Files
litellm/tests/test_litellm/test_dashscope_image_generation.py
T
Sameer Kankute 2d1cc68e22 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
2026-04-23 18:41:01 +05:30

402 lines
14 KiB
Python

"""
Unit tests for DashScope image generation support (qwen-image-2.0, qwen-image-2.0-pro).
Run in docker: pytest tests/test_litellm/test_dashscope_image_generation.py -v
"""
import json
from unittest.mock import MagicMock, patch
import httpx
import pytest
import litellm
from litellm.llms.dashscope.image_generation.transformation import (
DashScopeImageGenerationConfig,
DEFAULT_API_BASE,
)
from litellm.types.utils import ImageObject, ImageResponse
from litellm.utils import get_llm_provider
# ---------------------------------------------------------------------------
# 1. Provider detection
# ---------------------------------------------------------------------------
@pytest.mark.parametrize(
"model_string",
[
"dashscope/qwen-image-2.0",
"dashscope/qwen-image-2.0-pro",
],
)
def test_get_llm_provider_returns_dashscope(model_string: str):
model, provider, _, _ = get_llm_provider(model_string)
assert provider == "dashscope", f"Expected 'dashscope', got '{provider}'"
assert "qwen-image" in model
# ---------------------------------------------------------------------------
# 2. Model info: mode == "image_generation"
# ---------------------------------------------------------------------------
@pytest.mark.parametrize(
"model_string, custom_provider",
[
("dashscope/qwen-image-2.0", "dashscope"),
("dashscope/qwen-image-2.0-pro", "dashscope"),
],
)
def test_get_model_info_mode_is_image_generation(
model_string: str, custom_provider: str
):
import os
prev_env = os.environ.get("LITELLM_LOCAL_MODEL_COST_MAP")
prev_model_cost = litellm.model_cost
try:
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = litellm.get_model_cost_map(url="")
info = litellm.get_model_info(
model=model_string, custom_llm_provider=custom_provider
)
assert (
info["mode"] == "image_generation"
), f"Expected mode='image_generation', got '{info['mode']}'"
finally:
if prev_env is None:
os.environ.pop("LITELLM_LOCAL_MODEL_COST_MAP", None)
else:
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = prev_env
litellm.model_cost = prev_model_cost
# ---------------------------------------------------------------------------
# 3. Request transformation
# ---------------------------------------------------------------------------
class TestDashScopeImageGenerationConfig:
def setup_method(self):
self.cfg = DashScopeImageGenerationConfig()
def test_get_complete_url_default(self):
url = self.cfg.get_complete_url(None, None, "qwen-image-2.0", {}, {})
assert url == DEFAULT_API_BASE
def test_get_complete_url_custom(self):
custom = "https://custom.endpoint/generate"
url = self.cfg.get_complete_url(custom, None, "qwen-image-2.0", {}, {})
assert url == custom
def test_validate_environment_sets_auth_header(self):
headers = self.cfg.validate_environment(
headers={},
model="qwen-image-2.0",
messages=[],
optional_params={},
litellm_params={},
api_key="sk-test-key",
)
assert headers["Authorization"] == "Bearer sk-test-key"
assert headers["Content-Type"] == "application/json"
def test_validate_environment_raises_without_key(self):
with patch(
"litellm.llms.dashscope.image_generation.transformation.get_secret_str",
return_value=None,
):
with pytest.raises(ValueError, match="DASHSCOPE_API_KEY"):
self.cfg.validate_environment(
headers={},
model="qwen-image-2.0",
messages=[],
optional_params={},
litellm_params={},
api_key=None,
)
def test_transform_request_structure(self):
req = self.cfg.transform_image_generation_request(
model="qwen-image-2.0",
prompt="a puppy on green grass",
optional_params={"size": "1024*1024"},
litellm_params={},
headers={},
)
assert req["model"] == "qwen-image-2.0"
messages = req["input"]["messages"]
assert len(messages) == 1
assert messages[0]["role"] == "user"
assert messages[0]["content"][0]["text"] == "a puppy on green grass"
assert req["parameters"]["size"] == "1024*1024"
def test_transform_request_empty_params(self):
req = self.cfg.transform_image_generation_request(
model="qwen-image-2.0-pro",
prompt="sunset over the ocean",
optional_params={},
litellm_params={},
headers={},
)
assert req["parameters"] == {}
# ---------------------------------------------------------------------------
# 4. Response transformation
# ---------------------------------------------------------------------------
def _make_mock_response(self, image_url: str) -> httpx.Response:
body = {
"status_code": 200,
"request_id": "test-request-id",
"output": {
"choices": [
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": [{"image": image_url}],
},
}
]
},
"usage": {
"input_tokens": 0,
"output_tokens": 0,
"width": 1024,
"height": 1024,
"image_count": 1,
},
}
mock_resp = MagicMock(spec=httpx.Response)
mock_resp.status_code = 200
mock_resp.headers = {}
mock_resp.json.return_value = body
return mock_resp
def test_transform_response_extracts_url(self):
image_url = "https://example.oss.aliyuncs.com/generated/test.png"
mock_resp = self._make_mock_response(image_url)
model_response = ImageResponse()
result = self.cfg.transform_image_generation_response(
model="qwen-image-2.0",
raw_response=mock_resp,
model_response=model_response,
logging_obj=MagicMock(),
request_data={},
optional_params={},
litellm_params={},
encoding=None,
)
assert result.data is not None
assert len(result.data) == 1
assert result.data[0].url == image_url
def test_transform_response_multiple_images(self):
body = {
"output": {
"choices": [
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": [{"image": "https://example.com/img1.png"}],
},
},
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": [{"image": "https://example.com/img2.png"}],
},
},
]
},
"usage": {},
}
mock_resp = MagicMock(spec=httpx.Response)
mock_resp.status_code = 200
mock_resp.headers = {}
mock_resp.json.return_value = body
model_response = ImageResponse()
result = self.cfg.transform_image_generation_response(
model="qwen-image-2.0",
raw_response=mock_resp,
model_response=model_response,
logging_obj=MagicMock(),
request_data={},
optional_params={},
litellm_params={},
encoding=None,
)
assert len(result.data) == 2
assert result.data[0].url == "https://example.com/img1.png"
assert result.data[1].url == "https://example.com/img2.png"
def test_transform_response_raises_on_non_200_status(self):
mock_resp = MagicMock(spec=httpx.Response)
mock_resp.status_code = 400
mock_resp.headers = {}
mock_resp.text = '{"code":"InvalidParameter","message":"Size not supported"}'
mock_resp.json.return_value = {
"code": "InvalidParameter",
"message": "Size not supported",
}
with pytest.raises(Exception):
self.cfg.transform_image_generation_response(
model="qwen-image-2.0",
raw_response=mock_resp,
model_response=ImageResponse(),
logging_obj=MagicMock(),
request_data={},
optional_params={},
litellm_params={},
encoding=None,
)
def test_transform_response_raises_on_api_error_body(self):
mock_resp = MagicMock(spec=httpx.Response)
mock_resp.status_code = 200
mock_resp.headers = {}
mock_resp.json.return_value = {
"code": "InvalidParameter",
"message": "Size not supported",
}
with pytest.raises(Exception):
self.cfg.transform_image_generation_response(
model="qwen-image-2.0",
raw_response=mock_resp,
model_response=ImageResponse(),
logging_obj=MagicMock(),
request_data={},
optional_params={},
litellm_params={},
encoding=None,
)
# ---------------------------------------------------------------------------
# 5. OpenAI → DashScope parameter mapping
# ---------------------------------------------------------------------------
def test_map_openai_params_size_conversion(self):
mapped = self.cfg.map_openai_params(
non_default_params={"size": "1024x1024"},
optional_params={},
model="qwen-image-2.0",
drop_params=False,
)
assert mapped["size"] == "1024*1024"
def test_map_openai_params_n_to_image_count(self):
mapped = self.cfg.map_openai_params(
non_default_params={"n": 2},
optional_params={},
model="qwen-image-2.0",
drop_params=False,
)
assert mapped["image_count"] == 2
def test_map_openai_params_unknown_size_uses_asterisk(self):
mapped = self.cfg.map_openai_params(
non_default_params={"size": "768x768"},
optional_params={},
model="qwen-image-2.0",
drop_params=False,
)
assert mapped["size"] == "768*768"
@pytest.mark.parametrize(
"openai_size, expected",
[
("256x256", "256*256"),
("512x512", "512*512"),
("1024x1024", "1024*1024"),
("1792x1024", "1792*1024"),
("1024x1792", "1024*1792"),
("2048x2048", "2048*2048"),
],
)
def test_map_openai_params_size_table(self, openai_size: str, expected: str):
mapped = self.cfg.map_openai_params(
non_default_params={"size": openai_size},
optional_params={},
model="qwen-image-2.0",
drop_params=False,
)
assert mapped["size"] == expected
# ---------------------------------------------------------------------------
# 6. End-to-end flow via litellm.image_generation (HTTP mocked)
# ---------------------------------------------------------------------------
def test_litellm_image_generation_dashscope_end_to_end():
mock_response_body = {
"output": {
"choices": [
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": [
{
"image": "https://dashscope-result.oss.aliyuncs.com/test.png"
}
],
},
}
]
},
"usage": {
"input_tokens": 0,
"output_tokens": 0,
"width": 1024,
"height": 1024,
"image_count": 1,
},
}
with patch(
"litellm.llms.custom_httpx.llm_http_handler.HTTPHandler.post"
) as mock_post:
mock_http_response = MagicMock()
mock_http_response.json.return_value = mock_response_body
mock_http_response.status_code = 200
mock_http_response.headers = {}
mock_post.return_value = mock_http_response
response = litellm.image_generation(
model="dashscope/qwen-image-2.0",
prompt="a puppy playing on green grass",
api_key="sk-test-key",
size="1024x1024",
)
assert response is not None
assert response.data is not None
assert len(response.data) == 1
assert (
response.data[0].url == "https://dashscope-result.oss.aliyuncs.com/test.png"
)
# Verify the HTTP call was made to the DashScope endpoint
call_args = mock_post.call_args
called_url = (
call_args[0][0] if call_args[0] else call_args.kwargs.get("url", "")
)
assert "dashscope" in called_url or "aliyuncs" in called_url
# Verify request body contains DashScope format
call_kwargs = call_args[1] if call_args[1] else {}
if "json" in call_kwargs:
body = call_kwargs["json"]
assert "input" in body
assert "messages" in body["input"]