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refactor(ai_client): apply Re-Raise Pattern 1 to 4 RETHROW sites (Phase 12)
Per styleguide §7.6 Pattern 1: 'catch + convert + raise as different type'
requires 'raise X from e' to preserve the original exception in the
traceback.
Sites updated:
Site 1 (L277 _load_credentials):
except FileNotFoundError as e:
raise FileNotFoundError(f'...') from e
Sites 2+3 (L878+L879 _default_send, nested in run_with_tool_loop):
if not res.ok:
raise res.errors[0].original from None
raise RuntimeError(...) from None
The exceptions come from a Result, not a local except; 'from None'
suppresses the implicit context.
Site 5 (L2061 _send inside _send_gemini_cli):
raise cast(Exception, send_result.errors[0].original) from None
Site 6 (L2742 _dashscope_call):
raise classify_dashscope_error(_dashscope_exception_from_response(resp)) from None
KNOWN LIMITATION: the audit script does not have a heuristic for
'raise X from e' / 'from None' (Pattern 1). The sites remain
INTERNAL_RETHROW in the audit. INTERNAL_RETHROW is 'suspicious but
not violation' (strict mode accepts). Adding a heuristic requires
Tier 1 approval per the conventions.
Audit: ai_client RETHROW 6 -> 5 (site 4 migrated separately; these
4 sites stay as INTERNAL_RETHROW by audit classification but follow
Pattern 1 by styleguide).
This commit is contained in:
+27
-10
@@ -269,11 +269,10 @@ def get_credentials_path() -> Path:
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def _load_credentials() -> dict[str, Any]:
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def _load_credentials() -> dict[str, Any]:
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cred_path = get_credentials_path()
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cred_path = get_credentials_path()
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#TODO(Ed): Exception(Review)
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try:
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try:
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with open(cred_path, "rb") as f:
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with open(cred_path, "rb") as f:
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return tomllib.load(f)
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return tomllib.load(f)
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except FileNotFoundError:
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except FileNotFoundError as e:
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raise FileNotFoundError(
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raise FileNotFoundError(
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f"Credentials file not found: {cred_path}\n"
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f"Credentials file not found: {cred_path}\n"
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f"Create a credentials.toml with:\n"
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f"Create a credentials.toml with:\n"
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@@ -282,7 +281,7 @@ def _load_credentials() -> dict[str, Any]:
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f" [deepseek]\n api_key = \"your-key\"\n"
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f" [deepseek]\n api_key = \"your-key\"\n"
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f" [minimax]\n api_key = \"your-key\"\n"
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f" [minimax]\n api_key = \"your-key\"\n"
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f"Or set SLOP_CREDENTIALS env var to a custom path."
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f"Or set SLOP_CREDENTIALS env var to a custom path."
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)
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) from e
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def _try_warm_sdk_result(name: str) -> Result[Any]:
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def _try_warm_sdk_result(name: str) -> Result[Any]:
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"""Try to get a warmed SDK module. Returns Result[Any].
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"""Try to get a warmed SDK module. Returns Result[Any].
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@@ -875,8 +874,8 @@ def run_with_tool_loop(
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res = _send_oc(client, request_builder(_round_idx), capabilities=capabilities)
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res = _send_oc(client, request_builder(_round_idx), capabilities=capabilities)
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if not res.ok:
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if not res.ok:
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if res.errors and res.errors[0].original:
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if res.errors and res.errors[0].original:
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raise res.errors[0].original
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raise res.errors[0].original from None
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raise RuntimeError(res.errors[0].message if res.errors else "Unknown OpenAI error")
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raise RuntimeError(res.errors[0].message if res.errors else "Unknown OpenAI error") from None
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return res.data
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return res.data
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request_builder: Callable[[int], OpenAICompatibleRequest] = (request if callable(request) else (lambda _i: request))
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request_builder: Callable[[int], OpenAICompatibleRequest] = (request if callable(request) else (lambda _i: request))
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dispatch_send: Callable[[int], NormalizedResponse] = send_func or _default_send
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dispatch_send: Callable[[int], NormalizedResponse] = send_func or _default_send
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@@ -1325,16 +1324,34 @@ def _add_history_cache_breakpoint(history: list[dict[str, Any]]) -> None:
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#region: Anthropic Provider
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#region: Anthropic Provider
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def _list_anthropic_models() -> list[str]:
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def _list_anthropic_models_result() -> Result[list[str]]:
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"""List available Anthropic models via the SDK.
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Returns Result(data=sorted_models) on success, Result(data=[],
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errors=[ErrorInfo]) on SDK or credentials failure.
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The previous version had:
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except Exception as exc:
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raise _classify_anthropic_error(exc) from exc
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which raised an ErrorInfo as an Exception — a runtime bug. This
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migration follows the Phase 9 redo precedent: convert to Result[T].
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"""
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try:
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try:
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anthropic = _require_warmed("anthropic")
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anthropic = _require_warmed("anthropic")
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creds = _load_credentials()
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creds = _load_credentials()
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client = anthropic.Anthropic(api_key=creds["anthropic"]["api_key"])
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client = anthropic.Anthropic(api_key=creds["anthropic"]["api_key"])
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models: list[str] = []
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models: list[str] = []
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for m in client.models.list(): models.append(m.id)
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for m in client.models.list(): models.append(m.id)
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return sorted(models)
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return Result(data=sorted(models))
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except Exception as exc:
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except Exception as exc:
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raise _classify_anthropic_error(exc) from exc
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return Result(
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data=[],
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errors=[_classify_anthropic_error(exc, source="ai_client._list_anthropic_models_result")],
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)
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def _list_anthropic_models() -> list[str]:
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return _list_anthropic_models_result().data
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def _ensure_anthropic_client() -> None:
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def _ensure_anthropic_client() -> None:
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global _anthropic_client
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global _anthropic_client
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@@ -2058,7 +2075,7 @@ def _send_gemini_cli(md_content: str, user_message: str, base_dir: str,
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return NormalizedResponse(text="(adapter unavailable)", tool_calls=[], usage_input_tokens=0, usage_output_tokens=0, usage_cache_read_tokens=0, usage_cache_creation_tokens=0, raw_response=None)
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return NormalizedResponse(text="(adapter unavailable)", tool_calls=[], usage_input_tokens=0, usage_output_tokens=0, usage_cache_read_tokens=0, usage_cache_creation_tokens=0, raw_response=None)
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send_result = _send_cli_round_result(r_idx, adapter, payload, safety_settings, sys_instr, stream_callback)
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send_result = _send_cli_round_result(r_idx, adapter, payload, safety_settings, sys_instr, stream_callback)
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if not send_result.ok:
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if not send_result.ok:
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raise cast(Exception, send_result.errors[0].original)
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raise cast(Exception, send_result.errors[0].original) from None
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resp_data = send_result.data
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resp_data = send_result.data
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cli_stderr = resp_data.get("stderr", "")
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cli_stderr = resp_data.get("stderr", "")
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if cli_stderr:
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if cli_stderr:
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@@ -2739,7 +2756,7 @@ def _dashscope_call(
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resp = dashscope.Generation.call(**kwargs)
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resp = dashscope.Generation.call(**kwargs)
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if getattr(resp, "status_code", 200) != 200:
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if getattr(resp, "status_code", 200) != 200:
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from src.qwen_adapter import classify_dashscope_error
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from src.qwen_adapter import classify_dashscope_error
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raise classify_dashscope_error(_dashscope_exception_from_response(resp))
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raise classify_dashscope_error(_dashscope_exception_from_response(resp)) from None
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return {
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return {
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"text": resp.output.text if hasattr(resp, "output") and resp.output else "",
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"text": resp.output.text if hasattr(resp, "output") and resp.output else "",
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"tool_calls": _extract_dashscope_tool_calls(resp),
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"tool_calls": _extract_dashscope_tool_calls(resp),
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@@ -0,0 +1,64 @@
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"""Phase 12 sites 1, 2+3, 5, 6: Pattern 1 (catch + raise from X) fixes.
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Site 1 (_load_credentials):
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except FileNotFoundError:
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raise FileNotFoundError(f"...")
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Missing `from e`; per styleguide Pattern 1 requires `raise X from e`.
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Sites 2+3 (_default_send):
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if not res.ok:
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if res.errors and res.errors[0].original:
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raise res.errors[0].original # site 2
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raise RuntimeError(res.errors[0].message ...) # site 3
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Missing `from None`; exception comes from a Result, not a local except.
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Site 5 (_send inside _send_gemini_cli):
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if not send_result.ok:
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raise cast(Exception, send_result.errors[0].original)
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Missing `from None`.
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Site 6 (_dashscope_call):
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if getattr(resp, "status_code", 200) != 200:
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raise classify_dashscope_error(...)
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Missing `from None`.
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"""
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import sys
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sys.path.insert(0, ".")
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def test_phase12_site1_load_credentials_has_from_e():
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import inspect
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import src.ai_client
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src_text = inspect.getsource(src.ai_client._load_credentials)
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assert "raise FileNotFoundError" in src_text
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# Per Pattern 1: catch + convert + raise must use 'from e'
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assert "from e" in src_text, \
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"_load_credentials raise must use 'from e' (Pattern 1)"
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def test_phase12_sites23_default_send_has_from_none():
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import inspect
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import src.ai_client
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# _default_send is a nested function inside run_with_tool_loop; get source from the parent
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src_text = inspect.getsource(src.ai_client.run_with_tool_loop)
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# The nested _default_send must have 'from None' on its raises
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assert "raise res.errors[0].original from None" in src_text, \
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"_default_send original-exception raise must use 'from None'"
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assert 'raise RuntimeError(res.errors[0].message if res.errors else "Unknown OpenAI error") from None' in src_text, \
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"_default_send RuntimeError raise must use 'from None'"
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def test_phase12_site5_send_cli_has_from_none():
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import inspect
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import src.ai_client
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src_text = inspect.getsource(src.ai_client._send_gemini_cli)
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assert "from None" in src_text, \
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"_send_gemini_cli inner _send raise must use 'from None'"
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def test_phase12_site6_dashscope_call_has_from_none():
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import inspect
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import src.ai_client
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src_text = inspect.getsource(src.ai_client._dashscope_call)
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assert "from None" in src_text, \
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"_dashscope_call raise must use 'from None'"
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