fix(oci): preserve all tool results for parallel function calls

src/google/adk/cli/conformance/cli_record.py

@@ -72,23 +72,18 @@ async def _create_conformance_test_files(
         # long-running tool. Replace the function call ID with the actual
         # function call ID. This is needed because the function call ID is not
         # known when writing the test case.
-        if (
-            user_message.content.parts
-            and user_message.content.parts[0].function_response
-            and user_message.content.parts[0].function_response.name
-        ):
-          if (
-              user_message.content.parts[0].function_response.name
-              not in function_call_name_to_id_map
-          ):
-            raise ValueError(
-                "Function response for"
-                f" {user_message.content.parts[0].function_response.name} does"
-                " not match any pending function call."
-            )
-          content.parts[0].function_response.id = function_call_name_to_id_map[
-              user_message.content.parts[0].function_response.name
-          ]
+        if user_message.content.parts:
+          for part in content.parts:
+            if part.function_response and part.function_response.name:
+              if part.function_response.name not in function_call_name_to_id_map:
+                raise ValueError(
+                    "Function response for"
+                    f" {part.function_response.name} does"
+                    " not match any pending function call."
+                )
+              part.function_response.id = function_call_name_to_id_map[
+                  part.function_response.name
+              ]
       elif user_message.text is not None:
         content = types.UserContent(parts=[types.Part(text=user_message.text)])
       else:

src/google/adk/cli/conformance/cli_test.py

@@ -142,23 +142,18 @@ async def _run_user_messages(
         # long-running tool. Replace the function call ID with the actual
         # function call ID. This is needed because the function call ID is not
         # known when writing the test case.
-        if (
-            user_message.content.parts
-            and user_message.content.parts[0].function_response
-            and user_message.content.parts[0].function_response.name
-        ):
-          if (
-              user_message.content.parts[0].function_response.name
-              not in function_call_name_to_id_map
-          ):
-            raise ValueError(
-                "Function response for"
-                f" {user_message.content.parts[0].function_response.name} does"
-                " not match any pending function call."
-            )
-          content.parts[0].function_response.id = function_call_name_to_id_map[
-              user_message.content.parts[0].function_response.name
-          ]
+        if user_message.content.parts:
+          for part in content.parts:
+            if part.function_response and part.function_response.name:
+              if part.function_response.name not in function_call_name_to_id_map:
+                raise ValueError(
+                    "Function response for"
+                    f" {part.function_response.name} does"
+                    " not match any pending function call."
+                )
+              part.function_response.id = function_call_name_to_id_map[
+                  part.function_response.name
+              ]
       elif user_message.text is not None:
         content = types.UserContent(parts=[types.Part(text=user_message.text)])
       else:

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

@@ -714,12 +714,10 @@ async def run_live(
                 # the same function response. By handling agent transfer here,
                 # we ensure that only child agent processes its own function
                 # responses after the transfer.
-                if (
-                    event.content
-                    and event.content.parts
-                    and event.content.parts[0].function_response
-                    and event.content.parts[0].function_response.name
-                    == 'transfer_to_agent'
+                if event.content and event.content.parts and any(
+                    part.function_response
+                    and part.function_response.name == 'transfer_to_agent'
+                    for part in event.content.parts
                 ):
                   await asyncio.sleep(DEFAULT_TRANSFER_AGENT_DELAY)
                   # cancel the tasks that belongs to the closed connection.
@@ -751,12 +749,10 @@ async def run_live(
                     ) as agen:
                       async for item in agen:
                         yield item
-                if (
-                    event.content
-                    and event.content.parts
-                    and event.content.parts[0].function_response
-                    and event.content.parts[0].function_response.name
-                    == 'task_completed'
+                if event.content and event.content.parts and any(
+                    part.function_response
+                    and part.function_response.name == 'task_completed'
+                    for part in event.content.parts
                 ):
                   # this is used for sequential agent to signal the end of the agent.
                   await asyncio.sleep(DEFAULT_TASK_COMPLETION_DELAY)

src/google/adk/integrations/oci/_oci_genai_llm.py

@@ -198,12 +198,15 @@ def _content_to_oci_message(content: types.Content) -> Any:
 
   # Tool results map to ToolMessage (one per result)
   if tool_results:
-    call_id, result_text = tool_results[0]
-    return oci_models.ToolMessage(
-        role=oci_models.ToolMessage.ROLE_TOOL,
-        tool_call_id=call_id,
-        content=[oci_models.TextContent(type="TEXT", text=result_text)],
-    )
+    tool_messages = [
+        oci_models.ToolMessage(
+            role=oci_models.ToolMessage.ROLE_TOOL,
+            tool_call_id=call_id,
+            content=[oci_models.TextContent(type="TEXT", text=result_text)],
+        )
+        for call_id, result_text in tool_results
+    ]
+    return tool_messages if len(tool_messages) > 1 else tool_messages[0]
 
   if role == "ASSISTANT":
     oci_content: list[Any] = []
@@ -451,7 +454,13 @@ def _build_chat_details(
     """Build OCI ChatDetails from an LlmRequest."""
     import oci.generative_ai_inference.models as oci_models
 
-    messages = [_content_to_oci_message(c) for c in llm_request.contents or []]
+    messages = []
+    for c in llm_request.contents or []:
+      message_or_list = _content_to_oci_message(c)
+      if isinstance(message_or_list, list):
+        messages.extend(message_or_list)
+      else:
+        messages.append(message_or_list)
 
     # Prepend SystemMessage when a system instruction is present
     if llm_request.config and llm_request.config.system_instruction:

src/google/adk/telemetry/tracing.py

@@ -260,8 +260,11 @@ def trace_tool_call(
       and function_response_event.content is not None
       and function_response_event.content.parts
   ):
-    response_parts = function_response_event.content.parts
-    function_response = response_parts[0].function_response
+    function_response = None
+    for part in function_response_event.content.parts:
+      if part.function_response and part.function_response.name == tool.name:
+        function_response = part.function_response
+        break
     if function_response is not None:
       if function_response.id is not None:
         tool_call_id = function_response.id

src/google/adk/tools/load_artifacts_tool.py

@@ -286,46 +286,47 @@ async def _append_artifacts_to_llm_request(
     # Attach the content of the artifacts if the model requests them.
     # This only adds the content to the model request, instead of the session.
     if llm_request.contents and llm_request.contents[-1].parts:
-      function_response = llm_request.contents[-1].parts[0].function_response
-      if function_response and function_response.name == 'load_artifacts':
-        response = function_response.response or {}
-        artifact_names = response.get('artifact_names', [])
-        for artifact_name in artifact_names:
-          # Try session-scoped first (default behavior)
-          artifact = await tool_context.load_artifact(artifact_name)
-
-          # If not found and name doesn't already have user: prefix,
-          # try cross-session artifacts with user: prefix
-          if artifact is None and not artifact_name.startswith('user:'):
-            prefixed_name = f'user:{artifact_name}'
-            artifact = await tool_context.load_artifact(prefixed_name)
-
-          if artifact is None:
-            logger.warning('Artifact "%s" not found, skipping', artifact_name)
-            continue
-
-          artifact_part = _as_safe_part_for_llm(artifact, artifact_name)
-          if artifact_part is not artifact:
-            mime_type = (
-                artifact.inline_data.mime_type if artifact.inline_data else None
-            )
-            logger.debug(
-                'Converted artifact "%s" (mime_type=%s) to text Part',
-                artifact_name,
-                mime_type,
-            )
-
-          llm_request.contents.append(
-              types.Content(
-                  role='user',
-                  parts=[
-                      types.Part.from_text(
-                          text=f'Artifact {artifact_name} is:'
-                      ),
-                      artifact_part,
-                  ],
+      for part in llm_request.contents[-1].parts:
+        function_response = part.function_response
+        if function_response and function_response.name == 'load_artifacts':
+          response = function_response.response or {}
+          artifact_names = response.get('artifact_names', [])
+          for artifact_name in artifact_names:
+            # Try session-scoped first (default behavior)
+            artifact = await tool_context.load_artifact(artifact_name)
+
+            # If not found and name doesn't already have user: prefix,
+            # try cross-session artifacts with user: prefix
+            if artifact is None and not artifact_name.startswith('user:'):
+              prefixed_name = f'user:{artifact_name}'
+              artifact = await tool_context.load_artifact(prefixed_name)
+
+            if artifact is None:
+              logger.warning('Artifact "%s" not found, skipping', artifact_name)
+              continue
+
+            artifact_part = _as_safe_part_for_llm(artifact, artifact_name)
+            if artifact_part is not artifact:
+              mime_type = (
+                  artifact.inline_data.mime_type if artifact.inline_data else None
+              )
+              logger.debug(
+                  'Converted artifact "%s" (mime_type=%s) to text Part',
+                  artifact_name,
+                  mime_type,
               )
-          )
+
+            llm_request.contents.append(
+                types.Content(
+                    role='user',
+                    parts=[
+                        types.Part.from_text(
+                            text=f'Artifact {artifact_name} is:'
+                        ),
+                        artifact_part,
+                    ],
+                )
+            )
 
 
 load_artifacts_tool = LoadArtifactsTool()

src/google/adk/tools/load_mcp_resource_tool.py

@@ -124,32 +124,33 @@ async def _append_resources_to_llm_request(
 
     # Attach content
     if llm_request.contents and llm_request.contents[-1].parts:
-      function_response = llm_request.contents[-1].parts[0].function_response
-      if function_response and function_response.name == self.name:
-        response = function_response.response or {}
-        resource_names = response.get("resource_names", [])
-        for resource_name in resource_names:
-          try:
-            contents = await self._mcp_toolset.read_resource(resource_name)
-
-            for content in contents:
-              part = self._mcp_content_to_part(content, resource_name)
-              llm_request.contents.append(
-                  types.Content(
-                      role="user",
-                      parts=[
-                          types.Part.from_text(
-                              text=f"Resource {resource_name} is:"
-                          ),
-                          part,
-                      ],
-                  )
+      for part in llm_request.contents[-1].parts:
+        function_response = part.function_response
+        if function_response and function_response.name == self.name:
+          response = function_response.response or {}
+          resource_names = response.get("resource_names", [])
+          for resource_name in resource_names:
+            try:
+              contents = await self._mcp_toolset.read_resource(resource_name)
+
+              for content in contents:
+                part = self._mcp_content_to_part(content, resource_name)
+                llm_request.contents.append(
+                    types.Content(
+                        role="user",
+                        parts=[
+                            types.Part.from_text(
+                                text=f"Resource {resource_name} is:"
+                            ),
+                            part,
+                        ],
+                    )
+                )
+            except Exception as e:
+              logger.warning(
+                  "Failed to read MCP resource '%s': %s", resource_name, e
               )
-          except Exception as e:
-            logger.warning(
-                "Failed to read MCP resource '%s': %s", resource_name, e
-            )
-            continue
+              continue
 
   def _mcp_content_to_part(
       self, content: Any, resource_name: str

tests/unittests/integrations/oci/test_oci_genai_llm.py

@@ -227,6 +227,60 @@ def test_content_to_oci_message_function_response():
   assert msg.content[0].text
 
 
+def test_content_to_oci_message_multiple_function_responses():
+  import oci.generative_ai_inference.models as oci_models
+
+  part1 = Part.from_function_response(
+      name="get_weather", response={"result": "Sunny, 22°C"}
+  )
+  part1.function_response.id = "call_A"
+
+  part2 = Part.from_function_response(
+      name="get_price", response={"result": "$150"}
+  )
+  part2.function_response.id = "call_B"
+
+  content = Content(role="user", parts=[part1, part2])
+  msgs = _content_to_oci_message(content)
+
+  assert isinstance(msgs, list)
+  assert len(msgs) == 2
+
+  assert isinstance(msgs[0], oci_models.ToolMessage)
+  assert msgs[0].tool_call_id == "call_A"
+
+  assert isinstance(msgs[1], oci_models.ToolMessage)
+  assert msgs[1].tool_call_id == "call_B"
+
+
+def test_build_chat_details_flattens_multiple_tool_messages(oci_llm):
+  import oci.generative_ai_inference.models as oci_models
+
+  part1 = Part.from_function_response(
+      name="get_weather", response={"result": "Sunny, 22°C"}
+  )
+  part1.function_response.id = "call_A"
+
+  part2 = Part.from_function_response(
+      name="get_price", response={"result": "$150"}
+  )
+  part2.function_response.id = "call_B"
+
+  request = LlmRequest(
+      model="google.gemini-2.5-flash",
+      contents=[Content(role="user", parts=[part1, part2])]
+  )
+
+  chat_details = oci_llm._build_chat_details(request)
+  messages = chat_details.chat_request.messages
+
+  assert len(messages) == 2
+  assert isinstance(messages[0], oci_models.ToolMessage)
+  assert messages[0].tool_call_id == "call_A"
+  assert isinstance(messages[1], oci_models.ToolMessage)
+  assert messages[1].tool_call_id == "call_B"
+
+
 # ---------------------------------------------------------------------------
 # _oci_response_to_llm_response
 # ---------------------------------------------------------------------------

tests/unittests/telemetry/test_spans.py

@@ -542,7 +542,7 @@ def test_trace_tool_call_with_scalar_response(
           types.Part(
               function_response=types.FunctionResponse(
                   id=test_tool_call_id,
-                  name='test_function_1',
+                  name=mock_tool_fixture.name,
                   response={'result': scalar_function_response},
               )
           ),
@@ -602,7 +602,7 @@ def test_trace_tool_call_with_dict_response(
           types.Part(
               function_response=types.FunctionResponse(
                   id=test_tool_call_id,
-                  name='test_function_1',
+                  name=mock_tool_fixture.name,
                   response=dict_function_response,
               )
           ),