refactor(ai_client): remove ProviderError class; ErrorInfo is the new error type

tests/test_openai_compatible.py

@@ -22,15 +22,14 @@ def _mock_completion(text: str = "hello", tool_calls=None, usage_input: int = 10
  m.usage.completion_tokens_details = None
  return m
 
-def test_send_non_streaming_returns_normalized_response(caps: VendorCapabilities) -> None:
+def test_send_non_streaming_returns_text_in_result(caps: VendorCapabilities) -> None:
  client = MagicMock()
  client.chat.completions.create.return_value = _mock_completion("hi", usage_input=20, usage_output=10)
  request = OpenAICompatibleRequest(messages=[{"role": "user", "content": "ping"}], model="m", max_tokens=100)
- response = send_openai_compatible(client, request, capabilities=caps)
- assert response.text == "hi"
- assert response.tool_calls == []
- assert response.usage_input_tokens == 20
- assert response.usage_output_tokens == 10
+ result = send_openai_compatible(client, request, capabilities=caps)
+ assert result.ok
+ assert result.data == "hi"
+ assert result.errors == []
 
 def test_send_streaming_aggregates_chunks(caps: VendorCapabilities) -> None:
  client = MagicMock()
@@ -42,12 +41,13 @@ def test_send_streaming_aggregates_chunks(caps: VendorCapabilities) -> None:
  client.chat.completions.create.return_value = iter(chunks)
  received: list = []
  request = OpenAICompatibleRequest(messages=[{"role": "user", "content": "ping"}], model="m", stream=True, stream_callback=received.append)
- response = send_openai_compatible(client, request, capabilities=caps)
- assert response.text == "hello"
+ result = send_openai_compatible(client, request, capabilities=caps)
+ assert result.ok
+ assert result.data == "hello"
  assert received == ["hel", "lo"]
- assert response.usage_input_tokens == 15
 
-def test_tool_call_detection_in_response(caps: VendorCapabilities) -> None:
+def test_tool_call_detection_in_blocking_response(caps: VendorCapabilities) -> None:
+ from src.openai_compatible import _send_blocking
  tool_call = MagicMock()
  tool_call.id = "call_1"
  tool_call.function.name = "read_file"
@@ -55,8 +55,8 @@ def test_tool_call_detection_in_response(caps: VendorCapabilities) -> None:
  completion = _mock_completion(text="", tool_calls=[tool_call])
  client = MagicMock()
  client.chat.completions.create.return_value = completion
- request = OpenAICompatibleRequest(messages=[{"role": "user", "content": "ping"}], model="m")
- response = send_openai_compatible(client, request, capabilities=caps)
+ kwargs = {"model": "m", "messages": [{"role": "user", "content": "ping"}], "temperature": 0.0, "top_p": 1.0, "max_tokens": 8192, "stream": False}
+ response = _send_blocking(client, kwargs)
  assert len(response.tool_calls) == 1
  assert response.tool_calls[0]["function"]["name"] == "read_file"
  assert response.tool_calls[0]["id"] == "call_1"
@@ -66,20 +66,21 @@ def test_vision_multimodal_message(caps: VendorCapabilities) -> None:
  client.chat.completions.create.return_value = _mock_completion("looks like a cat")
  messages = [{"role": "user", "content": [{"type": "text", "text": "what is this?"}, {"type": "image_url", "image_url": {"url": "data:image/png;base64,..."}}]}]
  request = OpenAICompatibleRequest(messages=messages, model="m")
- response = send_openai_compatible(client, request, capabilities=caps)
+ result = send_openai_compatible(client, request, capabilities=caps)
  sent_messages = client.chat.completions.create.call_args.kwargs["messages"]
  assert sent_messages[0]["content"] == messages[0]["content"]
- assert response.text == "looks like a cat"
+ assert result.data == "looks like a cat"
 
 def test_error_classification_429_to_rate_limit(caps: VendorCapabilities) -> None:
  from openai import RateLimitError
- from src.ai_client import ProviderError
+ from src.result_types import Result, ErrorKind
  client = MagicMock()
  client.chat.completions.create.side_effect = RateLimitError("rate limited", response=MagicMock(status_code=429), body=None)
  request = OpenAICompatibleRequest(messages=[{"role": "user", "content": "ping"}], model="m")
- with pytest.raises(ProviderError) as exc_info:
-  send_openai_compatible(client, request, capabilities=caps)
- assert exc_info.value.kind == "rate_limit"
+ result = send_openai_compatible(client, request, capabilities=caps)
+ assert isinstance(result, Result)
+ assert not result.ok
+ assert result.errors[0].kind == ErrorKind.RATE_LIMIT
 
 def test_normalized_response_is_frozen_dataclass() -> None:
  from dataclasses import FrozenInstanceError

tests/test_qwen_provider.py

@@ -39,12 +39,12 @@ def test_qwen_tool_format_translation() -> None:
  assert "parameters" in ds_tools[0]
 
 def test_qwen_error_classification() -> None:
- from src.ai_client import ProviderError
+ from src.result_types import ErrorKind
  from src.qwen_adapter import classify_dashscope_error
  from dashscope.common.error import AuthenticationError
  err = classify_dashscope_error(AuthenticationError("bad key"))
- assert err.kind == "auth"
- assert err.provider == "qwen"
+ assert err.kind == ErrorKind.AUTH
+ assert err.source == "qwen_adapter"
 
 def test_list_qwen_models_returns_hardcoded_registry() -> None:
  from src.ai_client import _list_qwen_models