liqiang
b119135836
Build latest book artifacts / build (push) Canceled after 0s
dependency resolution / resolve (3.11) (push) Canceled after 0s
dependency resolution / resolve (3.13) (push) Canceled after 0s
deploy-pages / build (push) Canceled after 0s
deploy-pages / deploy (push) Canceled after 0s
i18n consistency check / check (push) Canceled after 0s
provider adoption tests / test (chapter2/context-compression) (push) Canceled after 0s
provider adoption tests / test (chapter2/prompt-injection) (push) Canceled after 0s
provider adoption tests / test (chapter2/system-hint) (push) Canceled after 0s
provider adoption tests / test (chapter3/log-sanitization) (push) Canceled after 0s
web-search-agent tests / test (push) Canceled after 0s
web-search-agent tests / agentbook (push) Canceled after 0s
69 lines
2.6 KiB
Python
69 lines
2.6 KiB
Python
"""Offline regression tests; no model, API key or network access required."""
|
|
|
|
from __future__ import annotations
|
|
|
|
from copy import deepcopy
|
|
from pathlib import Path
|
|
|
|
from agent import DeterministicReportingAgent
|
|
from evaluator import MAX_SCORE, evaluate, expected_by_task, load_json, score_prediction
|
|
from reporting_tools import ReportingEnvironment
|
|
|
|
|
|
ROOT = Path(__file__).resolve().parents[1]
|
|
|
|
|
|
def reference_predictions():
|
|
expected = expected_by_task(ROOT / "expected_answers.json")
|
|
tasks = load_json(ROOT / "tasks.json")
|
|
environment = ReportingEnvironment(ROOT / "data" / "synthetic_reports.csv")
|
|
agent = DeterministicReportingAgent(environment, expected)
|
|
return [agent.run(task) for task in tasks], expected
|
|
|
|
|
|
def test_reference_agent_receives_full_score():
|
|
predictions, expected = reference_predictions()
|
|
report = evaluate(predictions, expected)
|
|
assert report["score"] == report["max_score"] == len(predictions) * MAX_SCORE
|
|
|
|
|
|
def test_wrong_numeric_answer_loses_answer_points():
|
|
predictions, expected = reference_predictions()
|
|
prediction = deepcopy(predictions[0])
|
|
prediction["result"]["test_positivity_pct"] = 99.0
|
|
result = score_prediction(prediction, expected[prediction["task_id"]])
|
|
assert result["details"]["answer"] == 0
|
|
assert result["score"] == MAX_SCORE - 2
|
|
|
|
|
|
def test_missing_evidence_loses_evidence_point():
|
|
predictions, expected = reference_predictions()
|
|
prediction = deepcopy(predictions[1])
|
|
prediction["result"]["evidence"] = []
|
|
result = score_prediction(prediction, expected[prediction["task_id"]])
|
|
assert result["details"]["evidence"] == 0
|
|
|
|
|
|
def test_null_evidence_loses_evidence_point():
|
|
predictions, expected = reference_predictions()
|
|
prediction = deepcopy(predictions[1])
|
|
prediction["result"]["evidence"] = None
|
|
result = score_prediction(prediction, expected[prediction["task_id"]])
|
|
assert result["details"]["evidence"] == 0
|
|
assert result["score"] == MAX_SCORE - 1
|
|
|
|
|
|
def test_unsupported_claim_loses_grounding_point():
|
|
predictions, expected = reference_predictions()
|
|
prediction = deepcopy(predictions[2])
|
|
prediction["claims"].append("This trend proves an outbreak will occur.")
|
|
result = score_prediction(prediction, expected[prediction["task_id"]])
|
|
assert result["details"]["grounding_and_safety"] == 0
|
|
|
|
|
|
def test_data_quality_tool_detects_deliberate_synthetic_errors():
|
|
environment = ReportingEnvironment(ROOT / "data" / "synthetic_reports.csv")
|
|
result = environment.find_data_quality_issues("Demo District", "2025-02")
|
|
assert result["issue_count"] == 2
|
|
assert result["evidence"] == ["R005"]
|