output="The task should be completed with periodic reasoning.",
-        agent=agent
+        agent=agent,
    )
-    
-    with patch('crewai.agent.Agent.create_agent_executor') as mock_create_executor:
-        mock_executor = MagicMock()
-        mock_executor._handle_mid_execution_reasoning = MagicMock()
-        mock_executor.invoke.return_value = mock_llm_responses["final_result"]
-        mock_create_executor.return_value = mock_executor
-        
+
+    # Create a mock executor that will be injected into the agent
+    mock_executor = MagicMock()
+    # Simulate the executor deciding to reason on the second step
+    mock_executor._should_trigger_reasoning = MagicMock(side_effect=[False, True])
+    mock_executor._handle_mid_execution_reasoning = MagicMock()
+    mock_executor.invoke.return_value = "Task completed successfully."
+
+    # Monkey-patch create_agent_executor so that it sets our mock_executor
+    def _fake_create_agent_executor(self, tools=None, task=None):  # noqa: D401,E501
+        """Replace the real executor with the mock while preserving behaviour."""
+        self.agent_executor = mock_executor
+        return mock_executor
+
+    with patch.object(Agent, "create_agent_executor", _fake_create_agent_executor):
        result = agent.execute_task(task)
-        
-        assert result == mock_llm_responses["final_result"]
-        
-        mock_executor._handle_mid_execution_reasoning.assert_called()
+
+    # Validate results and that reasoning happened when expected
+    assert result == "Task completed successfully."
+    # _handle_mid_execution_reasoning should be called once (on the second step)
+    mock_executor._handle_mid_execution_reasoning.assert_called()


 def test_agent_with_adaptive_reasoning(mock_llm_responses):
    """Test agent with adaptive reasoning."""
    with patch('crewai.llm.LLM.call') as mock_llm_call:
        mock_llm_call.return_value = mock_llm_responses["initial_reasoning"]
-        
+
        llm = MagicMock()
        llm.call.return_value = mock_llm_responses["initial_reasoning"]
-        
+
        agent = Agent(
            role="Test Agent",
            goal="To test the adaptive reasoning feature",
@@ -73,26 +69,26 @@ def test_agent_with_adaptive_reasoning(mock_llm_responses):
            adaptive_reasoning=True,
            verbose=True
        )
-    
+
    task = Task(
        description="Complex task that requires adaptive reasoning.",
        expected_output="The task should be completed with adaptive reasoning.",
        agent=agent
    )
-    
+
    with patch('crewai.agent.Agent.create_agent_executor') as mock_create_executor:
        mock_executor = MagicMock()
        mock_executor._should_adaptive_reason = MagicMock(return_value=True)
        mock_executor._handle_mid_execution_reasoning = MagicMock()
        mock_executor.invoke.return_value = mock_llm_responses["final_result"]
        mock_create_executor.return_value = mock_executor
-        
+
        result = agent.execute_task(task)
-        
+
        assert result == mock_llm_responses["final_result"]
-        
+
        mock_executor._should_adaptive_reason.assert_called()
-        
+
        mock_executor._handle_mid_execution_reasoning.assert_called()


@@ -100,7 +96,7 @@ def test_mid_execution_reasoning_handler():
    """Test the mid-execution reasoning handler."""
    llm = MagicMock()
    llm.call.return_value = "Based on progress, I'll adjust my approach.\n\nREADY: I am ready to continue executing the task."
-    
+
    agent = Agent(
        role="Test Agent",
        goal="To test the mid-execution reasoning handler",
@@ -109,17 +105,17 @@ def test_mid_execution_reasoning_handler():
        reasoning=True,
        verbose=True
    )
-    
+
    task = Task(
        description="Task to test mid-execution reasoning handler.",
        expected_output="The mid-execution reasoning handler should work correctly.",
        agent=agent
    )
-    
+
    agent.llm.call = MagicMock(return_value="Based on progress, I'll adjust my approach.\n\nREADY: I am ready to continue executing the task.")
-    
+
    reasoning_handler = AgentReasoning(task=task, agent=agent)
-    
+
    result = reasoning_handler.handle_mid_execution_reasoning(
        current_steps=3,
        tools_used=["search_tool", "calculator_tool"],
@@ -131,7 +127,7 @@ def test_mid_execution_reasoning_handler():
            {"role": "system", "content": "Calculation result: 42"}
        ]
    )
-    
+
    assert result is not None
    assert hasattr(result, 'plan')
    assert hasattr(result.plan, 'plan')
@@ -145,7 +141,7 @@ def test_should_trigger_reasoning_interval():
    agent.reasoning = True
    agent.reasoning_interval = 3
    agent.adaptive_reasoning = False
-    
+
    executor = CrewAgentExecutor(
        llm=MagicMock(),
        task=MagicMock(),
@@ -159,16 +155,16 @@ def test_should_trigger_reasoning_interval():
        tools_description="",
        tools_handler=MagicMock()
    )
-    
+
    executor.steps_since_reasoning = 0
    assert executor._should_trigger_reasoning() is False
-    
+
    executor.steps_since_reasoning = 2
    assert executor._should_trigger_reasoning() is False
-    
+
    executor.steps_since_reasoning = 3
    assert executor._should_trigger_reasoning() is True
-    
+
    executor.steps_since_reasoning = 4
    assert executor._should_trigger_reasoning() is True

@@ -179,7 +175,7 @@ def test_should_trigger_adaptive_reasoning():
    agent.reasoning = True
    agent.reasoning_interval = None
    agent.adaptive_reasoning = True
-    
+
    executor = CrewAgentExecutor(
        llm=MagicMock(),
        task=MagicMock(),
@@ -193,14 +189,14 @@ def test_should_trigger_adaptive_reasoning():
        tools_description="",
        tools_handler=MagicMock()
    )
-    
+
    executor.tools_used = ["tool1", "tool2", "tool3"]
    assert executor._should_adaptive_reason() is True
-    
+
    executor.tools_used = ["tool1", "tool1", "tool1"]
    executor.iterations = 6  # > max_iter // 2
    assert executor._should_adaptive_reason() is True
-    
+
    executor.tools_used = ["tool1", "tool1", "tool1"]
    executor.iterations = 2
    executor.messages = [
@@ -209,7 +205,7 @@ def test_should_trigger_adaptive_reasoning():
        {"role": "assistant", "content": "Let me try something else."}
    ]
    assert executor._should_adaptive_reason() is True
-    
+
    executor.tools_used = ["tool1", "tool1", "tool1"]
    executor.iterations = 2
    executor.messages = [
@@ -233,7 +229,7 @@ def test_reasoning_interval_scenarios(interval, steps, should_reason):
    agent.reasoning = True
    agent.reasoning_interval = interval
    agent.adaptive_reasoning = False
-    
+
    executor = CrewAgentExecutor(
        llm=MagicMock(),
        task=MagicMock(),
@@ -247,6 +243,6 @@ def test_reasoning_interval_scenarios(interval, steps, should_reason):
        tools_description="",
        tools_handler=MagicMock()
    )
-    
+
    executor.steps_since_reasoning = steps
    assert executor._should_trigger_reasoning() is should_reason