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ai-agent-book 精选快照(<2MB 代码与文档,来自 github.com/bojieli/ai-agent-book)
2026-08-20 13:12:50 +00:00

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"""Focused, offline checks for Experiment 7-12 evidence/reporting."""
from __future__ import annotations
from argparse import Namespace
import sqlite3
import pytest
from experiment_core import (
BASELINE_TASK_COUNT,
aggregate_episodes,
choose_decision,
choose_efficiency_decision,
enforce_scope_claims,
paired_rows,
redact_text,
render_report,
)
from run_controlled_experiment import (
_context_safe_output_cap,
_missing_retro_queue_as_empty,
_read_nonempty_with_retry,
_retry_clipper_foreground,
_truncate_current_ui_section,
_validate_resume_evidence,
)
def _episode(arm: str, task: str, success: bool, latency: float) -> dict:
return {
"pair_id": task + ":trial-1",
"task": task,
"trial": 1,
"arm": arm,
"status": "completed",
"success": success,
"evaluator_reward": float(success),
"steps": 3 if success else 10,
"elapsed_s": latency,
"llm": {"calls": 4, "input_tokens": 100, "output_tokens": 20},
}
def test_redaction_covers_explicit_and_pattern_credentials() -> None:
secret = "definitely-not-for-output"
text = redact_text(
f"api_key={secret} Authorization: Bearer abcdefghijk sk-example123456789",
[secret],
)
assert secret not in text
assert "abcdefghijk" not in text
assert "sk-example123456789" not in text
assert text.count("[REDACTED]") >= 3
def test_retro_missing_queue_schema_becomes_empty_observation() -> None:
def missing_queue(_env: object) -> list[str]:
raise sqlite3.OperationalError("no such table: playing_queue")
assert _missing_retro_queue_as_empty(missing_queue)(object()) == []
def test_retro_compatibility_does_not_hide_other_sqlite_errors() -> None:
def corrupt_database(_env: object) -> list[str]:
raise sqlite3.OperationalError("database disk image is malformed")
with pytest.raises(sqlite3.OperationalError, match="malformed"):
_missing_retro_queue_as_empty(corrupt_database)(object())
def test_context_cap_keeps_headroom_for_provider_lower_bound() -> None:
error = (
"This model's maximum context length is 32768 tokens. However, you "
"requested 1024 output tokens and your prompt contains at least 31745 "
"input tokens."
)
assert _context_safe_output_cap(error, 1024) == 991
assert _context_safe_output_cap("unrelated provider error", 1024) is None
def test_context_truncation_is_limited_to_middle_of_current_ui() -> None:
prefix = "prefix and goal"
ui = "A" * 9000 + "M" * 16384 + "Z" * 9000
suffix = "guidance and output format"
prompt = (
prefix
+ "\n\nHere is a list of descriptions for some UI elements on the current screen:\n"
+ ui
+ "\nHere are some useful guidelines you need to follow:\n"
+ suffix
)
result = _truncate_current_ui_section(prompt)
assert result is not None
truncated, removed = result
assert prefix in truncated and suffix in truncated
assert "A" * 1000 in truncated and "Z" * 1000 in truncated
assert removed > 0
assert len(truncated) < len(prompt)
def test_context_truncation_handles_before_and_after_summary_ui() -> None:
before = "B" * 12000
after = "A" * 12000
prompt = (
"goal and summary rules\n"
"Here is the description for the before screenshot:\n"
+ before
+ "\nHere is the description for the after screenshot:\n"
+ after
+ "\nThis is the action you picked: click\nBased on the reason: test"
)
result = _truncate_current_ui_section(prompt)
assert result is not None
truncated, removed = result
assert "goal and summary rules" in truncated
assert "This is the action you picked: click" in truncated
assert "B" * 500 in truncated and "A" * 500 in truncated
assert removed > 0
def test_sms_inbox_poll_preserves_empty_then_observed_result() -> None:
reads = iter([[], [], ["Row: 0, address=123, body=hello"]])
assert _read_nonempty_with_retry(
lambda: next(reads), attempts=3, delay_s=0
) == ["Row: 0, address=123, body=hello"]
def test_clipper_retry_is_limited_to_exact_foreground_error() -> None:
attempts = iter([
RuntimeError(
"Clipper app must be in the foreground to access clipboard. "
"Additionally, app privileges must be granted manually."
),
"clipboard value",
])
def flaky_call() -> str:
result = next(attempts)
if isinstance(result, Exception):
raise result
return result
assert _retry_clipper_foreground(flaky_call, delay_s=0) == "clipboard value"
with pytest.raises(RuntimeError, match="unrelated"):
_retry_clipper_foreground(
lambda: (_ for _ in ()).throw(RuntimeError("unrelated")), delay_s=0
)
def test_paired_comparison_and_conservative_candidate_decision() -> None:
episodes = []
for index in range(4):
task = f"wifi-{index}"
episodes.extend([
_episode("control", task, index > 0, 10.0),
_episode("treatment", task, True, 11.0),
])
summary = aggregate_episodes(episodes)
pairs = paired_rows(episodes)
decision = choose_decision(summary, pairs)
assert len(pairs) == 4
assert decision["net_success_delta"] == 1
assert decision["paired_regressions"] == 0
assert decision["promote_to_full_suite_candidate"] is True
assert decision["outcome"] == "promote_candidate_to_full_suite_rerun"
def test_subset_can_never_claim_full_suite_completion() -> None:
evidence = {
"scope": {
"mode": "candidate_rerun",
"tasks": ["a", "b", "c", "d"],
"trials_per_task": 5,
"completed_episodes": 20,
"error_episodes": 0,
},
"decision": {"source_paired_run_id": "paired-real"},
}
enforce_scope_claims(evidence)
assert evidence["scope"]["full_suite_completed"] is False
assert evidence["experiment_complete"] is False
def test_full_suite_gate_requires_direct_116_by_5_evidence() -> None:
tasks = [f"task-{index}" for index in range(BASELINE_TASK_COUNT)]
episodes = [
{
"task": task,
"trial": trial,
"pair_seed": task_index * 1009 + trial,
"arm": "candidate",
"status": "completed",
"evaluator_reward": 1.0,
}
for task_index, task in enumerate(tasks)
for trial in range(1, 6)
]
evidence = {
"scope": {
"mode": "candidate_rerun",
"tasks": tasks,
"trials_per_task": 5,
"completed_episodes": BASELINE_TASK_COUNT * 5,
"error_episodes": 0,
},
"episodes": episodes,
"decision": {"source_paired_run_id": "paired-real"},
"environment": {
"api_level": 33,
"emulator_setup_completed": True,
"app_provisioning": {"complete": True},
},
}
enforce_scope_claims(evidence)
assert evidence["scope"]["full_suite_completed"] is True
assert evidence["experiment_complete"] is True
def test_full_suite_gate_requires_reference_api_and_apps() -> None:
tasks = [f"task-{index}" for index in range(BASELINE_TASK_COUNT)]
episodes = [
{
"task": task,
"trial": trial,
"pair_seed": task_index * 1009 + trial,
"arm": "candidate",
"status": "completed",
"evaluator_reward": 0.0,
}
for task_index, task in enumerate(tasks)
for trial in range(1, 6)
]
evidence = {
"scope": {
"mode": "candidate_rerun",
"tasks": tasks,
"trials_per_task": 5,
},
"episodes": episodes,
"decision": {"source_paired_run_id": "paired-real"},
"environment": {
"api_level": 35,
"emulator_setup_completed": False,
"app_provisioning": {"complete": False},
},
}
enforce_scope_claims(evidence)
assert evidence["scope"]["direct_episode_gate_completed"] is True
assert evidence["scope"]["full_suite_completed"] is False
assert evidence["experiment_complete"] is False
def test_full_suite_gate_rejects_counters_without_direct_episodes() -> None:
evidence = {
"scope": {
"mode": "candidate_rerun",
"tasks": [f"task-{index}" for index in range(BASELINE_TASK_COUNT)],
"trials_per_task": 5,
"completed_episodes": BASELINE_TASK_COUNT * 5,
"error_episodes": 0,
},
"episodes": [],
"decision": {"source_paired_run_id": "paired-real"},
}
enforce_scope_claims(evidence)
assert evidence["scope"]["direct_episode_gate_completed"] is False
assert evidence["scope"]["full_suite_completed"] is False
assert evidence["experiment_complete"] is False
def test_success_gain_over_cost_guardrail_is_not_promoted() -> None:
episodes = []
for index in range(4):
task = f"wifi-{index}"
control = _episode("control", task, index > 0, 10.0)
treatment = _episode("treatment", task, True, 20.0)
treatment["llm"]["input_tokens"] = 1000
treatment["llm"]["output_tokens"] = 200
episodes.extend([control, treatment])
summary = aggregate_episodes(episodes)
decision = choose_decision(summary, paired_rows(episodes))
assert decision["outcome"] == "restrict_candidate_due_to_cost"
assert decision["guardrails"]["passed"] is False
assert decision["promote_to_full_suite_candidate"] is False
assert decision["deployment_approved"] is False
def test_efficiency_refinement_can_promote_without_inventing_success_gain() -> None:
episodes = []
for index in range(4):
task = f"wifi-{index}"
control = _episode("control", task, True, 10.0)
treatment = _episode("treatment", task, True, 9.0)
treatment["llm"]["input_tokens"] = 40
treatment["llm"]["output_tokens"] = 10
episodes.extend([control, treatment])
decision = choose_efficiency_decision(
aggregate_episodes(episodes), paired_rows(episodes)
)
assert decision["net_success_delta"] == 0
assert decision["paired_regressions"] == 0
assert decision["guardrails"]["passed"] is True
assert decision["promote_to_full_suite_candidate"] is True
assert decision["deployment_approved"] is False
def test_efficiency_refinement_rejects_cheap_but_unsuccessful_treatment() -> None:
episodes = []
for index in range(4):
task = f"wifi-{index}"
control = _episode("control", task, False, 10.0)
treatment = _episode("treatment", task, False, 9.0)
treatment["llm"]["input_tokens"] = 40
treatment["llm"]["output_tokens"] = 10
episodes.extend([control, treatment])
decision = choose_efficiency_decision(
aggregate_episodes(episodes), paired_rows(episodes)
)
assert decision["mean_token_ratio_treatment_over_control"] < 0.75
assert decision["success_preservation_passed"] is False
assert decision["guardrails"]["passed"] is False
assert decision["outcome"] == "reject_efficiency_candidate_due_to_regression"
assert decision["promote_to_full_suite_candidate"] is False
def test_report_labels_historical_and_hypothetical_numbers() -> None:
evidence = {
"run_id": "test-run",
"generated_at_utc": "2026-07-29T00:00:00Z",
"environment": {
"android_world_commit": "abc123",
"device_model": "emulator",
"api_level": 35,
"upstream_tested_api_level": 33,
},
"model": {"provider": "real-provider", "model": "real-model"},
"scope": {
"tasks": ["SystemWifiTurnOn"],
"trials_per_task": 1,
"mode": "paired",
"full_suite_completed": False,
},
"diagnosis": {"findings": ["Historical finding."]},
"hypothesis": {
"id": "H1",
"change": "Add a task guideline.",
"expected_result": "Improve paired reward.",
"guardrails": "Same task and model.",
},
"arm_summary": {},
"paired_comparison": [],
"decision": {
"outcome": "insufficient_evidence",
"reason": "Need four pairs.",
},
"episodes": [],
"environment_boundaries": ["API mismatch."],
"llm_analysis": {
"status": "completed",
"summary": "Observed subset summary.",
"observed_failure_pattern": ["One bounded residual pattern."],
"cost_benefit_interpretation": "No deployment approval.",
"next_hypothesis": {
"id": "H5",
"layer": "middle",
"idea": "Test the input path.",
"target": "One paired gain.",
"verification": "Matched paired run.",
},
},
}
report = render_report(evidence)
assert "historical input evidence" in report
assert "explicitly hypothetical" in report
assert "not the complete AndroidWorld benchmark" in report
assert "Full 116-task × 5-seed suite completed: **false**" in report
assert "Observed subset summary." in report
assert "No deployment approval." in report
def test_resume_rejects_changed_configuration() -> None:
evidence = {
"experiment": "7-12",
"hypothesis": {"id": "H5"},
"scope": {
"mode": "paired",
"tasks": ["SystemWifiTurnOff"],
"trials_per_task": 1,
"max_steps": 10,
},
"model": {
"model": "real-model",
"seed": 42,
"provider": "real-provider",
"base_url": "https://provider.invalid/v1",
"max_tokens": 1024,
},
"environment": {
"skip_device_time": True,
"device_serial": "emulator-5554",
"grpc_port": 8554,
},
"episodes": [],
}
args = Namespace(
tasks="SystemWifiTurnOff",
hypothesis="H5",
mode="paired",
trials=1,
max_steps=11,
model="real-model",
model_seed=42,
provider="real-provider",
base_url="https://provider.invalid/v1",
max_model_tokens=1024,
transition_pause=None,
skip_device_time=True,
console_port=5554,
grpc_port=8554,
seed=42,
)
with pytest.raises(RuntimeError, match="max_steps"):
_validate_resume_evidence(evidence, args)
def test_resume_rejects_changed_pair_seed() -> None:
evidence = {
"experiment": "7-12",
"hypothesis": {"id": "H5C"},
"scope": {
"mode": "paired",
"tasks": ["SystemWifiTurnOff"],
"trials_per_task": 1,
"max_steps": 10,
},
"model": {
"model": "real-model",
"seed": 42,
"provider": "real-provider",
"base_url": "https://provider.invalid/v1",
"max_tokens": 1024,
},
"environment": {
"skip_device_time": True,
"device_serial": "emulator-5554",
"grpc_port": 8554,
},
"episodes": [{
"task": "SystemWifiTurnOff",
"trial": 1,
"arm": "control",
"pair_seed": 42,
}],
}
args = Namespace(
tasks="SystemWifiTurnOff",
hypothesis="H5C",
mode="paired",
trials=1,
max_steps=10,
model="real-model",
model_seed=42,
provider="real-provider",
base_url="https://provider.invalid/v1",
max_model_tokens=1024,
transition_pause=None,
skip_device_time=True,
console_port=5554,
grpc_port=8554,
seed=43,
)
with pytest.raises(RuntimeError, match="Resume seed mismatch"):
_validate_resume_evidence(evidence, args)