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

src/ai_client.py

@@ -2247,50 +2247,53 @@ def _ensure_grok_client() -> Any:
   _grok_client = openai.OpenAI(api_key=api_key, base_url="https://api.x.ai/v1")
  return _grok_client
 
-def _send_grok(md_content: str, user_message: str, base_dir: str,
+def _send_grok_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:
- from src.openai_compatible import OpenAICompatibleRequest
- client = _ensure_grok_client()
- tools: list[dict[str, Any]] | None = _get_deepseek_tools() or None
- caps = get_capabilities("grok", _model)
- with _grok_history_lock:
-  user_content = user_message
-  if file_items:
-   for fi in file_items:
-    if fi.get("is_image") and fi.get("base64_data"):
-     user_content = f"[IMAGE: {fi.get('path', 'attachment')}]\n{user_content}"
-  if discussion_history and not _grok_history:
-   _grok_history.append({"role": "user", "content": f"[DISCUSSION HISTORY]\n\n{discussion_history}\n\n---\n\n{user_message}"})
-  else:
-   _grok_history.append({"role": "user", "content": user_content})
- def _build_grok_request(_round_idx: int) -> OpenAICompatibleRequest:
+ patch_callback: Optional[Callable[[str, str], Optional[str]]] = None) -> Result[str]:
+ from src.openai_compatible import OpenAICompatibleRequest, _classify_openai_compatible_error
+ try:
+  client = _ensure_grok_client()
+  tools: list[dict[str, Any]] | None = _get_deepseek_tools() or None
+  caps = get_capabilities("grok", _model)
   with _grok_history_lock:
-   messages: list[dict[str, Any]] = [{"role": "system", "content": f"{_get_combined_system_prompt()}\n\n<context>\n{md_content}\n</context>"}]
-   messages.extend(_grok_history)
-  extra_body: dict[str, Any] = {}
-  if caps.web_search:
-   extra_body["search_parameters"] = {"mode": "auto"}
-  if caps.x_search:
-   extra_body.setdefault("search_parameters", {})
-   extra_body["search_parameters"]["sources"] = [{"type": "x"}]
-  return OpenAICompatibleRequest(
-   messages=messages, model=_model, temperature=_temperature, top_p=_top_p,
-   max_tokens=_max_tokens, stream=stream, stream_callback=stream_callback,
-   tools=tools, tool_choice="auto" if tools else "auto",
-   extra_body=extra_body or None,
-  )
- return run_with_tool_loop(
-  client, _build_grok_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="grok",
-  history_lock=_grok_history_lock, history=_grok_history,
- )
+   user_content = user_message
+   if file_items:
+    for fi in file_items:
+     if fi.get("is_image") and fi.get("base64_data"):
+      user_content = f"[IMAGE: {fi.get('path', 'attachment')}]\n{user_content}"
+   if discussion_history and not _grok_history:
+    _grok_history.append({"role": "user", "content": f"[DISCUSSION HISTORY]\n\n{discussion_history}\n\n---\n\n{user_message}"})
+   else:
+    _grok_history.append({"role": "user", "content": user_content})
+  def _build_grok_request(_round_idx: int) -> OpenAICompatibleRequest:
+   with _grok_history_lock:
+    messages: list[dict[str, Any]] = [{"role": "system", "content": f"{_get_combined_system_prompt()}\n\n<context>\n{md_content}\n</context>"}]
+    messages.extend(_grok_history)
+   extra_body: dict[str, Any] = {}
+   if caps.web_search:
+    extra_body["search_parameters"] = {"mode": "auto"}
+   if caps.x_search:
+    extra_body.setdefault("search_parameters", {})
+    extra_body["search_parameters"]["sources"] = [{"type": "x"}]
+   return OpenAICompatibleRequest(
+    messages=messages, model=_model, temperature=_temperature, top_p=_top_p,
+    max_tokens=_max_tokens, stream=stream, stream_callback=stream_callback,
+    tools=tools, tool_choice="auto" if tools else "auto",
+    extra_body=extra_body or None,
+   )
+  return Result(data=run_with_tool_loop(
+   client, _build_grok_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="grok",
+   history_lock=_grok_history_lock, history=_grok_history,
+  ))
+ except Exception as exc:
+  return Result(data="", errors=[_classify_openai_compatible_error(exc, source="ai_client.grok")])
 
 def _list_grok_models() -> list[str]:
  from src.vendor_capabilities import list_models_for_vendor