Refactor token tracking: Remove token_cost_process parameter for cleaner code

src/crewai/utilities/token_counter_callback.py

@@ -217,4 +217,9 @@ class LangChainTokenCounter(BaseCallbackHandler, AbstractTokenCounter):
 
 
 # For backward compatibility
-TokenCalcHandler = LiteLLMTokenCounter
+class TokenCalcHandler(LiteLLMTokenCounter):
+    """
+    Alias for LiteLLMTokenCounter.
+    """
+
+    pass

tests/llm_test.py

@@ -18,15 +18,15 @@ def test_llm_callback_replacement():
     llm1 = LLM(model="gpt-4o-mini")
     llm2 = LLM(model="gpt-4o-mini")
 
-    calc_handler_1 = TokenCalcHandler(token_cost_process=TokenProcess())
-    calc_handler_2 = TokenCalcHandler(token_cost_process=TokenProcess())
+    calc_handler_1 = TokenCalcHandler(token_process=TokenProcess())
+    calc_handler_2 = TokenCalcHandler(token_process=TokenProcess())
 
     result1 = llm1.call(
         messages=[{"role": "user", "content": "Hello, world!"}],
         callbacks=[calc_handler_1],
     )
     print("result1:", result1)
-    usage_metrics_1 = calc_handler_1.token_cost_process.get_summary()
+    usage_metrics_1 = calc_handler_1.token_process.get_summary()
     print("usage_metrics_1:", usage_metrics_1)
 
     result2 = llm2.call(
@@ -35,13 +35,13 @@ def test_llm_callback_replacement():
     )
     sleep(5)
     print("result2:", result2)
-    usage_metrics_2 = calc_handler_2.token_cost_process.get_summary()
+    usage_metrics_2 = calc_handler_2.token_process.get_summary()
     print("usage_metrics_2:", usage_metrics_2)
 
     # The first handler should not have been updated
     assert usage_metrics_1.successful_requests == 1
     assert usage_metrics_2.successful_requests == 1
-    assert usage_metrics_1 == calc_handler_1.token_cost_process.get_summary()
+    assert usage_metrics_1 == calc_handler_1.token_process.get_summary()
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -57,14 +57,14 @@ def test_llm_call_with_string_input():
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_llm_call_with_string_input_and_callbacks():
     llm = LLM(model="gpt-4o-mini")
-    calc_handler = TokenCalcHandler(token_cost_process=TokenProcess())
+    calc_handler = TokenCalcHandler(token_process=TokenProcess())
 
     # Test the call method with a string input and callbacks
     result = llm.call(
         "Tell me a joke.",
         callbacks=[calc_handler],
     )
-    usage_metrics = calc_handler.token_cost_process.get_summary()
+    usage_metrics = calc_handler.token_process.get_summary()
 
     assert isinstance(result, str)
     assert len(result.strip()) > 0
@@ -285,6 +285,7 @@ def test_o3_mini_reasoning_effort_medium():
     assert isinstance(result, str)
     assert "Paris" in result
 
+
 def test_context_window_validation():
     """Test that context window validation works correctly."""
     # Test valid window size

tests/utilities/test_token_tracking.py

@@ -133,8 +133,14 @@ class TestTokenTracking:
         Integration test for token tracking with LangChainAgentAdapter.
         This test requires an OpenAI API key.
         """
+        # Skip if LangGraph is not installed
+        try:
+            from langgraph.prebuilt import ToolNode
+        except ImportError:
+            pytest.skip("LangGraph is not installed. Install it with: uv add langgraph")
+
         # Initialize a ChatOpenAI model
-        llm = ChatOpenAI(model="gpt-3.5-turbo")
+        llm = ChatOpenAI(model="gpt-4o")
 
         # Create a LangChainAgentAdapter with the direct LLM
         agent = LangChainAgentAdapter(