G0~G8 성과·동맹 측정 OS 작업 일괄 고정
8월 7일까지 워킹트리에만 남아 있던 미커밋 작업을 커밋한다. 여러 사본 폴더(worktree·clone)에 흩어져 있던 중간 스냅샷을 정리하기 전에 원본을 git 이력으로 고정하는 것이 목적이다. - contracts/routes/services: measurement, outcome_trajectory, rupture_repair, deliberate_practice, calibration_transfer, supervision_research, multimodal_alliance, continuous_improvement 계열 신규 모듈과 테스트 - infra/db/init: 07~16 마이그레이션(측정 기반~calibration transfer 실행) - apps/web: 세션 리뷰 카드·관리 화면·E2E 스펙 추가 - docs/ops: G0~G8 라이브 통합·배포·롤백 증거 문서와 evidence JSON/PNG - scripts: smoke·ledger·릴리스 에이전트·NAS 프리뷰 운영 스크립트 engine.public 로그 .bak과 apps/web/test-results 산출물은 커밋에서 제외했다.
This commit is contained in:
Yun Chan
parent
93dd8f82d7
commit
16e791e044
390 changed files with 243188 additions and 499 deletions
621
scripts/smoke-multimodal-alliance-api.py
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621
scripts/smoke-multimodal-alliance-api.py
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"""Exercise the G7 multimodal-alliance lifecycle over live HTTP.
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The smoke uses a synthetic WAV only to derive deterministic metadata. It never
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uploads or prints transcript/audio content. Durable fixtures are intentionally
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left in the development database as auditable integration evidence.
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"""
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from __future__ import annotations
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import argparse
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import copy
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import hashlib
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import io
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import json
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import math
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import secrets
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import struct
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import time
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import urllib.error
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import urllib.request
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import wave
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from dataclasses import dataclass
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from datetime import UTC, datetime
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from http.cookiejar import CookieJar
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from pathlib import Path
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from typing import Any
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from uuid import uuid4
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COHORT_ID = "e2e-hanshin"
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OTHER_COHORT_ID = "e2e-other-cohort"
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INTERNAL_HEADER = "X-Vignette-Multimodal-Token"
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class SmokeError(RuntimeError):
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pass
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@dataclass(frozen=True)
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class ApiResponse:
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status: int
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body: Any
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class ApiClient:
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def __init__(self, base_url: str, timeout: float) -> None:
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self.base_url = base_url.rstrip("/")
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self.timeout = timeout
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self._opener = urllib.request.build_opener(
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urllib.request.HTTPCookieProcessor(CookieJar())
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)
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def request(
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self,
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method: str,
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path: str,
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payload: dict[str, Any] | None = None,
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*,
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expected: set[int] | None = None,
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headers: dict[str, str] | None = None,
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) -> ApiResponse:
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data = None
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request_headers = {"Accept": "application/json", **(headers or {})}
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if payload is not None:
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data = json.dumps(payload, ensure_ascii=False).encode("utf-8")
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request_headers["Content-Type"] = "application/json"
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request = urllib.request.Request(
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f"{self.base_url}{path}",
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data=data,
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headers=request_headers,
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method=method,
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)
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try:
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with self._opener.open(request, timeout=self.timeout) as response:
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raw = response.read().decode("utf-8")
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result = ApiResponse(response.status, json.loads(raw) if raw else {})
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except urllib.error.HTTPError as exc:
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raw = exc.read().decode("utf-8", errors="replace")
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try:
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body = json.loads(raw) if raw else {}
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except json.JSONDecodeError:
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body = {"detail": raw[:500]}
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result = ApiResponse(exc.code, body)
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except urllib.error.URLError as exc:
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raise SmokeError(
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f"{method} {path} transport failed: {type(exc.reason).__name__}"
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) from exc
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if result.status not in (expected or {200}):
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detail = result.body.get("detail") if isinstance(result.body, dict) else None
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raise SmokeError(
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f"{method} {path} returned HTTP {result.status}; detail={detail!r}"
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)
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return result
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def _sign_in(
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client: ApiClient,
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*,
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suffix: str,
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identity: str,
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role: str,
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cohort_ids: list[str],
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) -> str:
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login = client.request(
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"POST",
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"/auth/dev-login",
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{
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"email": f"dev.e2e.multimodal.{identity}.{suffix}@hs.ac.kr",
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"role": role,
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"display_name": f"Multimodal {identity.title()}",
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"cohort_ids": cohort_ids,
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},
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)
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client.request(
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"POST",
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"/users/me/onboarding",
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{
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"legal_name": f"Multimodal {identity.title()}",
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"affiliation": "한신대학교",
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"department": "상담심리학과",
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"grade_level": "통합검증",
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"phone": "010-0000-0000",
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"contact_address": "경기도 오산시 한신대학교",
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"nickname": f"Multimodal {identity.title()}",
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"self_introduction": "G7 멀티모달 동맹 API 검증 fixture입니다.",
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"avatar_url": "",
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"terms_accepted": True,
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"privacy_accepted": True,
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},
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)
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user_id = str(login.body.get("user_id") or "")
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if not user_id:
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raise SmokeError(f"dev-login omitted user_id for {identity}")
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return user_id
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def _choose_persona(client: ApiClient) -> str:
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response = client.request("GET", "/personas")
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usable = [
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item
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for item in response.body
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if isinstance(item, dict)
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and item.get("source") == "database"
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and not item.get("degraded")
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and item.get("code")
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]
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if not usable:
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raise SmokeError("persona catalog has no non-degraded database persona")
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preferred = next((item for item in usable if item.get("code") == "P1"), usable[0])
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return str(preferred["code"])
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def _synthetic_wav() -> bytes:
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sample_rate = 16_000
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frames = sample_rate * 1200 // 1000
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output = io.BytesIO()
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with wave.open(output, "wb") as writer:
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writer.setnchannels(1)
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writer.setsampwidth(2)
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writer.setframerate(sample_rate)
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payload = bytearray()
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for index in range(frames):
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value = int(3200 * math.sin(2 * math.pi * 220 * index / sample_rate))
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payload.extend(struct.pack("<h", value))
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writer.writeframes(bytes(payload))
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return output.getvalue()
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def _timeline(live_suffix: str) -> dict[str, Any]:
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return {
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"audio_duration_ms": 1200,
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"words": [
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{
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"word_index": 0,
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"start_ms": 40,
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"end_ms": 220,
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"speaker": "learner",
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"token_hash": "a" * 64,
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},
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{
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"word_index": 1,
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"start_ms": 500,
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"end_ms": 710,
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"speaker": "client",
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"token_hash": "b" * 64,
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},
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],
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"events": [
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{
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"event_id": f"oas-g7-event-{live_suffix}-silence",
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"event_type": "silence",
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"start_ms": 220,
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"end_ms": 500,
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"actor": "both",
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"observed_feature": "280ms turn transition silence",
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"uncertainty": 0.05,
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"source": "stt_word_timestamps",
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},
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{
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"event_id": f"oas-g7-event-{live_suffix}-overlap",
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"event_type": "overlap",
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"start_ms": 710,
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"end_ms": 770,
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"actor": "both",
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"observed_feature": "60ms simultaneous speech segment",
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"uncertainty": 0.1,
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"source": "observed_audio_runtime",
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},
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{
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"event_id": f"oas-g7-event-{live_suffix}-interruption",
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"event_type": "interruption",
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"start_ms": 770,
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"end_ms": 840,
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"actor": "learner",
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"observed_feature": "learner segment began before client segment ended",
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"uncertainty": 0.12,
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"source": "observed_audio_runtime",
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},
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{
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"event_id": f"oas-g7-event-{live_suffix}-prosody",
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"event_type": "prosody",
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"start_ms": 840,
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"end_ms": 1080,
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"actor": "learner",
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"observed_feature": "median intensity decreased by 3dB",
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"uncertainty": 0.2,
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"source": "observed_audio_runtime",
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},
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],
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}
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def _stable_retry(
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client: ApiClient,
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path: str,
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body: dict[str, Any],
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*,
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id_field: str,
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headers: dict[str, str] | None = None,
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) -> dict[str, Any]:
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created = client.request("POST", path, body, expected={201}, headers=headers)
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retried = client.request("POST", path, body, expected={201}, headers=headers)
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if created.body.get(id_field) != retried.body.get(id_field):
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raise SmokeError(f"same submission changed {id_field} for {path}")
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if retried.body.get("idempotent_replay") is not True:
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raise SmokeError(f"same submission retry was not stable for {path}")
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return created.body
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def _assert_safe_metadata(value: Any, path: str = "response") -> None:
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if isinstance(value, dict):
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forbidden = {
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"raw_transcript",
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"transcript",
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"utterance_text",
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"diagnosis",
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"emotion_label",
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"total_score",
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} & set(value)
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if forbidden:
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raise SmokeError(f"{path} exposed forbidden keys: {sorted(forbidden)}")
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if value.get("clinical_claim_allowed") is True:
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raise SmokeError(f"{path} enabled a clinical claim")
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for key, child in value.items():
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_assert_safe_metadata(child, f"{path}.{key}")
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elif isinstance(value, list):
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for index, child in enumerate(value):
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_assert_safe_metadata(child, f"{path}[{index}]")
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def _prepare_case(case: dict[str, Any], suffix: str) -> dict[str, Any]:
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result = copy.deepcopy(case)
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for key in ("text_measurement", "voice_measurement"):
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measurement = result[key]
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measurement["measurement_id"] = f"{measurement['measurement_id']}-{suffix}"
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if measurement["status"] == "ready":
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measurement["model_run_id"] = str(uuid4())
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result["calibration"]["calibration_id"] = (
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f"{result['calibration']['calibration_id']}-{suffix}"
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)
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return result
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def run(args: argparse.Namespace) -> dict[str, Any]:
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if len(args.internal_token) < 32:
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raise SmokeError("--internal-token must contain at least 32 characters")
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root = ApiClient(args.api_base_url, args.request_timeout)
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health = root.request("GET", "/health")
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if not health.body.get("db") or not health.body.get("engine"):
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raise SmokeError("API health is not DB+engine ready")
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internal = ApiClient(args.api_base_url, args.request_timeout)
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internal.request(
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"POST",
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"/internal/sessions/00000000-0000-4000-8000-000000000000/multimodal-alliance/timelines",
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{},
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expected={401},
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)
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internal.request(
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"POST",
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"/internal/sessions/00000000-0000-4000-8000-000000000000/multimodal-alliance/timelines",
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{},
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expected={403},
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headers={INTERNAL_HEADER: "wrong-token"},
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)
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token_header = {INTERNAL_HEADER: args.internal_token}
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login_suffix = f"{int(time.time())}.{secrets.token_hex(3)}"
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live_suffix = secrets.token_hex(5)
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learner = ApiClient(args.api_base_url, args.request_timeout)
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teacher = ApiClient(args.api_base_url, args.request_timeout)
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outsider = ApiClient(args.api_base_url, args.request_timeout)
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learner_id = _sign_in(
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learner,
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suffix=login_suffix,
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identity="learner",
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role="learner",
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cohort_ids=[COHORT_ID],
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)
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_sign_in(
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teacher,
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suffix=login_suffix,
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identity="teacher",
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role="teacher",
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cohort_ids=[COHORT_ID],
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)
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_sign_in(
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outsider,
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suffix=login_suffix,
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identity="outsider",
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role="teacher",
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cohort_ids=[OTHER_COHORT_ID],
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)
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started = learner.request(
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"POST",
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"/sessions",
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{
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"persona_code": _choose_persona(learner),
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"theory_mode": "humanistic",
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"goal_stages": ["라포", "탐색"],
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},
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expected={201},
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)
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session_id = str(started.body.get("session_id") or "")
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if not session_id or started.body.get("degraded"):
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raise SmokeError("session start did not produce a durable non-degraded session")
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consent_path = f"/sessions/{session_id}/multimodal-alliance/consent"
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consent_body = {
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"submission_id": str(uuid4()),
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"consent_status": "granted",
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"retain_audio": True,
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"retain_derived_features": True,
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"transcript_retained": True,
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"retention_days": 30,
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"policy_version": "g7-live-v1",
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"reason_code": None,
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}
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consent = _stable_retry(
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learner,
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consent_path,
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consent_body,
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id_field="consent_snapshot_id",
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)
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changed_consent = copy.deepcopy(consent_body)
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changed_consent["retention_days"] = 31
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learner.request("POST", consent_path, changed_consent, expected={409})
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synthetic_audio = _synthetic_wav()
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timeline_body = {
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"submission_id": str(uuid4()),
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"timeline": _timeline(live_suffix),
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"audio_asset": {
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"audio_ref": f"g7-live://synthetic/{live_suffix}.wav",
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"audio_sha256": hashlib.sha256(synthetic_audio).hexdigest(),
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"media_type": "audio/wav",
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"byte_size": len(synthetic_audio),
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},
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}
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timeline_path = f"/internal/sessions/{session_id}/multimodal-alliance/timelines"
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timeline = _stable_retry(
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internal,
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timeline_path,
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timeline_body,
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id_field="timeline_id",
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headers=token_header,
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)
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changed_timeline = copy.deepcopy(timeline_body)
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changed_timeline["timeline"]["audio_duration_ms"] = 1300
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internal.request(
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"POST", timeline_path, changed_timeline, expected={409}, headers=token_header
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)
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pack = json.loads(Path(args.benchmark_path).read_text(encoding="utf-8"))
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measurement_path = (
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f"/internal/sessions/{session_id}/multimodal-alliance/measurements"
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)
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fusion_results: list[dict[str, Any]] = []
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first_body: dict[str, Any] | None = None
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provenance = {
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"instrument_id": "alliance-axis-observer",
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"instrument_version": "g7-live-v1",
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"model_name": "synthetic-observer",
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"prompt_version": "g7-live-v1",
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}
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for index, source_case in enumerate(pack["cases"]):
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case = _prepare_case(source_case, live_suffix)
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body = {
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"submission_id": str(uuid4()),
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"text_measurement": case["text_measurement"],
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"text_provenance": provenance,
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"voice_measurement": case["voice_measurement"],
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"voice_provenance": provenance,
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"calibration": case["calibration"],
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}
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if index == 0:
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result = _stable_retry(
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internal,
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measurement_path,
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body,
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id_field="fusion_record_id",
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headers=token_header,
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)
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first_body = body
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else:
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result = internal.request(
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"POST", measurement_path, body, expected={201}, headers=token_header
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).body
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applied = bool(result["result"]["fusion_applied"])
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if applied is not bool(case["expected_fusion_applied"]):
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raise SmokeError(f"fusion gate mismatch for {case['case_id']}")
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fusion_results.append(result)
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if first_body is None:
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raise SmokeError("benchmark pack did not yield a measurement case")
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changed_measurement = copy.deepcopy(first_body)
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changed_measurement["text_measurement"]["value"] = 0.63
|
||||
internal.request(
|
||||
"POST",
|
||||
measurement_path,
|
||||
changed_measurement,
|
||||
expected={409},
|
||||
headers=token_header,
|
||||
)
|
||||
|
||||
metadata_path = f"/sessions/{session_id}/multimodal-alliance"
|
||||
learner_view = learner.request("GET", metadata_path).body
|
||||
teacher_view = teacher.request("GET", metadata_path).body
|
||||
outsider.request("GET", metadata_path, expected={404})
|
||||
teacher.request(
|
||||
"GET", f"{metadata_path}/raw-audio", expected={403}
|
||||
)
|
||||
raw_before = learner.request("GET", f"{metadata_path}/raw-audio").body
|
||||
_assert_safe_metadata(learner_view)
|
||||
_assert_safe_metadata(teacher_view)
|
||||
if len(learner_view.get("word_timestamps") or []) != 2:
|
||||
raise SmokeError("single audio clock did not retain two word timestamps")
|
||||
if len(learner_view.get("voice_events") or []) != 4:
|
||||
raise SmokeError("single audio clock did not retain four interaction events")
|
||||
if len(learner_view.get("measurements") or []) != 6:
|
||||
raise SmokeError("text and voice measurements were not independently retained")
|
||||
if len(learner_view.get("fusion_decisions") or []) != 3:
|
||||
raise SmokeError("all three benchmark fusion decisions were not retained")
|
||||
if len(raw_before.get("items") or []) != 1:
|
||||
raise SmokeError("learner raw-audio access did not expose one retained asset")
|
||||
|
||||
deletion_body = {
|
||||
"submission_id": str(uuid4()),
|
||||
"scopes": ["audio", "derived_features"],
|
||||
}
|
||||
deletion_path = f"{metadata_path}/deletion-requests"
|
||||
explicit_deletion = _stable_retry(
|
||||
learner,
|
||||
deletion_path,
|
||||
deletion_body,
|
||||
id_field="deletion_request_id",
|
||||
)
|
||||
|
||||
withdrawal_body = {
|
||||
"submission_id": str(uuid4()),
|
||||
"policy_version": "g7-live-v1",
|
||||
"reason_code": "learner_withdrawal",
|
||||
"transcript_retained": True,
|
||||
}
|
||||
withdrawal = _stable_retry(
|
||||
learner,
|
||||
f"/sessions/{session_id}/multimodal-alliance/withdraw",
|
||||
withdrawal_body,
|
||||
id_field="consent_snapshot_id",
|
||||
)
|
||||
internal.request(
|
||||
"POST",
|
||||
timeline_path,
|
||||
{
|
||||
**timeline_body,
|
||||
"submission_id": str(uuid4()),
|
||||
},
|
||||
expected={409},
|
||||
headers=token_header,
|
||||
)
|
||||
|
||||
deleted_at = datetime.now(UTC).isoformat().replace("+00:00", "Z")
|
||||
tombstones = [
|
||||
{
|
||||
"scope": "audio",
|
||||
"target_ref_hash": hashlib.sha256(
|
||||
timeline_body["audio_asset"]["audio_ref"].encode("utf-8")
|
||||
).hexdigest(),
|
||||
"deletion_proof": "synthetic object-store delete acknowledged",
|
||||
"deleted_at": deleted_at,
|
||||
},
|
||||
{
|
||||
"scope": "derived_features",
|
||||
"target_ref_hash": hashlib.sha256(
|
||||
str(timeline["timeline_id"]).encode("utf-8")
|
||||
).hexdigest(),
|
||||
"deletion_proof": "derived feature access tombstoned",
|
||||
"deleted_at": deleted_at,
|
||||
},
|
||||
]
|
||||
completion_ids: list[str] = []
|
||||
for deletion_request_id in (
|
||||
explicit_deletion["deletion_request_id"],
|
||||
withdrawal["deletion_request_id"],
|
||||
):
|
||||
completion = _stable_retry(
|
||||
internal,
|
||||
f"/internal/multimodal-alliance/deletion-requests/{deletion_request_id}/complete",
|
||||
{
|
||||
"submission_id": str(uuid4()),
|
||||
"actor_uid": None,
|
||||
"actor_kind": "retention_worker",
|
||||
"tombstones": tombstones,
|
||||
},
|
||||
id_field="deletion_request_id",
|
||||
headers=token_header,
|
||||
)
|
||||
completion_ids.extend(str(item) for item in completion["tombstone_ids"])
|
||||
|
||||
after = learner.request("GET", metadata_path).body
|
||||
raw_after = learner.request("GET", f"{metadata_path}/raw-audio").body
|
||||
if raw_after.get("items"):
|
||||
raise SmokeError("audio tombstone did not remove raw-audio access")
|
||||
if after.get("word_timestamps") or after.get("voice_events"):
|
||||
raise SmokeError("derived-feature tombstone did not hide voice timeline detail")
|
||||
if any(item.get("modality") != "text" for item in after.get("measurements") or []):
|
||||
raise SmokeError("deleted derived features leaked voice measurements")
|
||||
if any(
|
||||
"voice" in (item.get("modalities_used") or [])
|
||||
for item in after.get("fusion_decisions") or []
|
||||
):
|
||||
raise SmokeError("deleted derived features leaked voice fusion decisions")
|
||||
|
||||
return {
|
||||
"schema": "vignette.multimodal-alliance-live-api-evidence.v1",
|
||||
"generated_at": datetime.now(UTC).isoformat(),
|
||||
"api_base_url": args.api_base_url.rstrip("/"),
|
||||
"health": {"db": True, "engine": True},
|
||||
"learner_id": learner_id,
|
||||
"session_id": session_id,
|
||||
"consent_snapshot_id": str(consent["consent_snapshot_id"]),
|
||||
"timeline_id": str(timeline["timeline_id"]),
|
||||
"audio_asset_id": str(timeline["audio_asset_id"]),
|
||||
"fusion_record_ids": [str(item["fusion_record_id"]) for item in fusion_results],
|
||||
"fusion_applied": [bool(item["result"]["fusion_applied"]) for item in fusion_results],
|
||||
"withdrawal_snapshot_id": str(withdrawal["consent_snapshot_id"]),
|
||||
"deletion_request_ids": [
|
||||
str(explicit_deletion["deletion_request_id"]),
|
||||
str(withdrawal["deletion_request_id"]),
|
||||
],
|
||||
"tombstone_ids": completion_ids,
|
||||
"assertions": {
|
||||
"internal_missing_token_401": True,
|
||||
"internal_wrong_token_403": True,
|
||||
"stable_retries": True,
|
||||
"changed_payload_conflicts_409": True,
|
||||
"single_clock_word_count": 2,
|
||||
"interaction_event_count": 4,
|
||||
"independent_measurement_count": 6,
|
||||
"fusion_benchmark_cases": 3,
|
||||
"fusion_gain_gate": [True, False, False],
|
||||
"teacher_metadata_without_raw_audio": True,
|
||||
"cross_cohort_hidden_404": True,
|
||||
"clinical_claim_allowed": False,
|
||||
"withdrawal_blocks_voice_processing": True,
|
||||
"raw_audio_deleted": True,
|
||||
"derived_voice_features_deleted": True,
|
||||
"transcript_retained": True,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def parse_args() -> argparse.Namespace:
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--api-base-url", default="http://127.0.0.1:8014")
|
||||
parser.add_argument("--internal-token", required=True)
|
||||
parser.add_argument(
|
||||
"--benchmark-path",
|
||||
default="apps/api/app/data/multimodal_alliance_benchmark_g7.v1.json",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--output",
|
||||
default="docs/ops/evidence/multimodal-alliance-live-api-2026-08-06.json",
|
||||
)
|
||||
parser.add_argument("--request-timeout", type=float, default=30.0)
|
||||
return parser.parse_args()
|
||||
|
||||
|
||||
def main() -> None:
|
||||
args = parse_args()
|
||||
evidence = run(args)
|
||||
output = Path(args.output)
|
||||
output.parent.mkdir(parents=True, exist_ok=True)
|
||||
output.write_text(
|
||||
json.dumps(evidence, ensure_ascii=False, indent=2) + "\n", encoding="utf-8"
|
||||
)
|
||||
print(json.dumps(evidence, ensure_ascii=False, indent=2))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Add table
Add a link
Reference in a new issue