File size: 6,654 Bytes
6cfe55f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 | """issue #282 回归测试:UniversalGPT 拼装 content 时按是否有图片切换 string / array 形态。
DeepSeek deepseek-chat 等非多模态模型只接受 ``content`` 为字符串,旧实现无条件
emit ``[{"type":"text","text":...}]`` 导致 ``invalid_request_error``。
"""
import importlib.util
import pathlib
import sys
import types
import unittest
def _install_stubs():
app_mod = types.ModuleType("app")
gpt_pkg = types.ModuleType("app.gpt")
models_pkg = types.ModuleType("app.models")
base_mod = types.ModuleType("app.gpt.base")
class _GPT:
pass
base_mod.GPT = _GPT
prompt_builder_mod = types.ModuleType("app.gpt.prompt_builder")
def _generate_base_prompt(**_kwargs):
return "PROMPT_BODY"
prompt_builder_mod.generate_base_prompt = _generate_base_prompt
prompt_mod = types.ModuleType("app.gpt.prompt")
prompt_mod.BASE_PROMPT = ""
prompt_mod.AI_SUM = ""
prompt_mod.SCREENSHOT = ""
prompt_mod.LINK = ""
prompt_mod.MERGE_PROMPT = "MERGE_HEAD"
utils_mod = types.ModuleType("app.gpt.utils")
def _fix_markdown(text):
return text
utils_mod.fix_markdown = _fix_markdown
utils_mod.strip_think_blocks = lambda text: (text or "").strip()
request_chunker_mod = types.ModuleType("app.gpt.request_chunker")
class _RequestChunker:
def __init__(self, *_args, **_kwargs):
pass
def group_texts_by_budget(self, texts, _builder, **_kwargs):
return [texts]
request_chunker_mod.RequestChunker = _RequestChunker
gpt_model_mod = types.ModuleType("app.models.gpt_model")
class _GPTSource:
pass
gpt_model_mod.GPTSource = _GPTSource
transcriber_model_mod = types.ModuleType("app.models.transcriber_model")
class _TranscriptSegment:
def __init__(self, **kwargs):
self.start = kwargs.get("start", 0)
self.end = kwargs.get("end", 0)
self.text = kwargs.get("text", "")
transcriber_model_mod.TranscriptSegment = _TranscriptSegment
sys.modules.setdefault("app", app_mod)
sys.modules.setdefault("app.gpt", gpt_pkg)
sys.modules.setdefault("app.models", models_pkg)
sys.modules["app.gpt.base"] = base_mod
sys.modules["app.gpt.prompt_builder"] = prompt_builder_mod
sys.modules["app.gpt.prompt"] = prompt_mod
sys.modules["app.gpt.utils"] = utils_mod
sys.modules["app.gpt.request_chunker"] = request_chunker_mod
sys.modules["app.models.gpt_model"] = gpt_model_mod
sys.modules["app.models.transcriber_model"] = transcriber_model_mod
def _load_universal_gpt_class():
_install_stubs()
root = pathlib.Path(__file__).resolve().parents[1]
module_path = root / "app" / "gpt" / "universal_gpt.py"
spec = importlib.util.spec_from_file_location(
"universal_gpt_content_format", module_path
)
if spec is None or spec.loader is None:
raise ImportError("universal_gpt module spec not found")
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module.UniversalGPT
UniversalGPT = _load_universal_gpt_class()
class _DummyClient:
"""create_messages 不会真的调用 client,给个空壳即可。"""
def _make_gpt():
return UniversalGPT(_DummyClient(), model="deepseek-chat")
class TestCreateMessagesContentFormat(unittest.TestCase):
"""覆盖 create_messages 在不同 video_img_urls 输入下的输出形态。"""
def test_no_images_emits_string_content(self):
"""无图片时 content 为 str(DeepSeek / 非多模态模型可解析)。"""
gpt = _make_gpt()
messages = gpt.create_messages(segments=[])
self.assertEqual(len(messages), 1)
self.assertEqual(messages[0]["role"], "user")
self.assertIsInstance(messages[0]["content"], str)
self.assertEqual(messages[0]["content"], "PROMPT_BODY")
def test_empty_image_list_emits_string_content(self):
"""显式传入空列表也要走纯文本分支,避免图片字段误触发。"""
gpt = _make_gpt()
messages = gpt.create_messages(segments=[], video_img_urls=[])
self.assertIsInstance(messages[0]["content"], str)
def test_with_images_emits_multimodal_array(self):
"""有图片时保留多模态 array 形态,确保多模态模型功能不退化。"""
gpt = _make_gpt()
messages = gpt.create_messages(
segments=[],
video_img_urls=["https://example.com/a.jpg", "https://example.com/b.jpg"],
)
content = messages[0]["content"]
self.assertIsInstance(content, list)
self.assertEqual(len(content), 3) # 1 text + 2 images
self.assertEqual(content[0], {"type": "text", "text": "PROMPT_BODY"})
self.assertEqual(content[1]["type"], "image_url")
self.assertEqual(content[1]["image_url"]["url"], "https://example.com/a.jpg")
# 不应携带 detail 字段:MiniMax 等兼容接口对 detail:"auto" 报 400 (2013),
# OpenAI 缺省值本来就是 auto
self.assertNotIn("detail", content[1]["image_url"])
self.assertEqual(content[2]["image_url"]["url"], "https://example.com/b.jpg")
def test_no_image_url_field_when_no_images(self):
"""纯文本响应里不应该出现 image_url 关键字 —— 这是触发 DeepSeek 400 的根因。"""
gpt = _make_gpt()
messages = gpt.create_messages(segments=[])
import json
serialized = json.dumps(messages, ensure_ascii=False)
self.assertNotIn("image_url", serialized)
class TestBuildMergeMessagesContentFormat(unittest.TestCase):
"""合并阶段从不带图片,应该统一走 string content 路径。"""
def test_merge_messages_use_string_content(self):
"""否则长视频 chunk 后的合并阶段还会复现 issue #282 错误。"""
gpt = _make_gpt()
messages = gpt._build_merge_messages(["partial-A", "partial-B"])
self.assertEqual(len(messages), 1)
self.assertEqual(messages[0]["role"], "user")
self.assertIsInstance(messages[0]["content"], str)
self.assertIn("MERGE_HEAD", messages[0]["content"])
self.assertIn("partial-A", messages[0]["content"])
self.assertIn("partial-B", messages[0]["content"])
def test_merge_messages_no_image_url_field(self):
gpt = _make_gpt()
messages = gpt._build_merge_messages(["x"])
import json
serialized = json.dumps(messages, ensure_ascii=False)
self.assertNotIn("image_url", serialized)
if __name__ == "__main__":
unittest.main()
|