Files
hyungi_document_server/app/core/config.py
T
Hyungi Ahn 1e2c004dd4 feat(media): §3 audio STT + video 재생 인프라
plan: ~/.claude/plans/luminous-sprouting-hamster.md §3

스키마:
- migrations/147_audio_segments_table.sql: audio_segments (STT 타임스탬프
  세그먼트)
- migrations/148_audio_segments_idx.sql: (document_id, start_s) idx
- migrations/149_document_media_cols.sql: documents.thumbnail_path +
  needs_conversion
- migrations/150_queue_stage_stt.sql: process_stage += 'stt'
- migrations/151_queue_stage_thumbnail.sql: process_stage += 'thumbnail'
- app/models/audio_segment.py, document.py (thumbnail_path/needs_conversion)

서비스:
- services/stt/{Dockerfile, requirements.txt, server.py} — faster-whisper
  large-v3 GPU 컨테이너. /transcribe (filePath/langs/beamSize) +
  /health + /ready (cuda device_count + model_loaded). NFC/NFD 경로
  resolver (OCR 교훈).
- docker-compose.yml: stt-service 추가 (GPU 1 예약, :3300, NAS ro mount,
  stt_models volume, start_period 300s), fastapi env 에 STT_ENDPOINT.

파이프라인 (의존 §1 category):
- app/workers/stt_worker.py 신규: stage='stt' pickup → STT_ENDPOINT 호출 →
  extracted_text + audio_segments 저장. Timeout 30분.
- app/workers/thumbnail_worker.py 신규: ffmpeg 50% 지점 1장 →
  PKM/Videos/.thumbs/{id}.jpg + thumbnail_path 세팅.
  needs_conversion=true 는 skip.
- app/workers/file_watcher.py 확장: PKM/{Inbox, Recordings, Videos}
  스캔. 확장자→category, audio→stage=stt, video .mp4/.webm→
  stage=thumbnail, video .mov/.mkv/.avi→needs_conversion=true + stage
  없음. settings.roon_library_path prefix skip.
- app/workers/queue_consumer.py 확장: stt + thumbnail workers 등록,
  BATCH_SIZE(stt=1, thumbnail=3), next_stages 에 stt→[classify] 추가
  (audio 는 extract 건너뜀).
- app/Dockerfile: ffmpeg 추가 (썸네일 subprocess 용).

API (의존 §1):
- /api/audio/{id}/segments — AudioSegment ORDER BY start_s
- /api/video/{id}/thumbnail — thumbnail_path FileResponse (쿼리 토큰)
- /api/documents/{id}/file: media_types 에 audio/video mime 포함 (§2
  커밋에 이미 포함). Starlette FileResponse 가 Range 자동.
- upload_document: .mov/.mkv/.avi 웹 업로드 거부 (error_code
  unsupported_codec). NAS 드롭은 file_watcher 가 quarantine 수용.

프론트:
- AudioPlayer.svelte: HTML5 audio + 전사 세그먼트 sticky 패널 + 줄
  클릭 seek. activeIdx 하이라이트.
- VideoPlayer.svelte: HTML5 video direct play + needs_conversion 안내
  카드. poster 는 thumbnail endpoint.
- /audio (목록 grid) + /audio/[id] (플레이어)
- /video (썸네일 grid + 변환 필요 배지) + /video/[id] (플레이어)
- Sidebar.svelte: Mic/Film 아이콘 + audio/video 네비 활성, count
  배지 (§2 /stats/category-counts 재사용).

설정:
- app/core/config.py: stt_endpoint + roon_library_path.

DoD 배포 후 smoke: /ready cuda:true, 회의 mp3 transcribe, audio
extract 없이 classify 진행(queue 회귀), /audio 재생, .mp4 재생,
.mov 웹 400, .mov NAS quarantine, Sidebar 네비 + count.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 06:47:36 +09:00

157 lines
5.0 KiB
Python

"""설정 로딩 — config.yaml + credentials.env"""
import os
from pathlib import Path
import yaml
from pydantic import BaseModel
class UploadConfig(BaseModel):
max_bytes: int = 100_000_000
content_length_slack_ratio: float = 1.05
stream_chunk_bytes: int = 1_048_576
class AIModelConfig(BaseModel):
endpoint: str
model: str
max_tokens: int = 4096
timeout: int = 60
daily_budget_usd: float | None = None
require_explicit_trigger: bool = False
class AIConfig(BaseModel):
gateway_endpoint: str
primary: AIModelConfig
fallback: AIModelConfig
premium: AIModelConfig
embedding: AIModelConfig
vision: AIModelConfig
rerank: AIModelConfig
# Phase 3.5a: exaone classifier (optional — 없으면 score-only gate)
classifier: AIModelConfig | None = None
# Phase 3.5b: exaone verifier (optional — 없으면 grounding-only)
verifier: AIModelConfig | None = None
class Settings(BaseModel):
# DB
database_url: str = ""
# AI
ai: AIConfig | None = None
# NAS
nas_mount_path: str = "/documents"
nas_pkm_root: str = "/documents/PKM"
# 인증
jwt_secret: str = ""
totp_secret: str = ""
# Phase 3.5: eval runner shared secret — X-Source=eval / X-Eval-Case-Id 헤더 신뢰 검증.
# 비어있으면 모든 eval 헤더 거부 (부재 = 비활성).
eval_runner_token: str = ""
# kordoc
kordoc_endpoint: str = "http://kordoc-service:3100"
# OCR (Surya)
ocr_endpoint: str = "http://ocr-service:3200"
# STT (faster-whisper, §3)
stt_endpoint: str = "http://stt-service:3300"
# §3 file_watcher: Roon 음원 경로 (prefix match 로 skip).
# 빈 문자열이면 skip 없음. 예: "/documents/PKM/../Music/roon-library" 또는
# NFS 경유 별도 마운트된 Roon 라이브러리.
roon_library_path: str = ""
# 분류 체계
taxonomy: dict = {}
document_types: list[str] = []
# 업로드 한도 (authoritative policy)
upload: UploadConfig = UploadConfig()
def load_settings() -> Settings:
"""config.yaml + 환경변수에서 설정 로딩"""
# 환경변수 (docker-compose에서 주입)
database_url = os.getenv("DATABASE_URL", "")
jwt_secret = os.getenv("JWT_SECRET", "")
totp_secret = os.getenv("TOTP_SECRET", "")
eval_runner_token = os.getenv("EVAL_RUNNER_TOKEN", "")
kordoc_endpoint = os.getenv("KORDOC_ENDPOINT", "http://kordoc-service:3100")
ocr_endpoint = os.getenv("OCR_ENDPOINT", "http://ocr-service:3200")
stt_endpoint = os.getenv("STT_ENDPOINT", "http://stt-service:3300")
roon_library_path = os.getenv("ROON_LIBRARY_PATH", "")
# config.yaml — Docker 컨테이너 내부(/app/config.yaml) 또는 프로젝트 루트
config_path = Path("/app/config.yaml")
if not config_path.exists():
config_path = Path(__file__).parent.parent.parent / "config.yaml"
ai_config = None
nas_mount = "/documents"
nas_pkm = "/documents/PKM"
if config_path.exists():
with open(config_path) as f:
raw = yaml.safe_load(f)
if "ai" in raw:
ai_raw = raw["ai"]
ai_config = AIConfig(
gateway_endpoint=ai_raw.get("gateway", {}).get("endpoint", ""),
primary=AIModelConfig(**ai_raw["models"]["primary"]),
fallback=AIModelConfig(**ai_raw["models"]["fallback"]),
premium=AIModelConfig(**ai_raw["models"]["premium"]),
embedding=AIModelConfig(**ai_raw["models"]["embedding"]),
vision=AIModelConfig(**ai_raw["models"]["vision"]),
rerank=AIModelConfig(**ai_raw["models"]["rerank"]),
classifier=(
AIModelConfig(**ai_raw["models"]["classifier"])
if "classifier" in ai_raw.get("models", {})
else None
),
verifier=(
AIModelConfig(**ai_raw["models"]["verifier"])
if "verifier" in ai_raw.get("models", {})
else None
),
)
if "nas" in raw:
nas_mount = raw["nas"].get("mount_path", nas_mount)
nas_pkm = raw["nas"].get("pkm_root", nas_pkm)
taxonomy = raw.get("taxonomy", {}) if config_path.exists() and raw else {}
document_types = raw.get("document_types", []) if config_path.exists() and raw else []
upload_cfg = (
UploadConfig(**raw["upload"])
if config_path.exists() and raw and "upload" in raw
else UploadConfig()
)
return Settings(
database_url=database_url,
ai=ai_config,
nas_mount_path=nas_mount,
nas_pkm_root=nas_pkm,
jwt_secret=jwt_secret,
totp_secret=totp_secret,
eval_runner_token=eval_runner_token,
kordoc_endpoint=kordoc_endpoint,
ocr_endpoint=ocr_endpoint,
stt_endpoint=stt_endpoint,
roon_library_path=roon_library_path,
taxonomy=taxonomy,
document_types=document_types,
upload=upload_cfg,
)
settings = load_settings()