adding new converter logic

tests/agent_test.py

@@ -241,7 +241,7 @@ def test_agent_custom_max_iterations():
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_repeated_tool_usage(capsys):
     @tool
-    def get_final_answer(numbers) -> float:
+    def get_final_answer(anything: str) -> float:
         """Get the final answer but don't give it yet, just re-use this
         tool non-stop."""
         return 42
@@ -251,6 +251,7 @@ def test_agent_repeated_tool_usage(capsys):
         goal="test goal",
         backstory="test backstory",
         max_iter=4,
+        llm=ChatOpenAI(model="gpt-4-0125-preview"),
         allow_delegation=False,
         verbose=True,
     )
@@ -267,10 +268,7 @@ def test_agent_repeated_tool_usage(capsys):
 
     captured = capsys.readouterr()
 
-    assert (
-        "I have been instructed to give the final answer now, so I will proceed to do so using the exact expected format."
-        in captured.out
-    )
+    assert "Final Answer: 42" in captured.out
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -551,7 +549,7 @@ def test_agent_step_callback():
 def test_agent_function_calling_llm():
     from langchain_openai import ChatOpenAI
 
-    llm = ChatOpenAI(model="gpt-3.5")
+    llm = ChatOpenAI(model="gpt-3.5-turbo-0125")
 
     with patch.object(llm.client, "create", wraps=llm.client.create) as private_mock:
 
@@ -565,6 +563,7 @@ def test_agent_function_calling_llm():
             goal="test goal",
             backstory="test backstory",
             tools=[learn_about_AI],
+            llm=ChatOpenAI(model="gpt-4-0125-preview"),
             function_calling_llm=llm,
         )
 

tests/crew_test.py

@@ -299,9 +299,10 @@ def test_api_calls_throttling(capsys):
     from unittest.mock import patch
 
     from langchain.tools import tool
+    from langchain_openai import ChatOpenAI
 
     @tool
-    def get_final_answer(numbers) -> float:
+    def get_final_answer(anything) -> float:
         """Get the final answer but don't give it yet, just re-use this
         tool non-stop."""
         return 42
@@ -313,6 +314,7 @@ def test_api_calls_throttling(capsys):
         max_iter=5,
         allow_delegation=False,
         verbose=True,
+        llm=ChatOpenAI(model="gpt-4-0125-preview"),
     )
 
     task = Task(
@@ -501,7 +503,7 @@ def test_crew_function_calling_llm():
     from langchain.tools import tool
     from langchain_openai import ChatOpenAI
 
-    llm = ChatOpenAI(model="gpt-3.5")
+    llm = ChatOpenAI(model="gpt-3.5-turbo-0125")
 
     with patch.object(llm.client, "create", wraps=llm.client.create) as private_mock:
 
@@ -514,6 +516,7 @@ def test_crew_function_calling_llm():
             role="test role",
             goal="test goal",
             backstory="test backstory",
+            llm=ChatOpenAI(model="gpt-4-0125-preview"),
             tools=[learn_about_AI],
         )
 

tests/task_test.py

@@ -204,6 +204,8 @@ def test_output_json():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_output_pydantic_to_another_task():
+    from langchain_openai import ChatOpenAI
+
     class ScoreOutput(BaseModel):
         score: int
 
@@ -212,6 +214,9 @@ def test_output_pydantic_to_another_task():
         goal="Score the title",
         backstory="You're an expert scorer, specialized in scoring titles.",
         allow_delegation=False,
+        llm=ChatOpenAI(model="gpt-4-0125-preview"),
+        function_calling_llm=ChatOpenAI(model="gpt-3.5-turbo-0125"),
+        verbose=True,
     )
 
     task1 = Task(
@@ -222,15 +227,15 @@ def test_output_pydantic_to_another_task():
     )
 
     task2 = Task(
-        description="Given the score the title 'The impact of AI in the future of work' got, give me an integer score between 1-5 for the following title: 'Return of the Jedi'",
+        description="Given the score the title 'The impact of AI in the future of work' got, give me an integer score between 1-5 for the following title: 'Return of the Jedi', you MUST give it a score, use your best judgment",
         expected_output="The score of the title.",
         output_pydantic=ScoreOutput,
         agent=scorer,
     )
 
-    crew = Crew(agents=[scorer], tasks=[task1, task2])
+    crew = Crew(agents=[scorer], tasks=[task1, task2], verbose=2)
     result = crew.kickoff()
-    assert 4 == result.score
+    assert 5 == result.score
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])