Merge branch 'main' into feature/kickoff-consistent-output

tests/crew_test.py

@@ -413,42 +413,42 @@ def test_api_calls_throttling(capsys):
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
-def test_crew_full_ouput():
+def test_crew_kickoff_for_each_full_ouput():
+    inputs = [
+        {"topic": "dog"},
+        {"topic": "cat"},
+        {"topic": "apple"},
+    ]
+
     agent = Agent(
-        role="test role",
-        goal="test goal",
-        backstory="test backstory",
-        allow_delegation=False,
-        verbose=True,
+        role="{topic} Researcher",
+        goal="Express hot takes on {topic}.",
+        backstory="You have a lot of experience with {topic}.",
     )
 
-    task1 = Task(
-        description="just say hi!",
-        expected_output="your greeting",
-        agent=agent,
-    )
-    task2 = Task(
-        description="just say hello!",
-        expected_output="your greeting",
+    task = Task(
+        description="Give me an analysis around {topic}.",
+        expected_output="1 bullet point about {topic} that's under 15 words.",
         agent=agent,
     )
 
-    crew = Crew(agents=[agent], tasks=[task1, task2], full_output=True)
+    crew = Crew(agents=[agent], tasks=[task], full_output=True)
+    results = crew.kickoff_for_each(inputs=inputs)
 
-    result = crew.kickoff()
+    assert len(results) == len(inputs)
+    for result in results:
+        assert "usage_metrics" in result
+        assert isinstance(result["usage_metrics"], dict)
 
-    expected_usage_metrics = {
-        "total_tokens": 348,
-        "prompt_tokens": 314,
-        "completion_tokens": 34,
-        "successful_requests": 2,
-    }
-    print(result.output)
-    assert result.token_usage == expected_usage_metrics
-    expected_final_string_output = "Hello!"
-    assert result.tasks_output == [task1.output, task2.output]
-    assert result.result() == expected_final_string_output
-    assert result.raw_output() == expected_final_string_output
+        # Assert that all required keys are in usage_metrics and their values are not None
+        for key in [
+            "total_tokens",
+            "prompt_tokens",
+            "completion_tokens",
+            "successful_requests",
+        ]:
+            assert key in result["usage_metrics"]
+            assert result["usage_metrics"][key] > 0
 
 
 def test_agents_rpm_is_never_set_if_crew_max_RPM_is_not_set():
@@ -490,7 +490,7 @@ TODO: TEST THE SAME THING BUT WITH HIERARCHICAL PROCESS
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_sequential_async_task_execution_completion():
     list_ideas = Task(
-        description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
+        description="Give me a list of 5 interesting ideas to explore for an article, what makes them unique and interesting.",
         expected_output="Bullet point list of 5 important events.",
         agent=researcher,
         async_execution=True,
@@ -1128,9 +1128,12 @@ def test_code_execution_flag_adds_code_tool_upon_kickoff():
     )
 
     crew = Crew(agents=[programmer], tasks=[task])
-    crew.kickoff()
-    assert len(programmer.tools) == 1
-    assert programmer.tools[0].__class__ == CodeInterpreterTool
+
+    with patch.object(Agent, "execute_task") as executor:
+        executor.return_value = "ok"
+        crew.kickoff()
+        assert len(programmer.tools) == 1
+        assert programmer.tools[0].__class__ == CodeInterpreterTool
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -1204,6 +1207,29 @@ def test_agent_usage_metrics_are_captured_for_sequential_process():
         assert crew.usage_metrics[key] > 0, f"Value for key '{key}' is zero"
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_sequential_crew_creation_tasks_without_agents():
+    task = Task(
+        description="Come up with a list of 5 interesting ideas to explore for an article, then write one amazing paragraph highlight for each idea that showcases how good an article about this topic could be. Return the list of ideas with their paragraph and your notes.",
+        expected_output="5 bullet points with a paragraph for each idea.",
+        # agent=researcher, # not having an agent on the task should throw an error
+    )
+
+    # Expected Output: The sequential crew should fail to create because the task is missing an agent
+    with pytest.raises(pydantic_core._pydantic_core.ValidationError) as exec_info:
+        Crew(
+            tasks=[task],
+            agents=[researcher],
+            process=Process.sequential,
+        )
+
+    assert exec_info.value.errors()[0]["type"] == "missing_agent_in_task"
+    assert (
+        "Agent is missing in the task with the following description"
+        in exec_info.value.errors()[0]["msg"]
+    )
+
+
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_usage_metrics_are_captured_for_hierarchical_process():
     from langchain_openai import ChatOpenAI
@@ -1227,15 +1253,67 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
     result = crew.kickoff()
     assert result.raw_output() == '"Howdy!"'
 
-    required_keys = [
-        "total_tokens",
-        "prompt_tokens",
-        "completion_tokens",
-        "successful_requests",
-    ]
-    for key in required_keys:
-        assert key in crew.usage_metrics, f"Key '{key}' not found in usage_metrics"
-        assert crew.usage_metrics[key] > 0, f"Value for key '{key}' is zero"
+    assert crew.usage_metrics == {
+        "total_tokens": 1927,
+        "prompt_tokens": 1557,
+        "completion_tokens": 370,
+        "successful_requests": 4,
+    }
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_hierarchical_crew_creation_tasks_with_agents():
+    """
+    Agents are not required for tasks in a hierarchical process but sometimes they are still added
+    This test makes sure that the manager still delegates the task to the agent even if the agent is passed in the task
+    """
+    from langchain_openai import ChatOpenAI
+
+    task = Task(
+        description="Write one amazing paragraph about AI.",
+        expected_output="A single paragraph with 4 sentences.",
+        agent=writer,
+    )
+
+    crew = Crew(
+        tasks=[task],
+        agents=[writer, researcher],
+        process=Process.hierarchical,
+        manager_llm=ChatOpenAI(model="gpt-4o"),
+    )
+    crew.kickoff()
+    assert crew.manager_agent is not None
+    assert crew.manager_agent.tools is not None
+    assert crew.manager_agent.tools[0].description.startswith(
+        "Delegate a specific task to one of the following coworkers: [Senior Writer]"
+    )
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_hierarchical_crew_creation_tasks_without_async_execution():
+    from langchain_openai import ChatOpenAI
+
+    task = Task(
+        description="Come up with a list of 5 interesting ideas to explore for an article, then write one amazing paragraph highlight for each idea that showcases how good an article about this topic could be. Return the list of ideas with their paragraph and your notes.",
+        expected_output="5 bullet points with a paragraph for each idea.",
+        async_execution=True,  # should throw an error
+    )
+
+    with pytest.raises(pydantic_core._pydantic_core.ValidationError) as exec_info:
+        Crew(
+            tasks=[task],
+            agents=[researcher],
+            process=Process.hierarchical,
+            manager_llm=ChatOpenAI(model="gpt-4o"),
+        )
+
+    assert (
+        exec_info.value.errors()[0]["type"] == "async_execution_in_hierarchical_process"
+    )
+    assert (
+        "Hierarchical process error: Tasks cannot be flagged with async_execution."
+        in exec_info.value.errors()[0]["msg"]
+    )
 
 
 def test_crew_inputs_interpolate_both_agents_and_tasks():
@@ -1248,9 +1326,10 @@ def test_crew_inputs_interpolate_both_agents_and_tasks():
     task = Task(
         description="Give me an analysis around {topic}.",
         expected_output="{points} bullet points about {topic}.",
+        agent=agent,
     )
 
-    crew = Crew(agents=[agent], tasks=[task], inputs={"topic": "AI", "points": 5})
+    crew = Crew(agents=[agent], tasks=[task])
     inputs = {"topic": "AI", "points": 5}
     crew._interpolate_inputs(inputs=inputs)  # Manual call for now
 
@@ -1643,6 +1722,7 @@ def test_crew_train_success(task_evaluator, crew_training_handler, kickoff):
     task = Task(
         description="Come up with a list of 5 interesting ideas to explore for an article, then write one amazing paragraph highlight for each idea that showcases how good an article about this topic could be. Return the list of ideas with their paragraph and your notes.",
         expected_output="5 bullet points with a paragraph for each idea.",
+        agent=researcher,
     )
 
     crew = Crew(
@@ -1697,6 +1777,7 @@ def test_crew_train_error():
     task = Task(
         description="Come up with a list of 5 interesting ideas to explore for an article",
         expected_output="5 bullet points with a paragraph for each idea.",
+        agent=researcher,
     )
 
     crew = Crew(
@@ -1718,6 +1799,7 @@ def test__setup_for_training():
     task = Task(
         description="Come up with a list of 5 interesting ideas to explore for an article",
         expected_output="5 bullet points with a paragraph for each idea.",
+        agent=researcher,
     )
 
     crew = Crew(