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.
2026-06-11 16:15:49 -04:00
parent 4748d13490
commit 9ddfa98133
3 changed files with 22 additions and 16 deletions
@@ -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>"}]
@@ -34,7 +34,7 @@ def _make_normalized_response(text: str = "ok", tool_calls: list[dict[str, Any]]

 def test_run_with_tool_loop_no_tool_calls_returns_immediately(caps: VendorCapabilities) -> None:
 client = MagicMock()
- with patch("src.ai_client.send_openai_compatible", return_value=_make_normalized_response("hello")) as call:
+ with patch("src.openai_compatible.send_openai_compatible", return_value=_make_normalized_response("hello")) as call:
  result = run_with_tool_loop(
   client, OpenAICompatibleRequest(messages=[{"role": "user", "content": "x"}], model="m"),
   capabilities=caps,
@@ -50,7 +50,7 @@ def test_run_with_tool_loop_dispatches_tool_calls(caps: VendorCapabilities) -> N
  "first response", tool_calls=[{"id": "c1", "type": "function", "function": {"name": "read_file", "arguments": "{}"}}]
 )
 final_response = _make_normalized_response("after tool")
- with patch("src.ai_client.send_openai_compatible", side_effect=[tool_response, final_response]) as call, \
+ with patch("src.openai_compatible.send_openai_compatible", side_effect=[tool_response, final_response]) as call, \
      patch("src.ai_client._execute_tool_calls_concurrently", return_value=[("read_file", "c1", "result", "")]) as dispatch:
  result = run_with_tool_loop(
   client, OpenAICompatibleRequest(messages=[{"role": "user", "content": "x"}], model="m"),
@@ -67,7 +67,7 @@ def test_run_with_tool_loop_respects_max_rounds(caps: VendorCapabilities) -> Non
 infinite_tool_response = _make_normalized_response(
  "loop", tool_calls=[{"id": "c1", "type": "function", "function": {"name": "noop", "arguments": "{}"}}]
 )
- with patch("src.ai_client.send_openai_compatible", return_value=infinite_tool_response), \
+ with patch("src.openai_compatible.send_openai_compatible", return_value=infinite_tool_response), \
      patch("src.ai_client._execute_tool_calls_concurrently", return_value=[("noop", "c1", "result", "")]):
  result = run_with_tool_loop(
   client, OpenAICompatibleRequest(messages=[{"role": "user", "content": "x"}], model="m"),
@@ -83,7 +83,7 @@ def test_run_with_tool_loop_appends_to_history(caps: VendorCapabilities) -> None
 history_lock = MagicMock()
 history_lock.__enter__ = MagicMock(return_value=history_lock)
 history_lock.__exit__ = MagicMock(return_value=False)
- with patch("src.ai_client.send_openai_compatible", return_value=_make_normalized_response("hi")):
+ with patch("src.openai_compatible.send_openai_compatible", return_value=_make_normalized_response("hi")):
  run_with_tool_loop(
   client, OpenAICompatibleRequest(messages=[{"role": "user", "content": "x"}], model="m"),
   capabilities=caps,
@@ -98,7 +98,7 @@ def test_run_with_tool_loop_does_not_crash_on_tool_error(caps: VendorCapabilitie
  "err", tool_calls=[{"id": "c1", "type": "function", "function": {"name": "fail", "arguments": "{}"}}]
 )
 final_response = _make_normalized_response("recovered")
- with patch("src.ai_client.send_openai_compatible", side_effect=[tool_response, final_response]), \
+ with patch("src.openai_compatible.send_openai_compatible", side_effect=[tool_response, final_response]), \
      patch("src.ai_client._execute_tool_calls_concurrently", return_value=[("fail", "c1", "", "ToolExecutionError")]):
  result = run_with_tool_loop(
   client, OpenAICompatibleRequest(messages=[{"role": "user", "content": "x"}], model="m"),
@@ -30,7 +30,7 @@ def test_run_with_tool_loop_calls_request_builder_each_round() -> None:
 def builder(round_idx: int) -> OpenAICompatibleRequest:
  builder_calls.append(round_idx)
  return OpenAICompatibleRequest(messages=[{"role": "user", "content": f"round={round_idx}"}], model="m")
- with patch("src.ai_client.send_openai_compatible", side_effect=[tool_response, final]), \
+ with patch("src.openai_compatible.send_openai_compatible", side_effect=[tool_response, final]), \
      patch("src.ai_client._execute_tool_calls_concurrently", return_value=[("noop", "c1", "r", "")]):
  result = run_with_tool_loop(
   client, builder, capabilities=caps,