fix(dashscope): fail fast on image generation API errors
Prevent silent empty image responses by raising provider errors for non-200 HTTP statuses and DashScope API-level error payloads, with regression tests covering both paths. Made-with: Cursor
This commit is contained in:
Sameer Kankute
parent
2e3a4bb27a
commit
2d1cc68e22
@ -165,6 +165,13 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
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DashScope response: output.choices[0].message.content[0].image
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OpenAI response: data[0].url
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"""
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if raw_response.status_code != 200:
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raise self.get_error_class(
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error_message=raw_response.text,
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status_code=raw_response.status_code,
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headers=raw_response.headers,
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)
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try:
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response_data = raw_response.json()
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except Exception as e:
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@ -174,6 +181,15 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
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headers=raw_response.headers,
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)
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# DashScope can return API-level errors in a 200 response body.
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# Example: {"code": "InvalidParameter", "message": "Size not supported"}
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if "code" in response_data and "output" not in response_data:
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raise self.get_error_class(
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error_message=str(response_data.get("message", response_data)),
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status_code=raw_response.status_code,
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headers=raw_response.headers,
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)
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if not model_response.data:
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model_response.data = []
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@ -49,7 +49,9 @@ def test_get_llm_provider_returns_dashscope(model_string: str):
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("dashscope/qwen-image-2.0-pro", "dashscope"),
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],
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)
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def test_get_model_info_mode_is_image_generation(model_string: str, custom_provider: str):
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def test_get_model_info_mode_is_image_generation(
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model_string: str, custom_provider: str
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):
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import os
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prev_env = os.environ.get("LITELLM_LOCAL_MODEL_COST_MAP")
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@ -58,10 +60,12 @@ def test_get_model_info_mode_is_image_generation(model_string: str, custom_provi
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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info = litellm.get_model_info(model=model_string, custom_llm_provider=custom_provider)
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assert info["mode"] == "image_generation", (
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f"Expected mode='image_generation', got '{info['mode']}'"
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info = litellm.get_model_info(
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model=model_string, custom_llm_provider=custom_provider
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)
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assert (
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info["mode"] == "image_generation"
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), f"Expected mode='image_generation', got '{info['mode']}'"
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finally:
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if prev_env is None:
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os.environ.pop("LITELLM_LOCAL_MODEL_COST_MAP", None)
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@ -101,7 +105,10 @@ class TestDashScopeImageGenerationConfig:
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assert headers["Content-Type"] == "application/json"
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def test_validate_environment_raises_without_key(self):
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with patch("litellm.llms.dashscope.image_generation.transformation.get_secret_str", return_value=None):
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with patch(
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"litellm.llms.dashscope.image_generation.transformation.get_secret_str",
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return_value=None,
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):
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with pytest.raises(ValueError, match="DASHSCOPE_API_KEY"):
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self.cfg.validate_environment(
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headers={},
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@ -192,8 +199,20 @@ class TestDashScopeImageGenerationConfig:
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body = {
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"output": {
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"choices": [
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{"finish_reason": "stop", "message": {"role": "assistant", "content": [{"image": "https://example.com/img1.png"}]}},
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{"finish_reason": "stop", "message": {"role": "assistant", "content": [{"image": "https://example.com/img2.png"}]}},
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{
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"finish_reason": "stop",
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"message": {
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"role": "assistant",
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"content": [{"image": "https://example.com/img1.png"}],
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},
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},
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{
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"finish_reason": "stop",
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"message": {
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"role": "assistant",
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"content": [{"image": "https://example.com/img2.png"}],
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},
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},
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]
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},
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"usage": {},
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@ -218,6 +237,49 @@ class TestDashScopeImageGenerationConfig:
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assert result.data[0].url == "https://example.com/img1.png"
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assert result.data[1].url == "https://example.com/img2.png"
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def test_transform_response_raises_on_non_200_status(self):
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mock_resp = MagicMock(spec=httpx.Response)
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mock_resp.status_code = 400
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mock_resp.headers = {}
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mock_resp.text = '{"code":"InvalidParameter","message":"Size not supported"}'
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mock_resp.json.return_value = {
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"code": "InvalidParameter",
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"message": "Size not supported",
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}
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with pytest.raises(Exception):
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self.cfg.transform_image_generation_response(
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model="qwen-image-2.0",
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raw_response=mock_resp,
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model_response=ImageResponse(),
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logging_obj=MagicMock(),
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request_data={},
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optional_params={},
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litellm_params={},
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encoding=None,
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)
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def test_transform_response_raises_on_api_error_body(self):
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mock_resp = MagicMock(spec=httpx.Response)
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mock_resp.status_code = 200
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mock_resp.headers = {}
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mock_resp.json.return_value = {
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"code": "InvalidParameter",
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"message": "Size not supported",
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}
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with pytest.raises(Exception):
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self.cfg.transform_image_generation_response(
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model="qwen-image-2.0",
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raw_response=mock_resp,
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model_response=ImageResponse(),
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logging_obj=MagicMock(),
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request_data={},
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optional_params={},
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litellm_params={},
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encoding=None,
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)
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# ---------------------------------------------------------------------------
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# 5. OpenAI → DashScope parameter mapping
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# ---------------------------------------------------------------------------
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@ -284,13 +346,21 @@ def test_litellm_image_generation_dashscope_end_to_end():
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"message": {
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"role": "assistant",
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"content": [
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{"image": "https://dashscope-result.oss.aliyuncs.com/test.png"}
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{
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"image": "https://dashscope-result.oss.aliyuncs.com/test.png"
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}
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],
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},
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}
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]
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},
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"usage": {"input_tokens": 0, "output_tokens": 0, "width": 1024, "height": 1024, "image_count": 1},
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"usage": {
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"input_tokens": 0,
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"output_tokens": 0,
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"width": 1024,
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"height": 1024,
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"image_count": 1,
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},
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}
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with patch(
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@ -312,11 +382,15 @@ def test_litellm_image_generation_dashscope_end_to_end():
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assert response is not None
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assert response.data is not None
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assert len(response.data) == 1
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assert response.data[0].url == "https://dashscope-result.oss.aliyuncs.com/test.png"
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assert (
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response.data[0].url == "https://dashscope-result.oss.aliyuncs.com/test.png"
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)
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# Verify the HTTP call was made to the DashScope endpoint
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call_args = mock_post.call_args
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called_url = call_args[0][0] if call_args[0] else call_args.kwargs.get("url", "")
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called_url = (
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call_args[0][0] if call_args[0] else call_args.kwargs.get("url", "")
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)
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assert "dashscope" in called_url or "aliyuncs" in called_url
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# Verify request body contains DashScope format
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@ -325,4 +399,3 @@ def test_litellm_image_generation_dashscope_end_to_end():
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body = call_kwargs["json"]
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assert "input" in body
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assert "messages" in body["input"]
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