fix: apply ruff formatting to _sap_ai_core.py

Author: Huimin Tai

python/packages/kagent-adk/src/kagent/adk/models/_sap_ai_core.py

@@ -114,11 +114,13 @@ def _build_orchestration_template(
             if text_parts:
                 template.append({"role": role, "content": "\n".join(text_parts)})
             for tool_call_id, resp_content in function_responses:
-                template.append({
-                    "role": "tool",
-                    "tool_call_id": tool_call_id,
-                    "content": resp_content,
-                })
+                template.append(
+                    {
+                        "role": "tool",
+                        "tool_call_id": tool_call_id,
+                        "content": resp_content,
+                    }
+                )
         elif text_parts:
             template.append({"role": role, "content": "\n".join(text_parts)})
 
@@ -131,14 +133,16 @@ def _build_orchestration_tools(
     openai_tools = _convert_tools_to_openai(tools)
     result = []
     for t in openai_tools:
-        result.append({
-            "type": "function",
-            "function": {
-                "name": t["function"]["name"],
-                "description": t["function"].get("description", ""),
-                "parameters": t["function"].get("parameters", {"type": "object", "properties": {}}),
-            },
-        })
+        result.append(
+            {
+                "type": "function",
+                "function": {
+                    "name": t["function"]["name"],
+                    "description": t["function"].get("description", ""),
+                    "parameters": t["function"].get("parameters", {"type": "object", "properties": {}}),
+                },
+            }
+        )
     return result
 
 
@@ -316,8 +320,7 @@ async def generate_content_async(
 
         if llm_request.config and llm_request.config.tools:
             genai_tools: list[types.Tool] = [
-                t for t in llm_request.config.tools
-                if isinstance(t, types.Tool) and hasattr(t, "function_declarations")
+                t for t in llm_request.config.tools if isinstance(t, types.Tool) and hasattr(t, "function_declarations")
             ]
             if genai_tools:
                 orch_tools = _build_orchestration_tools(genai_tools)
@@ -388,7 +391,7 @@ async def _stream_request(
                 if not line:
                     continue
 
-                payload = line[len("data: "):] if line.startswith("data: ") else line
+                payload = line[len("data: ") :] if line.startswith("data: ") else line
                 if payload == "[DONE]":
                     break
 
@@ -463,9 +466,7 @@ async def _stream_request(
             usage_metadata=usage_metadata,
         )
 
-    async def _non_stream_request(
-        self, url: str, headers: dict[str, str], body: dict[str, Any]
-    ) -> LlmResponse:
+    async def _non_stream_request(self, url: str, headers: dict[str, str], body: dict[str, Any]) -> LlmResponse:
         client = self._get_http_client()
         resp = await client.post(url, headers=headers, json=body)
         resp.raise_for_status()
@@ -490,11 +491,15 @@ async def _non_stream_request(
                 parts.append(part)
 
         usage = result.get("usage", {})
-        usage_metadata = types.GenerateContentResponseUsageMetadata(
-            prompt_token_count=usage.get("prompt_tokens"),
-            candidates_token_count=usage.get("completion_tokens"),
-            total_token_count=usage.get("total_tokens"),
-        ) if usage else None
+        usage_metadata = (
+            types.GenerateContentResponseUsageMetadata(
+                prompt_token_count=usage.get("prompt_tokens"),
+                candidates_token_count=usage.get("completion_tokens"),
+                total_token_count=usage.get("total_tokens"),
+            )
+            if usage
+            else None
+        )
 
         stop_reason = result.get("choices", [{}])[0].get("finish_reason", "stop")
         fr = self._map_finish_reason(stop_reason)