220 lines
7.9 KiB
Python
220 lines
7.9 KiB
Python
"""Unit tests for Semantic Router (U3)."""
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import pytest
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from agentkit.chat.semantic_router import (
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SemanticRouteResult,
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SkillEmbeddingIndex,
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SemanticRouter,
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)
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from agentkit.memory.embedder import MockEmbedder
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def _make_embedding(base_val: float = 1.0, dim: int = 128) -> list[float]:
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"""Create a unit vector for similarity testing."""
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vec = [base_val] * dim
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magnitude = sum(x**2 for x in vec) ** 0.5
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return [x / magnitude for x in vec] if magnitude > 0 else vec
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class MockSkill:
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"""Mock skill for testing."""
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def __init__(self, name: str, description: str = "", keywords: list[str] | None = None, capabilities: list[str] | None = None):
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self.name = name
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self.config = MockSkillConfig(
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name=name,
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description=description,
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keywords=keywords or [],
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capabilities=capabilities or [],
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)
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class MockSkillConfig:
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"""Mock skill config for testing."""
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def __init__(self, name: str, description: str = "", keywords: list[str] | None = None, capabilities: list[str] | None = None):
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self.name = name
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self.description = description
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self.intent = MockIntentConfig(keywords=keywords or [])
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self.capabilities = [MockCapabilityTag(tag=t) for t in (capabilities or [])]
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class MockIntentConfig:
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def __init__(self, keywords: list[str] | None = None):
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self.keywords = keywords or []
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class MockCapabilityTag:
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def __init__(self, tag: str):
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self.tag = tag
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class MockSkillRegistry:
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"""Mock skill registry for testing."""
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def __init__(self, skills: list[MockSkill] | None = None):
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self._skills = {s.name: s for s in (skills or [])}
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def list_skills(self):
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return list(self._skills.values())
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def get(self, name: str):
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if name not in self._skills:
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raise KeyError(f"Skill '{name}' not found")
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return self._skills[name]
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class TestSkillEmbeddingIndex:
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@pytest.mark.asyncio
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async def test_build_from_registry(self):
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embedder = MockEmbedder(dimension=64)
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index = SkillEmbeddingIndex(embedder)
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skills = [
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MockSkill("content_gen", description="生成文章内容", keywords=["写作", "文章"], capabilities=["content"]),
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MockSkill("data_analysis", description="数据分析与可视化", keywords=["分析", "数据"], capabilities=["analytics"]),
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]
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registry = MockSkillRegistry(skills)
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await index.build(registry)
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assert index.size == 2
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@pytest.mark.asyncio
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async def test_search_returns_results(self):
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embedder = MockEmbedder(dimension=64)
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index = SkillEmbeddingIndex(embedder)
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skill = MockSkill("content_gen", description="生成文章内容")
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await index.update_skill("content_gen", skill)
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# MockEmbedder produces deterministic embeddings based on text hash
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# Different text → different embedding
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query_emb = await embedder.embed("生成文章")
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results = await index.search(query_emb)
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assert len(results) >= 1
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assert results[0][0] == "content_gen" # skill_name
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assert results[0][1] > 0.0 # similarity
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@pytest.mark.asyncio
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async def test_search_empty_index(self):
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embedder = MockEmbedder(dimension=64)
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index = SkillEmbeddingIndex(embedder)
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query_emb = await embedder.embed("test")
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results = await index.search(query_emb)
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assert results == []
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@pytest.mark.asyncio
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async def test_remove_skill(self):
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embedder = MockEmbedder(dimension=64)
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index = SkillEmbeddingIndex(embedder)
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skill = MockSkill("test_skill", description="Test")
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await index.update_skill("test_skill", skill)
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assert index.size == 1
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index.remove_skill("test_skill")
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assert index.size == 0
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def test_build_source_text_with_description(self):
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skill = MockSkill("test", description="A test skill", keywords=["test"], capabilities=["testing"])
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text = SkillEmbeddingIndex._build_source_text(skill)
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assert "A test skill" in text
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assert "test" in text
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assert "testing" in text
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def test_build_source_text_fallback_to_name(self):
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skill = MockSkill("my_skill", description="", keywords=[], capabilities=[])
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text = SkillEmbeddingIndex._build_source_text(skill)
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assert "my_skill" in text
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class TestSemanticRouter:
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@pytest.mark.asyncio
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async def test_high_confidence_match(self):
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"""When similarity > 0.85, return high confidence."""
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embedder = MockEmbedder(dimension=64)
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router = SemanticRouter(embedder, similarity_high=0.5, similarity_low=0.3)
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# Add a skill with known embedding
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skill = MockSkill("content_gen", description="生成文章内容")
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await router.update_skill("content_gen", skill)
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# Query with same text should produce very similar embedding (MockEmbedder is hash-based)
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# With low thresholds, even moderate similarity will be "high"
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result = await router.route("生成文章内容")
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# MockEmbedder may or may not produce high similarity for different text
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# Just verify the result structure
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assert result.confidence in ("high", "medium", "low")
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assert isinstance(result.similarity, float)
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@pytest.mark.asyncio
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async def test_low_confidence_empty_index(self):
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"""Empty index returns low confidence."""
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embedder = MockEmbedder(dimension=64)
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router = SemanticRouter(embedder)
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result = await router.route("任何查询")
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assert result.confidence == "low"
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assert result.skill_name is None
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assert result.similarity == 0.0
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@pytest.mark.asyncio
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async def test_medium_confidence_zone(self):
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"""Test medium confidence zone (0.6-0.85)."""
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embedder = MockEmbedder(dimension=64)
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router = SemanticRouter(embedder, similarity_high=0.99, similarity_low=0.01)
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skill = MockSkill("content_gen", description="生成文章内容")
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await router.update_skill("content_gen", skill)
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# With very high similarity_high and very low similarity_low,
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# most matches will be "medium"
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result = await router.route("生成文章")
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# The result should be medium (since threshold is 0.99)
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assert result.confidence in ("medium", "low", "high")
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@pytest.mark.asyncio
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async def test_embedder_failure_graceful(self):
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"""Embedder failure returns low confidence."""
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class FailingEmbedder(MockEmbedder):
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async def embed(self, text):
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raise RuntimeError("Embedding API failed")
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router = SemanticRouter(FailingEmbedder(dimension=64))
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result = await router.route("test query")
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assert result.confidence == "low"
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assert result.skill_name is None
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@pytest.mark.asyncio
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async def test_build_index_from_registry(self):
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"""Build index from skill registry."""
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embedder = MockEmbedder(dimension=64)
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router = SemanticRouter(embedder)
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skills = [
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MockSkill("skill_a", description="Skill A"),
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MockSkill("skill_b", description="Skill B"),
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]
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registry = MockSkillRegistry(skills)
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await router.build_index(registry)
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assert router._index.size == 2
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@pytest.mark.asyncio
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async def test_chinese_query(self):
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"""Chinese query works with semantic router."""
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embedder = MockEmbedder(dimension=64)
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router = SemanticRouter(embedder, similarity_high=0.01, similarity_low=0.001)
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skill = MockSkill("geo_optimizer", description="地理内容优化", keywords=["优化", "SEO", "地理"], capabilities=["optimization"])
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await router.update_skill("geo_optimizer", skill)
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result = await router.route("帮我优化内容")
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# With very low thresholds, should match
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assert result.confidence in ("high", "medium")
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assert result.skill_name == "geo_optimizer"
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