lukehemmin
8f6f8969fd
- api/: FastAPI app, X-API-Key 인증(미설정 시 임시키), 엔진 load-once 풀 (+transcribe lock), POST /v1/transcribe(multipart, 동기), /health, /v1/system, /v1/models. 업로드 임시파일 finally 삭제(프라이버시). - postprocess/: llm.correct(scripts/llm_correct.py 승격; opt-in·allowlist·감사로그·재시도) + rules.normalize(EmbeddingGemma 등 정규화). - results/formats.py: txt/srt/vtt. connectivity/tunnel.py: cloudflared quick tunnel(Colab). - cli serve: uvicorn 단일워커 + --tunnel cloudflare; config llm_* 필드; pyproject api/queue extra 분리(+python-multipart, dev httpx). 검증: 22 단위테스트(API TestClient·formats·postprocess) + 실서버 e2e (/health·auth 401·실제 전사(JFK)·SRT·임시파일 삭제). KO 품질은 turbo/large-v3 필요(tiny는 한국어 degenerate). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
41 lines
1.1 KiB
TOML
41 lines
1.1 KiB
TOML
[project]
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name = "luke-scribe"
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version = "0.1.0"
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description = "내부용 로컬 STT 전사 API (faster-whisper, hardware-adaptive)"
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requires-python = ">=3.11"
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dependencies = [
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"pydantic>=2.7",
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"pydantic-settings>=2.3",
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"typer>=0.12",
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"rich>=13.7",
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"psutil>=5.9",
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"nvidia-ml-py>=12.535",
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"huggingface-hub>=0.24",
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]
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[project.optional-dependencies]
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# 엔진 — transcribe/bench 증분에서 설치 (uv sync --extra engine)
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engine = ["faster-whisper>=1.0.3", "av>=11"]
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# GPU CUDA 런타임 (faster-whisper GPU 추론 시)
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gpu = ["nvidia-cublas-cu12", "nvidia-cudnn-cu12"]
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# 테스트 API (동기) — serve
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api = ["fastapi>=0.110", "uvicorn[standard]>=0.29", "python-multipart>=0.0.9"]
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# P2 비동기 큐 (보류)
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queue = ["redis>=5.0", "rq>=1.16"]
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# P5 옵션
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diarize = ["pyannote.audio>=3.1"]
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llm = ["openai>=1.30"]
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[project.scripts]
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luke-scribe = "luke_scribe.cli:main"
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["src/luke_scribe"]
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[dependency-groups]
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dev = ["pytest>=8.2", "ruff>=0.5", "httpx>=0.27"]
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