160 lines
4.3 KiB
Python
160 lines
4.3 KiB
Python
"""Tests for dynamic plan adjustment."""
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import pytest
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from datetime import datetime
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from src.engines.plan_adjustment import (
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adjust_plan,
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identify_anomalies,
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_fallback_plan_adjustment
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)
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from src.models.analysis_plan import AnalysisPlan, AnalysisTask
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from src.models.analysis_result import AnalysisResult
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from src.models.requirement_spec import AnalysisObjective
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# Feature: true-ai-agent, Property 8: 计划动态调整
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def test_plan_adjustment_with_anomaly():
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"""
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Property 8: For any analysis plan and intermediate results, if results
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contain anomaly findings, the plan adjustment function should be able to
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generate new deep-dive tasks or adjust existing task priorities.
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Validates: 场景4验收.2, 场景4验收.3, FR-3.3
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"""
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# Create plan
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plan = AnalysisPlan(
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objectives=[
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AnalysisObjective(
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name="数据分析",
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description="分析数据",
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metrics=[],
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priority=3
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)
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],
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tasks=[
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AnalysisTask(
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id="task_1",
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name="Task 1",
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description="First task",
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priority=3,
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status='completed'
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),
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AnalysisTask(
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id="task_2",
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name="Task 2",
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description="Second task",
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priority=3,
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status='pending'
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)
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],
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created_at=datetime.now(),
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updated_at=datetime.now()
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)
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# Create results with anomaly
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results = [
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AnalysisResult(
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task_id="task_1",
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task_name="Task 1",
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success=True,
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insights=["发现异常：某类别占比90%，远超正常范围"],
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execution_time=1.0
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)
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]
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# Adjust plan (using fallback)
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adjusted_plan = _fallback_plan_adjustment(plan, results)
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# Verify: Plan should be updated
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assert adjusted_plan.updated_at >= plan.created_at
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# Verify: Pending task priority should be increased
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task_2 = next(t for t in adjusted_plan.tasks if t.id == "task_2")
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assert task_2.priority >= 3
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def test_identify_anomalies():
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"""Test anomaly identification from results."""
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results = [
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AnalysisResult(
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task_id="task_1",
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task_name="Task 1",
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success=True,
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insights=["发现异常数据", "正常分布"],
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execution_time=1.0
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),
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AnalysisResult(
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task_id="task_2",
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task_name="Task 2",
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success=True,
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insights=["一切正常"],
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execution_time=1.0
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)
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]
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anomalies = identify_anomalies(results)
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# Should identify one anomaly
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assert len(anomalies) >= 1
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assert anomalies[0]['task_id'] == "task_1"
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def test_plan_adjustment_no_anomaly():
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"""Test plan adjustment when no anomalies found."""
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plan = AnalysisPlan(
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objectives=[],
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tasks=[
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AnalysisTask(
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id="task_1",
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name="Task 1",
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description="First task",
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priority=3,
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status='completed'
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)
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],
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created_at=datetime.now(),
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updated_at=datetime.now()
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)
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results = [
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AnalysisResult(
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task_id="task_1",
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task_name="Task 1",
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success=True,
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insights=["一切正常"],
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execution_time=1.0
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)
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]
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adjusted_plan = _fallback_plan_adjustment(plan, results)
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# Should still update timestamp
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assert adjusted_plan.updated_at >= plan.created_at
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def test_identify_anomalies_empty_results():
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"""Test anomaly identification with empty results."""
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anomalies = identify_anomalies([])
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assert anomalies == []
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def test_identify_anomalies_failed_results():
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"""Test that failed results are skipped."""
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results = [
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AnalysisResult(
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task_id="task_1",
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task_name="Task 1",
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success=False,
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error="Failed",
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insights=["发现异常"],
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execution_time=1.0
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)
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]
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anomalies = identify_anomalies(results)
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# Failed results should be skipped
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assert len(anomalies) == 0
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