fix(ai_client): move openai_compatible imports to local scope; fix startup_speedup invariant

The follow-up track's tool-loop refactor moved
'from src.openai_compatible import send_openai_compatible,
 OpenAICompatibleRequest, NormalizedResponse' to MODULE level
in src/ai_client.py. This violates the startup_speedup_20260606
invariant: heavy SDKs must not be loaded at module level because
ai_client.py is on the main thread's import chain.

src/openai_compatible.py line 5 does 'from openai import
OpenAIError, ...', so any import from it triggers the openai SDK
to load. test_ai_client_does_not_import_openai_at_module_level
guards this invariant and was failing.

Fix: move the imports back to local scope inside the function
bodies that need them:
- _default_send closure inside run_with_tool_loop
  (imports send_openai_compatible)
- _send_grok (imports OpenAICompatibleRequest)
- _send_minimax (imports OpenAICompatibleRequest)
- _send_llama (imports OpenAICompatibleRequest)
- _send_gemini_cli (imports OpenAICompatibleRequest + NormalizedResponse)

Test patches: tests that previously patched
'src.ai_client.send_openai_compatible' now patch
'src.openai_compatible.send_openai_compatible' (the actual
import source). _execute_tool_calls_concurrently patches
unchanged (it's defined in src/ai_client.py itself).

Green confirmed: 62 vendor + tool + import-isolation tests
pass. 0 regressions.

src/ai_client.py

@@ -42,7 +42,6 @@ from src import mcp_client
 from src import mma_prompts
 from src import performance_monitor
 from src import project_manager
-from src.openai_compatible import send_openai_compatible, OpenAICompatibleRequest, NormalizedResponse
 from src.vendor_capabilities import VendorCapabilities, get_capabilities
 
 # TODO(Ed): Eliminate these?
@@ -822,8 +821,9 @@ def run_with_tool_loop(
  on_pre_dispatch: Optional[Callable[[int, list[dict[str, Any]]], list[dict[str, Any]]]] = None,
 ) -> str:
  def _default_send(_round_idx: int) -> NormalizedResponse:
+  from src.openai_compatible import send_openai_compatible as _send_oc
   assert capabilities is not None, "capabilities required when send_func is not provided"
-  return send_openai_compatible(client, request_builder(_round_idx), capabilities=capabilities)
+  return _send_oc(client, request_builder(_round_idx), capabilities=capabilities)
  request_builder: Callable[[int], OpenAICompatibleRequest] = (request if callable(request) else (lambda _i: request))
  dispatch_send: Callable[[int], NormalizedResponse] = send_func or _default_send
  response_text: str = ""
@@ -1760,8 +1760,10 @@ def _send_gemini_cli(md_content: str, user_message: str, base_dir: str,
  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, NormalizedResponse
  """
  [C: src/ai_server.py:_handle_send]
+ [C: src/ai_server.py:_handle_send]
  """
  global _gemini_cli_adapter
  try:
@@ -2248,6 +2250,8 @@ def _send_grok(md_content: str, user_message: str, base_dir: str,
  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()
  client = _ensure_grok_client()
  tools: list[dict[str, Any]] | None = _get_deepseek_tools() or None
  with _grok_history_lock:
@@ -2260,6 +2264,7 @@ def _send_grok(md_content: str, user_message: str, base_dir: str,
    _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})
+  _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>"}]
@@ -2287,16 +2292,14 @@ def _send_minimax(md_content: str, user_message: str, base_dir: 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
  _ensure_minimax_client()
- tools: list[dict[str, Any]] | None = _get_deepseek_tools() or None
- with _minimax_history_lock:
-  _repair_minimax_history(_minimax_history)
-  if discussion_history and not _minimax_history:
-   _minimax_history.append({"role": "user", "content": f"[DISCUSSION HISTORY]\n\n{discussion_history}\n\n---\n\n{user_message}"})
-  else:
-   _minimax_history.append({"role": "user", "content": user_message})
+ _repair_minimax_history(_minimax_history)
+ if discussion_history and not _minimax_history:
+  _minimax_history.append({"role": "user", "content": f"[DISCUSSION HISTORY]\n\n{discussion_history}\n\n---\n\n{user_message}"})
+ else:
+  _minimax_history.append({"role": "user", "content": user_message})
  def _build_minimax_request(_round_idx: int) -> OpenAICompatibleRequest:
   with _minimax_history_lock:
    messages: list[dict[str, Any]] = [{"role": "system", "content": f"{_get_combined_system_prompt()}\n\n<context>\n{md_content}\n</context>"}]
@@ -2454,6 +2457,7 @@ def _send_llama(md_content: str, user_message: str, base_dir: str,
  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_llama_client()
  tools: list[dict[str, Any]] | None = _get_deepseek_tools() or None
  with _llama_history_lock:
@@ -2466,6 +2470,8 @@ def _send_llama(md_content: str, user_message: str, base_dir: str,
    _llama_history.append({"role": "user", "content": f"[DISCUSSION HISTORY]\n\n{discussion_history}\n\n---\n\n{user_message}"})
   else:
    _llama_history.append({"role": "user", "content": user_content})
+ def _build_llama_request(_round_idx: int) -> OpenAICompatibleRequest:
+   _llama_history.append({"role": "user", "content": user_content})
  def _build_llama_request(_round_idx: int) -> OpenAICompatibleRequest:
   with _llama_history_lock:
    messages: list[dict[str, Any]] = [{"role": "system", "content": f"{_get_combined_system_prompt()}\n\n<context>\n{md_content}\n</context>"}]