fix(litellm): collect all tools so native tools aren't dropped

_get_completion_inputs only converted tools[0].function_declarations, so
Tools carrying only native/built-in tools (e.g. google_search) produced
tools=None and any Tool past index 0 was ignored entirely. Loop over all
config.tools instead: convert function declarations as before and serialize
native tools via model_dump(by_alias=True, exclude_none=True) into the same
list. Apply the same fix to the tools[0]-only slice in _build_request_log.

Fixes #6091

Author: vup903

src/google/adk/models/lite_llm.py

@@ -27,7 +27,6 @@
 import sys
 from typing import Any
 from typing import AsyncGenerator
-from typing import cast
 from typing import Dict
 from typing import Generator
 from typing import Iterable
@@ -2376,15 +2375,22 @@ async def _get_completion_inputs(
 
   # 2. Convert tool declarations
   tools: Optional[List[Dict[str, Any]]] = None
-  if (
-      llm_request.config
-      and llm_request.config.tools
-      and llm_request.config.tools[0].function_declarations
-  ):
-    tools = [
-        _function_declaration_to_tool_param(tool)
-        for tool in llm_request.config.tools[0].function_declarations
-    ]
+  if llm_request.config and llm_request.config.tools:
+    tools = []
+    for tool in llm_request.config.tools:
+      if not isinstance(tool, types.Tool):
+        continue
+      if tool.function_declarations:
+        tools.extend(
+            _function_declaration_to_tool_param(func_decl)
+            for func_decl in tool.function_declarations
+        )
+      else:
+        # Native/built-in tools (e.g. google_search) carry no
+        # function_declarations; serialize them as-is so they reach the
+        # provider or proxy instead of being silently dropped.
+        tools.append(tool.model_dump(by_alias=True, exclude_none=True))
+    tools = tools or None
 
   # 3. Handle response format
   response_format: dict[str, Any] | None = None
@@ -2458,10 +2464,12 @@ def _build_request_log(req: LlmRequest) -> str:
     The request log.
   """
 
-  function_decls: list[types.FunctionDeclaration] = cast(
-      list[types.FunctionDeclaration],
-      req.config.tools[0].function_declarations if req.config.tools else [],
-  )
+  function_decls: list[types.FunctionDeclaration] = [
+      func_decl
+      for tool in req.config.tools or []
+      if isinstance(tool, types.Tool) and tool.function_declarations
+      for func_decl in tool.function_declarations
+  ]
   function_logs = (
       [
           _build_function_declaration_log(func_decl)

tests/unittests/models/test_litellm.py

@@ -668,6 +668,105 @@ async def test_get_completion_inputs_inserts_missing_tool_results():
   assert tool_message["content"] == _MISSING_TOOL_RESULT_MESSAGE
 
 
+@pytest.mark.asyncio
+async def test_get_completion_inputs_serializes_native_only_tool():
+  llm_request = LlmRequest(
+      config=types.GenerateContentConfig(
+          tools=[types.Tool(google_search=types.GoogleSearch())]
+      )
+  )
+
+  _, tools, _, _ = await _get_completion_inputs(
+      llm_request, model="openai/gpt-4o"
+  )
+
+  assert tools == [
+      types.Tool(google_search=types.GoogleSearch()).model_dump(
+          by_alias=True, exclude_none=True
+      )
+  ]
+
+
+@pytest.mark.asyncio
+async def test_get_completion_inputs_mixed_native_and_function_tools():
+  llm_request = LlmRequest(
+      config=types.GenerateContentConfig(
+          tools=[
+              types.Tool(google_search=types.GoogleSearch()),
+              types.Tool(
+                  function_declarations=[
+                      types.FunctionDeclaration(
+                          name="get_weather",
+                          description="Gets the weather.",
+                          parameters=types.Schema(
+                              type=types.Type.OBJECT,
+                              properties={
+                                  "city": types.Schema(type=types.Type.STRING)
+                              },
+                          ),
+                      )
+                  ]
+              ),
+          ]
+      )
+  )
+
+  _, tools, _, _ = await _get_completion_inputs(
+      llm_request, model="openai/gpt-4o"
+  )
+
+  assert len(tools) == 2
+  native_tools = [t for t in tools if "type" not in t]
+  function_tools = [t for t in tools if t.get("type") == "function"]
+  assert len(native_tools) == 1
+  assert len(function_tools) == 1
+  assert function_tools[0]["function"]["name"] == "get_weather"
+
+
+@pytest.mark.asyncio
+async def test_get_completion_inputs_collects_tools_beyond_index_zero():
+  llm_request = LlmRequest(
+      config=types.GenerateContentConfig(
+          tools=[
+              types.Tool(
+                  function_declarations=[
+                      types.FunctionDeclaration(
+                          name="first_tool", description="First tool."
+                      )
+                  ]
+              ),
+              types.Tool(
+                  function_declarations=[
+                      types.FunctionDeclaration(
+                          name="second_tool", description="Second tool."
+                      )
+                  ]
+              ),
+          ]
+      )
+  )
+
+  _, tools, _, _ = await _get_completion_inputs(
+      llm_request, model="openai/gpt-4o"
+  )
+
+  assert [t["function"]["name"] for t in tools] == [
+      "first_tool",
+      "second_tool",
+  ]
+
+
+@pytest.mark.asyncio
+async def test_get_completion_inputs_no_tools_returns_none():
+  llm_request = LlmRequest(config=types.GenerateContentConfig())
+
+  _, tools, _, _ = await _get_completion_inputs(
+      llm_request, model="openai/gpt-4o"
+  )
+
+  assert tools is None
+
+
 def test_schema_to_dict_filters_none_enum_values():
   # Use model_construct to bypass strict enum validation.
   top_level_schema = types.Schema.model_construct(