minor fix

tests/integration/inference/test_text_inference.py

@@ -496,48 +496,53 @@ def test_text_chat_completion_tool_calling_tools_not_in_request(
 @pytest.mark.parametrize(
     "test_case",
     [
+        # Tests if the model can handle simple messages like "Hi" or
+        # a message unrelated to one of the tool calls
         "inference:chat_completion:multi_turn_tool_calling_01",
+        # Tests if the model can do full tool call with responses correctly
         "inference:chat_completion:multi_turn_tool_calling_02",
+        # Tests if model can generate multiple params and
+        # read outputs correctly
         "inference:chat_completion:multi_turn_tool_calling_03",
+        # Tests if model can do different tool calls in a seqeunce
+        # and use the information between appropriately
         "inference:chat_completion:multi_turn_tool_calling_04",
+        # Tests if model can use current date and run multiple tool calls
+        # sequentially and infer using both
         "inference:chat_completion:multi_turn_tool_calling_05",
     ],
 )
-def test_text_chat_completion_with_tool_calling_loop_non_streaming(client_with_models, text_model_id, test_case):
-    from rich.pretty import pprint
-
+def test_text_chat_completion_with_multi_turn_tool_calling(client_with_models, text_model_id, test_case):
+    """This test tests the model's tool calling loop in various scenarios"""
     tc = TestCase(test_case)
     messages = []
+
     # keep going until either
     # 1. we have messages to test in multi-turn
     # 2. no messages bust last message is tool response
     while len(tc["messages"]) > 0 or (len(messages) > 0 and messages[-1]["role"] == "tool"):
         # do not take new messages if last message is tool response
-        if (
-            len(messages) == 0
-            or (isinstance(messages[-1], dict) and messages[-1]["role"] != "tool")
-            or (not isinstance(messages[-1], dict) and messages[-1].role != "tool")
-        ):
+        if len(messages) == 0 or messages[-1]["role"] != "tool":
             new_messages = tc["messages"].pop(0)
             messages += new_messages
 
-        pprint(messages)
+        # pprint(messages)
         response = client_with_models.inference.chat_completion(
             model_id=text_model_id,
             messages=messages,
             tools=tc["tools"],
             stream=False,
-            # sampling_params={
-            #     "strategy": {
-            #         "type": "top_p",
-            #         "top_p": 0.9,
-            #         "temperature": 0.6,
-            #     }
-            # },
+            sampling_params={
+                "strategy": {
+                    "type": "top_p",
+                    "top_p": 0.9,
+                    "temperature": 0.6,
+                }
+            },
         )
         op_msg = response.completion_message
         messages.append(op_msg.model_dump())
-        pprint(op_msg)
+        # pprint(op_msg)
 
         assert op_msg.role == "assistant"
         expected = tc["expected"].pop(0)
@@ -558,5 +563,5 @@ def test_text_chat_completion_with_tool_calling_loop_non_streaming(client_with_m
             )
         else:
             actual_answer = op_msg.content.lower()
-            pprint(actual_answer)
+            # pprint(actual_answer)
             assert expected["answer"] in actual_answer

tests/integration/test_cases/inference/chat_completion.json

@@ -94,8 +94,7 @@
         }
       ],
       "expected": {
-        "num_tool_calls": 1,
-        "expected": "San Francisco, CA"
+        "location": "San Francisco, CA"
       }
     }
   },