fix: Change instruction insertion to respect tool call/response pairs

Make sure _add_instructions_to_user_content skips over user messages that carry function_response parts so tool_use/tool_result blocks stay together

Close #3229

Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 826076141

Author: GWeale

src/google/adk/flows/llm_flows/contents.py

@@ -668,6 +668,16 @@ def _is_live_model_audio_event(event: Event) -> bool:
   return False
 
 
+def _content_contains_function_response(content: types.Content) -> bool:
+  """Checks whether the content includes any function response parts."""
+  if not content.parts:
+    return False
+  for part in content.parts:
+    if part.function_response:
+      return True
+  return False
+
+
 async def _add_instructions_to_user_content(
     invocation_context: InvocationContext,
     llm_request: LlmRequest,
@@ -695,13 +705,14 @@ async def _add_instructions_to_user_content(
 
   if llm_request.contents:
     for i in range(len(llm_request.contents) - 1, -1, -1):
-      if llm_request.contents[i].role != 'user':
+      content = llm_request.contents[i]
+      if content.role != 'user':
         insert_index = i + 1
         break
-      elif i == 0:
-        # All content from start is user content
-        insert_index = 0
+      if _content_contains_function_response(content):
+        insert_index = i + 1
         break
+      insert_index = i
   else:
     # No contents remaining, just append at the end
     insert_index = 0

tests/unittests/flows/llm_flows/test_instructions.py

@@ -923,6 +923,41 @@ async def test_no_dynamic_instructions_when_no_static(llm_backend):
   assert llm_request.contents[0].parts[0].text == "Hello world"
 
 
+@pytest.mark.asyncio
+async def test_instructions_insert_after_function_response():
+  """Ensure instruction insertion does not split tool_use/tool_result pairs."""
+  agent = LlmAgent(name="test_agent")
+  invocation_context = await _create_invocation_context(agent)
+
+  tool_call = types.Part.from_function_call(
+      name="echo_tool", args={"echo": "value"}
+  )
+  tool_response = types.Part.from_function_response(
+      name="echo_tool", response={"result": "value"}
+  )
+
+  llm_request = LlmRequest(
+      contents=[
+          types.Content(role="assistant", parts=[tool_call]),
+          types.Content(role="user", parts=[tool_response]),
+      ]
+  )
+  instruction_contents = [
+      types.Content(
+          role="user", parts=[types.Part.from_text(text="Dynamic instruction")]
+      )
+  ]
+
+  await _add_instructions_to_user_content(
+      invocation_context, llm_request, instruction_contents
+  )
+
+  assert len(llm_request.contents) == 3
+  assert llm_request.contents[0].parts[0].function_call
+  assert llm_request.contents[1].parts[0].function_response
+  assert llm_request.contents[2].parts[0].text == "Dynamic instruction"
+
+
 @pytest.mark.parametrize("llm_backend", ["GOOGLE_AI", "VERTEX"])
 @pytest.mark.asyncio
 async def test_static_instruction_with_files_and_text(llm_backend):