fix: harden Responses API tool call conversion

lib/crewai/src/crewai/llms/providers/openai/completion.py

@@ -683,14 +683,17 @@ class OpenAICompletion(BaseLLM):
 
         if role == "assistant" and message.get("tool_calls"):
             items: list[dict[str, Any] | LLMMessage] = []
+            if message.get("content"):
+                items.append({"role": "assistant", "content": message["content"]})
             for tool_call in message["tool_calls"]:
                 function = tool_call.get("function", {})
+                args = function.get("arguments", "")
                 items.append(
                     {
                         "type": "function_call",
-                        "call_id": tool_call.get("id", ""),
+                        "call_id": tool_call.get("id") or f"call_{id(tool_call)}",
                         "name": function.get("name", ""),
-                        "arguments": function.get("arguments", ""),
+                        "arguments": args if isinstance(args, str) else json.dumps(args),
                     }
                 )
             return items

lib/crewai/src/crewai/utilities/agent_utils.py

@@ -1277,7 +1277,9 @@ def is_tool_call_list(response: list[Any]) -> bool:
     # Bedrock-style
     if isinstance(first_item, dict) and "name" in first_item and "input" in first_item:
         return True
-    # OpenAI Responses API-style (flat dict, no nested "function" key)
+    # OpenAI Responses API-style (flat dict, no nested "function" key). This
+    # intentionally accepts the same broad shape as the Bedrock check above;
+    # only provider paths that return lists reach this classifier.
     if (
         isinstance(first_item, dict)
         and "name" in first_item

lib/crewai/tests/llms/openai/test_openai.py

@@ -1006,6 +1006,37 @@ def test_openai_responses_api_converts_assistant_tool_calls_message():
     }
 
 
+def test_openai_responses_api_preserves_assistant_content_with_tool_calls():
+    """Assistant text must be retained when it accompanies tool calls."""
+    llm = OpenAICompletion(model="gpt-4o-mini", api="responses")
+
+    messages = [
+        {
+            "role": "assistant",
+            "content": "I'll fetch that page now.",
+            "tool_calls": [
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "fetch_page",
+                        "arguments": {"url": "https://example.com"},
+                    },
+                }
+            ],
+        }
+    ]
+
+    params = llm._prepare_responses_params(messages)
+
+    assert params["input"][0] == {
+        "role": "assistant",
+        "content": "I'll fetch that page now.",
+    }
+    assert params["input"][1]["type"] == "function_call"
+    assert params["input"][1]["call_id"].startswith("call_")
+    assert params["input"][1]["arguments"] == '{"url": "https://example.com"}'
+
+
 def test_openai_responses_api_converts_tool_result_message():
     """Regression: tool-role messages (Chat-Completions shape) must become
     function_call_output input items for the Responses API.