starmen1265
87d64b57c0
- Test schema validation for AnalyzeInput (metadata_file, content_file, content_type, output_file) - Test schema validation for AnalyzeOutput (analysis_file, summary, main_topics, key_insights, tags, stats) - Test AnalyzeProcessor integration with DeepAnalyzer - Test state recording on success and failure Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
418 lines
17 KiB
Python
418 lines
17 KiB
Python
"""Tests for AnalyzeProcessor and AnalyzeInput/AnalyzeOutput schemas.
|
|
|
|
Test coverage:
|
|
- AnalyzeInput schema validation
|
|
- AnalyzeOutput schema validation
|
|
- AnalyzeProcessor DeepAnalyzer integration
|
|
- AnalyzeProcessor state recording
|
|
"""
|
|
|
|
import pytest
|
|
import json
|
|
from datetime import datetime
|
|
from unittest.mock import AsyncMock, MagicMock, patch
|
|
from pathlib import Path
|
|
|
|
from kb_pipeline.schemas import AnalyzeInput, AnalyzeOutput
|
|
|
|
|
|
class TestAnalyzeInputSchema:
|
|
"""Tests for AnalyzeInput schema validation."""
|
|
|
|
def test_schema_analyze_input_validates_required_fields(self):
|
|
"""Test 1: AnalyzeInput validates required fields"""
|
|
input_data = AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file="/tmp/content/bilibili_BV1xx_metadata.json",
|
|
content_file="/tmp/content/bilibili_BV1xx.json",
|
|
content_type="video",
|
|
output_file="/tmp/content/bilibili_BV1xx_analysis.md"
|
|
)
|
|
assert input_data.content_id == "BV1xx"
|
|
assert input_data.platform == "bilibili"
|
|
assert input_data.metadata_file == "/tmp/content/bilibili_BV1xx_metadata.json"
|
|
assert input_data.content_file == "/tmp/content/bilibili_BV1xx.json"
|
|
assert input_data.content_type == "video"
|
|
assert input_data.output_file == "/tmp/content/bilibili_BV1xx_analysis.md"
|
|
|
|
def test_schema_analyze_input_requires_metadata_file(self):
|
|
"""AnalyzeInput should require metadata_file"""
|
|
with pytest.raises(Exception): # ValidationError from pydantic
|
|
AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
content_file="/tmp/content/bilibili_BV1xx.json",
|
|
content_type="video",
|
|
output_file="/tmp/content/bilibili_BV1xx_analysis.md"
|
|
# Missing metadata_file
|
|
)
|
|
|
|
def test_schema_analyze_input_requires_content_file(self):
|
|
"""AnalyzeInput should require content_file"""
|
|
with pytest.raises(Exception): # ValidationError from pydantic
|
|
AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file="/tmp/content/bilibili_BV1xx_metadata.json",
|
|
content_type="video",
|
|
output_file="/tmp/content/bilibili_BV1xx_analysis.md"
|
|
# Missing content_file
|
|
)
|
|
|
|
def test_schema_analyze_input_requires_content_type(self):
|
|
"""AnalyzeInput should require content_type"""
|
|
with pytest.raises(Exception): # ValidationError from pydantic
|
|
AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file="/tmp/content/bilibili_BV1xx_metadata.json",
|
|
content_file="/tmp/content/bilibili_BV1xx.json",
|
|
output_file="/tmp/content/bilibili_BV1xx_analysis.md"
|
|
# Missing content_type
|
|
)
|
|
|
|
def test_schema_analyze_input_requires_output_file(self):
|
|
"""AnalyzeInput should require output_file"""
|
|
with pytest.raises(Exception): # ValidationError from pydantic
|
|
AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file="/tmp/content/bilibili_BV1xx_metadata.json",
|
|
content_file="/tmp/content/bilibili_BV1xx.json",
|
|
content_type="video"
|
|
# Missing output_file
|
|
)
|
|
|
|
|
|
class TestAnalyzeOutputSchema:
|
|
"""Tests for AnalyzeOutput schema validation."""
|
|
|
|
def test_schema_analyze_output_validates_required_fields(self):
|
|
"""Test 2: AnalyzeOutput validates required fields"""
|
|
output = AnalyzeOutput(
|
|
success=True,
|
|
analysis_file="/tmp/content/bilibili_BV1xx_analysis.md",
|
|
summary="This is a test summary",
|
|
main_topics=["Topic 1", "Topic 2"],
|
|
key_insights=["Insight 1", "Insight 2"],
|
|
tags=["tag1", "tag2"],
|
|
stats={"segments_count": 10}
|
|
)
|
|
assert output.success is True
|
|
assert output.analysis_file == "/tmp/content/bilibili_BV1xx_analysis.md"
|
|
assert output.summary == "This is a test summary"
|
|
assert output.main_topics == ["Topic 1", "Topic 2"]
|
|
assert output.key_insights == ["Insight 1", "Insight 2"]
|
|
assert output.tags == ["tag1", "tag2"]
|
|
assert output.stats == {"segments_count": 10}
|
|
|
|
def test_schema_analyze_output_handles_video_content_type(self):
|
|
"""Test 3: AnalyzeOutput handles video content type"""
|
|
output = AnalyzeOutput(
|
|
success=True,
|
|
analysis_file="/tmp/content/bilibili_BV1xx_analysis.md",
|
|
summary="Video summary",
|
|
main_topics=["Topic 1"],
|
|
key_insights=["Insight 1"],
|
|
tags=["video", "test"],
|
|
stats={"duration": 300, "segments": 15}
|
|
)
|
|
assert output.success is True
|
|
assert "duration" in output.stats
|
|
assert output.stats["segments"] == 15
|
|
|
|
def test_schema_analyze_output_handles_article_content_type(self):
|
|
"""Test 3: AnalyzeOutput handles article content type"""
|
|
output = AnalyzeOutput(
|
|
success=True,
|
|
analysis_file="/tmp/content/zhihu_123_analysis.md",
|
|
summary="Article summary",
|
|
main_topics=["Topic 1"],
|
|
key_insights=[],
|
|
tags=["article", "zhihu"],
|
|
stats={"word_count": 2000}
|
|
)
|
|
assert output.success is True
|
|
assert "word_count" in output.stats
|
|
|
|
def test_schema_analyze_output_handles_failure(self):
|
|
"""AnalyzeOutput should handle failure case"""
|
|
output = AnalyzeOutput(
|
|
success=False,
|
|
error_message="AI API error",
|
|
analysis_file="",
|
|
summary="",
|
|
main_topics=[],
|
|
key_insights=[],
|
|
tags=[],
|
|
stats={}
|
|
)
|
|
assert output.success is False
|
|
assert output.error_message == "AI API error"
|
|
|
|
|
|
class TestAnalyzeProcessorIntegration:
|
|
"""Tests for AnalyzeProcessor DeepAnalyzer integration."""
|
|
|
|
@pytest.fixture
|
|
def mock_deep_analyzer(self):
|
|
"""Create a mock DeepAnalyzer result."""
|
|
from dataclasses import dataclass, field
|
|
from typing import List
|
|
|
|
@dataclass
|
|
class AnalysisResult:
|
|
summary: str = "Test summary"
|
|
main_topics: List[str] = field(default_factory=lambda: ["Topic 1", "Topic 2"])
|
|
key_insights: List[str] = field(default_factory=lambda: ["Insight 1"])
|
|
recommended_tags: List[str] = field(default_factory=lambda: ["tag1", "tag2"])
|
|
full_analysis: str = "## Summary\n\nTest analysis content"
|
|
original_text: str = ""
|
|
|
|
return AnalysisResult()
|
|
|
|
@pytest.fixture
|
|
def mock_state_manager(self):
|
|
"""Create a mock WorkflowStateManager."""
|
|
manager = MagicMock()
|
|
manager.load = MagicMock(return_value=None)
|
|
manager.save = MagicMock()
|
|
return manager
|
|
|
|
@pytest.fixture
|
|
def sample_metadata(self, tmp_path):
|
|
"""Create sample metadata file."""
|
|
metadata = {
|
|
"title": "Test Video Title",
|
|
"author": "Test Author",
|
|
"pubtime": "2024-01-01",
|
|
"duration": 300,
|
|
"bvid": "BV1xx",
|
|
"platform": "bilibili",
|
|
"url": "https://www.bilibili.com/video/BV1xx"
|
|
}
|
|
metadata_file = tmp_path / "bilibili_BV1xx_metadata.json"
|
|
metadata_file.write_text(json.dumps(metadata, ensure_ascii=False), encoding="utf-8")
|
|
return str(metadata_file)
|
|
|
|
@pytest.fixture
|
|
def sample_content(self, tmp_path):
|
|
"""Create sample content file."""
|
|
content = {
|
|
"text": "This is the full transcript of the video."
|
|
}
|
|
content_file = tmp_path / "bilibili_BV1xx.json"
|
|
content_file.write_text(json.dumps(content, ensure_ascii=False), encoding="utf-8")
|
|
return str(content_file)
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_analyze_loads_metadata_and_content_from_files(
|
|
self, mock_deep_analyzer, mock_state_manager, sample_metadata, sample_content, tmp_path
|
|
):
|
|
"""Test 1: AnalyzeProcessor loads metadata and content from files"""
|
|
from kb_pipeline.processors.analyze import AnalyzeProcessor
|
|
from kb_pipeline.schemas import AnalyzeInput
|
|
|
|
output_file = str(tmp_path / "bilibili_BV1xx_analysis.md")
|
|
|
|
input_data = AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file=sample_metadata,
|
|
content_file=sample_content,
|
|
content_type="video",
|
|
output_file=output_file
|
|
)
|
|
|
|
with patch("kb_pipeline.processors.base.get_settings") as mock_settings:
|
|
mock_settings.return_value = MagicMock()
|
|
with patch("kb_pipeline.processors.analyze.DeepAnalyzer") as MockDeepAnalyzer:
|
|
mock_analyzer_instance = MagicMock()
|
|
mock_analyzer_instance.analyze = MagicMock(return_value=mock_deep_analyzer)
|
|
MockDeepAnalyzer.return_value = mock_analyzer_instance
|
|
|
|
processor = AnalyzeProcessor(state_manager=mock_state_manager)
|
|
result = await processor.process(input_data)
|
|
|
|
assert result.success is True
|
|
# Verify DeepAnalyzer.analyze was called with loaded data
|
|
mock_analyzer_instance.analyze.assert_called_once()
|
|
call_args = mock_analyzer_instance.analyze.call_args
|
|
assert "title" in call_args[0][0] # metadata dict
|
|
assert "text" in call_args[0][1] # content dict
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_analyze_calls_deep_analyzer_with_correct_parameters(
|
|
self, mock_deep_analyzer, mock_state_manager, sample_metadata, sample_content, tmp_path
|
|
):
|
|
"""Test 2: AnalyzeProcessor calls DeepAnalyzer.analyze() with correct parameters"""
|
|
from kb_pipeline.processors.analyze import AnalyzeProcessor
|
|
from kb_pipeline.schemas import AnalyzeInput
|
|
|
|
output_file = str(tmp_path / "bilibili_BV1xx_analysis.md")
|
|
|
|
input_data = AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file=sample_metadata,
|
|
content_file=sample_content,
|
|
content_type="video",
|
|
output_file=output_file
|
|
)
|
|
|
|
with patch("kb_pipeline.processors.base.get_settings") as mock_settings:
|
|
mock_settings.return_value = MagicMock()
|
|
with patch("kb_pipeline.processors.analyze.DeepAnalyzer") as MockDeepAnalyzer:
|
|
mock_analyzer_instance = MagicMock()
|
|
mock_analyzer_instance.analyze = MagicMock(return_value=mock_deep_analyzer)
|
|
MockDeepAnalyzer.return_value = mock_analyzer_instance
|
|
|
|
processor = AnalyzeProcessor(state_manager=mock_state_manager)
|
|
result = await processor.process(input_data)
|
|
|
|
assert result.success is True
|
|
# Verify content_type was passed correctly
|
|
call_kwargs = mock_analyzer_instance.analyze.call_args
|
|
assert call_kwargs[0][2] == "video" # content_type parameter
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_analyze_saves_analysis_report_as_markdown(
|
|
self, mock_deep_analyzer, mock_state_manager, sample_metadata, sample_content, tmp_path
|
|
):
|
|
"""Test 3: AnalyzeProcessor saves analysis report as Markdown"""
|
|
from kb_pipeline.processors.analyze import AnalyzeProcessor
|
|
from kb_pipeline.schemas import AnalyzeInput
|
|
|
|
output_file = str(tmp_path / "bilibili_BV1xx_analysis.md")
|
|
|
|
input_data = AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file=sample_metadata,
|
|
content_file=sample_content,
|
|
content_type="video",
|
|
output_file=output_file
|
|
)
|
|
|
|
with patch("kb_pipeline.processors.base.get_settings") as mock_settings:
|
|
mock_settings.return_value = MagicMock()
|
|
with patch("kb_pipeline.processors.analyze.DeepAnalyzer") as MockDeepAnalyzer:
|
|
mock_analyzer_instance = MagicMock()
|
|
mock_analyzer_instance.analyze = MagicMock(return_value=mock_deep_analyzer)
|
|
MockDeepAnalyzer.return_value = mock_analyzer_instance
|
|
|
|
processor = AnalyzeProcessor(state_manager=mock_state_manager)
|
|
result = await processor.process(input_data)
|
|
|
|
assert result.success is True
|
|
assert result.analysis_file == output_file
|
|
|
|
# Verify Markdown file was created
|
|
output_path = Path(output_file)
|
|
assert output_path.exists()
|
|
|
|
# Verify content includes frontmatter and analysis
|
|
content = output_path.read_text(encoding="utf-8")
|
|
assert content.startswith("---") # YAML frontmatter
|
|
assert "##" in content # Markdown headers
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_analyze_records_state_on_success(
|
|
self, mock_deep_analyzer, mock_state_manager, sample_metadata, sample_content, tmp_path
|
|
):
|
|
"""Test 4: AnalyzeProcessor records state on success"""
|
|
from kb_pipeline.processors.analyze import AnalyzeProcessor
|
|
from kb_pipeline.schemas import AnalyzeInput, WorkflowState
|
|
|
|
# Create a mock state that will be updated
|
|
mock_state = MagicMock(spec=WorkflowState)
|
|
mock_state.is_step_completed = MagicMock(return_value=False)
|
|
mock_state_manager.load.return_value = mock_state
|
|
|
|
output_file = str(tmp_path / "bilibili_BV1xx_analysis.md")
|
|
|
|
input_data = AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file=sample_metadata,
|
|
content_file=sample_content,
|
|
content_type="video",
|
|
output_file=output_file
|
|
)
|
|
|
|
with patch("kb_pipeline.processors.base.get_settings") as mock_settings:
|
|
mock_settings.return_value = MagicMock()
|
|
with patch("kb_pipeline.processors.analyze.DeepAnalyzer") as MockDeepAnalyzer:
|
|
mock_analyzer_instance = MagicMock()
|
|
mock_analyzer_instance.analyze = MagicMock(return_value=mock_deep_analyzer)
|
|
MockDeepAnalyzer.return_value = mock_analyzer_instance
|
|
|
|
processor = AnalyzeProcessor(state_manager=mock_state_manager)
|
|
result = await processor.process(input_data)
|
|
|
|
assert result.success is True
|
|
|
|
# Verify state was recorded
|
|
mock_state.mark_step_completed.assert_called_once()
|
|
call_args = mock_state.mark_step_completed.call_args
|
|
assert call_args[0][0] == "analyze" # step_name
|
|
mock_state_manager.save.assert_called_once_with(mock_state)
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_analyze_records_state_on_failure(
|
|
self, mock_state_manager, sample_metadata, sample_content, tmp_path
|
|
):
|
|
"""Test 5: AnalyzeProcessor records state on failure"""
|
|
from kb_pipeline.processors.analyze import AnalyzeProcessor
|
|
from kb_pipeline.schemas import AnalyzeInput, WorkflowState
|
|
|
|
# Create a mock state that will be updated
|
|
mock_state = MagicMock(spec=WorkflowState)
|
|
mock_state.is_step_completed = MagicMock(return_value=False)
|
|
mock_state_manager.load.return_value = mock_state
|
|
|
|
output_file = str(tmp_path / "bilibili_BV1xx_analysis.md")
|
|
|
|
input_data = AnalyzeInput(
|
|
content_id="BV1xx",
|
|
platform="bilibili",
|
|
metadata_file=sample_metadata,
|
|
content_file=sample_content,
|
|
content_type="video",
|
|
output_file=output_file
|
|
)
|
|
|
|
with patch("kb_pipeline.processors.base.get_settings") as mock_settings:
|
|
mock_settings.return_value = MagicMock()
|
|
with patch("kb_pipeline.processors.analyze.DeepAnalyzer") as MockDeepAnalyzer:
|
|
mock_analyzer_instance = MagicMock()
|
|
mock_analyzer_instance.analyze = MagicMock(
|
|
side_effect=ValueError("AI API error")
|
|
)
|
|
MockDeepAnalyzer.return_value = mock_analyzer_instance
|
|
|
|
processor = AnalyzeProcessor(state_manager=mock_state_manager)
|
|
result = await processor.process(input_data)
|
|
|
|
assert result.success is False
|
|
assert "AI API error" in result.error_message
|
|
|
|
# Verify failure was recorded
|
|
mock_state.mark_step_failed.assert_called_once()
|
|
call_args = mock_state.mark_step_failed.call_args
|
|
assert call_args[0][0] == "analyze" # step_name
|
|
mock_state_manager.save.assert_called_once_with(mock_state)
|
|
|
|
|
|
class TestAnalyzeProcessorModuleExport:
|
|
"""Tests for AnalyzeProcessor module export."""
|
|
|
|
def test_analyze_processor_importable_from_processors(self):
|
|
"""Test: AnalyzeProcessor can be imported from kb_pipeline.processors"""
|
|
from kb_pipeline.processors import AnalyzeProcessor
|
|
|
|
assert AnalyzeProcessor is not None
|
|
assert hasattr(AnalyzeProcessor, 'STEP_NAME')
|
|
assert AnalyzeProcessor.STEP_NAME == "analyze"
|