Fix bug using Ollama with Agents and None tool_calls in final message (#19844)

* fix bug with agents and ollama where it retrieves tools from ollama message, but is None and tries to check len.  This error occurs when you create an agent with streaming = false and give it an ollama llm

* added test to check get_tool_calls_from_response gracefully returns if no tools were called

* Added more tests for achat and chat with tools.  Also fixed tests because sometimes chat was still trying to use song generation tool to respond to greeting even when told not to.  Switched to a math tool and result is more consistent with it no using the passed in tool.

* Updated version to 0.7.3

* Removed unused tool for test

* Removed unused test

Author: woofy0

llama-index-integrations/llms/llama-index-llms-ollama/llama_index/llms/ollama/base.py

@@ -308,7 +308,7 @@ def get_tool_calls_from_response(
         error_on_no_tool_call: bool = True,
     ) -> List[ToolSelection]:
         """Predict and call the tool."""
-        tool_calls = response.message.additional_kwargs.get("tool_calls", [])
+        tool_calls = response.message.additional_kwargs.get("tool_calls", []) or []
         if len(tool_calls) < 1:
             if error_on_no_tool_call:
                 raise ValueError(
@@ -353,7 +353,7 @@ def chat(self, messages: Sequence[ChatMessage], **kwargs: Any) -> ChatResponse:
 
         response = dict(response)
 
-        tool_calls = response["message"].get("tool_calls", [])
+        tool_calls = response["message"].get("tool_calls", []) or []
         thinking = response["message"].get("thinking", None)
         token_counts = self._get_response_token_counts(response)
         if token_counts:
@@ -535,7 +535,7 @@ async def achat(
 
         response = dict(response)
 
-        tool_calls = response["message"].get("tool_calls", [])
+        tool_calls = response["message"].get("tool_calls", []) or []
         thinking = response["message"].get("thinking", None)
         token_counts = self._get_response_token_counts(response)
         if token_counts:

llama-index-integrations/llms/llama-index-llms-ollama/pyproject.toml

@@ -27,7 +27,7 @@ dev = [
 
 [project]
 name = "llama-index-llms-ollama"
-version = "0.7.2"
+version = "0.7.3"
 description = "llama-index llms ollama integration"
 authors = [{name = "Your Name", email = "[email protected]"}]
 requires-python = ">=3.9,<4.0"

llama-index-integrations/llms/llama-index-llms-ollama/tests/test_llms_ollama.py

@@ -208,3 +208,51 @@ async def test_async_chat_with_think() -> None:
     think = response.message.additional_kwargs.get("thinking", None)
     assert think is not None
     assert str(think).strip() != ""
+
+
+@pytest.mark.skipif(
+    client is None, reason="Ollama client is not available or test model is missing"
+)
+def test_chat_with_tools_returns_empty_array_if_no_tools_were_called() -> None:
+    """Make sure get_tool_calls_from_response can gracefully handle no tools in response"""
+    llm = Ollama(model=test_model, context_window=1000)
+    response = llm.chat(
+        tools=[],
+        messages=[
+            ChatMessage(
+                role="system",
+                content="You are a useful tool calling agent.",
+            ),
+            ChatMessage(role="user", content="Hello, how are you?"),
+        ],
+    )
+
+    assert response.message.additional_kwargs.get("tool_calls", []) == []
+
+    tool_calls = llm.get_tool_calls_from_response(response, error_on_no_tool_call=False)
+    assert len(tool_calls) == 0
+
+
+@pytest.mark.skipif(
+    client is None, reason="Ollama client is not available or test model is missing"
+)
+@pytest.mark.asyncio
+async def test_async_chat_with_tools_returns_empty_array_if_no_tools_were_called() -> (
+    None
+):
+    """
+    Test that achat returns [] for no tool calls since subsequent processes expect []
+    instead of None
+    """
+    llm = Ollama(model=test_model, context_window=1000)
+    response = await llm.achat(
+        tools=[],
+        messages=[
+            ChatMessage(
+                role="system",
+                content="You are a useful tool calling agent.",
+            ),
+            ChatMessage(role="user", content="Hello, how are you?"),
+        ],
+    )
+    assert response.message.additional_kwargs.get("tool_calls", []) == []