refactor(ai_client): _send_minimax_result() returns Result[str]

src/ai_client.py

@@ -2299,15 +2299,16 @@ def _list_grok_models() -> list[str]:
  from src.vendor_capabilities import list_models_for_vendor
  return list_models_for_vendor("grok")
 
-def _send_minimax(md_content: str, user_message: str, base_dir: str,
+def _send_minimax_result(md_content: str, user_message: str, base_dir: str,
  file_items: list[dict[str, Any]] | None = None,
  discussion_history: str = "",
  stream: bool = False,
  pre_tool_callback: Optional[Callable[[str, str, Optional[Callable[[str], str]]], Optional[str]]] = None,
  qa_callback: Optional[Callable[[str], str]] = None,
  stream_callback: Optional[Callable[[str], None]] = None,
- patch_callback: Optional[Callable[[str, str], Optional[str]]] = None) -> str:
+ patch_callback: Optional[Callable[[str, str], Optional[str]]] = None) -> Result[str]:
  from src.openai_compatible import OpenAICompatibleRequest
+ try:
   _ensure_minimax_client()
   tools: list[dict[str, Any]] | None = _get_deepseek_tools() or None
   _repair_minimax_history(_minimax_history)
@@ -2331,14 +2332,16 @@ def _send_minimax(md_content: str, user_message: str, base_dir: str,
      return choice.message.reasoning_details[0].get("text", "") or ""
    return ""
   caps = get_capabilities("minimax", _model)
- return run_with_tool_loop(
+  return Result(data=run_with_tool_loop(
    _minimax_client, _build_minimax_request, capabilities=caps,
    pre_tool_callback=pre_tool_callback, qa_callback=qa_callback, stream_callback=stream_callback,
    patch_callback=patch_callback, base_dir=base_dir, vendor_name="minimax",
    history_lock=_minimax_history_lock, history=_minimax_history,
    trim_func=lambda h: _trim_minimax_history(_build_minimax_request(0).messages, h),
    reasoning_extractor=_extract_minimax_reasoning if caps.reasoning else None,
- )
+  ))
+ except Exception as exc:
+  return Result(data="", errors=[_classify_minimax_error(exc, source="ai_client.minimax")])
 
 #endregion: MiniMax Provider