fix(google_genai): read functionDeclarations.parameters in the generateContent bridge

The generate_content -> chat/completions bridge only read
functionDeclarations[].parametersJsonSchema, the field gemini-cli sends.
The google-genai SDKs serialize tool schemas to `parameters`, so those
requests reached the upstream provider with a function that had a name
and description but no arguments, and the model invented its own.

Fall back to `parameters` when `parametersJsonSchema` is absent, and
declare it on _GenAIFunctionDeclaration.

litellm/google_genai/adapters/transformation.py

@@ -47,6 +47,7 @@ class _GenAIPart(TypedDict, total=False):
 class _GenAIFunctionDeclaration(TypedDict, total=False):
     name: ReadOnly[str]
     description: ReadOnly[str]
+    parameters: ReadOnly[dict[str, object]]
     parametersJsonSchema: ReadOnly[dict[str, object]]
 
 
@@ -359,6 +360,8 @@ class GoogleGenAIAdapter:
                         function_chunk["description"] = func_decl["description"]
                     if "parametersJsonSchema" in func_decl:
                         function_chunk["parameters"] = func_decl["parametersJsonSchema"]
+                    elif "parameters" in func_decl:
+                        function_chunk["parameters"] = func_decl["parameters"]
 
                     openai_tool: dict[str, object] = {"type": "function", "function": function_chunk}
                     openai_tools.append(openai_tool)

tests/test_litellm/google_genai/test_google_genai_adapter.py

@@ -1276,3 +1276,85 @@ def test_inline_data_backward_compatibility_text_only():
         content, str
     ), "Content should be a string for text-only messages (backward compatibility)"
     assert content == "Hello, how are you?"
+
+
+def test_tools_transformation_parameters_field():
+    """FunctionDeclaration.parameters must survive the generate_content -> completion bridge.
+
+    The google-genai SDKs serialize tool schemas to `parameters`; only gemini-cli
+    sends `parametersJsonSchema`. Reading just the latter silently dropped the
+    schema, so the upstream model received a function with no arguments.
+    """
+    from litellm.google_genai.adapters.transformation import GoogleGenAIAdapter
+
+    adapter = GoogleGenAIAdapter()
+
+    schema = {
+        "type": "OBJECT",
+        "properties": {"city": {"type": "STRING", "description": "City name"}},
+        "required": ["city"],
+    }
+    tools = [
+        {
+            "functionDeclarations": [
+                {
+                    "name": "get_weather",
+                    "description": "Get the weather for a city",
+                    "parameters": schema,
+                }
+            ]
+        }
+    ]
+
+    completion_request = adapter.translate_generate_content_to_completion(
+        model="gpt-3.5-turbo",
+        contents={"role": "user", "parts": [{"text": "Weather in Hanoi?"}]},
+        tools=tools,
+    )
+
+    function = completion_request["tools"][0]["function"]
+    assert function["name"] == "get_weather"
+    assert function["parameters"] == {
+        "type": "object",
+        "properties": {"city": {"type": "string", "description": "City name"}},
+        "required": ["city"],
+    }
+
+
+def test_tools_transformation_prefers_parameters_json_schema():
+    """When both fields are present, parametersJsonSchema wins."""
+    from litellm.google_genai.adapters.transformation import GoogleGenAIAdapter
+
+    adapter = GoogleGenAIAdapter()
+
+    tools = [
+        {
+            "functionDeclarations": [
+                {
+                    "name": "get_weather",
+                    "parameters": {
+                        "type": "OBJECT",
+                        "properties": {"ignored": {"type": "STRING"}},
+                    },
+                    "parametersJsonSchema": {
+                        "type": "object",
+                        "properties": {"city": {"type": "string"}},
+                        "required": ["city"],
+                    },
+                }
+            ]
+        }
+    ]
+
+    completion_request = adapter.translate_generate_content_to_completion(
+        model="gpt-3.5-turbo",
+        contents={"role": "user", "parts": [{"text": "Weather in Hanoi?"}]},
+        tools=tools,
+    )
+
+    function = completion_request["tools"][0]["function"]
+    assert function["parameters"] == {
+        "type": "object",
+        "properties": {"city": {"type": "string"}},
+        "required": ["city"],
+    }