address review feedback

Author: douglas-reid

contributing/samples/hello_world_gemma3_ollama/agent.py

@@ -72,8 +72,8 @@ async def check_prime(nums: list[int]) -> str:
     instruction="""
       You roll dice and answer questions about the outcome of the dice rolls.
       You can roll dice of different sizes.
-      You can use multiple tools in parallel by calling functions in parallel(in one request and in one round).
-      It is ok to discuss previous dice roles, and comment on the dice rolls.
+      You can use multiple tools in parallel by calling functions in parallel (in one request and in one round).
+      It is ok to discuss previous dice rolls, and comment on the dice rolls.
       When you are asked to roll a die, you must call the roll_die tool with the number of sides. Be sure to pass in an integer. Do not pass in a string.
       You should never roll a die on your own.
       When checking prime numbers, call the check_prime tool with a list of integers. Be sure to pass in a list of integers. You should never pass in a string.

contributing/samples/hello_world_gemma3_ollama/main.py

@@ -41,7 +41,7 @@ async def main():
       artifact_service=artifact_service,
       session_service=session_service,
   )
-  session_11 = await session_service.create_session(
+  session_1 = await session_service.create_session(
       app_name=app_name, user_id=user_id_1
   )
 
@@ -61,12 +61,12 @@ async def run_prompt(session: Session, new_message: str):
   start_time = time.time()
   print('Start time:', start_time)
   print('------------------------------------')
-  await run_prompt(session_11, 'Hi, introduce yourself.')
+  await run_prompt(session_1, 'Hi, introduce yourself.')
   await run_prompt(
-      session_11, 'Roll a die with 100 sides and check if it is prime'
+      session_1, 'Roll a die with 100 sides and check if it is prime'
   )
-  await run_prompt(session_11, 'Roll it again.')
-  await run_prompt(session_11, 'What numbers did I get?')
+  await run_prompt(session_1, 'Roll it again.')
+  await run_prompt(session_1, 'What numbers did I get?')
   end_time = time.time()
   print('------------------------------------')
   print('End time:', end_time)

pyproject.toml

@@ -113,6 +113,7 @@ test = [
   "a2a-sdk>=0.3.0,<0.4.0;python_version>='3.10'",
   "anthropic>=0.43.0",                            # For anthropic model tests
   "crewai[tools];python_version>='3.10'",         # For CrewaiTool tests
+  "instructor>=1.11.3",                           # For instructor (Gemma3 parsing)
   "kubernetes>=29.0.0",                           # For GkeCodeExecutor
   "langchain-community>=0.3.17",
   "langgraph>=0.2.60, <0.4.8",                    # For LangGraphAgent
@@ -144,14 +145,14 @@ extensions = [
   "beautifulsoup4>=3.2.2",                      # For load_web_page tool.
   "crewai[tools];python_version>='3.10'",       # For CrewaiTool
   "docker>=7.0.0",                              # For ContainerCodeExecutor
+  "instructor>=1.11.3",                         # For instructor (Gemma3 parsing)
   "kubernetes>=29.0.0",                         # For GkeCodeExecutor
   "langgraph>=0.2.60, <0.4.8",                  # For LangGraphAgent
   "litellm>=1.75.5",                            # For LiteLlm class. Currently has OpenAI limitations. TODO: once LiteLlm fix it
   "llama-index-readers-file>=0.4.0",            # For retrieval using LlamaIndex.
   "llama-index-embeddings-google-genai>=0.3.0", # For files retrieval using LlamaIndex.
   "lxml>=5.3.0",                                # For load_web_page tool.
   "toolbox-core>=0.1.0",                        # For tools.toolbox_toolset.ToolboxToolset
-  "instructor>=1.11.3",                         # For instructor (Gemma3 parsing)
 ]
 
 otel-gcp = ["opentelemetry-instrumentation-google-genai>=0.3b0, <1.0.0"]

src/google/adk/models/gemma_llm.py

@@ -243,7 +243,15 @@ def _extract_function_calls_from_response(llm_response: LlmResponse):
 
   try:
     import instructor
+  except ImportError as e:
+    logger.warning(
+        "The 'instructor' package is required for Gemma3 function calling but"
+        " is not installed. Text response will be returned. To enable function"
+        ' calling, run: pip install "google-adk[extensions]"'
+    )
+    return
 
+  try:
     json_candidate = instructor.utils.extract_json_from_codeblock(response_text)
 
     if not json_candidate:

tests/unittests/models/test_gemma_llm.py

@@ -122,6 +122,7 @@ async def test_gemma_gemini_preprocess_request(llm_request):
   assert llm_request.contents[0].parts[0].text == want_content_text
 
 
+@pytest.mark.asyncio
 async def test_gemma_gemini_preprocess_request_with_tools(
     llm_request_with_tools,
 ):