216 lines
7.2 KiB
Python
216 lines
7.2 KiB
Python
"""
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Unit tests for ScriptGenerator.
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[AC-IDS-04, AC-IDS-11] Test script generation for flexible mode.
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"""
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import asyncio
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import pytest
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from app.services.flow.script_generator import ScriptGenerator
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class MockLLMClient:
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"""Mock LLM client for testing."""
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def __init__(self, response: str = "您好，请问怎么称呼您？", delay: float = 0):
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self._response = response
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self._delay = delay
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async def generate_text(self, prompt: str) -> str:
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if self._delay > 0:
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await asyncio.sleep(self._delay)
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return self._response
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async def generate(self, messages: list) -> "MockResponse":
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if self._delay > 0:
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await asyncio.sleep(self._delay)
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return MockResponse(self._response)
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class MockResponse:
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"""Mock LLM response."""
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def __init__(self, content: str):
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self.content = content
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class TestScriptGenerator:
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"""[AC-IDS-04, AC-IDS-11] Test cases for ScriptGenerator."""
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@pytest.mark.asyncio
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async def test_generate_fixed_mode_returns_fallback(self):
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"""Test that fixed mode returns fallback content."""
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generator = ScriptGenerator(llm_client=None)
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result = await generator.generate(
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intent="获取用户姓名",
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intent_description="礼貌询问用户姓名",
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constraints=["必须礼貌"],
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context=None,
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history=None,
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fallback="请问怎么称呼您？",
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)
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assert result == "请问怎么称呼您？"
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@pytest.mark.asyncio
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async def test_generate_with_llm_client(self):
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"""Test script generation with LLM client."""
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llm_client = MockLLMClient(response="您好，请问您贵姓？")
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generator = ScriptGenerator(llm_client=llm_client)
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result = await generator.generate(
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intent="获取用户姓名",
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intent_description="礼貌询问用户姓名",
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constraints=["必须礼貌", "语气自然"],
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context={"inputs": [{"step": 1, "input": "我想咨询"}]},
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history=[{"role": "user", "content": "我想咨询"}],
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fallback="请问怎么称呼您？",
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)
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assert result == "您好，请问您贵姓？"
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@pytest.mark.asyncio
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async def test_generate_timeout_fallback(self):
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"""Test that timeout returns fallback content."""
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llm_client = MockLLMClient(response="生成的话术", delay=6.0)
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generator = ScriptGenerator(llm_client=llm_client)
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result = await generator.generate(
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intent="获取用户姓名",
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intent_description=None,
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constraints=None,
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context=None,
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history=None,
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fallback="请问怎么称呼您？",
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)
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assert result == "请问怎么称呼您？"
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@pytest.mark.asyncio
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async def test_generate_exception_fallback(self):
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"""Test that exception returns fallback content."""
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class FailingLLMClient:
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async def generate_text(self, prompt: str) -> str:
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raise RuntimeError("LLM service unavailable")
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generator = ScriptGenerator(llm_client=FailingLLMClient())
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result = await generator.generate(
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intent="获取用户姓名",
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intent_description=None,
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constraints=None,
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context=None,
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history=None,
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fallback="请问怎么称呼您？",
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)
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assert result == "请问怎么称呼您？"
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def test_build_prompt_basic(self):
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"""Test prompt building with basic parameters."""
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generator = ScriptGenerator(llm_client=None)
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prompt = generator._build_prompt(
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intent="获取用户姓名",
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intent_description=None,
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constraints=None,
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context=None,
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history=None,
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)
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assert "获取用户姓名" in prompt
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assert "步骤目标" in prompt
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def test_build_prompt_with_description(self):
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"""Test prompt building with intent description."""
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generator = ScriptGenerator(llm_client=None)
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prompt = generator._build_prompt(
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intent="获取用户姓名",
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intent_description="需要获取用户的真实姓名用于后续身份确认",
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constraints=None,
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context=None,
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history=None,
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)
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assert "获取用户姓名" in prompt
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assert "需要获取用户的真实姓名用于后续身份确认" in prompt
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assert "详细说明" in prompt
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def test_build_prompt_with_constraints(self):
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"""Test prompt building with constraints."""
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generator = ScriptGenerator(llm_client=None)
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prompt = generator._build_prompt(
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intent="获取用户姓名",
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intent_description=None,
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constraints=["必须礼貌", "语气自然", "不要生硬"],
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context=None,
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history=None,
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)
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assert "约束条件" in prompt
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assert "- 必须礼貌" in prompt
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assert "- 语气自然" in prompt
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assert "- 不要生硬" in prompt
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def test_build_prompt_with_history(self):
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"""Test prompt building with conversation history."""
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generator = ScriptGenerator(llm_client=None)
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prompt = generator._build_prompt(
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intent="获取用户姓名",
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intent_description=None,
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constraints=None,
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context=None,
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history=[
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{"role": "user", "content": "你好"},
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{"role": "assistant", "content": "您好，有什么可以帮您？"},
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{"role": "user", "content": "我想咨询"},
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],
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)
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assert "对话历史" in prompt
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assert "用户: 你好" in prompt
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assert "客服: 您好，有什么可以帮您？" in prompt
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def test_build_prompt_with_context(self):
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"""Test prompt building with session context."""
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generator = ScriptGenerator(llm_client=None)
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prompt = generator._build_prompt(
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intent="获取用户姓名",
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intent_description=None,
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constraints=None,
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context={
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"inputs": [
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{"step": 1, "input": "我想咨询产品"},
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{"step": 2, "input": "手机"},
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]
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},
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history=None,
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)
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assert "已收集信息" in prompt
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assert "步骤1: 我想咨询产品" in prompt
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assert "步骤2: 手机" in prompt
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def test_build_prompt_complete(self):
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"""Test prompt building with all parameters."""
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generator = ScriptGenerator(llm_client=None)
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prompt = generator._build_prompt(
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intent="获取用户姓名",
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intent_description="需要获取用户的真实姓名",
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constraints=["必须礼貌", "语气自然"],
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context={"inputs": [{"step": 1, "input": "咨询"}]},
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history=[{"role": "user", "content": "你好"}],
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)
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assert "步骤目标" in prompt
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assert "详细说明" in prompt
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assert "约束条件" in prompt
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assert "对话历史" in prompt
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assert "已收集信息" in prompt
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assert "不超过200字" in prompt
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