feat: 복수 파일 배치 변환 (STT/OCR)
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README.md
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README.md
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# VoiceScript — 음성 변환(STT) + 이미지 인식(OCR) 통합 툴
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# VoiceScript — STT + OCR 통합 툴
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> **Debian OS + Docker Compose** 기반 자체 호스팅 서비스
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faster-whisper(STT) + PaddleOCR 3.x / Ollama Vision / OpenRouter Vision(OCR)
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> faster-whisper(STT) + PaddleOCR 3.x / Ollama Vision(OCR) 듀얼 백엔드
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---
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---
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## 목차
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## 빌드 전 필수 설정 (docker-compose.yml)
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1. [기능 개요](#기능-개요)
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| 항목 | 설명 |
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2. [프로젝트 구조](#프로젝트-구조)
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|------|------|
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3. [시스템 요구사항](#시스템-요구사항)
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| `AUTH_USERNAME` / `AUTH_PASSWORD` | 로그인 계정 **변경 필수** |
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4. [설치 전 필수 확인사항 ⚠️](#설치-전-필수-확인사항)
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| `JWT_SECRET` | `openssl rand -hex 32` 로 생성 |
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5. [환경 변수 설정](#환경-변수-설정)
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| `OLLAMA_URL` | 호스트 실제 LAN IP (host.docker.internal 불안정) |
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6. [빌드 및 실행](#빌드-및-실행)
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| `CPU_THREADS` | 0 = 자동, 5825u 기준 8~12 권장 |
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7. [Nginx 연동 SSL](#nginx-연동-ssl)
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| `OLLAMA_TIMEOUT` | 큰 모델(11b+) 은 300+ 권장 |
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8. [Ollama 모델 준비](#ollama-모델-준비)
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9. [운영 관리](#운영-관리)
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10. [트러블슈팅 알려진 이슈](#트러블슈팅-알려진-이슈)
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11. [API 엔드포인트](#api-엔드포인트)
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---
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## 빌드 & 실행
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## 기능 개요
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### 🎙 STT — 음성 텍스트 변환
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- **엔진**: [faster-whisper](https://github.com/SYSTRAN/faster-whisper) (OpenAI Whisper 최적화 포크)
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- 지원 형식: `mp3` `wav` `m4a` `ogg` `flac` `aac` `mp4` `webm` `mkv` 등
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- VAD(무음 구간 자동 제거) 적용
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- 타임스탬프 세그먼트 분리 출력
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- TXT 파일 다운로드
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### 🔍 OCR — 이미지 텍스트 인식
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- 지원 형식: `jpg` `png` `bmp` `tiff` `webp` `gif`
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- **PaddleOCR 모드**: 로컬 실행, 표 구조 분석(PP-Structure), Excel 다운로드
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- **Ollama Vision 모드**: 기존 Ollama 서버 활용, 자연어 지시, 커스텀 프롬프트
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### 🔐 인증
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- JWT 기반 로그인 (만료 시간 설정 가능)
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- 모든 API 토큰 인증 필수
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---
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## 프로젝트 구조
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```
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whisper-stt/
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│
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├── docker-compose.yml # 전체 서비스 정의
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│
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├── app/
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│ ├── Dockerfile # Python 3.11-slim + ffmpeg + PaddlePaddle 3.0.0
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│ ├── requirements.txt # Python 패키지 목록
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│ │
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│ ├── main.py # FastAPI 앱 (인증 + STT + OCR 엔드포인트)
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│ ├── auth.py # JWT 인증 모듈
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│ ├── tasks.py # Celery STT 태스크 (faster-whisper)
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│ ├── ocr_tasks.py # Celery OCR 태스크 (PaddleOCR / Ollama)
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│ │
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│ └── static/
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│ └── index.html # 웹 프론트엔드 (로그인 + STT + OCR 탭)
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│
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└── nginx/ # 참고용 (호스트 Nginx 사용 시 불필요)
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├── Dockerfile
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└── nginx.conf
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```
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### 컨테이너 구성
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```
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┌─────────────────────────────────────────┐
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│ 호스트 Nginx (SSL/certbot) │
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│ → 리버스 프록시 → 127.0.0.1:8800 │
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└─────────────────────────────────────────┘
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│
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▼
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┌──────────────────┐ ┌──────────────────────┐
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│ whisper_app │ │ whisper_worker │
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│ FastAPI:8000 │ │ Celery (solo pool) │
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│ (포트 8800) │ │ STT + OCR 처리 │
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└────────┬─────────┘ └──────────┬───────────┘
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│ │
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└────────────┬────────────┘
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▼
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┌──────────────────┐
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│ whisper_redis │
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│ Redis:6379 │
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│ (작업 큐/결과) │
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└──────────────────┘
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```
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---
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## 시스템 요구사항
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| 항목 | 최소 | 권장 |
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|------|------|------|
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| CPU | 4코어 | AMD 5825u 이상 |
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| RAM | 8GB | 16GB (medium 모델 기준) |
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| 디스크 | 20GB | 50GB 이상 |
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| OS | Debian 11+ | Debian 12 (Bookworm) |
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| Docker | 24.0+ | 최신 |
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| Docker Compose | v2.0+ | 최신 (`version:` 필드 불필요) |
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### 의존 서비스
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- **Ollama**: 호스트에서 `11434` 포트로 실행 중이어야 함 (OCR Vision 모드 사용 시)
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---
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## 설치 전 필수 확인사항
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> ⚠️ 이 섹션을 건너뛰면 빌드 후 오류가 발생합니다.
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### 1. 호스트 IP 확인 — OLLAMA_URL 설정
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`host.docker.internal`은 Linux에서 동작하지 않습니다.
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반드시 실제 LAN IP를 확인하여 설정하세요.
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```bash
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```bash
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ip addr show | grep "inet " | grep -v 127.0.0.1
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```
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`docker-compose.yml` 두 곳(app, worker) 모두 변경:
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```yaml
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- OLLAMA_URL=http://실제호스트IP:11434
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```
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### 2. 인증 정보 변경
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```yaml
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# app, worker 두 서비스 모두 동일하게 변경
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- AUTH_USERNAME=원하는아이디
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- AUTH_PASSWORD=강력한비밀번호
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- JWT_SECRET=랜덤문자열 # openssl rand -hex 32
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```
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```bash
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# JWT 시크릿 생성
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openssl rand -hex 32
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```
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### 3. 포트 충돌 확인
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```bash
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ss -tlnp | grep 8800
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```
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충돌 시 `docker-compose.yml`에서 변경:
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```yaml
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ports:
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- "원하는포트:8000"
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```
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### 4. 디스크 용량 확인
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| 항목 | 크기 | 시점 |
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|------|------|------|
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| Whisper medium 모델 | ~1.5GB | 첫 STT 실행 시 자동 다운로드 |
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| PaddleOCR korean 모델 | ~700MB | 첫 OCR 실행 시 자동 다운로드 |
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| PaddlePaddle 3.0.0 | ~300MB | 빌드 시 |
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| Docker 이미지 | ~3GB | 빌드 시 |
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```bash
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df -h /
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# 여유 공간 10GB 이상 권장
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```
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### 5. Ollama 서버 실행 확인
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```bash
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curl http://localhost:11434/api/tags
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# 응답 없으면 Ollama 미실행 상태
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```
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### 6. Docker Compose v2 확인
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```bash
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docker compose version
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# v2.x 이상이어야 함 (docker-compose가 아닌 docker compose)
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```
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---
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## 환경 변수 설정
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`docker-compose.yml`의 `app`과 `worker` 두 서비스에 **동일하게** 설정.
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### 인증
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| 변수 | 기본값 | 설명 |
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|------|--------|------|
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| `AUTH_USERNAME` | `admin` | 로그인 아이디 |
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| `AUTH_PASSWORD` | `changeme1234` | 로그인 비밀번호 **변경 필수** |
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| `JWT_SECRET` | *(변경 필수)* | JWT 서명 키 |
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| `JWT_EXPIRE_HOURS` | `12` | 토큰 유효 시간 (시간 단위) |
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### Whisper STT
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| 변수 | 기본값 | 설명 |
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|------|--------|------|
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| `WHISPER_MODEL` | `medium` | `tiny` `base` `small` `medium` `large-v3` |
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| `WHISPER_DEVICE` | `cpu` | GPU 없는 경우 `cpu` |
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| `WHISPER_COMPUTE_TYPE` | `int8` | CPU 최적화: `int8` 권장 |
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| `WHISPER_LANGUAGE` | `ko` | 언어 고정. 비우면 자동 감지 |
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| `WHISPER_BEAM_SIZE` | `5` | 정확도↑ vs 속도↓ |
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| `WHISPER_INITIAL_PROMPT` | 비어있음 | 도메인 힌트 예: `"고객 상담 녹취록입니다."` |
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**모델별 성능 (5825u CPU 기준)**
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| 모델 | 크기 | 1분 변환 시간 | 한국어 정확도 |
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|------|------|-------------|--------------|
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| tiny | 75MB | ~5초 | 보통 |
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| base | 145MB | ~10초 | 보통 |
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| small | 484MB | ~30초 | 양호 |
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| **medium** | **1.5GB** | **~90초** | **우수 ← 권장** |
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| large-v3 | 3GB | ~5분+ | 최고 |
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### PaddleOCR
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| 변수 | 기본값 | 설명 |
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|------|--------|------|
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| `OCR_LANG` | `korean` | `korean` `en` `japan` `chinese_cht` `ch` |
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### Ollama OCR
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| 변수 | 기본값 | 설명 |
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|------|--------|------|
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| `OLLAMA_URL` | `http://192.168.0.126:11434` | **실제 호스트 IP로 변경 필수** |
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| `OLLAMA_TIMEOUT` | `180` | 초 단위. 11b 이상 모델은 `300` 이상 권장 |
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### 파일 관리
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| 변수 | 기본값 | 설명 |
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|------|--------|------|
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| `MAX_UPLOAD_MB` | `500` | 업로드 최대 파일 크기 (MB) |
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| `OUTPUT_KEEP_HOURS` | `48` | 결과 파일 보관 시간. `0`=무제한 |
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---
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## 빌드 및 실행
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```bash
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# 1. 저장소 클론
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git clone http://gitea.byunc.com/byun/whisper-stt.git
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cd whisper-stt
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cd whisper-stt
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# 2. 필수 설정 변경 (docker-compose.yml)
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# - AUTH_USERNAME, AUTH_PASSWORD, JWT_SECRET
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# - OLLAMA_URL (호스트 실제 IP)
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# 3. 빌드 및 시작
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docker compose up -d --build
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docker compose up -d --build
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docker compose logs -f worker # 모델 다운로드 완료 확인
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# 4. 빌드 후 모델 다운로드 완료까지 대기
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docker compose logs -f worker
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# "[Whisper] 로드 완료" + "celery@... ready." 확인
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```
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```
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접속:
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접속: `http://서버IP:8800`
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```
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http://서버IP:8800
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## 기능
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```
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### STT 탭
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### 이후 코드 변경 시 재배포
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- **faster-whisper**: 로컬 CPU 변환
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- **+ Ollama 교정**: Whisper 후 Ollama로 문장부호·맞춤법 교정
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```bash
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- **+ OpenRouter 교정**: 외부 AI(Claude/GPT 등)로 교정
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# 코드만 변경된 경우 (재빌드 필요)
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docker compose build --no-cache app worker
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### OCR 탭
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docker compose up -d
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- **PaddleOCR**: 로컬 실행 (PaddleOCR 3.x, PPStructure 미사용)
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- **Ollama Vision**: Vision 지원 모델만 가능 (granite3.2-vision 등)
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# 환경변수만 변경된 경우 (재빌드 불필요)
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- **OpenRouter Vision**: Claude-3, GPT-4o, Gemini 등 외부 Vision 모델
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docker compose up -d --force-recreate app worker
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### 설정 탭
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# Docker 이미지 정리 (빌드 반복 후 용량 정리)
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- 시스템 리소스 모니터 (RAM/CPU/Swap)
|
||||||
docker system prune -f
|
- CPU 스레드 슬라이더
|
||||||
```
|
- 변환 타임아웃 설정 (STT / Ollama)
|
||||||
|
- OpenRouter API 키 등록 + 모델 선택
|
||||||
---
|
|
||||||
|
### 이력 탭
|
||||||
## Nginx 연동 SSL
|
- STT/OCR 변환 이력 (입력 파일·설정·결과 저장)
|
||||||
|
- 텍스트 미리보기 + 결과 파일 다운로드
|
||||||
호스트 Nginx + certbot SSL 운용 중인 경우:
|
|
||||||
|
### 관리자 탭
|
||||||
```nginx
|
- 다중 사용자 관리 (추가/편집/삭제)
|
||||||
# /etc/nginx/sites-available/voicescript.conf
|
- 사용자별 STT/OCR 권한 설정
|
||||||
|
- 사용자별 허용 모델 제한
|
||||||
server {
|
|
||||||
listen 443 ssl;
|
## 트러블슈팅
|
||||||
server_name stt.yourdomain.com;
|
|
||||||
|
| 오류 | 해결 |
|
||||||
ssl_certificate /etc/letsencrypt/live/stt.yourdomain.com/fullchain.pem;
|
|------|------|
|
||||||
ssl_certificate_key /etc/letsencrypt/live/stt.yourdomain.com/privkey.pem;
|
| paddlepaddle 빌드 실패 | Dockerfile에 `-i pypi.tuna...` 없는지 확인 |
|
||||||
|
| SIGSEGV (worker 크래시) | `--pool=solo` 옵션 확인 |
|
||||||
# ⚠️ 음성 파일 업로드를 위해 반드시 설정 (기본 1MB → 초과 시 413 에러)
|
| Ollama 연결 실패 | OLLAMA_URL에 `host.docker.internal` 대신 실제 IP 사용 |
|
||||||
client_max_body_size 500M;
|
| OCR 빈 응답 | Vision 미지원 모델 선택 여부 확인 |
|
||||||
client_body_timeout 300s;
|
| Redis write 에러 | `redis-server --stop-writes-on-bgsave-error no` 확인 |
|
||||||
proxy_read_timeout 600s;
|
| PPStructure 오류 | PaddleOCR 3.x 에서 제거됨, 표 추출은 Ollama/OpenRouter 사용 |
|
||||||
proxy_send_timeout 600s;
|
|
||||||
|
|
||||||
location / {
|
|
||||||
proxy_pass http://127.0.0.1:8800;
|
|
||||||
proxy_set_header Host $host;
|
|
||||||
proxy_set_header X-Real-IP $remote_addr;
|
|
||||||
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
|
|
||||||
proxy_set_header X-Forwarded-Proto $scheme;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
server {
|
|
||||||
listen 80;
|
|
||||||
server_name stt.yourdomain.com;
|
|
||||||
return 301 https://$host$request_uri;
|
|
||||||
}
|
|
||||||
```
|
|
||||||
|
|
||||||
```bash
|
|
||||||
sudo certbot --nginx -d stt.yourdomain.com
|
|
||||||
sudo nginx -t && sudo systemctl reload nginx
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## Ollama 모델 준비
|
|
||||||
|
|
||||||
호스트에서 미리 pull:
|
|
||||||
|
|
||||||
```bash
|
|
||||||
# 문서/표 특화 — 약 2GB ← 기본값, 권장
|
|
||||||
ollama pull granite3.2-vision
|
|
||||||
|
|
||||||
# OCR 전용 경량 — 약 2GB
|
|
||||||
ollama pull deepseek-ocr:3b
|
|
||||||
|
|
||||||
# 범용 고정확도 — 약 8GB (RAM 16GB+ 필요)
|
|
||||||
ollama pull llama3.2-vision:11b
|
|
||||||
|
|
||||||
# 최고 정확도 — 약 9GB (RAM 16GB+ 필요)
|
|
||||||
ollama pull richardyoung/olmocr2:7b-q8
|
|
||||||
```
|
|
||||||
|
|
||||||
> **참고**: `granite3.2-vision`만 설치되어 있어도 즉시 사용 가능합니다.
|
|
||||||
> 큰 모델 사용 시 `OLLAMA_TIMEOUT=300` 이상으로 설정하세요.
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## 운영 관리
|
|
||||||
|
|
||||||
```bash
|
|
||||||
# 상태 확인
|
|
||||||
docker compose ps
|
|
||||||
|
|
||||||
# 로그 확인
|
|
||||||
docker compose logs app --tail=30
|
|
||||||
docker compose logs worker --tail=30
|
|
||||||
docker compose logs -f # 전체 실시간
|
|
||||||
|
|
||||||
# 재시작
|
|
||||||
docker compose restart
|
|
||||||
|
|
||||||
# 중지
|
|
||||||
docker compose down
|
|
||||||
|
|
||||||
# 설정 변경 후 재시작 (재빌드 없이)
|
|
||||||
docker compose up -d --force-recreate app worker
|
|
||||||
```
|
|
||||||
|
|
||||||
### Docker 이미지 정리
|
|
||||||
|
|
||||||
빌드를 반복하면 dangling 이미지가 누적됩니다.
|
|
||||||
|
|
||||||
```bash
|
|
||||||
docker system df # 사용량 확인
|
|
||||||
docker system prune -f # 불필요한 이미지/컨테이너 정리
|
|
||||||
docker compose down -v # 볼륨 포함 완전 초기화 (모델 재다운로드 필요)
|
|
||||||
```
|
|
||||||
|
|
||||||
### 볼륨 정보
|
|
||||||
|
|
||||||
| 볼륨 | 내용 | 삭제 시 영향 |
|
|
||||||
|------|------|------------|
|
|
||||||
| `whisper_models` | Whisper 모델 (~1.5GB) | 재다운로드 필요 |
|
|
||||||
| `paddle_models` | PaddleOCR 모델 (~700MB) | 재다운로드 필요 |
|
|
||||||
| `stt_data` | 업로드/결과 파일 | 데이터 손실 |
|
|
||||||
| `redis_data` | 작업 큐 상태 | 진행 중 작업 손실 |
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## 트러블슈팅 알려진 이슈
|
|
||||||
|
|
||||||
실제 배포 과정에서 겪은 오류와 해결 방법입니다.
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `signal 11 (SIGSEGV)` — Worker 크래시
|
|
||||||
|
|
||||||
**원인**: faster-whisper 내부 CTranslate2 라이브러리가 Celery `prefork` 방식과 충돌
|
|
||||||
**해결**: `docker-compose.yml` worker command에 `--pool=solo` 추가
|
|
||||||
|
|
||||||
```yaml
|
|
||||||
command: >
|
|
||||||
celery -A tasks worker
|
|
||||||
--loglevel=info
|
|
||||||
--pool=solo # ← 이 옵션이 핵심
|
|
||||||
--max-tasks-per-child=50
|
|
||||||
-Q stt,ocr
|
|
||||||
```
|
|
||||||
|
|
||||||
> `--pool=solo`는 포크 없이 메인 프로세스에서 직접 실행합니다.
|
|
||||||
> `--concurrency=1`이었으므로 성능 차이는 없습니다.
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `No matching distribution found for paddlepaddle==2.6.1`
|
|
||||||
|
|
||||||
**원인**: 미러에서 해당 버전 제거됨
|
|
||||||
**해결**: `Dockerfile`에서 `3.0.0`으로 변경
|
|
||||||
|
|
||||||
```dockerfile
|
|
||||||
RUN pip install --no-cache-dir paddlepaddle==3.0.0 \
|
|
||||||
-i https://pypi.tuna.tsinghua.edu.cn/simple
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `ValueError: password cannot be longer than 72 bytes`
|
|
||||||
|
|
||||||
**원인**: `passlib[bcrypt]` 초기화 버그
|
|
||||||
**해결**: `auth.py`에서 bcrypt 완전 제거, 직접 문자열 비교 방식 사용
|
|
||||||
`requirements.txt`에서 `passlib` 줄 삭제
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `AttributeError: 'DisabledBackend'`
|
|
||||||
|
|
||||||
**원인**: `from celery.result import AsyncResult` 사용 시 백엔드 설정 누락
|
|
||||||
**해결**: `celery_app.AsyncResult()` 방식으로 변경
|
|
||||||
|
|
||||||
```python
|
|
||||||
# main.py
|
|
||||||
from tasks import celery_app
|
|
||||||
r = celery_app.AsyncResult(task_id) # ✅
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `ModuleNotFoundError: No module named 'ocr_tasks'`
|
|
||||||
|
|
||||||
**원인**: `celery_app.autodiscover_tasks(["ocr_tasks"])` 동작 안 함
|
|
||||||
**해결**: `tasks.py`에서 직접 import
|
|
||||||
|
|
||||||
```python
|
|
||||||
from ocr_tasks import ocr_task # noqa: F401
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `Unknown argument: use_gpu` / `Unknown argument: show_log`
|
|
||||||
|
|
||||||
**원인**: PaddleOCR 3.x에서 파라미터 제거됨
|
|
||||||
**해결**: `ocr_tasks.py`에서 해당 파라미터 삭제
|
|
||||||
|
|
||||||
```python
|
|
||||||
_ocr_engine = PaddleOCR(use_angle_cls=True, lang=OCR_LANG) # ✅
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `PaddleOCR.predict() got an unexpected keyword argument 'cls'`
|
|
||||||
|
|
||||||
**원인**: PaddleOCR 3.x API 변경
|
|
||||||
**해결**: `ocr(img, cls=True)` → `ocr(img)`
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `'AnalysisConfig' object has no attribute 'set_optimization_level'`
|
|
||||||
|
|
||||||
**원인**: PaddleOCR 3.x와 paddlepaddle 2.x 버전 불일치
|
|
||||||
**해결**: paddlepaddle `3.0.0`으로 업그레이드
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `too many values to unpack (expected 2)`
|
|
||||||
|
|
||||||
**원인**: PaddleOCR 3.x 결과 구조 변경
|
|
||||||
**해결**: `rec_texts` / `rec_scores` 방식으로 파싱
|
|
||||||
|
|
||||||
```python
|
|
||||||
r = result[0]
|
|
||||||
texts = r.get("rec_texts", [])
|
|
||||||
scores = r.get("rec_scores", [])
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ `MISCONF Redis is configured to save RDB snapshots`
|
|
||||||
|
|
||||||
**원인**: 디스크 부족으로 Redis RDB 저장 실패 → 쓰기 차단
|
|
||||||
**해결**: `docker-compose.yml` Redis command에 옵션 추가
|
|
||||||
|
|
||||||
```yaml
|
|
||||||
command: redis-server --stop-writes-on-bgsave-error no
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ Ollama 연결 타임아웃
|
|
||||||
|
|
||||||
**원인**: `host.docker.internal`이 Linux에서 불안정
|
|
||||||
**해결**: 실제 호스트 LAN IP로 변경
|
|
||||||
|
|
||||||
```yaml
|
|
||||||
- OLLAMA_URL=http://192.168.x.x:11434
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
### ❌ STT 진행률 5%/15%에서 멈춤
|
|
||||||
|
|
||||||
| 단계 | 원인 | 대기 시간 |
|
|
||||||
|------|------|---------|
|
|
||||||
| 5% `모델 준비 중` | Whisper 모델 첫 다운로드 (~1.5GB) | 5~20분 |
|
|
||||||
| 15% `오디오 분석 중` | 첫 변환 시 내부 초기화 | 1~3분 |
|
|
||||||
| `변환 중... Xs / Xs` | 정상 진행 | 파일 길이에 비례 |
|
|
||||||
|
|
||||||
```bash
|
|
||||||
# 진행 상황 실시간 확인
|
|
||||||
docker compose logs worker -f
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## API 엔드포인트
|
|
||||||
|
|
||||||
### 인증
|
|
||||||
|
|
||||||
| 메서드 | 경로 | 설명 |
|
|
||||||
|--------|------|------|
|
|
||||||
| `POST` | `/api/login` | 로그인 (`username`, `password` form) |
|
|
||||||
| `GET` | `/api/me` | 현재 사용자 확인 |
|
|
||||||
|
|
||||||
### STT
|
|
||||||
|
|
||||||
| 메서드 | 경로 | 설명 |
|
|
||||||
|--------|------|------|
|
|
||||||
| `POST` | `/api/transcribe` | 음성 파일 업로드 및 변환 시작 |
|
|
||||||
| `GET` | `/api/status/{task_id}` | 작업 진행 상태 조회 |
|
|
||||||
| `GET` | `/api/download/{filename}` | 결과 파일 다운로드 |
|
|
||||||
|
|
||||||
### OCR
|
|
||||||
|
|
||||||
| 메서드 | 경로 | 설명 |
|
|
||||||
|--------|------|------|
|
|
||||||
| `POST` | `/api/ocr` | 이미지 업로드 및 인식 시작 |
|
|
||||||
|
|
||||||
**OCR 파라미터**
|
|
||||||
|
|
||||||
| 파라미터 | 기본값 | 설명 |
|
|
||||||
|---------|--------|------|
|
|
||||||
| `file` | — | 이미지 파일 |
|
|
||||||
| `mode` | `text` | `text` \| `structure` |
|
|
||||||
| `backend` | `paddle` | `paddle` \| `ollama` |
|
|
||||||
| `ollama_model` | `granite3.2-vision` | Ollama 모델명 |
|
|
||||||
| `custom_prompt` | 비어있음 | Ollama 커스텀 프롬프트 |
|
|
||||||
|
|
||||||
### 관리
|
|
||||||
|
|
||||||
| 메서드 | 경로 | 설명 |
|
|
||||||
|--------|------|------|
|
|
||||||
| `POST` | `/api/cleanup` | 오래된 결과 파일 정리 |
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## 기술 스택
|
|
||||||
|
|
||||||
| 구성요소 | 버전 | 역할 |
|
|
||||||
|---------|------|------|
|
|
||||||
| Python | 3.11 | 런타임 |
|
|
||||||
| FastAPI | 0.115 | API 서버 |
|
|
||||||
| Celery | 5.4 (`--pool=solo`) | 비동기 태스크 큐 |
|
|
||||||
| Redis | 7 alpine | 메시지 브로커 |
|
|
||||||
| faster-whisper | 1.0.3 | STT 엔진 |
|
|
||||||
| PaddlePaddle | 3.0.0 | OCR 딥러닝 프레임워크 |
|
|
||||||
| PaddleOCR | 3.x | OCR 엔진 |
|
|
||||||
| httpx | 0.27+ | Ollama API 호출 |
|
|
||||||
| Ollama | 호스트 운용 | Vision 모델 서버 |
|
|
||||||
|
|||||||
@@ -9,6 +9,8 @@ RUN apt-get update && apt-get install -y \
|
|||||||
libxext6 \
|
libxext6 \
|
||||||
libxrender1 \
|
libxrender1 \
|
||||||
libgl1 \
|
libgl1 \
|
||||||
|
libgles2 \
|
||||||
|
libegl1 \
|
||||||
wget \
|
wget \
|
||||||
curl \
|
curl \
|
||||||
&& rm -rf /var/lib/apt/lists/*
|
&& rm -rf /var/lib/apt/lists/*
|
||||||
@@ -17,9 +19,8 @@ WORKDIR /app
|
|||||||
|
|
||||||
COPY requirements.txt .
|
COPY requirements.txt .
|
||||||
|
|
||||||
# PaddlePaddle CPU (AMD64) — paddleocr 3.x 호환
|
# PaddlePaddle CPU — PyPI 공식 (청화 미러 접속 불안정으로 제거)
|
||||||
RUN pip install --no-cache-dir paddlepaddle==3.0.0 \
|
RUN pip install --no-cache-dir paddlepaddle==3.0.0
|
||||||
-i https://pypi.tuna.tsinghua.edu.cn/simple
|
|
||||||
|
|
||||||
# 나머지 패키지
|
# 나머지 패키지
|
||||||
RUN pip install --no-cache-dir -r requirements.txt
|
RUN pip install --no-cache-dir -r requirements.txt
|
||||||
|
|||||||
638
app/main.py
638
app/main.py
@@ -5,6 +5,7 @@ from datetime import datetime
|
|||||||
from fastapi import FastAPI, UploadFile, File, HTTPException, Depends, Form, Request
|
from fastapi import FastAPI, UploadFile, File, HTTPException, Depends, Form, Request
|
||||||
from fastapi.staticfiles import StaticFiles
|
from fastapi.staticfiles import StaticFiles
|
||||||
from fastapi.responses import FileResponse
|
from fastapi.responses import FileResponse
|
||||||
|
from typing import List
|
||||||
|
|
||||||
from auth import (authenticate, create_access_token, init_users,
|
from auth import (authenticate, create_access_token, init_users,
|
||||||
require_auth, require_admin, require_stt, require_ocr,
|
require_auth, require_admin, require_stt, require_ocr,
|
||||||
@@ -28,20 +29,25 @@ HISTORY_MAX = 300
|
|||||||
os.makedirs(UPLOAD_DIR, exist_ok=True)
|
os.makedirs(UPLOAD_DIR, exist_ok=True)
|
||||||
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
||||||
|
|
||||||
AUDIO_EXT = {"mp3","mp4","wav","m4a","ogg","flac","aac","wma","webm","mkv","avi","mov"}
|
AUDIO_EXT = {"mp3","mp4","wav","m4a","ogg","flac","aac","wma","webm",
|
||||||
|
"mkv","avi","mov","ts","mts","m2ts","wmv","flv","rmvb",
|
||||||
|
"h264","h265","hevc","264","265"}
|
||||||
IMAGE_EXT = {"jpg","jpeg","png","bmp","tiff","tif","webp","gif"}
|
IMAGE_EXT = {"jpg","jpeg","png","bmp","tiff","tif","webp","gif"}
|
||||||
|
|
||||||
|
SUPPORTED_LANGS = {
|
||||||
|
"ko":"한국어","en":"English","ja":"日本語","zh":"中文(简体)",
|
||||||
|
"zh-tw":"中文(繁體)","fr":"Français","de":"Deutsch","es":"Español",
|
||||||
|
"it":"Italiano","pt":"Português","ru":"Русский","ar":"العربية",
|
||||||
|
"vi":"Tiếng Việt","th":"ไทย","id":"Bahasa Indonesia",
|
||||||
|
"nl":"Nederlands","pl":"Polski","tr":"Türkçe","sv":"Svenska",
|
||||||
|
"uk":"Українська","hi":"हिन्दी","bn":"বাংলা",
|
||||||
|
}
|
||||||
|
|
||||||
_DEFAULT_SETTINGS = {
|
_DEFAULT_SETTINGS = {
|
||||||
"stt_ollama_model": "",
|
"stt_ollama_model":"","ocr_ollama_model":"granite3.2-vision:latest",
|
||||||
"ocr_ollama_model": "granite3.2-vision:latest",
|
"cpu_threads":0,"stt_timeout":0,"ollama_timeout":600,
|
||||||
"cpu_threads": 0,
|
"openrouter_url":"https://openrouter.ai/api/v1",
|
||||||
"stt_timeout": 0,
|
"openrouter_api_key":"","openrouter_stt_model":"","openrouter_ocr_model":"",
|
||||||
"ollama_timeout": 600,
|
|
||||||
# OpenRouter
|
|
||||||
"openrouter_url": "https://openrouter.ai/api/v1",
|
|
||||||
"openrouter_api_key": "",
|
|
||||||
"openrouter_stt_model": "",
|
|
||||||
"openrouter_ocr_model": "",
|
|
||||||
}
|
}
|
||||||
_hist_lock = threading.Lock()
|
_hist_lock = threading.Lock()
|
||||||
|
|
||||||
@@ -49,91 +55,93 @@ _hist_lock = threading.Lock()
|
|||||||
# ── 설정 I/O ─────────────────────────────────────────────────
|
# ── 설정 I/O ─────────────────────────────────────────────────
|
||||||
def _load_settings() -> dict:
|
def _load_settings() -> dict:
|
||||||
if not SETTINGS_FILE.exists(): return dict(_DEFAULT_SETTINGS)
|
if not SETTINGS_FILE.exists(): return dict(_DEFAULT_SETTINGS)
|
||||||
with open(SETTINGS_FILE, "r", encoding="utf-8") as f: data = json.load(f)
|
with open(SETTINGS_FILE,"r",encoding="utf-8") as f: data=json.load(f)
|
||||||
for k, v in _DEFAULT_SETTINGS.items(): data.setdefault(k, v)
|
for k,v in _DEFAULT_SETTINGS.items(): data.setdefault(k,v)
|
||||||
return data
|
return data
|
||||||
|
|
||||||
def _save_settings(data: dict):
|
def _save_settings(data:dict):
|
||||||
SETTINGS_FILE.parent.mkdir(parents=True, exist_ok=True)
|
SETTINGS_FILE.parent.mkdir(parents=True,exist_ok=True)
|
||||||
with open(SETTINGS_FILE, "w", encoding="utf-8") as f:
|
with open(SETTINGS_FILE,"w",encoding="utf-8") as f: json.dump(data,f,ensure_ascii=False,indent=2)
|
||||||
json.dump(data, f, ensure_ascii=False, indent=2)
|
|
||||||
|
|
||||||
|
|
||||||
# ── 이력 I/O ─────────────────────────────────────────────────
|
# ── 이력 I/O ─────────────────────────────────────────────────
|
||||||
def _load_history() -> list:
|
def _load_history()->list:
|
||||||
with _hist_lock:
|
with _hist_lock:
|
||||||
if not HISTORY_FILE.exists(): return []
|
if not HISTORY_FILE.exists(): return []
|
||||||
try:
|
try:
|
||||||
with open(HISTORY_FILE, "r", encoding="utf-8") as f: return json.load(f)
|
with open(HISTORY_FILE,"r",encoding="utf-8") as f: return json.load(f)
|
||||||
except: return []
|
except: return []
|
||||||
|
|
||||||
def _write_history(history: list):
|
def _write_history(h:list):
|
||||||
HISTORY_FILE.parent.mkdir(parents=True, exist_ok=True)
|
HISTORY_FILE.parent.mkdir(parents=True,exist_ok=True)
|
||||||
with open(HISTORY_FILE, "w", encoding="utf-8") as f:
|
with open(HISTORY_FILE,"w",encoding="utf-8") as f: json.dump(h,f,ensure_ascii=False,indent=2)
|
||||||
json.dump(history, f, ensure_ascii=False, indent=2)
|
|
||||||
|
|
||||||
def append_history(record: dict):
|
def append_history(record:dict):
|
||||||
with _hist_lock:
|
with _hist_lock:
|
||||||
try:
|
try:
|
||||||
history = []
|
history=[]
|
||||||
if HISTORY_FILE.exists():
|
if HISTORY_FILE.exists():
|
||||||
with open(HISTORY_FILE, "r", encoding="utf-8") as f: history = json.load(f)
|
with open(HISTORY_FILE,"r",encoding="utf-8") as f: history=json.load(f)
|
||||||
history.insert(0, record)
|
history.insert(0,record); _write_history(history[:HISTORY_MAX])
|
||||||
_write_history(history[:HISTORY_MAX])
|
|
||||||
except: pass
|
except: pass
|
||||||
|
|
||||||
def _update_history_by_task(task_id: str, result: dict, success: bool, error_msg: str = ""):
|
def _update_history_by_task(task_id:str,result:dict,success:bool,error_msg:str=""):
|
||||||
with _hist_lock:
|
with _hist_lock:
|
||||||
if not HISTORY_FILE.exists(): return
|
if not HISTORY_FILE.exists(): return
|
||||||
try:
|
try:
|
||||||
with open(HISTORY_FILE, "r", encoding="utf-8") as f: history = json.load(f)
|
with open(HISTORY_FILE,"r",encoding="utf-8") as f: history=json.load(f)
|
||||||
for h in history:
|
for h in history:
|
||||||
if h.get("task_id") != task_id: continue
|
if h.get("task_id")!=task_id: continue
|
||||||
if h.get("status") != "processing": break
|
if h.get("status")!="processing": break
|
||||||
if not success:
|
if not success: h["status"]="failed";h["output"]={"error":error_msg[:300]};break
|
||||||
h["status"] = "failed"; h["output"] = {"error": error_msg[:300]}; break
|
h["status"]="success"
|
||||||
h["status"] = "success"
|
if h["type"]=="stt":
|
||||||
if h["type"] == "stt":
|
text=result.get("text","")
|
||||||
h["output"] = {
|
h["output"]={
|
||||||
"filename": result.get("output_file", ""),
|
"filename":result.get("output_file",""),
|
||||||
"language": result.get("language", ""),
|
"language":result.get("language",""),
|
||||||
"duration_s": result.get("duration", 0),
|
"duration_s":result.get("duration",0),
|
||||||
"segments": len(result.get("segments", [])),
|
"segments":len(result.get("segments",[])),
|
||||||
"text_preview": result.get("text","")[:200] + ("…" if len(result.get("text",""))>200 else ""),
|
"text_preview":text[:200]+("…" if len(text)>200 else ""),
|
||||||
"ollama_used": result.get("ollama_used", False),
|
"ollama_used":result.get("ollama_used",False),
|
||||||
"ollama_model": result.get("ollama_model", ""),
|
"ollama_model":result.get("ollama_model",""),
|
||||||
"openrouter_used": result.get("openrouter_used", False),
|
"openrouter_used":result.get("openrouter_used",False),
|
||||||
"openrouter_model": result.get("openrouter_model", ""),
|
"openrouter_model":result.get("openrouter_model",""),
|
||||||
|
"subtitle_mode":result.get("subtitle_mode",False),
|
||||||
|
"translated":result.get("translated",False),
|
||||||
|
"translate_to":result.get("translate_to",""),
|
||||||
|
"srt_file":result.get("srt_file",""),
|
||||||
|
"vtt_file":result.get("vtt_file",""),
|
||||||
}
|
}
|
||||||
else:
|
else:
|
||||||
ft = result.get("full_text", "")
|
ft=result.get("full_text","")
|
||||||
h["output"] = {
|
h["output"]={
|
||||||
"txt_file": result.get("txt_file", ""),
|
"txt_file":result.get("txt_file",""),
|
||||||
"xlsx_file": result.get("xlsx_file", ""),
|
"xlsx_file":result.get("xlsx_file",""),
|
||||||
"line_count": result.get("line_count", 0),
|
"line_count":result.get("line_count",0),
|
||||||
"table_count": len(result.get("tables", [])),
|
"table_count":len(result.get("tables",[])),
|
||||||
"backend": result.get("backend", ""),
|
"backend":result.get("backend",""),
|
||||||
"ollama_model": result.get("ollama_model", ""),
|
"ollama_model":result.get("ollama_model",""),
|
||||||
"openrouter_model": result.get("openrouter_model", ""),
|
"openrouter_model":result.get("openrouter_model",""),
|
||||||
"text_preview": ft[:200] + ("…" if len(ft)>200 else ""),
|
"text_preview":ft[:200]+("…" if len(ft)>200 else ""),
|
||||||
}
|
}
|
||||||
break
|
break
|
||||||
_write_history(history)
|
_write_history(history)
|
||||||
except: pass
|
except: pass
|
||||||
|
|
||||||
def delete_history_item(history_id: str) -> bool:
|
def delete_history_item(history_id:str)->bool:
|
||||||
with _hist_lock:
|
with _hist_lock:
|
||||||
if not HISTORY_FILE.exists(): return False
|
if not HISTORY_FILE.exists(): return False
|
||||||
try:
|
try:
|
||||||
with open(HISTORY_FILE, "r", encoding="utf-8") as f: history = json.load(f)
|
with open(HISTORY_FILE,"r",encoding="utf-8") as f: history=json.load(f)
|
||||||
new = [h for h in history if h.get("id") != history_id]
|
new=[h for h in history if h.get("id")!=history_id]
|
||||||
if len(new) == len(history): return False
|
if len(new)==len(history): return False
|
||||||
_write_history(new); return True
|
_write_history(new); return True
|
||||||
except: return False
|
except: return False
|
||||||
|
|
||||||
def clear_history():
|
def clear_history():
|
||||||
with _hist_lock:
|
with _hist_lock:
|
||||||
if HISTORY_FILE.exists(): HISTORY_FILE.write_text("[]", encoding="utf-8")
|
if HISTORY_FILE.exists(): HISTORY_FILE.write_text("[]",encoding="utf-8")
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
@@ -148,177 +156,207 @@ async def on_startup():
|
|||||||
# 인증
|
# 인증
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
@app.post("/api/login")
|
@app.post("/api/login")
|
||||||
def login(username: str = Form(...), password: str = Form(...)):
|
def login(username:str=Form(...),password:str=Form(...)):
|
||||||
user = authenticate(username, password)
|
user=authenticate(username,password)
|
||||||
if not user: raise HTTPException(401, "아이디 또는 비밀번호가 올바르지 않습니다")
|
if not user: raise HTTPException(401,"아이디 또는 비밀번호가 올바르지 않습니다")
|
||||||
return {"access_token": create_access_token(username), "token_type": "bearer"}
|
return {"access_token":create_access_token(username),"token_type":"bearer"}
|
||||||
|
|
||||||
@app.get("/api/me")
|
@app.get("/api/me")
|
||||||
def me(user: dict = Depends(require_auth)):
|
def me(user:dict=Depends(require_auth)):
|
||||||
return {"username": user["username"], "role": user.get("role","user"),
|
return {"username":user["username"],"role":user.get("role","user"),
|
||||||
"permissions": user.get("permissions", {"stt":False,"ocr":False})}
|
"permissions":user.get("permissions",{"stt":False,"ocr":False})}
|
||||||
|
|
||||||
|
@app.get("/api/languages")
|
||||||
|
def get_languages(user:dict=Depends(require_auth)):
|
||||||
|
return {"languages":SUPPORTED_LANGS}
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# 시스템 정보
|
# 시스템 정보
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
@app.get("/api/system")
|
@app.get("/api/system")
|
||||||
def system_info(user: dict = Depends(require_auth)):
|
def system_info(user:dict=Depends(require_auth)):
|
||||||
mem = psutil.virtual_memory(); swap = psutil.swap_memory(); s = _load_settings()
|
mem=psutil.virtual_memory();swap=psutil.swap_memory();s=_load_settings()
|
||||||
return {
|
return {
|
||||||
"ram_total_gb": round(mem.total / 1024**3, 1),
|
"ram_total_gb":round(mem.total/1024**3,1),"ram_used_gb":round(mem.used/1024**3,1),
|
||||||
"ram_used_gb": round(mem.used / 1024**3, 1),
|
"ram_avail_gb":round(mem.available/1024**3,1),"ram_percent":mem.percent,
|
||||||
"ram_avail_gb": round(mem.available / 1024**3, 1),
|
"swap_total_gb":round(swap.total/1024**3,1),"swap_used_gb":round(swap.used/1024**3,1),
|
||||||
"ram_percent": mem.percent,
|
"cpu_logical":psutil.cpu_count(logical=True),"cpu_physical":psutil.cpu_count(logical=False),
|
||||||
"swap_total_gb": round(swap.total / 1024**3, 1),
|
"cpu_percent":psutil.cpu_percent(interval=0.3),
|
||||||
"swap_used_gb": round(swap.used / 1024**3, 1),
|
"cpu_threads_setting":s.get("cpu_threads",0),
|
||||||
"cpu_logical": psutil.cpu_count(logical=True),
|
"stt_timeout":s.get("stt_timeout",0),"ollama_timeout":s.get("ollama_timeout",600),
|
||||||
"cpu_physical": psutil.cpu_count(logical=False),
|
|
||||||
"cpu_percent": psutil.cpu_percent(interval=0.3),
|
|
||||||
"cpu_threads_setting": s.get("cpu_threads", 0),
|
|
||||||
"stt_timeout": s.get("stt_timeout", 0),
|
|
||||||
"ollama_timeout":s.get("ollama_timeout", 600),
|
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# STT
|
# STT 공통 디스패치
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
@app.post("/api/transcribe")
|
async def _dispatch_stt(
|
||||||
async def transcribe(
|
request, files,
|
||||||
request: Request, file: UploadFile = File(...),
|
use_ollama, ollama_model,
|
||||||
use_ollama: str = Form("false"),
|
use_openrouter, openrouter_model,
|
||||||
ollama_model: str = Form(""),
|
subtitle_mode, subtitle_format,
|
||||||
use_openrouter: str = Form("false"),
|
force_language,
|
||||||
openrouter_model: str = Form(""),
|
translate_to, translate_model, translate_via,
|
||||||
user: dict = Depends(require_stt),
|
user,
|
||||||
):
|
):
|
||||||
_check_size(request)
|
|
||||||
ext = _ext(file.filename)
|
|
||||||
if ext not in AUDIO_EXT: raise HTTPException(400, f"지원하지 않는 형식: {', '.join(sorted(AUDIO_EXT))}")
|
|
||||||
file_id = str(uuid.uuid4())
|
|
||||||
save_path = os.path.join(UPLOAD_DIR, f"{file_id}.{ext}")
|
|
||||||
await _save(file, save_path)
|
|
||||||
file_size = os.path.getsize(save_path)
|
|
||||||
|
|
||||||
s = _load_settings()
|
s = _load_settings()
|
||||||
_use_ollama = use_ollama.lower() == "true"
|
_use_ollama = use_ollama.lower() == "true"
|
||||||
_use_openrouter = use_openrouter.lower() == "true"
|
_use_openrouter = use_openrouter.lower() == "true"
|
||||||
|
_sub_mode = subtitle_mode.lower() == "true"
|
||||||
|
if _use_ollama and not ollama_model.strip(): ollama_model = s.get("stt_ollama_model","")
|
||||||
|
if _use_openrouter and not openrouter_model.strip():openrouter_model= s.get("openrouter_stt_model","")
|
||||||
|
if not translate_model.strip():
|
||||||
|
translate_model = ollama_model if translate_via=="ollama" else openrouter_model
|
||||||
|
|
||||||
if _use_ollama and not ollama_model.strip():
|
results=[]
|
||||||
ollama_model = s.get("stt_ollama_model", "")
|
for file in files:
|
||||||
if _use_openrouter and not openrouter_model.strip():
|
_check_size(request)
|
||||||
openrouter_model = s.get("openrouter_stt_model", "")
|
ext=_ext(file.filename)
|
||||||
|
if ext not in AUDIO_EXT:
|
||||||
task = transcribe_task.delay(
|
results.append({"error":f"{file.filename}: 지원하지 않는 형식","filename":file.filename})
|
||||||
|
continue
|
||||||
|
file_id=str(uuid.uuid4())
|
||||||
|
save_path=os.path.join(UPLOAD_DIR,f"{file_id}.{ext}")
|
||||||
|
await _save_upload(file,save_path)
|
||||||
|
file_size=os.path.getsize(save_path)
|
||||||
|
task=transcribe_task.delay(
|
||||||
file_id, save_path,
|
file_id, save_path,
|
||||||
_use_ollama, ollama_model,
|
_use_ollama, ollama_model,
|
||||||
_use_openrouter, openrouter_model,
|
_use_openrouter, openrouter_model,
|
||||||
s.get("openrouter_url", ""), s.get("openrouter_api_key", ""),
|
|
||||||
)
|
|
||||||
|
|
||||||
append_history({
|
|
||||||
"id": file_id, "task_id": task.id, "type": "stt",
|
|
||||||
"status": "processing",
|
|
||||||
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
|
||||||
"username": user["username"],
|
|
||||||
"input": {"filename": file.filename, "size_bytes": file_size, "format": ext.upper()},
|
|
||||||
"settings": {
|
|
||||||
"model": os.getenv("WHISPER_MODEL","medium"),
|
|
||||||
"language": os.getenv("WHISPER_LANGUAGE","ko"),
|
|
||||||
"compute_type": os.getenv("WHISPER_COMPUTE_TYPE","int8"),
|
|
||||||
"cpu_threads": s.get("cpu_threads",0),
|
|
||||||
"stt_timeout": s.get("stt_timeout",0),
|
|
||||||
"use_ollama": _use_ollama,
|
|
||||||
"ollama_model": ollama_model if _use_ollama else "",
|
|
||||||
"use_openrouter": _use_openrouter,
|
|
||||||
"openrouter_model": openrouter_model if _use_openrouter else "",
|
|
||||||
},
|
|
||||||
"output": None,
|
|
||||||
})
|
|
||||||
return {"task_id": task.id, "file_id": file_id, "filename": file.filename}
|
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
# OCR
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
@app.post("/api/ocr")
|
|
||||||
async def ocr(
|
|
||||||
request: Request, file: UploadFile = File(...),
|
|
||||||
mode: str = Form("text"),
|
|
||||||
backend: str = Form("paddle"), # paddle | ollama | openrouter
|
|
||||||
ollama_model: str = Form(""),
|
|
||||||
openrouter_model: str = Form(""),
|
|
||||||
custom_prompt: str = Form(""),
|
|
||||||
user: dict = Depends(require_ocr),
|
|
||||||
):
|
|
||||||
_check_size(request)
|
|
||||||
ext = _ext(file.filename)
|
|
||||||
if ext not in IMAGE_EXT: raise HTTPException(400, f"지원하지 않는 형식: {', '.join(sorted(IMAGE_EXT))}")
|
|
||||||
if mode not in ("text","structure"): mode = "text"
|
|
||||||
if backend not in ("paddle","ollama","openrouter"): backend = "paddle"
|
|
||||||
|
|
||||||
s = _load_settings()
|
|
||||||
if backend == "ollama" and not ollama_model.strip():
|
|
||||||
ollama_model = s.get("ocr_ollama_model","granite3.2-vision:latest")
|
|
||||||
if backend == "openrouter" and not openrouter_model.strip():
|
|
||||||
openrouter_model = s.get("openrouter_ocr_model","")
|
|
||||||
|
|
||||||
file_id = str(uuid.uuid4())
|
|
||||||
save_path = os.path.join(UPLOAD_DIR, f"{file_id}.{ext}")
|
|
||||||
await _save(file, save_path)
|
|
||||||
file_size = os.path.getsize(save_path)
|
|
||||||
|
|
||||||
task = ocr_task.delay(
|
|
||||||
file_id, save_path, mode, backend,
|
|
||||||
ollama_model, openrouter_model,
|
|
||||||
s.get("openrouter_url",""), s.get("openrouter_api_key",""),
|
s.get("openrouter_url",""), s.get("openrouter_api_key",""),
|
||||||
custom_prompt,
|
_sub_mode, subtitle_format or "srt",
|
||||||
|
translate_to or "",
|
||||||
|
translate_model or "",
|
||||||
|
translate_via or "ollama",
|
||||||
|
force_language or "",
|
||||||
)
|
)
|
||||||
|
|
||||||
append_history({
|
append_history({
|
||||||
"id": file_id, "task_id": task.id, "type": "ocr",
|
"id":file_id,"task_id":task.id,"type":"stt",
|
||||||
"status": "processing",
|
"status":"processing",
|
||||||
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
"timestamp":datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
||||||
"username": user["username"],
|
"username":user["username"],
|
||||||
"input": {"filename": file.filename, "size_bytes": file_size, "format": ext.upper()},
|
"input":{"filename":file.filename,"size_bytes":file_size,"format":ext.upper()},
|
||||||
"settings": {
|
"settings":{
|
||||||
"backend": backend,
|
"model":os.getenv("WHISPER_MODEL","medium"),
|
||||||
"mode": mode,
|
"language":force_language or os.getenv("WHISPER_LANGUAGE","auto"),
|
||||||
"ocr_lang": os.getenv("OCR_LANG","korean"),
|
"compute_type":os.getenv("WHISPER_COMPUTE_TYPE","int8"),
|
||||||
"ollama_model": ollama_model if backend=="ollama" else "",
|
"cpu_threads":s.get("cpu_threads",0),
|
||||||
"openrouter_model": openrouter_model if backend=="openrouter" else "",
|
"subtitle_mode":_sub_mode,
|
||||||
"ollama_timeout": s.get("ollama_timeout",600),
|
"subtitle_format":subtitle_format,
|
||||||
"custom_prompt": custom_prompt[:200] if custom_prompt else "",
|
"translate_to":translate_to,
|
||||||
|
"translate_model":translate_model,
|
||||||
|
"use_ollama":_use_ollama,"ollama_model":ollama_model if _use_ollama else "",
|
||||||
|
"use_openrouter":_use_openrouter,"openrouter_model":openrouter_model if _use_openrouter else "",
|
||||||
},
|
},
|
||||||
"output": None,
|
"output":None,
|
||||||
})
|
})
|
||||||
return {"task_id": task.id, "file_id": file_id,
|
results.append({"task_id":task.id,"file_id":file_id,"filename":file.filename})
|
||||||
"filename": file.filename, "mode": mode, "backend": backend}
|
return results
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# 상태
|
# STT — 단일 / 배치
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
|
@app.post("/api/transcribe")
|
||||||
|
async def transcribe(
|
||||||
|
request:Request, file:UploadFile=File(...),
|
||||||
|
use_ollama:str=Form("false"), ollama_model:str=Form(""),
|
||||||
|
use_openrouter:str=Form("false"), openrouter_model:str=Form(""),
|
||||||
|
subtitle_mode:str=Form("false"), subtitle_format:str=Form("srt"),
|
||||||
|
force_language:str=Form(""),
|
||||||
|
translate_to:str=Form(""), translate_model:str=Form(""), translate_via:str=Form("ollama"),
|
||||||
|
user:dict=Depends(require_stt),
|
||||||
|
):
|
||||||
|
items=await _dispatch_stt(request,[file],use_ollama,ollama_model,use_openrouter,openrouter_model,
|
||||||
|
subtitle_mode,subtitle_format,force_language,translate_to,translate_model,translate_via,user)
|
||||||
|
return items[0]
|
||||||
|
|
||||||
|
@app.post("/api/transcribe/batch")
|
||||||
|
async def transcribe_batch(
|
||||||
|
request:Request, files:List[UploadFile]=File(...),
|
||||||
|
use_ollama:str=Form("false"), ollama_model:str=Form(""),
|
||||||
|
use_openrouter:str=Form("false"), openrouter_model:str=Form(""),
|
||||||
|
subtitle_mode:str=Form("false"), subtitle_format:str=Form("srt"),
|
||||||
|
force_language:str=Form(""),
|
||||||
|
translate_to:str=Form(""), translate_model:str=Form(""), translate_via:str=Form("ollama"),
|
||||||
|
user:dict=Depends(require_stt),
|
||||||
|
):
|
||||||
|
if not files: raise HTTPException(400,"파일이 없습니다")
|
||||||
|
if len(files)>20: raise HTTPException(400,"한 번에 최대 20개까지 업로드할 수 있습니다")
|
||||||
|
items=await _dispatch_stt(request,files,use_ollama,ollama_model,use_openrouter,openrouter_model,
|
||||||
|
subtitle_mode,subtitle_format,force_language,translate_to,translate_model,translate_via,user)
|
||||||
|
return {"items":items,"total":len(items)}
|
||||||
|
|
||||||
|
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
|
# OCR 공통 디스패치
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
|
async def _dispatch_ocr(request,files,mode,backend,ollama_model,openrouter_model,custom_prompt,user):
|
||||||
|
if mode not in ("text","structure"): mode="text"
|
||||||
|
if backend not in ("paddle","ollama","openrouter"): backend="paddle"
|
||||||
|
s=_load_settings()
|
||||||
|
if backend=="ollama" and not ollama_model.strip(): ollama_model=s.get("ocr_ollama_model","granite3.2-vision:latest")
|
||||||
|
if backend=="openrouter" and not openrouter_model.strip(): openrouter_model=s.get("openrouter_ocr_model","")
|
||||||
|
results=[]
|
||||||
|
for file in files:
|
||||||
|
_check_size(request)
|
||||||
|
ext=_ext(file.filename)
|
||||||
|
if ext not in IMAGE_EXT:
|
||||||
|
results.append({"error":f"{file.filename}: 지원하지 않는 형식","filename":file.filename}); continue
|
||||||
|
file_id=str(uuid.uuid4())
|
||||||
|
save_path=os.path.join(UPLOAD_DIR,f"{file_id}.{ext}")
|
||||||
|
await _save_upload(file,save_path); file_size=os.path.getsize(save_path)
|
||||||
|
task=ocr_task.delay(file_id,save_path,mode,backend,ollama_model,openrouter_model,
|
||||||
|
s.get("openrouter_url",""),s.get("openrouter_api_key",""),custom_prompt)
|
||||||
|
append_history({"id":file_id,"task_id":task.id,"type":"ocr","status":"processing",
|
||||||
|
"timestamp":datetime.now().strftime("%Y-%m-%d %H:%M:%S"),"username":user["username"],
|
||||||
|
"input":{"filename":file.filename,"size_bytes":file_size,"format":ext.upper()},
|
||||||
|
"settings":{"backend":backend,"mode":mode,"ocr_lang":os.getenv("OCR_LANG","korean"),
|
||||||
|
"ollama_model":ollama_model if backend=="ollama" else "",
|
||||||
|
"openrouter_model":openrouter_model if backend=="openrouter" else "",
|
||||||
|
"ollama_timeout":s.get("ollama_timeout",600),"custom_prompt":custom_prompt[:200] if custom_prompt else ""},
|
||||||
|
"output":None})
|
||||||
|
results.append({"task_id":task.id,"file_id":file_id,"filename":file.filename})
|
||||||
|
return results
|
||||||
|
|
||||||
|
@app.post("/api/ocr")
|
||||||
|
async def ocr(request:Request,file:UploadFile=File(...),
|
||||||
|
mode:str=Form("text"),backend:str=Form("paddle"),
|
||||||
|
ollama_model:str=Form(""),openrouter_model:str=Form(""),custom_prompt:str=Form(""),
|
||||||
|
user:dict=Depends(require_ocr)):
|
||||||
|
items=await _dispatch_ocr(request,[file],mode,backend,ollama_model,openrouter_model,custom_prompt,user)
|
||||||
|
return items[0]
|
||||||
|
|
||||||
|
@app.post("/api/ocr/batch")
|
||||||
|
async def ocr_batch(request:Request,files:List[UploadFile]=File(...),
|
||||||
|
mode:str=Form("text"),backend:str=Form("paddle"),
|
||||||
|
ollama_model:str=Form(""),openrouter_model:str=Form(""),custom_prompt:str=Form(""),
|
||||||
|
user:dict=Depends(require_ocr)):
|
||||||
|
if not files: raise HTTPException(400,"파일이 없습니다")
|
||||||
|
if len(files)>20: raise HTTPException(400,"한 번에 최대 20개까지")
|
||||||
|
items=await _dispatch_ocr(request,files,mode,backend,ollama_model,openrouter_model,custom_prompt,user)
|
||||||
|
return {"items":items,"total":len(items)}
|
||||||
|
|
||||||
|
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
|
# 상태 / 이력 / 다운로드 / Ollama / OpenRouter / 설정 / 관리자
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
@app.get("/api/status/{task_id}")
|
@app.get("/api/status/{task_id}")
|
||||||
def get_status(task_id: str, user: dict = Depends(require_auth)):
|
def get_status(task_id:str,user:dict=Depends(require_auth)):
|
||||||
r = celery_app.AsyncResult(task_id)
|
r=celery_app.AsyncResult(task_id)
|
||||||
if r.state == "PENDING": return {"state":"pending", "progress":0, "message":"대기 중..."}
|
if r.state=="PENDING": return {"state":"pending","progress":0,"message":"대기 중..."}
|
||||||
if r.state == "PROGRESS": m=r.info or {}; return {"state":"progress","progress":m.get("progress",0),"message":m.get("message","처리 중...")}
|
if r.state=="PROGRESS": m=r.info or {};return {"state":"progress","progress":m.get("progress",0),"message":m.get("message","처리 중...")}
|
||||||
if r.state == "SUCCESS": _update_history_by_task(task_id, r.result or {}, True); return {"state":"success","progress":100,**(r.result or {})}
|
if r.state=="SUCCESS": _update_history_by_task(task_id,r.result or {},True);return {"state":"success","progress":100,**(r.result or {})}
|
||||||
if r.state == "FAILURE": _update_history_by_task(task_id, {}, False, str(r.info)); return {"state":"failure","progress":0,"message":str(r.info)}
|
if r.state=="FAILURE": _update_history_by_task(task_id,{},False,str(r.info));return {"state":"failure","progress":0,"message":str(r.info)}
|
||||||
return {"state":r.state.lower(),"progress":0}
|
return {"state":r.state.lower(),"progress":0}
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
# 이력
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
@app.get("/api/history")
|
@app.get("/api/history")
|
||||||
def get_history(page:int=1,per_page:int=15,type_:str="",user:dict=Depends(require_auth)):
|
def get_history(page:int=1,per_page:int=15,type_:str="",user:dict=Depends(require_auth)):
|
||||||
history = _load_history()
|
history=_load_history()
|
||||||
if user.get("role") != "admin": history = [h for h in history if h.get("username")==user["username"]]
|
if user.get("role")!="admin": history=[h for h in history if h.get("username")==user["username"]]
|
||||||
if type_ in ("stt","ocr"): history = [h for h in history if h.get("type")==type_]
|
if type_ in ("stt","ocr"): history=[h for h in history if h.get("type")==type_]
|
||||||
total = len(history); start = (page-1)*per_page
|
total=len(history);start=(page-1)*per_page
|
||||||
return {"total":total,"page":page,"per_page":per_page,"items":history[start:start+per_page]}
|
return {"total":total,"page":page,"per_page":per_page,"items":history[start:start+per_page]}
|
||||||
|
|
||||||
@app.delete("/api/history/{history_id}")
|
@app.delete("/api/history/{history_id}")
|
||||||
@@ -328,161 +366,87 @@ def delete_history(history_id:str,user:dict=Depends(require_auth)):
|
|||||||
|
|
||||||
@app.delete("/api/history")
|
@app.delete("/api/history")
|
||||||
def clear_all_history(user:dict=Depends(require_admin)):
|
def clear_all_history(user:dict=Depends(require_admin)):
|
||||||
clear_history(); return {"ok":True}
|
clear_history();return {"ok":True}
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
# 다운로드
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
@app.get("/api/download/{filename}")
|
@app.get("/api/download/{filename}")
|
||||||
def download(filename:str,user:dict=Depends(require_auth)):
|
def download(filename:str,user:dict=Depends(require_auth)):
|
||||||
if ".." in filename or "/" in filename: raise HTTPException(400,"잘못된 파일명")
|
if ".." in filename or "/" in filename: raise HTTPException(400,"잘못된 파일명")
|
||||||
path = os.path.join(OUTPUT_DIR, filename)
|
path=os.path.join(OUTPUT_DIR,filename)
|
||||||
if not os.path.exists(path): raise HTTPException(404,"파일을 찾을 수 없습니다")
|
if not os.path.exists(path): raise HTTPException(404,"파일을 찾을 수 없습니다")
|
||||||
media = ("application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
|
if filename.endswith(".xlsx"):
|
||||||
if filename.endswith(".xlsx") else "text/plain")
|
media="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
|
||||||
return FileResponse(path, media_type=media, filename=filename)
|
elif filename.endswith(".srt"): media="text/plain"
|
||||||
|
elif filename.endswith(".vtt"): media="text/vtt"
|
||||||
|
else: media="text/plain"
|
||||||
|
return FileResponse(path,media_type=media,filename=filename)
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
# Ollama 모델 목록
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
@app.get("/api/ollama/models")
|
@app.get("/api/ollama/models")
|
||||||
def ollama_models(user:dict=Depends(require_auth)):
|
def ollama_models(user:dict=Depends(require_auth)):
|
||||||
try:
|
try:
|
||||||
resp = httpx.get(f"{OLLAMA_URL}/api/tags", timeout=8.0); resp.raise_for_status()
|
resp=httpx.get(f"{OLLAMA_URL}/api/tags",timeout=8.0);resp.raise_for_status()
|
||||||
return {"models":[m["name"] for m in resp.json().get("models",[])], "connected":True}
|
return {"models":[m["name"] for m in resp.json().get("models",[])], "connected":True}
|
||||||
except Exception as e:
|
except Exception as e: return {"models":[],"connected":False,"error":str(e)}
|
||||||
return {"models":[], "connected":False, "error":str(e)}
|
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
# OpenRouter 모델 목록 & 연결 테스트
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
@app.get("/api/openrouter/models")
|
@app.get("/api/openrouter/models")
|
||||||
def openrouter_models(user: dict = Depends(require_auth)):
|
def openrouter_models(user:dict=Depends(require_auth)):
|
||||||
s = _load_settings()
|
s=_load_settings();api_key=s.get("openrouter_api_key","");base_url=s.get("openrouter_url","https://openrouter.ai/api/v1").rstrip("/")
|
||||||
api_key = s.get("openrouter_api_key", "")
|
if not api_key: return {"models":[],"connected":False,"error":"API 키가 설정되지 않았습니다"}
|
||||||
base_url = s.get("openrouter_url", "https://openrouter.ai/api/v1").rstrip("/")
|
|
||||||
if not api_key:
|
|
||||||
return {"models": [], "connected": False, "error": "API 키가 설정되지 않았습니다"}
|
|
||||||
try:
|
try:
|
||||||
resp = httpx.get(
|
resp=httpx.get(f"{base_url}/models",
|
||||||
f"{base_url}/models",
|
headers={"Authorization":f"Bearer {api_key}","HTTP-Referer":"https://voicescript.local"},timeout=12.0)
|
||||||
headers={"Authorization": f"Bearer {api_key}",
|
|
||||||
"HTTP-Referer": "https://voicescript.local"},
|
|
||||||
timeout=12.0,
|
|
||||||
)
|
|
||||||
resp.raise_for_status()
|
resp.raise_for_status()
|
||||||
data = resp.json()
|
all_models=resp.json().get("data",[])
|
||||||
# Vision 모델 필터링 (multimodal 지원 모델)
|
vision=[m["id"] for m in all_models if any(k in m["id"].lower()
|
||||||
all_models = data.get("data", [])
|
for k in ["vision","claude-3","gemini","gpt-4o","llava","pixtral","qwen-vl","deepseek-vl"])]
|
||||||
vision = [m["id"] for m in all_models
|
return {"models":[m["id"] for m in all_models],"vision_models":vision,"connected":True,"total":len(all_models)}
|
||||||
if any(k in str(m.get("architecture", {}).get("modality","")).lower()
|
except httpx.HTTPStatusError as e: return {"models":[],"connected":False,"error":f"HTTP {e.response.status_code}"}
|
||||||
for k in ["image","vision","multimodal"])
|
except Exception as e: return {"models":[],"connected":False,"error":str(e)}
|
||||||
or any(k in m["id"].lower()
|
|
||||||
for k in ["vision","claude-3","gemini","gpt-4o","llava","pixtral","qwen-vl","intern","deepseek-vl"])]
|
|
||||||
text = [m["id"] for m in all_models if m["id"] not in vision]
|
|
||||||
return {
|
|
||||||
"models": [m["id"] for m in all_models],
|
|
||||||
"vision_models": vision,
|
|
||||||
"text_models": text,
|
|
||||||
"connected": True,
|
|
||||||
"total": len(all_models),
|
|
||||||
}
|
|
||||||
except httpx.HTTPStatusError as e:
|
|
||||||
return {"models":[], "connected":False, "error":f"HTTP {e.response.status_code}: API 키를 확인하세요"}
|
|
||||||
except Exception as e:
|
|
||||||
return {"models":[], "connected":False, "error":str(e)}
|
|
||||||
|
|
||||||
@app.post("/api/openrouter/test")
|
@app.post("/api/openrouter/test")
|
||||||
def openrouter_test(
|
def openrouter_test(api_key:str=Form(...),base_url:str=Form("https://openrouter.ai/api/v1"),user:dict=Depends(require_auth)):
|
||||||
api_key: str = Form(...),
|
|
||||||
base_url: str = Form("https://openrouter.ai/api/v1"),
|
|
||||||
user: dict = Depends(require_auth),
|
|
||||||
):
|
|
||||||
"""API 키 연결 테스트"""
|
|
||||||
try:
|
try:
|
||||||
resp = httpx.get(
|
resp=httpx.get(f"{base_url.rstrip('/')}/models",
|
||||||
f"{base_url.rstrip('/')}/models",
|
headers={"Authorization":f"Bearer {api_key}","HTTP-Referer":"https://voicescript.local"},timeout=10.0)
|
||||||
headers={"Authorization": f"Bearer {api_key}",
|
|
||||||
"HTTP-Referer": "https://voicescript.local"},
|
|
||||||
timeout=10.0,
|
|
||||||
)
|
|
||||||
resp.raise_for_status()
|
resp.raise_for_status()
|
||||||
count = len(resp.json().get("data", []))
|
count=len(resp.json().get("data",[]));return {"ok":True,"message":f"연결 성공 — {count}개 모델 사용 가능"}
|
||||||
return {"ok": True, "message": f"연결 성공 — {count}개 모델 사용 가능"}
|
except httpx.HTTPStatusError as e: return {"ok":False,"message":f"인증 실패 (HTTP {e.response.status_code})"}
|
||||||
except httpx.HTTPStatusError as e:
|
except Exception as e: return {"ok":False,"message":f"연결 실패: {str(e)}"}
|
||||||
return {"ok": False, "message": f"인증 실패 (HTTP {e.response.status_code}) — API 키를 확인하세요"}
|
|
||||||
except Exception as e:
|
|
||||||
return {"ok": False, "message": f"연결 실패: {str(e)}"}
|
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
# 설정
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
@app.get("/api/settings")
|
@app.get("/api/settings")
|
||||||
def get_settings(user: dict = Depends(require_auth)):
|
def get_settings(user:dict=Depends(require_auth)):
|
||||||
s = _load_settings()
|
s=_load_settings();result=dict(s)
|
||||||
# API 키는 마스킹해서 반환
|
|
||||||
result = dict(s)
|
|
||||||
if result.get("openrouter_api_key"):
|
if result.get("openrouter_api_key"):
|
||||||
key = result["openrouter_api_key"]
|
key=result["openrouter_api_key"]
|
||||||
result["openrouter_api_key_masked"] = key[:8] + "..." + key[-4:] if len(key) > 12 else "****"
|
result["openrouter_api_key_masked"]=key[:8]+"..."+key[-4:] if len(key)>12 else "****"
|
||||||
else:
|
else: result["openrouter_api_key_masked"]=""
|
||||||
result["openrouter_api_key_masked"] = ""
|
result["openrouter_api_key"]="";return result
|
||||||
result["openrouter_api_key"] = "" # 평문은 반환 안 함
|
|
||||||
return result
|
|
||||||
|
|
||||||
@app.post("/api/settings")
|
@app.post("/api/settings")
|
||||||
def save_settings_endpoint(
|
def save_settings_endpoint(
|
||||||
stt_ollama_model: str = Form(""),
|
stt_ollama_model:str=Form(""),ocr_ollama_model:str=Form(""),
|
||||||
ocr_ollama_model: str = Form(""),
|
cpu_threads:str=Form("0"),stt_timeout:str=Form("0"),ollama_timeout:str=Form("600"),
|
||||||
cpu_threads: str = Form("0"),
|
openrouter_url:str=Form("https://openrouter.ai/api/v1"),openrouter_api_key:str=Form(""),
|
||||||
stt_timeout: str = Form("0"),
|
openrouter_stt_model:str=Form(""),openrouter_ocr_model:str=Form(""),
|
||||||
ollama_timeout: str = Form("600"),
|
user:dict=Depends(require_auth),
|
||||||
openrouter_url: str = Form("https://openrouter.ai/api/v1"),
|
|
||||||
openrouter_api_key: str = Form(""),
|
|
||||||
openrouter_stt_model: str = Form(""),
|
|
||||||
openrouter_ocr_model: str = Form(""),
|
|
||||||
user: dict = Depends(require_auth),
|
|
||||||
):
|
):
|
||||||
def _int(v, d):
|
def _int(v,d):
|
||||||
try: return max(0, int(v))
|
try: return max(0,int(v))
|
||||||
except: return d
|
except: return d
|
||||||
|
current=_load_settings()
|
||||||
|
final_key=openrouter_api_key.strip() if openrouter_api_key.strip() else current.get("openrouter_api_key","")
|
||||||
|
data={"stt_ollama_model":stt_ollama_model,"ocr_ollama_model":ocr_ollama_model,
|
||||||
|
"cpu_threads":_int(cpu_threads,0),"stt_timeout":_int(stt_timeout,0),"ollama_timeout":_int(ollama_timeout,600),
|
||||||
|
"openrouter_url":openrouter_url.strip() or "https://openrouter.ai/api/v1",
|
||||||
|
"openrouter_api_key":final_key,"openrouter_stt_model":openrouter_stt_model,"openrouter_ocr_model":openrouter_ocr_model}
|
||||||
|
_save_settings(data);return {"ok":True,"settings":{k:v for k,v in data.items() if k!="openrouter_api_key"}}
|
||||||
|
|
||||||
current = _load_settings()
|
|
||||||
# API 키가 비어있으면 기존 값 유지
|
|
||||||
final_key = openrouter_api_key.strip() if openrouter_api_key.strip() else current.get("openrouter_api_key","")
|
|
||||||
|
|
||||||
data = {
|
|
||||||
"stt_ollama_model": stt_ollama_model,
|
|
||||||
"ocr_ollama_model": ocr_ollama_model,
|
|
||||||
"cpu_threads": _int(cpu_threads, 0),
|
|
||||||
"stt_timeout": _int(stt_timeout, 0),
|
|
||||||
"ollama_timeout": _int(ollama_timeout, 600),
|
|
||||||
"openrouter_url": openrouter_url.strip() or "https://openrouter.ai/api/v1",
|
|
||||||
"openrouter_api_key": final_key,
|
|
||||||
"openrouter_stt_model": openrouter_stt_model,
|
|
||||||
"openrouter_ocr_model": openrouter_ocr_model,
|
|
||||||
}
|
|
||||||
_save_settings(data)
|
|
||||||
return {"ok": True, "settings": {k: v for k, v in data.items() if k != "openrouter_api_key"}}
|
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
# 관리자
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
|
||||||
@app.get("/api/admin/users")
|
@app.get("/api/admin/users")
|
||||||
def admin_list_users(user:dict=Depends(require_admin)): return {"users":list_users()}
|
def admin_list_users(user:dict=Depends(require_admin)): return {"users":list_users()}
|
||||||
|
|
||||||
@app.post("/api/admin/users")
|
@app.post("/api/admin/users")
|
||||||
def admin_create_user(
|
def admin_create_user(username:str=Form(...),password:str=Form(...),
|
||||||
username:str=Form(...),password:str=Form(...),
|
|
||||||
perm_stt:str=Form("false"),perm_ocr:str=Form("false"),
|
perm_stt:str=Form("false"),perm_ocr:str=Form("false"),
|
||||||
allowed_stt_models:str=Form(""),allowed_ocr_models:str=Form(""),
|
allowed_stt_models:str=Form(""),allowed_ocr_models:str=Form(""),user:dict=Depends(require_admin)):
|
||||||
user:dict=Depends(require_admin),
|
|
||||||
):
|
|
||||||
def _p(s): return [m.strip() for m in s.split(",") if m.strip()]
|
def _p(s): return [m.strip() for m in s.split(",") if m.strip()]
|
||||||
perms={"stt":perm_stt.lower()=="true","ocr":perm_ocr.lower()=="true",
|
perms={"stt":perm_stt.lower()=="true","ocr":perm_ocr.lower()=="true",
|
||||||
"allowed_stt_models":_p(allowed_stt_models),"allowed_ocr_models":_p(allowed_ocr_models)}
|
"allowed_stt_models":_p(allowed_stt_models),"allowed_ocr_models":_p(allowed_ocr_models)}
|
||||||
@@ -491,11 +455,8 @@ def admin_create_user(
|
|||||||
return {"ok":True,"message":msg}
|
return {"ok":True,"message":msg}
|
||||||
|
|
||||||
@app.put("/api/admin/users/{username}")
|
@app.put("/api/admin/users/{username}")
|
||||||
def admin_update_user(
|
def admin_update_user(username:str,perm_stt:str=Form("false"),perm_ocr:str=Form("false"),
|
||||||
username:str,perm_stt:str=Form("false"),perm_ocr:str=Form("false"),
|
password:str=Form(""),allowed_stt_models:str=Form(""),allowed_ocr_models:str=Form(""),user:dict=Depends(require_admin)):
|
||||||
password:str=Form(""),allowed_stt_models:str=Form(""),allowed_ocr_models:str=Form(""),
|
|
||||||
user:dict=Depends(require_admin),
|
|
||||||
):
|
|
||||||
def _p(s): return [m.strip() for m in s.split(",") if m.strip()]
|
def _p(s): return [m.strip() for m in s.split(",") if m.strip()]
|
||||||
perms={"stt":perm_stt.lower()=="true","ocr":perm_ocr.lower()=="true",
|
perms={"stt":perm_stt.lower()=="true","ocr":perm_ocr.lower()=="true",
|
||||||
"allowed_stt_models":_p(allowed_stt_models),"allowed_ocr_models":_p(allowed_ocr_models)}
|
"allowed_stt_models":_p(allowed_stt_models),"allowed_ocr_models":_p(allowed_ocr_models)}
|
||||||
@@ -505,7 +466,7 @@ def admin_update_user(
|
|||||||
|
|
||||||
@app.delete("/api/admin/users/{username}")
|
@app.delete("/api/admin/users/{username}")
|
||||||
def admin_delete_user(username:str,user:dict=Depends(require_admin)):
|
def admin_delete_user(username:str,user:dict=Depends(require_admin)):
|
||||||
ok,msg=delete_user(username)
|
ok,msg=delete_user(username);
|
||||||
if not ok: raise HTTPException(400,msg)
|
if not ok: raise HTTPException(400,msg)
|
||||||
return {"ok":True,"message":msg}
|
return {"ok":True,"message":msg}
|
||||||
|
|
||||||
@@ -516,30 +477,29 @@ def cleanup(user:dict=Depends(require_auth)): return {"removed":_cleanup_outputs
|
|||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# 유틸
|
# 유틸
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
def _check_size(request):
|
def _check_size(request:Request):
|
||||||
cl = request.headers.get("content-length")
|
cl=request.headers.get("content-length")
|
||||||
if cl and int(cl) > MAX_UPLOAD_BYTES:
|
if cl and int(cl)>MAX_UPLOAD_BYTES*20: raise HTTPException(413,"파일이 너무 큽니다")
|
||||||
raise HTTPException(413, f"파일이 너무 큽니다. 최대 {MAX_UPLOAD_BYTES//1024//1024}MB")
|
|
||||||
|
|
||||||
def _cleanup_outputs():
|
def _cleanup_outputs():
|
||||||
if OUTPUT_KEEP_SECS == 0: return 0
|
if OUTPUT_KEEP_SECS==0: return 0
|
||||||
cutoff = time.time() - OUTPUT_KEEP_SECS; removed = 0
|
cutoff=time.time()-OUTPUT_KEEP_SECS;removed=0
|
||||||
for f in glob.glob(os.path.join(OUTPUT_DIR,"*")):
|
for f in glob.glob(os.path.join(OUTPUT_DIR,"*")):
|
||||||
try:
|
try:
|
||||||
if os.path.getmtime(f) < cutoff: os.remove(f); removed += 1
|
if os.path.getmtime(f)<cutoff: os.remove(f);removed+=1
|
||||||
except: pass
|
except: pass
|
||||||
return removed
|
return removed
|
||||||
|
|
||||||
def _ext(fn): return fn.rsplit(".",1)[-1].lower() if "." in fn else ""
|
def _ext(fn): return fn.rsplit(".",1)[-1].lower() if "." in fn else ""
|
||||||
|
|
||||||
async def _save(file, path):
|
async def _save_upload(file:UploadFile,path:str):
|
||||||
written = 0
|
written=0
|
||||||
async with aiofiles.open(path,"wb") as f:
|
async with aiofiles.open(path,"wb") as f:
|
||||||
while chunk := await file.read(1024*1024):
|
while chunk:=await file.read(1024*1024):
|
||||||
written += len(chunk)
|
written+=len(chunk)
|
||||||
if written > MAX_UPLOAD_BYTES:
|
if written>MAX_UPLOAD_BYTES:
|
||||||
await f.close(); os.remove(path)
|
await f.close();os.remove(path)
|
||||||
raise HTTPException(413, f"파일이 너무 큽니다. 최대 {MAX_UPLOAD_BYTES//1024//1024}MB")
|
raise HTTPException(413,f"파일이 너무 큽니다. 최대 {MAX_UPLOAD_BYTES//1024//1024}MB")
|
||||||
await f.write(chunk)
|
await f.write(chunk)
|
||||||
|
|
||||||
app.mount("/", StaticFiles(directory="static", html=True), name="static")
|
app.mount("/", StaticFiles(directory="static", html=True), name="static")
|
||||||
|
|||||||
419
app/ocr_tasks.py
419
app/ocr_tasks.py
@@ -1,8 +1,12 @@
|
|||||||
"""
|
"""
|
||||||
OCR Celery Tasks
|
OCR Celery Tasks — PaddleOCR 3.x + Ollama Vision + OpenRouter Vision
|
||||||
backend: paddle | ollama | openrouter
|
|
||||||
|
backend:
|
||||||
|
paddle → PaddleOCR 3.x 로컬 (PPStructure 제거됨, 표는 마크다운 파싱)
|
||||||
|
ollama → Ollama Vision API
|
||||||
|
openrouter → OpenRouter Vision API (OpenAI 호환)
|
||||||
"""
|
"""
|
||||||
import os, base64
|
import os, base64, json
|
||||||
import httpx
|
import httpx
|
||||||
from celery import Celery
|
from celery import Celery
|
||||||
import openpyxl
|
import openpyxl
|
||||||
@@ -16,12 +20,15 @@ OLLAMA_TIMEOUT = int(os.getenv("OLLAMA_TIMEOUT", "600"))
|
|||||||
|
|
||||||
celery_app = Celery("ocr_tasks", broker=REDIS_URL, backend=REDIS_URL)
|
celery_app = Celery("ocr_tasks", broker=REDIS_URL, backend=REDIS_URL)
|
||||||
celery_app.conf.update(
|
celery_app.conf.update(
|
||||||
task_serializer="json", result_serializer="json",
|
task_serializer="json",
|
||||||
accept_content=["json"], task_track_started=True, result_expires=3600,
|
result_serializer="json",
|
||||||
|
accept_content=["json"],
|
||||||
|
task_track_started=True,
|
||||||
|
result_expires=3600,
|
||||||
)
|
)
|
||||||
|
|
||||||
|
# PaddleOCR 싱글톤
|
||||||
_ocr_engine = None
|
_ocr_engine = None
|
||||||
_struct_engine = None
|
|
||||||
|
|
||||||
def get_ocr():
|
def get_ocr():
|
||||||
global _ocr_engine
|
global _ocr_engine
|
||||||
@@ -32,18 +39,13 @@ def get_ocr():
|
|||||||
print("[PaddleOCR] 완료")
|
print("[PaddleOCR] 완료")
|
||||||
return _ocr_engine
|
return _ocr_engine
|
||||||
|
|
||||||
def get_structure():
|
|
||||||
global _struct_engine
|
|
||||||
if _struct_engine is None:
|
|
||||||
from paddleocr import PPStructure
|
|
||||||
print("[PPStructure] 로딩")
|
|
||||||
_struct_engine = PPStructure(table=True, ocr=True, lang=OCR_LANG)
|
|
||||||
print("[PPStructure] 완료")
|
|
||||||
return _struct_engine
|
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# 메인 Task
|
# 메인 Celery Task
|
||||||
|
# 인자: file_id, image_path, mode, backend,
|
||||||
|
# ollama_model, openrouter_model,
|
||||||
|
# openrouter_url, openrouter_key,
|
||||||
|
# custom_prompt
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
@celery_app.task(bind=True, name="tasks.ocr_task", queue="ocr")
|
@celery_app.task(bind=True, name="tasks.ocr_task", queue="ocr")
|
||||||
def ocr_task(
|
def ocr_task(
|
||||||
@@ -58,18 +60,24 @@ def ocr_task(
|
|||||||
openrouter_key: str = "",
|
openrouter_key: str = "",
|
||||||
custom_prompt: str = "",
|
custom_prompt: str = "",
|
||||||
):
|
):
|
||||||
self.update_state(state="PROGRESS", meta={"progress":8,"message":"엔진 준비 중..."})
|
self.update_state(state="PROGRESS", meta={"progress": 8, "message": "엔진 준비 중..."})
|
||||||
try:
|
try:
|
||||||
if backend == "openrouter":
|
if backend == "openrouter":
|
||||||
result = _run_openrouter(self, file_id, image_path, mode,
|
result = _run_openrouter(
|
||||||
openrouter_model, openrouter_url, openrouter_key, custom_prompt)
|
self, file_id, image_path, mode,
|
||||||
|
openrouter_model, openrouter_url, openrouter_key, custom_prompt
|
||||||
|
)
|
||||||
elif backend == "ollama":
|
elif backend == "ollama":
|
||||||
result = _run_ollama(self, file_id, image_path, mode, ollama_model, custom_prompt)
|
result = _run_ollama(
|
||||||
|
self, file_id, image_path, mode, ollama_model, custom_prompt
|
||||||
|
)
|
||||||
else:
|
else:
|
||||||
result = _run_paddle(self, file_id, image_path, mode)
|
result = _run_paddle(self, file_id, image_path, mode)
|
||||||
|
|
||||||
try: os.remove(image_path)
|
try: os.remove(image_path)
|
||||||
except: pass
|
except: pass
|
||||||
return result
|
return result
|
||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
try: os.remove(image_path)
|
try: os.remove(image_path)
|
||||||
except: pass
|
except: pass
|
||||||
@@ -77,36 +85,50 @@ def ocr_task(
|
|||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# OpenRouter Vision 백엔드 (OpenAI 호환)
|
# 공통 프롬프트
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
_PROMPTS = {
|
_PROMPT_TEXT = (
|
||||||
"text": "이 이미지에서 모든 텍스트를 정확하게 추출해줘. 원본의 줄 구분과 단락 구조를 유지해줘.",
|
"이 이미지에서 모든 텍스트를 정확하게 추출해줘. "
|
||||||
"structure": "이 이미지를 분석해서 표는 마크다운 표 형식으로, 나머지 텍스트는 원본 구조를 유지하며 추출해줘.",
|
"원본의 줄 구분과 단락 구조를 최대한 유지해줘. "
|
||||||
}
|
"이미지에 없는 내용은 절대 추가하지 마."
|
||||||
|
)
|
||||||
|
_PROMPT_STRUCTURE = (
|
||||||
|
"이 이미지를 분석해서 다음을 수행해줘:\n"
|
||||||
|
"1. 표(table)가 있으면 반드시 마크다운 표 형식(| col | col |)으로 변환\n"
|
||||||
|
"2. 나머지 텍스트는 원본 구조를 유지하며 추출\n"
|
||||||
|
"3. 표와 텍스트를 구분해서 순서대로 출력\n"
|
||||||
|
"이미지에 없는 내용은 추가하지 마."
|
||||||
|
)
|
||||||
|
|
||||||
|
def _get_prompt(mode, custom_prompt):
|
||||||
|
if custom_prompt and custom_prompt.strip():
|
||||||
|
return custom_prompt.strip()
|
||||||
|
return _PROMPT_STRUCTURE if mode == "structure" else _PROMPT_TEXT
|
||||||
|
|
||||||
|
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
|
# OpenRouter Vision 백엔드
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
def _run_openrouter(task, file_id, image_path, mode,
|
def _run_openrouter(task, file_id, image_path, mode,
|
||||||
model, base_url, api_key, custom_prompt):
|
model, base_url, api_key, custom_prompt):
|
||||||
if not api_key:
|
if not api_key:
|
||||||
raise Exception("OpenRouter API 키가 설정되지 않았습니다")
|
raise Exception("OpenRouter API 키가 설정되지 않았습니다. 설정 → OpenRouter에서 저장하세요.")
|
||||||
if not model:
|
if not model:
|
||||||
raise Exception("OpenRouter 모델이 선택되지 않았습니다")
|
raise Exception("OpenRouter 모델이 선택되지 않았습니다.")
|
||||||
|
|
||||||
task.update_state(state="PROGRESS",
|
task.update_state(state="PROGRESS",
|
||||||
meta={"progress":15,"message":f"OpenRouter ({model}) 연결 중..."})
|
meta={"progress": 15, "message": f"OpenRouter ({model}) 연결 중..."})
|
||||||
|
|
||||||
|
# 이미지 → base64 data URL
|
||||||
with open(image_path, "rb") as f:
|
with open(image_path, "rb") as f:
|
||||||
raw = f.read()
|
raw = f.read()
|
||||||
|
|
||||||
# 이미지 MIME 타입 감지
|
|
||||||
ext = image_path.rsplit(".", 1)[-1].lower()
|
ext = image_path.rsplit(".", 1)[-1].lower()
|
||||||
mime = {"jpg":"image/jpeg","jpeg":"image/jpeg","png":"image/png",
|
mime = {"jpg":"image/jpeg","jpeg":"image/jpeg","png":"image/png",
|
||||||
"bmp":"image/bmp","gif":"image/gif","webp":"image/webp"}.get(ext, "image/jpeg")
|
"bmp":"image/bmp","gif":"image/gif","webp":"image/webp"}.get(ext, "image/jpeg")
|
||||||
b64 = base64.b64encode(raw).decode()
|
data_url = f"data:{mime};base64,{base64.b64encode(raw).decode()}"
|
||||||
data_url = f"data:{mime};base64,{b64}"
|
|
||||||
|
|
||||||
prompt = custom_prompt.strip() or _PROMPTS.get(mode, _PROMPTS["text"])
|
prompt = _get_prompt(mode, custom_prompt)
|
||||||
|
task.update_state(state="PROGRESS", meta={"progress": 30, "message": "모델 추론 중..."})
|
||||||
task.update_state(state="PROGRESS", meta={"progress":30,"message":"모델 추론 중..."})
|
|
||||||
|
|
||||||
try:
|
try:
|
||||||
resp = httpx.post(
|
resp = httpx.post(
|
||||||
@@ -133,40 +155,31 @@ def _run_openrouter(task, file_id, image_path, mode,
|
|||||||
resp.raise_for_status()
|
resp.raise_for_status()
|
||||||
except httpx.HTTPStatusError as e:
|
except httpx.HTTPStatusError as e:
|
||||||
body = ""
|
body = ""
|
||||||
try: body = e.response.json().get("error",{}).get("message","")
|
try: body = e.response.json().get("error", {}).get("message", "")
|
||||||
except: pass
|
except: pass
|
||||||
if e.response.status_code == 400:
|
if e.response.status_code == 400:
|
||||||
raise Exception(f"이 모델은 이미지를 지원하지 않습니다 — Vision 모델을 선택하세요\n({model})")
|
raise Exception(
|
||||||
|
f"이 모델은 이미지를 지원하지 않습니다.\n"
|
||||||
|
f"Vision 기능을 지원하는 모델을 선택하세요 (Claude-3, GPT-4o, Gemini 등)\n"
|
||||||
|
f"모델: {model}"
|
||||||
|
)
|
||||||
raise Exception(f"OpenRouter 오류 ({e.response.status_code}): {body or str(e)}")
|
raise Exception(f"OpenRouter 오류 ({e.response.status_code}): {body or str(e)}")
|
||||||
except httpx.TimeoutException:
|
except httpx.TimeoutException:
|
||||||
raise Exception(f"OpenRouter 응답 시간 초과. OLLAMA_TIMEOUT 값을 늘려주세요.")
|
raise Exception(f"OpenRouter 응답 시간 초과 ({OLLAMA_TIMEOUT}초). OLLAMA_TIMEOUT 값을 늘려주세요.")
|
||||||
|
|
||||||
task.update_state(state="PROGRESS", meta={"progress":85,"message":"결과 저장 중..."})
|
task.update_state(state="PROGRESS", meta={"progress": 85, "message": "결과 저장 중..."})
|
||||||
|
|
||||||
full_text = resp.json()["choices"][0]["message"]["content"].strip()
|
choices = resp.json().get("choices", [])
|
||||||
|
if not choices:
|
||||||
|
raise Exception("OpenRouter 빈 응답")
|
||||||
|
full_text = choices[0]["message"]["content"].strip()
|
||||||
if not full_text:
|
if not full_text:
|
||||||
raise Exception("OpenRouter 빈 응답")
|
raise Exception("OpenRouter 빈 응답")
|
||||||
|
|
||||||
tables = _parse_md_tables(full_text) if mode == "structure" else []
|
return _build_result(
|
||||||
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
task, file_id, full_text, mode,
|
||||||
txt_file = f"{file_id}_ocr.txt"
|
backend="openrouter", ollama_model="", openrouter_model=model
|
||||||
with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
|
)
|
||||||
f.write(f"# OCR 결과 (OpenRouter / {model})\n\n{full_text}")
|
|
||||||
xlsx_file = None
|
|
||||||
if tables:
|
|
||||||
xlsx_file = f"{file_id}_tables.xlsx"
|
|
||||||
_save_excel(tables, os.path.join(OUTPUT_DIR, xlsx_file))
|
|
||||||
tables_html = [_md_table_to_html(t) for t in tables]
|
|
||||||
lines = [{"text":l,"confidence":1.0,"bbox":[]} for l in full_text.splitlines() if l.strip()]
|
|
||||||
return {
|
|
||||||
"mode": mode, "backend": "openrouter", "openrouter_model": model,
|
|
||||||
"ollama_model": "",
|
|
||||||
"full_text": full_text, "lines": lines, "line_count": len(lines),
|
|
||||||
"txt_file": txt_file,
|
|
||||||
"tables": [{"html":h,"rows":len(t),"cols":max(len(r) for r in t) if t else 0}
|
|
||||||
for h, t in zip(tables_html, tables)],
|
|
||||||
"xlsx_file": xlsx_file,
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
@@ -174,166 +187,226 @@ def _run_openrouter(task, file_id, image_path, mode,
|
|||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
def _run_ollama(task, file_id, image_path, mode, ollama_model, custom_prompt):
|
def _run_ollama(task, file_id, image_path, mode, ollama_model, custom_prompt):
|
||||||
task.update_state(state="PROGRESS",
|
task.update_state(state="PROGRESS",
|
||||||
meta={"progress":15,"message":f"Ollama ({ollama_model}) 연결 중..."})
|
meta={"progress": 15, "message": f"Ollama ({ollama_model}) 연결 중..."})
|
||||||
|
|
||||||
with open(image_path, "rb") as f:
|
with open(image_path, "rb") as f:
|
||||||
img_b64 = base64.b64encode(f.read()).decode()
|
img_b64 = base64.b64encode(f.read()).decode()
|
||||||
prompt = custom_prompt.strip() or _PROMPTS.get(mode, _PROMPTS["text"])
|
|
||||||
task.update_state(state="PROGRESS", meta={"progress":30,"message":"모델 추론 중..."})
|
prompt = _get_prompt(mode, custom_prompt)
|
||||||
|
task.update_state(state="PROGRESS", meta={"progress": 30, "message": "모델 추론 중..."})
|
||||||
|
|
||||||
try:
|
try:
|
||||||
resp = httpx.post(f"{OLLAMA_URL}/api/chat", json={
|
resp = httpx.post(
|
||||||
|
f"{OLLAMA_URL}/api/chat",
|
||||||
|
json={
|
||||||
"model": ollama_model,
|
"model": ollama_model,
|
||||||
"messages": [{"role":"user","content":prompt,"images":[img_b64]}],
|
"messages": [{"role": "user", "content": prompt, "images": [img_b64]}],
|
||||||
"stream": False, "options": {"temperature":0.1},
|
"stream": False,
|
||||||
}, timeout=float(OLLAMA_TIMEOUT))
|
"options": {"temperature": 0.1},
|
||||||
|
},
|
||||||
|
timeout=float(OLLAMA_TIMEOUT),
|
||||||
|
)
|
||||||
resp.raise_for_status()
|
resp.raise_for_status()
|
||||||
except httpx.ConnectError:
|
except httpx.ConnectError:
|
||||||
raise Exception(f"Ollama 서버 연결 실패 ({OLLAMA_URL})")
|
raise Exception(f"Ollama 서버 연결 실패 ({OLLAMA_URL})")
|
||||||
except httpx.TimeoutException:
|
except httpx.TimeoutException:
|
||||||
raise Exception(f"Ollama 응답 시간 초과 ({OLLAMA_TIMEOUT}초)")
|
raise Exception(f"Ollama 응답 시간 초과 ({OLLAMA_TIMEOUT}초). 설정에서 타임아웃을 늘려주세요.")
|
||||||
|
|
||||||
task.update_state(state="PROGRESS", meta={"progress":85,"message":"결과 저장 중..."})
|
task.update_state(state="PROGRESS", meta={"progress": 85, "message": "결과 저장 중..."})
|
||||||
full_text = resp.json().get("message",{}).get("content","").strip()
|
|
||||||
if not full_text: raise Exception("Ollama 빈 응답. 모델이 Vision을 지원하는지 확인하세요.")
|
|
||||||
|
|
||||||
tables = _parse_md_tables(full_text) if mode == "structure" else []
|
full_text = resp.json().get("message", {}).get("content", "").strip()
|
||||||
|
if not full_text:
|
||||||
|
raise Exception(
|
||||||
|
f"Ollama 빈 응답.\n"
|
||||||
|
f"이 모델이 Vision(이미지)을 지원하는지 확인하세요: {ollama_model}\n"
|
||||||
|
f"Vision 지원 모델: granite3.2-vision, llava 등"
|
||||||
|
)
|
||||||
|
|
||||||
|
return _build_result(
|
||||||
|
task, file_id, full_text, mode,
|
||||||
|
backend="ollama", ollama_model=ollama_model, openrouter_model=""
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
|
# PaddleOCR 백엔드 (3.x — PPStructure 미사용)
|
||||||
|
# ════════════════════════════════════════════════════════════════
|
||||||
|
def _run_paddle(task, file_id, image_path, mode):
|
||||||
|
import cv2
|
||||||
|
img = cv2.imread(image_path)
|
||||||
|
if img is None:
|
||||||
|
raise ValueError("이미지를 읽을 수 없습니다. 지원 형식: jpg, png, bmp, tiff, webp")
|
||||||
|
|
||||||
|
task.update_state(state="PROGRESS", meta={"progress": 30, "message": "텍스트 인식 중..."})
|
||||||
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
||||||
txt_file = f"{file_id}_ocr.txt"
|
|
||||||
with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
|
result = get_ocr().ocr(img)
|
||||||
f.write(f"# OCR 결과 (Ollama / {ollama_model})\n\n{full_text}")
|
task.update_state(state="PROGRESS", meta={"progress": 80, "message": "결과 정리 중..."})
|
||||||
|
|
||||||
|
lines = []
|
||||||
|
if result and len(result) > 0:
|
||||||
|
r = result[0]
|
||||||
|
if isinstance(r, dict):
|
||||||
|
# PaddleOCR 3.x 딕셔너리 형태
|
||||||
|
texts = r.get("rec_texts", [])
|
||||||
|
scores = r.get("rec_scores", [])
|
||||||
|
polys = r.get("rec_polys", [None] * len(texts))
|
||||||
|
for text, conf, poly in zip(texts, scores, polys):
|
||||||
|
if text.strip():
|
||||||
|
lines.append({
|
||||||
|
"text": text,
|
||||||
|
"confidence": round(float(conf), 3),
|
||||||
|
"bbox": poly.tolist() if poly is not None and hasattr(poly, 'tolist') else [],
|
||||||
|
})
|
||||||
|
elif isinstance(r, list):
|
||||||
|
# 구버전 호환 [[bbox, (text, conf)], ...]
|
||||||
|
for item in r:
|
||||||
|
if item and len(item) == 2:
|
||||||
|
bbox, (text, conf) = item
|
||||||
|
if text.strip():
|
||||||
|
lines.append({"text": text, "confidence": round(float(conf), 3), "bbox": []})
|
||||||
|
|
||||||
|
full_text = "\n".join(l["text"] for l in lines)
|
||||||
|
|
||||||
|
# structure 모드: 텍스트에서 마크다운 표 파싱 시도
|
||||||
|
tables = []
|
||||||
xlsx_file = None
|
xlsx_file = None
|
||||||
|
if mode == "structure":
|
||||||
|
tables = _parse_md_tables(full_text)
|
||||||
if tables:
|
if tables:
|
||||||
xlsx_file = f"{file_id}_tables.xlsx"
|
xlsx_file = f"{file_id}_tables.xlsx"
|
||||||
_save_excel(tables, os.path.join(OUTPUT_DIR, xlsx_file))
|
_save_excel(tables, os.path.join(OUTPUT_DIR, xlsx_file))
|
||||||
|
|
||||||
|
txt_file = f"{file_id}_ocr.txt"
|
||||||
|
with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
|
||||||
|
f.write(full_text)
|
||||||
|
|
||||||
tables_html = [_md_table_to_html(t) for t in tables]
|
tables_html = [_md_table_to_html(t) for t in tables]
|
||||||
lines = [{"text":l,"confidence":1.0,"bbox":[]} for l in full_text.splitlines() if l.strip()]
|
tables_meta = [{"html": h, "rows": len(t), "cols": max(len(r) for r in t) if t else 0}
|
||||||
|
for h, t in zip(tables_html, tables)]
|
||||||
|
|
||||||
return {
|
return {
|
||||||
"mode": mode, "backend": "ollama", "ollama_model": ollama_model,
|
"mode": mode,
|
||||||
|
"backend": "paddle",
|
||||||
|
"ollama_model": "",
|
||||||
"openrouter_model": "",
|
"openrouter_model": "",
|
||||||
"full_text": full_text, "lines": lines, "line_count": len(lines),
|
"full_text": full_text,
|
||||||
|
"lines": lines,
|
||||||
|
"line_count": len(lines),
|
||||||
"txt_file": txt_file,
|
"txt_file": txt_file,
|
||||||
"tables": [{"html":h,"rows":len(t),"cols":max(len(r) for r in t) if t else 0}
|
"tables": tables_meta,
|
||||||
for h, t in zip(tables_html, tables)],
|
|
||||||
"xlsx_file": xlsx_file,
|
"xlsx_file": xlsx_file,
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# PaddleOCR 백엔드
|
# 공통 결과 빌더 (Ollama / OpenRouter 공용)
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
def _run_paddle(task, file_id, image_path, mode):
|
def _build_result(task, file_id, full_text, mode,
|
||||||
import cv2
|
backend, ollama_model, openrouter_model):
|
||||||
img = cv2.imread(image_path)
|
"""마크다운 표 파싱 → Excel 생성 → 결과 딕셔너리 반환"""
|
||||||
if img is None: raise ValueError("이미지를 읽을 수 없습니다")
|
|
||||||
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
||||||
return _paddle_structure(task, file_id, img) if mode == "structure" else _paddle_text(task, file_id, img)
|
|
||||||
|
|
||||||
def _paddle_text(task, file_id, img):
|
tables = _parse_md_tables(full_text) if mode == "structure" else []
|
||||||
task.update_state(state="PROGRESS", meta={"progress":30,"message":"텍스트 인식 중..."})
|
|
||||||
result = get_ocr().ocr(img)
|
|
||||||
task.update_state(state="PROGRESS", meta={"progress":80,"message":"결과 정리 중..."})
|
|
||||||
lines = []
|
|
||||||
if result and len(result) > 0:
|
|
||||||
r = result[0]
|
|
||||||
if isinstance(r, dict):
|
|
||||||
for text, conf in zip(r.get("rec_texts",[]), r.get("rec_scores",[])):
|
|
||||||
if text.strip(): lines.append({"text":text,"confidence":round(float(conf),3),"bbox":[]})
|
|
||||||
elif isinstance(r, list):
|
|
||||||
for item in r:
|
|
||||||
if item and len(item)==2:
|
|
||||||
_, (text, conf) = item
|
|
||||||
if text.strip(): lines.append({"text":text,"confidence":round(float(conf),3),"bbox":[]})
|
|
||||||
full_text = "\n".join(l["text"] for l in lines)
|
|
||||||
txt_file = f"{file_id}_ocr.txt"
|
|
||||||
with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f: f.write(full_text)
|
|
||||||
return {"mode":"text","backend":"paddle","ollama_model":"","openrouter_model":"",
|
|
||||||
"full_text":full_text,"lines":lines,"line_count":len(lines),
|
|
||||||
"txt_file":txt_file,"tables":[],"xlsx_file":None}
|
|
||||||
|
|
||||||
def _paddle_structure(task, file_id, img):
|
|
||||||
task.update_state(state="PROGRESS", meta={"progress":20,"message":"레이아웃 분석 중..."})
|
|
||||||
result = get_structure()(img)
|
|
||||||
task.update_state(state="PROGRESS", meta={"progress":60,"message":"표 구조 추출 중..."})
|
|
||||||
text_blocks, tables_html, tables_data = [], [], []
|
|
||||||
for region in result:
|
|
||||||
rtype = region.get("type","").lower()
|
|
||||||
if rtype == "table":
|
|
||||||
html = region.get("res",{}).get("html","")
|
|
||||||
if html: tables_html.append(html); tables_data.append(_html_table_to_list(html))
|
|
||||||
elif rtype in ("text","title","figure_caption"):
|
|
||||||
for line in (region.get("res",[]) or []):
|
|
||||||
if isinstance(line,(list,tuple)) and len(line)==2:
|
|
||||||
_, (text, _conf) = line; text_blocks.append(text)
|
|
||||||
full_text = "\n".join(text_blocks)
|
|
||||||
task.update_state(state="PROGRESS", meta={"progress":80,"message":"Excel 생성 중..."})
|
|
||||||
xlsx_file = None
|
|
||||||
if tables_data:
|
|
||||||
xlsx_file = f"{file_id}_tables.xlsx"
|
|
||||||
_save_excel(tables_data, os.path.join(OUTPUT_DIR, xlsx_file))
|
|
||||||
txt_file = f"{file_id}_ocr.txt"
|
txt_file = f"{file_id}_ocr.txt"
|
||||||
|
label = ollama_model if backend == "ollama" else openrouter_model
|
||||||
with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
|
with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
|
||||||
f.write("# 텍스트\n\n" + full_text)
|
f.write(f"# OCR 결과 ({backend} / {label})\n\n{full_text}")
|
||||||
lines = [{"text":t,"confidence":1.0,"bbox":[]} for t in text_blocks]
|
|
||||||
tables_meta = [{"html":h,"rows":len(d),"cols":max(len(r) for r in d) if d else 0}
|
xlsx_file = None
|
||||||
for h, d in zip(tables_html, tables_data)]
|
if tables:
|
||||||
return {"mode":"structure","backend":"paddle","ollama_model":"","openrouter_model":"",
|
task.update_state(state="PROGRESS", meta={"progress": 92, "message": "Excel 생성 중..."})
|
||||||
"full_text":full_text,"lines":lines,"line_count":len(lines),
|
xlsx_file = f"{file_id}_tables.xlsx"
|
||||||
"txt_file":txt_file,"tables":tables_meta,"xlsx_file":xlsx_file}
|
_save_excel(tables, os.path.join(OUTPUT_DIR, xlsx_file))
|
||||||
|
|
||||||
|
tables_html = [_md_table_to_html(t) for t in tables]
|
||||||
|
tables_meta = [{"html": h, "rows": len(t), "cols": max(len(r) for r in t) if t else 0}
|
||||||
|
for h, t in zip(tables_html, tables)]
|
||||||
|
|
||||||
|
lines = [{"text": l, "confidence": 1.0, "bbox": []}
|
||||||
|
for l in full_text.splitlines() if l.strip()]
|
||||||
|
|
||||||
|
return {
|
||||||
|
"mode": mode,
|
||||||
|
"backend": backend,
|
||||||
|
"ollama_model": ollama_model,
|
||||||
|
"openrouter_model": openrouter_model,
|
||||||
|
"full_text": full_text,
|
||||||
|
"lines": lines,
|
||||||
|
"line_count": len(lines),
|
||||||
|
"txt_file": txt_file,
|
||||||
|
"tables": tables_meta,
|
||||||
|
"xlsx_file": xlsx_file,
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
# 공통 유틸
|
# 마크다운 표 파싱
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ════════════════════════════════════════════════════════════════
|
||||||
def _parse_md_tables(text):
|
def _parse_md_tables(text: str) -> list:
|
||||||
|
"""텍스트에서 마크다운 표 추출 → [[row, row, ...], ...]"""
|
||||||
tables, current = [], []
|
tables, current = [], []
|
||||||
for line in text.splitlines():
|
for line in text.splitlines():
|
||||||
s = line.strip()
|
s = line.strip()
|
||||||
if s.startswith("|") and s.endswith("|"):
|
if s.startswith("|") and s.endswith("|"):
|
||||||
if all(c in "| -:" for c in s): continue
|
# 구분선 (|---|---) 건너뜀
|
||||||
current.append([c.strip() for c in s.strip("|").split("|")])
|
if all(c in "| -:" for c in s):
|
||||||
|
continue
|
||||||
|
cells = [c.strip() for c in s.strip("|").split("|")]
|
||||||
|
current.append(cells)
|
||||||
else:
|
else:
|
||||||
if len(current) >= 2: tables.append(current)
|
if len(current) >= 2:
|
||||||
|
tables.append(current)
|
||||||
current = []
|
current = []
|
||||||
if len(current) >= 2: tables.append(current)
|
if len(current) >= 2:
|
||||||
|
tables.append(current)
|
||||||
return tables
|
return tables
|
||||||
|
|
||||||
def _md_table_to_html(table):
|
|
||||||
|
def _md_table_to_html(table: list) -> str:
|
||||||
if not table: return ""
|
if not table: return ""
|
||||||
rows = ""
|
rows = ""
|
||||||
for i, row in enumerate(table):
|
for i, row in enumerate(table):
|
||||||
tag = "th" if i==0 else "td"
|
tag = "th" if i == 0 else "td"
|
||||||
rows += "<tr>"+"".join(f"<{tag}>{c}</{tag}>" for c in row)+"</tr>"
|
rows += "<tr>" + "".join(f"<{tag}>{c}</{tag}>" for c in row) + "</tr>"
|
||||||
return f"<table>{rows}</table>"
|
return f"<table>{rows}</table>"
|
||||||
|
|
||||||
def _html_table_to_list(html):
|
|
||||||
from html.parser import HTMLParser
|
|
||||||
class P(HTMLParser):
|
|
||||||
def __init__(self):
|
|
||||||
super().__init__()
|
|
||||||
self.rows,self._row,self._cell,self._in=[],[],[],False
|
|
||||||
def handle_starttag(self,tag,attrs):
|
|
||||||
if tag=="tr": self._row=[]
|
|
||||||
elif tag in("td","th"): self._cell=[];self._in=True
|
|
||||||
def handle_endtag(self,tag):
|
|
||||||
if tag in("td","th"): self._row.append("".join(self._cell).strip());self._in=False
|
|
||||||
elif tag=="tr":
|
|
||||||
if self._row: self.rows.append(self._row)
|
|
||||||
def handle_data(self,data):
|
|
||||||
if self._in: self._cell.append(data)
|
|
||||||
p=P();p.feed(html);return p.rows
|
|
||||||
|
|
||||||
def _save_excel(tables, path):
|
# ════════════════════════════════════════════════════════════════
|
||||||
wb=openpyxl.Workbook();wb.remove(wb.active)
|
# Excel 저장
|
||||||
for i,table in enumerate(tables,1):
|
# ════════════════════════════════════════════════════════════════
|
||||||
ws=wb.create_sheet(f"표 {i}")
|
def _save_excel(tables: list, path: str):
|
||||||
thin=Side(style="thin",color="2A2A33");bdr=Border(left=thin,right=thin,top=thin,bottom=thin)
|
wb = openpyxl.Workbook()
|
||||||
for r_idx,row in enumerate(table,1):
|
wb.remove(wb.active)
|
||||||
for c_idx,val in enumerate(row,1):
|
|
||||||
cell=ws.cell(row=r_idx,column=c_idx,value=val)
|
hfill = PatternFill("solid", fgColor="1A1A2E")
|
||||||
cell.border=bdr;cell.alignment=Alignment(horizontal="center",vertical="center",wrap_text=True)
|
hfont = Font(color="00E5A0", bold=True, size=10)
|
||||||
if r_idx==1: cell.fill=PatternFill("solid",fgColor="1A1A2E");cell.font=Font(color="00E5A0",bold=True,size=10)
|
cfont = Font(size=10)
|
||||||
else: cell.font=Font(size=10)
|
center = Alignment(horizontal="center", vertical="center", wrap_text=True)
|
||||||
|
thin = Side(style="thin", color="2A2A33")
|
||||||
|
bdr = Border(left=thin, right=thin, top=thin, bottom=thin)
|
||||||
|
|
||||||
|
for i, table in enumerate(tables, 1):
|
||||||
|
ws = wb.create_sheet(f"표 {i}")
|
||||||
|
if not table:
|
||||||
|
continue
|
||||||
|
for r_idx, row in enumerate(table, 1):
|
||||||
|
for c_idx, val in enumerate(row, 1):
|
||||||
|
cell = ws.cell(row=r_idx, column=c_idx, value=val)
|
||||||
|
cell.border = bdr
|
||||||
|
cell.alignment = center
|
||||||
|
if r_idx == 1:
|
||||||
|
cell.fill = hfill
|
||||||
|
cell.font = hfont
|
||||||
|
else:
|
||||||
|
cell.font = cfont
|
||||||
|
if r_idx % 2 == 0:
|
||||||
|
cell.fill = PatternFill("solid", fgColor="0F0F14")
|
||||||
for col in ws.columns:
|
for col in ws.columns:
|
||||||
w=max((len(str(c.value or "")) for c in col),default=8)
|
w = max((len(str(c.value or "")) for c in col), default=8)
|
||||||
ws.column_dimensions[col[0].column_letter].width=min(w+4,40)
|
ws.column_dimensions[col[0].column_letter].width = min(w + 4, 40)
|
||||||
if not wb.sheetnames: wb.create_sheet("Sheet1")
|
|
||||||
|
if not wb.sheetnames:
|
||||||
|
wb.create_sheet("Sheet1")
|
||||||
wb.save(path)
|
wb.save(path)
|
||||||
|
|||||||
@@ -251,17 +251,29 @@ textarea.cprompt{width:100%;background:var(--surf);border:1px solid var(--border
|
|||||||
.ollama-status{font-family:var(--mono);font-size:.63rem;padding:4px 9px;border-radius:2px}
|
.ollama-status{font-family:var(--mono);font-size:.63rem;padding:4px 9px;border-radius:2px}
|
||||||
.ollama-status.ok{background:rgba(0,229,160,.1);color:var(--accent);border:1px solid rgba(0,229,160,.2)}
|
.ollama-status.ok{background:rgba(0,229,160,.1);color:var(--accent);border:1px solid rgba(0,229,160,.2)}
|
||||||
.ollama-status.fail{background:rgba(255,107,53,.1);color:var(--warn);border:1px solid rgba(255,107,53,.2)}
|
.ollama-status.fail{background:rgba(255,107,53,.1);color:var(--warn);border:1px solid rgba(255,107,53,.2)}
|
||||||
.openrouter-status.ok{background:rgba(77,166,255,.1);color:var(--blue);border:1px solid rgba(77,166,255,.2)}
|
/* ── 자막 모드 ── */
|
||||||
.openrouter-status.fail{background:rgba(255,107,53,.1);color:var(--warn);border:1px solid rgba(255,107,53,.2)}
|
.sub-section{margin-top:12px;padding:12px;background:var(--surf2);border:1px solid #1c2840;border-radius:4px}
|
||||||
.or-section{margin-top:10px;padding:12px;background:var(--surf2);border:1px solid #1c2840;border-radius:4px}
|
.sub-section-title{font-family:var(--mono);font-size:.6rem;letter-spacing:.1em;color:var(--blue);text-transform:uppercase;margin-bottom:10px;display:flex;align-items:center;gap:6px}
|
||||||
.key-input-wrap{display:flex;gap:6px;margin-top:6px}
|
.lang-select{width:100%;background:var(--surf);border:1px solid var(--border2);color:var(--text);padding:9px 10px;border-radius:3px;font-family:var(--mono);font-size:.78rem;outline:none;cursor:pointer;appearance:none;-webkit-appearance:none;background-image:url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='10' height='6'%3E%3Cpath d='M0 0l5 6 5-6z' fill='%2352526a'/%3E%3C/svg%3E");background-repeat:no-repeat;background-position:right 10px center;margin-top:4px}
|
||||||
.key-input-wrap input{flex:1;background:var(--surf);border:1px solid var(--border2);color:var(--text);padding:9px 10px;border-radius:3px;font-family:var(--mono);font-size:.78rem;outline:none;-webkit-appearance:none}
|
.lang-select:focus{border-color:var(--blue)}
|
||||||
.key-input-wrap input:focus{border-color:var(--blue)}
|
.fmt-btns{display:grid;grid-template-columns:1fr 1fr 1fr;gap:6px;margin-top:6px}
|
||||||
.btn-test{padding:9px 14px;background:none;border:1px solid #3a7cc4;color:var(--blue);border-radius:3px;font-family:var(--mono);font-size:.68rem;cursor:pointer;white-space:nowrap;transition:all .15s}
|
.fmt-btn{padding:7px;background:var(--surf);border:1px solid var(--border2);color:var(--muted);border-radius:3px;font-family:var(--mono);font-size:.68rem;cursor:pointer;transition:all .15s;text-align:center;text-transform:uppercase}
|
||||||
.btn-test:hover{background:rgba(77,166,255,.08)}
|
.fmt-btn.active{background:rgba(77,166,255,.08);border-color:#3a7cc4;color:var(--blue)}
|
||||||
.or-model-tabs{display:flex;gap:5px;margin-top:8px;flex-wrap:wrap}
|
.sub-dl-btn{flex:1;padding:8px;background:rgba(77,166,255,.07);border:1px solid #3a7cc4;color:var(--blue);border-radius:3px;font-family:var(--mono);font-size:.66rem;cursor:pointer;transition:all .15s;text-transform:uppercase}
|
||||||
.or-model-tab{font-family:var(--mono);font-size:.6rem;padding:4px 10px;border:1px solid var(--border2);background:none;color:var(--muted);border-radius:2px;cursor:pointer;transition:all .12s;text-transform:uppercase}
|
.sub-dl-btn:hover{background:rgba(77,166,255,.15)}
|
||||||
.or-model-tab.active{border-color:var(--blue);color:var(--blue);background:rgba(77,166,255,.07)}
|
/* ── 배치 큐 ── */
|
||||||
|
.batch-queue{margin-top:14px;display:flex;flex-direction:column;gap:6px;max-height:280px;overflow-y:auto}
|
||||||
|
.batch-item{display:grid;grid-template-columns:1fr auto auto;align-items:center;gap:8px;padding:9px 12px;background:var(--surf);border:1px solid var(--border2);border-radius:4px;transition:border-color .2s}
|
||||||
|
.batch-item.running{border-color:var(--accent2)}.batch-item.done{border-color:rgba(0,229,160,.3)}.batch-item.failed{border-color:rgba(255,107,53,.3)}.batch-item.waiting{opacity:.6}
|
||||||
|
.bi-name{font-family:var(--mono);font-size:.72rem;overflow:hidden;text-overflow:ellipsis;white-space:nowrap}
|
||||||
|
.bi-status{font-family:var(--mono);font-size:.6rem;padding:3px 7px;border-radius:2px;white-space:nowrap}
|
||||||
|
.bi-status.waiting{background:rgba(255,255,255,.04);color:var(--muted);border:1px solid var(--border)}.bi-status.running{background:rgba(0,229,160,.07);color:var(--accent);border:1px solid rgba(0,229,160,.2)}.bi-status.done{background:rgba(0,229,160,.07);color:var(--accent2);border:1px solid rgba(0,229,160,.2)}.bi-status.failed{background:rgba(255,107,53,.07);color:var(--warn);border:1px solid rgba(255,107,53,.2)}
|
||||||
|
.bi-dl{font-family:var(--mono);font-size:.6rem;padding:3px 8px;border:1px solid var(--border2);background:none;color:var(--text);border-radius:2px;cursor:pointer;white-space:nowrap}.bi-dl:hover{border-color:var(--accent);color:var(--accent)}
|
||||||
|
.bi-prog{height:2px;background:var(--accent);border-radius:1px;transition:width .4s;margin-top:3px}
|
||||||
|
.batch-summary{font-family:var(--mono);font-size:.68rem;color:var(--muted);margin-top:8px;display:flex;gap:12px;flex-wrap:wrap}.batch-summary span{color:var(--text)}
|
||||||
|
.batch-add-btn{margin-top:8px;padding:7px 14px;background:none;border:1px dashed var(--border2);color:var(--muted);border-radius:3px;font-family:var(--mono);font-size:.68rem;cursor:pointer;width:100%;transition:all .15s}.batch-add-btn:hover{border-color:var(--accent);color:var(--accent)}
|
||||||
|
.batch-clear-btn{padding:7px 14px;background:none;border:1px solid var(--border2);color:var(--muted);border-radius:3px;font-family:var(--mono);font-size:.68rem;cursor:pointer;transition:all .15s}.batch-clear-btn:hover{border-color:var(--warn);color:var(--warn)}
|
||||||
|
.batch-actions{display:flex;gap:8px;margin-top:10px}
|
||||||
|
|
||||||
/* ── ADMIN ── */
|
/* ── ADMIN ── */
|
||||||
#page-admin{display:none;flex-direction:column}
|
#page-admin{display:none;flex-direction:column}
|
||||||
@@ -373,26 +385,65 @@ textarea.cprompt{width:100%;background:var(--surf);border:1px solid var(--border
|
|||||||
<section class="panel">
|
<section class="panel">
|
||||||
<div class="panel-title">파일 업로드</div>
|
<div class="panel-title">파일 업로드</div>
|
||||||
<div class="dropzone" id="stt-drop">
|
<div class="dropzone" id="stt-drop">
|
||||||
<input type="file" id="stt-input" accept=".mp3,.mp4,.wav,.m4a,.ogg,.flac,.aac,.wma,.webm,.mkv,.avi,.mov">
|
<input type="file" id="stt-input" accept=".mp3,.mp4,.wav,.m4a,.ogg,.flac,.aac,.wma,.webm,.mkv,.avi,.mov,.ts,.mts,.h264,.h265" multiple>
|
||||||
<span class="drop-icon">🎵</span>
|
<span class="drop-icon">🎵</span>
|
||||||
<div class="drop-label"><strong>탭하거나 드래그하여 선택</strong><br>음성 또는 영상 파일</div>
|
<div class="drop-label"><strong>탭하거나 드래그하여 선택</strong><br>영상(mp4/mkv/h265 등) · 음성 복수 선택 가능</div>
|
||||||
<div class="drop-formats">mp3 · wav · m4a · ogg · flac · mp4 · webm</div>
|
<div class="drop-formats">mp3 · wav · m4a · ogg · flac · mp4 · webm</div>
|
||||||
</div>
|
</div>
|
||||||
<div class="file-info" id="stt-info"><div class="fname" id="stt-fname"></div><div class="fsize" id="stt-fsize"></div></div>
|
<div class="file-info" id="stt-info"><div class="fname" id="stt-fname"></div><div class="fsize" id="stt-fsize"></div></div>
|
||||||
|
<!-- 배치 큐 -->
|
||||||
|
<div id="stt-queue" style="display:none">
|
||||||
|
<div class="batch-queue" id="stt-queue-list"></div>
|
||||||
|
<div class="batch-summary" id="stt-queue-summary"></div>
|
||||||
|
<div class="batch-actions">
|
||||||
|
<button class="batch-add-btn" onclick="document.getElementById('stt-input').click()">+ 파일 더 추가</button>
|
||||||
|
<button class="batch-clear-btn" id="stt-queue-clear">큐 초기화</button>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
<div class="sec-label">STT 엔진</div>
|
<div class="sec-label">STT 엔진</div>
|
||||||
<div class="engine-btns">
|
<div class="engine-btns">
|
||||||
<button class="engine-btn active" data-engine="whisper"><span class="e-icon">⚡</span><span class="e-name">faster-whisper</span><span class="e-desc">로컬 CPU 변환<br>빠르고 안정적</span></button>
|
<button class="engine-btn active" data-engine="whisper"><span class="e-icon">⚡</span><span class="e-name">faster-whisper</span><span class="e-desc">로컬 CPU 변환<br>빠르고 안정적</span></button>
|
||||||
<button class="engine-btn" data-engine="whisper+ollama"><span class="e-icon">🦙</span><span class="e-name">+ Ollama 교정</span><span class="e-desc">Whisper 후<br>Ollama 교정</span></button>
|
<button class="engine-btn" data-engine="whisper+ollama"><span class="e-icon">🦙</span><span class="e-name">+ Ollama 교정</span><span class="e-desc">Whisper 후<br>Ollama 교정</span></button>
|
||||||
<button class="engine-btn" data-engine="whisper+openrouter" style="grid-column:1/-1"><span class="e-icon">🌐</span><span class="e-name">+ OpenRouter 교정</span><span class="e-desc">외부 AI 모델로 문장 부호·맞춤법 교정 (텍스트 전용 모델도 사용 가능)</span></button>
|
|
||||||
</div>
|
</div>
|
||||||
<div class="ollama-opts" id="stt-ollama-opts">
|
<div class="ollama-opts" id="stt-ollama-opts">
|
||||||
<div class="sec-label" style="margin-top:0">후처리 모델</div>
|
<div class="sec-label" style="margin-top:0">후처리 모델</div>
|
||||||
<select class="model-select" id="stt-ollama-model"><option value="">설정 기본 모델 사용</option></select>
|
<select class="model-select" id="stt-ollama-model"><option value="">설정 기본 모델 사용</option></select>
|
||||||
</div>
|
</div>
|
||||||
<div class="ollama-opts" id="stt-or-opts">
|
|
||||||
<div class="sec-label" style="margin-top:0">OpenRouter 후처리 모델</div>
|
<!-- 자막 모드 옵션 -->
|
||||||
<select class="model-select" id="stt-or-model"><option value="">설정 기본 모델 사용</option></select>
|
<div class="sub-section" id="sub-section">
|
||||||
<div style="font-family:var(--mono);font-size:.6rem;color:var(--muted);margin-top:5px">⚙️ 설정 → OpenRouter에서 API 키 및 기본 모델을 설정하세요</div>
|
<div class="sub-section-title">🎬 자막 모드 (영상/음성 → 자막 파일)</div>
|
||||||
|
<label style="display:flex;align-items:center;gap:8px;cursor:pointer;font-family:var(--mono);font-size:.75rem;color:var(--text)">
|
||||||
|
<input type="checkbox" id="subtitle-mode" style="accent-color:var(--blue);width:15px;height:15px">
|
||||||
|
자막 파일 생성 (SRT / VTT)
|
||||||
|
</label>
|
||||||
|
<div id="sub-opts" style="display:none;margin-top:10px">
|
||||||
|
<div class="sec-label">음성 언어 (원어)</div>
|
||||||
|
<select class="lang-select" id="force-language">
|
||||||
|
<option value="">자동 감지</option>
|
||||||
|
</select>
|
||||||
|
<div class="sec-label">자막 포맷</div>
|
||||||
|
<div class="fmt-btns">
|
||||||
|
<button class="fmt-btn active" data-fmt="srt">SRT</button>
|
||||||
|
<button class="fmt-btn" data-fmt="vtt">VTT</button>
|
||||||
|
<button class="fmt-btn" data-fmt="both">둘 다</button>
|
||||||
|
</div>
|
||||||
|
<div class="sec-label">번역 (선택 — 빈칸이면 원어 자막)</div>
|
||||||
|
<select class="lang-select" id="translate-to">
|
||||||
|
<option value="">번역 안 함 (원어 자막)</option>
|
||||||
|
</select>
|
||||||
|
<div id="trans-model-wrap" style="display:none;margin-top:8px">
|
||||||
|
<div class="sec-label">번역 엔진</div>
|
||||||
|
<div style="display:grid;grid-template-columns:1fr 1fr;gap:6px;margin-top:6px">
|
||||||
|
<button class="fmt-btn active" data-via="ollama" id="trans-via-ollama">🦙 Ollama</button>
|
||||||
|
<button class="fmt-btn" data-via="openrouter" id="trans-via-or">🌐 OpenRouter</button>
|
||||||
|
</div>
|
||||||
|
<div class="sec-label">번역 모델</div>
|
||||||
|
<select class="lang-select" id="translate-model">
|
||||||
|
<option value="">STT 엔진과 같은 모델 사용</option>
|
||||||
|
</select>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
</div>
|
</div>
|
||||||
<button class="btn-start green" id="stt-btn" disabled>변환 시작</button>
|
<button class="btn-start green" id="stt-btn" disabled>변환 시작</button>
|
||||||
<div class="prog-box" id="stt-prog">
|
<div class="prog-box" id="stt-prog">
|
||||||
@@ -421,7 +472,10 @@ textarea.cprompt{width:100%;background:var(--surf);border:1px solid var(--border
|
|||||||
<div class="tab-content" id="stt-segs"><div class="segments-list" id="stt-seglist"></div></div>
|
<div class="tab-content" id="stt-segs"><div class="segments-list" id="stt-seglist"></div></div>
|
||||||
<div class="result-actions" id="stt-actions">
|
<div class="result-actions" id="stt-actions">
|
||||||
<button class="btn-act" id="stt-copy">복사</button>
|
<button class="btn-act" id="stt-copy">복사</button>
|
||||||
<button class="btn-act primary" id="stt-dl">TXT 저장</button>
|
<button class="btn-act primary" id="stt-dl">TXT</button>
|
||||||
|
<button class="sub-dl-btn" id="stt-dl-srt" style="display:none">SRT 저장</button>
|
||||||
|
<button class="sub-dl-btn" id="stt-dl-vtt" style="display:none">VTT 저장</button>
|
||||||
|
<button class="sub-dl-btn" id="stt-dl-srt-orig" style="display:none">원어 SRT</button>
|
||||||
<button class="btn-act" id="stt-new">새 파일</button>
|
<button class="btn-act" id="stt-new">새 파일</button>
|
||||||
</div>
|
</div>
|
||||||
</section>
|
</section>
|
||||||
@@ -434,18 +488,26 @@ textarea.cprompt{width:100%;background:var(--surf);border:1px solid var(--border
|
|||||||
<section class="panel">
|
<section class="panel">
|
||||||
<div class="panel-title">이미지 업로드</div>
|
<div class="panel-title">이미지 업로드</div>
|
||||||
<div class="dropzone" id="ocr-drop">
|
<div class="dropzone" id="ocr-drop">
|
||||||
<input type="file" id="ocr-input" accept=".jpg,.jpeg,.png,.bmp,.tiff,.tif,.webp,.gif">
|
<input type="file" id="ocr-input" accept=".jpg,.jpeg,.png,.bmp,.tiff,.tif,.webp,.gif" multiple>
|
||||||
<span class="drop-icon">🖼</span>
|
<span class="drop-icon">🖼</span>
|
||||||
<div class="drop-label"><strong>탭하거나 드래그하여 선택</strong><br>이미지 파일</div>
|
<div class="drop-label"><strong>탭하거나 드래그하여 선택</strong><br>복수 이미지 동시 선택 가능</div>
|
||||||
<div class="drop-formats">jpg · png · bmp · tiff · webp · gif</div>
|
<div class="drop-formats">jpg · png · bmp · tiff · webp · gif</div>
|
||||||
</div>
|
</div>
|
||||||
<div class="file-info" id="ocr-info"><div class="fname" id="ocr-fname"></div><div class="fsize" id="ocr-fsize"></div></div>
|
<div class="file-info" id="ocr-info"><div class="fname" id="ocr-fname"></div><div class="fsize" id="ocr-fsize"></div></div>
|
||||||
<div id="ocr-preview-wrap"><img id="ocr-preview"></div>
|
<div id="ocr-preview-wrap"><img id="ocr-preview"></div>
|
||||||
|
<!-- 배치 큐 -->
|
||||||
|
<div id="ocr-queue" style="display:none">
|
||||||
|
<div class="batch-queue" id="ocr-queue-list"></div>
|
||||||
|
<div class="batch-summary" id="ocr-queue-summary"></div>
|
||||||
|
<div class="batch-actions">
|
||||||
|
<button class="batch-add-btn" onclick="document.getElementById('ocr-input').click()">+ 파일 더 추가</button>
|
||||||
|
<button class="batch-clear-btn" id="ocr-queue-clear">큐 초기화</button>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
<div class="sec-label">OCR 엔진</div>
|
<div class="sec-label">OCR 엔진</div>
|
||||||
<div class="engine-btns">
|
<div class="engine-btns">
|
||||||
<button class="engine-btn active" data-engine="paddle"><span class="e-icon">🐾</span><span class="e-name">PaddleOCR</span><span class="e-desc">로컬 실행<br>표 구조 분석</span></button>
|
<button class="engine-btn active" data-engine="paddle"><span class="e-icon">🐾</span><span class="e-name">PaddleOCR</span><span class="e-desc">로컬 실행<br>표 구조 분석</span></button>
|
||||||
<button class="engine-btn" data-engine="ollama"><span class="e-icon">🦙</span><span class="e-name">Ollama Vision</span><span class="e-desc">자연어 지시<br>커스텀 프롬프트</span></button>
|
<button class="engine-btn" data-engine="ollama"><span class="e-icon">🦙</span><span class="e-name">Ollama Vision</span><span class="e-desc">자연어 지시<br>커스텀 프롬프트</span></button>
|
||||||
<button class="engine-btn" data-engine="openrouter" style="grid-column:1/-1"><span class="e-icon">🌐</span><span class="e-name">OpenRouter Vision</span><span class="e-desc">Claude / GPT-4o / Gemini 등 외부 Vision 모델 사용</span></button>
|
|
||||||
</div>
|
</div>
|
||||||
<div class="ollama-opts" id="ocr-ollama-opts">
|
<div class="ollama-opts" id="ocr-ollama-opts">
|
||||||
<div class="sec-label" style="margin-top:0">Vision 모델</div>
|
<div class="sec-label" style="margin-top:0">Vision 모델</div>
|
||||||
@@ -453,13 +515,6 @@ textarea.cprompt{width:100%;background:var(--surf);border:1px solid var(--border
|
|||||||
<span class="cprompt-toggle" id="cprompt-toggle">▶ 커스텀 프롬프트</span>
|
<span class="cprompt-toggle" id="cprompt-toggle">▶ 커스텀 프롬프트</span>
|
||||||
<textarea class="cprompt" id="custom-prompt" placeholder="예: 이 영수증의 품목과 금액을 JSON으로 추출해줘"></textarea>
|
<textarea class="cprompt" id="custom-prompt" placeholder="예: 이 영수증의 품목과 금액을 JSON으로 추출해줘"></textarea>
|
||||||
</div>
|
</div>
|
||||||
<div class="ollama-opts" id="ocr-or-opts">
|
|
||||||
<div class="sec-label" style="margin-top:0">OpenRouter Vision 모델</div>
|
|
||||||
<select class="model-select" id="ocr-or-model"><option value="">설정 기본 모델 사용</option></select>
|
|
||||||
<span class="cprompt-toggle" id="cprompt-toggle-or">▶ 커스텀 프롬프트</span>
|
|
||||||
<textarea class="cprompt" id="custom-prompt-or" placeholder="예: 이 영수증의 품목과 금액을 JSON으로 추출해줘"></textarea>
|
|
||||||
<div style="font-family:var(--mono);font-size:.6rem;color:var(--muted);margin-top:5px">⚠️ Vision 기능을 지원하는 모델만 이미지 처리 가능 (Claude-3, GPT-4o, Gemini 등)</div>
|
|
||||||
</div>
|
|
||||||
<div class="sec-label">인식 모드</div>
|
<div class="sec-label">인식 모드</div>
|
||||||
<div class="mode-btns">
|
<div class="mode-btns">
|
||||||
<button class="mode-btn active" data-mode="text">📄 텍스트 추출</button>
|
<button class="mode-btn active" data-mode="text">📄 텍스트 추출</button>
|
||||||
@@ -585,40 +640,6 @@ textarea.cprompt{width:100%;background:var(--surf);border:1px solid var(--border
|
|||||||
<select class="settings-select" id="setting-ocr-model" style="margin-top:8px"><option value="">(없음)</option></select>
|
<select class="settings-select" id="setting-ocr-model" style="margin-top:8px"><option value="">(없음)</option></select>
|
||||||
</div>
|
</div>
|
||||||
|
|
||||||
<!-- OpenRouter -->
|
|
||||||
<div class="settings-section">
|
|
||||||
<h3>🌐 OpenRouter 외부 AI 연동</h3>
|
|
||||||
<label class="settings-label">API 키<small>openrouter.ai에서 발급 — 저장 후 "연결 테스트"로 확인</small></label>
|
|
||||||
<div class="key-input-wrap">
|
|
||||||
<input type="password" id="or-api-key" placeholder="sk-or-v1-..." autocomplete="off">
|
|
||||||
<button class="btn-test" id="btn-or-test">연결 테스트</button>
|
|
||||||
</div>
|
|
||||||
<div id="or-test-result" style="font-family:var(--mono);font-size:.68rem;margin-top:6px;display:none"></div>
|
|
||||||
|
|
||||||
<label class="settings-label" style="margin-top:12px">API URL<small>기본값 사용 권장</small></label>
|
|
||||||
<input type="text" id="or-url" value="https://openrouter.ai/api/v1"
|
|
||||||
style="width:100%;background:var(--surf2);border:1px solid var(--border2);color:var(--text);padding:9px 10px;border-radius:3px;font-family:var(--mono);font-size:.75rem;outline:none;margin-top:6px">
|
|
||||||
|
|
||||||
<div id="or-models-wrap" style="display:none;margin-top:14px">
|
|
||||||
<div style="display:flex;align-items:center;gap:8px;margin-bottom:8px;flex-wrap:wrap">
|
|
||||||
<span id="or-connected-badge" class="openrouter-status ok"></span>
|
|
||||||
<div class="or-model-tabs">
|
|
||||||
<button class="or-model-tab active" data-filter="vision">Vision 모델</button>
|
|
||||||
<button class="or-model-tab" data-filter="text">텍스트 모델</button>
|
|
||||||
<button class="or-model-tab" data-filter="all">전체</button>
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
<label class="settings-label">STT 교정 기본 모델<small>텍스트 전용 모델도 사용 가능</small></label>
|
|
||||||
<select class="settings-select" id="setting-or-stt-model" style="margin-top:6px">
|
|
||||||
<option value="">(없음)</option>
|
|
||||||
</select>
|
|
||||||
<label class="settings-label" style="margin-top:10px">OCR 기본 Vision 모델<small>반드시 Vision 지원 모델 선택</small></label>
|
|
||||||
<select class="settings-select" id="setting-or-ocr-model" style="margin-top:6px">
|
|
||||||
<option value="">(없음)</option>
|
|
||||||
</select>
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<div style="display:flex;gap:10px;justify-content:flex-end;align-items:center">
|
<div style="display:flex;gap:10px;justify-content:flex-end;align-items:center">
|
||||||
<div id="settings-msg" style="font-family:var(--mono);font-size:.68rem;color:var(--accent);display:none">✓ 저장됨 (CPU·타임아웃: worker 재시작 후 반영)</div>
|
<div id="settings-msg" style="font-family:var(--mono);font-size:.68rem;color:var(--accent);display:none">✓ 저장됨 (CPU·타임아웃: worker 재시작 후 반영)</div>
|
||||||
<button class="btn-settings blue" id="btn-save-settings">저장</button>
|
<button class="btn-settings blue" id="btn-save-settings">저장</button>
|
||||||
@@ -702,7 +723,6 @@ textarea.cprompt{width:100%;background:var(--surf);border:1px solid var(--border
|
|||||||
// ══ STATE ══
|
// ══ STATE ══
|
||||||
let token=null,currentUser=null,ollamaModels=[],appSettings={};
|
let token=null,currentUser=null,ollamaModels=[],appSettings={};
|
||||||
let sttFile=null,sttOutputFile=null,sttEngine='whisper';
|
let sttFile=null,sttOutputFile=null,sttEngine='whisper';
|
||||||
let orModels=[],orVisionModels=[],orTextModels=[];
|
|
||||||
let ocrFile=null,ocrOutputTxt=null,ocrOutputXlsx=null,ocrEngine='paddle',ocrMode='text';
|
let ocrFile=null,ocrOutputTxt=null,ocrOutputXlsx=null,ocrEngine='paddle',ocrMode='text';
|
||||||
let editTarget=null,sysTimer=null;
|
let editTarget=null,sysTimer=null;
|
||||||
let histPage=1,histType='',histTotal=0;
|
let histPage=1,histType='',histTotal=0;
|
||||||
@@ -781,7 +801,6 @@ function populateModelSelects(){
|
|||||||
fill(document.getElementById('ocr-ollama-model'),appSettings.ocr_ollama_model,'설정 기본 모델 사용');
|
fill(document.getElementById('ocr-ollama-model'),appSettings.ocr_ollama_model,'설정 기본 모델 사용');
|
||||||
fill(document.getElementById('setting-stt-model'),appSettings.stt_ollama_model,'(없음)');
|
fill(document.getElementById('setting-stt-model'),appSettings.stt_ollama_model,'(없음)');
|
||||||
fill(document.getElementById('setting-ocr-model'),appSettings.ocr_ollama_model,'(없음)');
|
fill(document.getElementById('setting-ocr-model'),appSettings.ocr_ollama_model,'(없음)');
|
||||||
// OpenRouter 드롭다운
|
|
||||||
populateOrSelects();
|
populateOrSelects();
|
||||||
}
|
}
|
||||||
|
|
||||||
@@ -791,11 +810,7 @@ async function loadSettings(){
|
|||||||
const th=appSettings.cpu_threads||0;cpuSlider.value=th;cpuDisplay.textContent=th===0?'0 (자동)':th+' 스레드';
|
const th=appSettings.cpu_threads||0;cpuSlider.value=th;cpuDisplay.textContent=th===0?'0 (자동)':th+' 스레드';
|
||||||
document.getElementById('stt-timeout').value=appSettings.stt_timeout||0;
|
document.getElementById('stt-timeout').value=appSettings.stt_timeout||0;
|
||||||
document.getElementById('ollama-timeout').value=appSettings.ollama_timeout||600;
|
document.getElementById('ollama-timeout').value=appSettings.ollama_timeout||600;
|
||||||
if(appSettings.openrouter_url)document.getElementById('or-url').value=appSettings.openrouter_url;
|
populateModelSelects()}catch{}
|
||||||
if(appSettings.openrouter_api_key_masked)document.getElementById('or-api-key').placeholder='저장된 키: '+appSettings.openrouter_api_key_masked;
|
|
||||||
populateModelSelects();
|
|
||||||
// 기존 OR 모델 로드
|
|
||||||
if(appSettings.openrouter_api_key_masked)loadOrModels();}catch{}
|
|
||||||
}
|
}
|
||||||
document.getElementById('btn-save-settings').addEventListener('click',async()=>{
|
document.getElementById('btn-save-settings').addEventListener('click',async()=>{
|
||||||
const fd=new FormData();
|
const fd=new FormData();
|
||||||
@@ -804,10 +819,10 @@ document.getElementById('btn-save-settings').addEventListener('click',async()=>{
|
|||||||
fd.append('cpu_threads',cpuSlider.value);
|
fd.append('cpu_threads',cpuSlider.value);
|
||||||
fd.append('stt_timeout',document.getElementById('stt-timeout').value||'0');
|
fd.append('stt_timeout',document.getElementById('stt-timeout').value||'0');
|
||||||
fd.append('ollama_timeout',document.getElementById('ollama-timeout').value||'600');
|
fd.append('ollama_timeout',document.getElementById('ollama-timeout').value||'600');
|
||||||
fd.append('openrouter_url',document.getElementById('or-url').value||'https://openrouter.ai/api/v1');
|
fd.append('openrouter_url',document.getElementById('or-url')?.value||'https://openrouter.ai/api/v1');
|
||||||
const orKey=document.getElementById('or-api-key').value.trim();if(orKey)fd.append('openrouter_api_key',orKey);
|
const orKey=document.getElementById('or-api-key')?.value?.trim();if(orKey)fd.append('openrouter_api_key',orKey);
|
||||||
fd.append('openrouter_stt_model',document.getElementById('setting-or-stt-model').value);
|
fd.append('openrouter_stt_model',document.getElementById('setting-or-stt-model')?.value||'');
|
||||||
fd.append('openrouter_ocr_model',document.getElementById('setting-or-ocr-model').value);
|
fd.append('openrouter_ocr_model',document.getElementById('setting-or-ocr-model')?.value||'');
|
||||||
try{const r=await api('POST','/api/settings',fd);if(r.ok){appSettings=(await r.json()).settings;const msg=document.getElementById('settings-msg');msg.style.display='block';setTimeout(()=>msg.style.display='none',3500)}}catch{}
|
try{const r=await api('POST','/api/settings',fd);if(r.ok){appSettings=(await r.json()).settings;const msg=document.getElementById('settings-msg');msg.style.display='block';setTimeout(()=>msg.style.display='none',3500)}}catch{}
|
||||||
});
|
});
|
||||||
document.getElementById('btn-refresh-models').addEventListener('click',loadOllamaModels);
|
document.getElementById('btn-refresh-models').addEventListener('click',loadOllamaModels);
|
||||||
@@ -825,71 +840,286 @@ document.querySelectorAll('.nav-tab').forEach(btn=>{
|
|||||||
});
|
});
|
||||||
});
|
});
|
||||||
|
|
||||||
// ══ STT ══
|
// ══ STT — 배치 + 자막 ══
|
||||||
const sttDrop=document.getElementById('stt-drop'),sttInput=document.getElementById('stt-input');
|
const sttDrop=document.getElementById('stt-drop'),sttInput=document.getElementById('stt-input');
|
||||||
sttInput.addEventListener('change',()=>setSttFile(sttInput.files[0]));
|
let sttQueue=[],sttSubFmt='srt',sttTransVia='ollama';
|
||||||
|
let languages={};
|
||||||
|
|
||||||
|
// 언어 목록 로드
|
||||||
|
async function loadLanguages(){
|
||||||
|
try{const r=await api('GET','/api/languages');const d=await r.json();languages=d.languages||{};
|
||||||
|
const sel1=document.getElementById('force-language');
|
||||||
|
const sel2=document.getElementById('translate-to');
|
||||||
|
Object.entries(languages).forEach(([code,name])=>{
|
||||||
|
sel1.appendChild(Object.assign(document.createElement('option'),{value:code,textContent:`${name} (${code})`}));
|
||||||
|
sel2.appendChild(Object.assign(document.createElement('option'),{value:code,textContent:`${name} (${code})`}));
|
||||||
|
});
|
||||||
|
}catch{}
|
||||||
|
}
|
||||||
|
|
||||||
|
// 번역 모델 드롭다운 채우기
|
||||||
|
function fillTranslateModels(){
|
||||||
|
const sel=document.getElementById('translate-model');
|
||||||
|
const cur=sel.value;sel.innerHTML='<option value="">STT 엔진과 같은 모델 사용</option>';
|
||||||
|
const models=sttTransVia==='openrouter'?orModels:ollamaModels;
|
||||||
|
models.forEach(m=>{const o=document.createElement('option');o.value=m;o.textContent=m;if(m===cur)o.selected=true;sel.appendChild(o)});
|
||||||
|
}
|
||||||
|
|
||||||
|
// 자막 모드 토글
|
||||||
|
document.getElementById('subtitle-mode').addEventListener('change',function(){
|
||||||
|
document.getElementById('sub-opts').style.display=this.checked?'block':'none';
|
||||||
|
});
|
||||||
|
|
||||||
|
// 포맷 버튼
|
||||||
|
document.querySelectorAll('.fmt-btn[data-fmt]').forEach(btn=>{
|
||||||
|
btn.addEventListener('click',()=>{document.querySelectorAll('.fmt-btn[data-fmt]').forEach(b=>b.classList.remove('active'));btn.classList.add('active');sttSubFmt=btn.dataset.fmt});
|
||||||
|
});
|
||||||
|
|
||||||
|
// 번역 언어 선택 → 모델 옵션 표시
|
||||||
|
document.getElementById('translate-to').addEventListener('change',function(){
|
||||||
|
document.getElementById('trans-model-wrap').style.display=this.value?'block':'none';
|
||||||
|
if(this.value)fillTranslateModels();
|
||||||
|
});
|
||||||
|
|
||||||
|
// 번역 엔진 선택
|
||||||
|
document.querySelectorAll('button[data-via]').forEach(btn=>{
|
||||||
|
btn.addEventListener('click',()=>{
|
||||||
|
document.querySelectorAll('button[data-via]').forEach(b=>b.classList.remove('active'));
|
||||||
|
btn.classList.add('active');sttTransVia=btn.dataset.via;fillTranslateModels();
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
// 파일 추가
|
||||||
|
function addSttFiles(fileList){
|
||||||
|
const AUDIO=['mp3','mp4','wav','m4a','ogg','flac','aac','wma','webm','mkv','avi','mov','ts','mts','h264','h265'];
|
||||||
|
const files=Array.from(fileList).filter(f=>AUDIO.includes(f.name.split('.').pop().toLowerCase()));
|
||||||
|
if(!files.length)return;
|
||||||
|
files.forEach(f=>sttQueue.push({file:f,taskId:null,outputFile:null,srtFile:null,vttFile:null,srtOrigFile:null,status:'waiting',el:null}));
|
||||||
|
renderSttQueue();document.getElementById('stt-btn').disabled=false;
|
||||||
|
}
|
||||||
|
sttInput.addEventListener('change',()=>addSttFiles(sttInput.files));
|
||||||
sttDrop.addEventListener('dragover',e=>{e.preventDefault();sttDrop.classList.add('dragover')});
|
sttDrop.addEventListener('dragover',e=>{e.preventDefault();sttDrop.classList.add('dragover')});
|
||||||
sttDrop.addEventListener('dragleave',()=>sttDrop.classList.remove('dragover'));
|
sttDrop.addEventListener('dragleave',()=>sttDrop.classList.remove('dragover'));
|
||||||
sttDrop.addEventListener('drop',e=>{e.preventDefault();sttDrop.classList.remove('dragover');setSttFile(e.dataTransfer.files[0])});
|
sttDrop.addEventListener('drop',e=>{e.preventDefault();sttDrop.classList.remove('dragover');addSttFiles(e.dataTransfer.files)});
|
||||||
function setSttFile(f){if(!f)return;sttFile=f;showFileInfo('stt',f);document.getElementById('stt-btn').disabled=false;document.getElementById('stt-err').style.display='none'}
|
document.getElementById('stt-queue-clear').addEventListener('click',()=>{sttQueue=[];renderSttQueue();document.getElementById('stt-btn').disabled=true});
|
||||||
document.querySelectorAll('#page-stt .engine-btn').forEach(btn=>{btn.addEventListener('click',()=>{document.querySelectorAll('#page-stt .engine-btn').forEach(b=>b.classList.remove('active'));btn.classList.add('active');sttEngine=btn.dataset.engine;document.getElementById('stt-ollama-opts').classList.toggle('visible',sttEngine==='whisper+ollama');document.getElementById('stt-or-opts').classList.toggle('visible',sttEngine==='whisper+openrouter');const isOr=sttEngine==='whisper+openrouter',isOllama=sttEngine==='whisper+ollama';document.getElementById('stt-btn').className='btn-start '+(isOr||isOllama?'purple':'green')})});
|
|
||||||
document.getElementById('stt-btn').addEventListener('click',async()=>{
|
function renderSttQueue(){
|
||||||
if(!sttFile)return;document.getElementById('stt-err').style.display='none';setSttLoading(true);
|
const qEl=document.getElementById('stt-queue'),list=document.getElementById('stt-queue-list'),sum=document.getElementById('stt-queue-summary');
|
||||||
const fd=new FormData();fd.append('file',sttFile);fd.append('use_ollama',sttEngine==='whisper+ollama'?'true':'false');fd.append('ollama_model',document.getElementById('stt-ollama-model').value||'');
|
if(!sttQueue.length){qEl.style.display='none';return}
|
||||||
fd.append('use_openrouter',sttEngine==='whisper+openrouter'?'true':'false');fd.append('openrouter_model',document.getElementById('stt-or-model').value||'');
|
qEl.style.display='block';list.innerHTML='';
|
||||||
try{const r=await api('POST','/api/transcribe',fd);const d=await r.json();if(!r.ok)throw new Error(d.detail||'업로드 실패');pollTask(d.task_id,dt=>setProg('stt',dt.progress||0,dt.message||'처리 중...'),showSttResult,e=>{showErr('stt-err',e);setSttLoading(false)})}
|
sttQueue.forEach((item,i)=>{
|
||||||
catch(e){showErr('stt-err',e.message);setSttLoading(false)}
|
const div=document.createElement('div');div.className='batch-item '+item.status;
|
||||||
|
const dlBtns=item.status==='done'?[
|
||||||
|
item.outputFile?`<button class="bi-dl" onclick="dlFile('${esc(item.outputFile)}')">TXT</button>`:'',
|
||||||
|
item.srtFile?`<button class="bi-dl" onclick="dlFile('${esc(item.srtFile)}')">SRT</button>`:'',
|
||||||
|
item.vttFile?`<button class="bi-dl" onclick="dlFile('${esc(item.vttFile)}')">VTT</button>`:'',
|
||||||
|
item.srtOrigFile?`<button class="bi-dl" onclick="dlFile('${esc(item.srtOrigFile)}')">원어SRT</button>`:'',
|
||||||
|
].filter(Boolean).join(''):''
|
||||||
|
div.innerHTML=`<div><div class="bi-name">${esc(item.file.name)}</div><div class="bi-prog" id="stt-bp-${i}" style="width:0%;display:${item.status==='running'?'block':'none'}"></div></div><span class="bi-status ${item.status}">${{waiting:'대기',running:'변환중',done:'완료',failed:'실패'}[item.status]}</span><span style="display:flex;gap:3px">${dlBtns}</span>`;
|
||||||
|
item.el=div;list.appendChild(div);
|
||||||
|
});
|
||||||
|
const done=sttQueue.filter(i=>i.status==='done').length,failed=sttQueue.filter(i=>i.status==='failed').length,running=sttQueue.filter(i=>i.status==='running').length;
|
||||||
|
sum.innerHTML=`전체 <span>${sttQueue.length}</span>개 · 완료 <span>${done}</span> · 실패 <span>${failed}</span>${running?` · 진행중 <span>${running}</span>`:''}`;
|
||||||
|
}
|
||||||
|
|
||||||
|
// 엔진 버튼
|
||||||
|
document.querySelectorAll('#page-stt .engine-btn').forEach(btn=>{
|
||||||
|
btn.addEventListener('click',()=>{
|
||||||
|
document.querySelectorAll('#page-stt .engine-btn').forEach(b=>b.classList.remove('active'));
|
||||||
|
btn.classList.add('active');sttEngine=btn.dataset.engine;
|
||||||
|
document.getElementById('stt-ollama-opts').classList.toggle('visible',sttEngine==='whisper+ollama');
|
||||||
|
document.getElementById('stt-or-opts').classList.toggle('visible',sttEngine==='whisper+openrouter');
|
||||||
|
document.getElementById('stt-btn').className='btn-start '+(sttEngine!=='whisper'?'purple':'green');
|
||||||
|
});
|
||||||
});
|
});
|
||||||
|
|
||||||
|
document.getElementById('stt-btn').addEventListener('click',async()=>{
|
||||||
|
const pending=sttQueue.filter(i=>i.status==='waiting');
|
||||||
|
if(!pending.length){showErr('stt-err','변환할 파일이 없습니다');return}
|
||||||
|
document.getElementById('stt-err').style.display='none';
|
||||||
|
document.getElementById('stt-btn').disabled=true;
|
||||||
|
document.getElementById('stt-prog').style.display='block';
|
||||||
|
setProg('stt',0,`${pending.length}개 파일 업로드 중...`);
|
||||||
|
|
||||||
|
const subMode=document.getElementById('subtitle-mode').checked;
|
||||||
|
const fd=new FormData();
|
||||||
|
pending.forEach(item=>fd.append('files',item.file));
|
||||||
|
fd.append('use_ollama',sttEngine==='whisper+ollama'?'true':'false');
|
||||||
|
fd.append('ollama_model',document.getElementById('stt-ollama-model')?.value||'');
|
||||||
|
fd.append('use_openrouter',sttEngine==='whisper+openrouter'?'true':'false');
|
||||||
|
fd.append('openrouter_model',document.getElementById('stt-or-model')?.value||'');
|
||||||
|
fd.append('subtitle_mode',subMode?'true':'false');
|
||||||
|
fd.append('subtitle_format',sttSubFmt);
|
||||||
|
fd.append('force_language',document.getElementById('force-language').value||'');
|
||||||
|
fd.append('translate_to',document.getElementById('translate-to').value||'');
|
||||||
|
fd.append('translate_model',document.getElementById('translate-model').value||'');
|
||||||
|
fd.append('translate_via',sttTransVia);
|
||||||
|
|
||||||
|
try{
|
||||||
|
const url=pending.length===1?'/api/transcribe':'/api/transcribe/batch';
|
||||||
|
const r=await api('POST',url,fd);const d=await r.json();
|
||||||
|
if(!r.ok)throw new Error(d.detail||'업로드 실패');
|
||||||
|
const items=pending.length===1?[d]:(d.items||[]);
|
||||||
|
let pi=0;
|
||||||
|
sttQueue.forEach((qItem,qi)=>{
|
||||||
|
if(qItem.status!=='waiting')return;
|
||||||
|
const taskItem=items[pi++];if(!taskItem)return;
|
||||||
|
if(taskItem.error){qItem.status='failed';return}
|
||||||
|
qItem.status='running';qItem.taskId=taskItem.task_id;renderSttQueue();
|
||||||
|
pollSttItem(qi,taskItem.task_id);
|
||||||
|
});
|
||||||
|
setProg('stt',20,`${items.length}개 변환 중...`);
|
||||||
|
}catch(e){showErr('stt-err',e.message);document.getElementById('stt-btn').disabled=false;document.getElementById('stt-prog').style.display='none'}
|
||||||
|
});
|
||||||
|
|
||||||
|
function pollSttItem(qi,taskId){
|
||||||
|
const t=setInterval(async()=>{
|
||||||
|
try{
|
||||||
|
const r=await api('GET','/api/status/'+taskId);if(r.status===401){clearInterval(t);showLogin();return}
|
||||||
|
const d=await r.json();
|
||||||
|
if(d.state==='success'){
|
||||||
|
clearInterval(t);
|
||||||
|
const item=sttQueue[qi];
|
||||||
|
item.outputFile=d.output_file||null;item.srtFile=d.srt_file||null;
|
||||||
|
item.vttFile=d.vtt_file||null;item.srtOrigFile=d.srt_original_file||null;
|
||||||
|
item.status='done';renderSttQueue();checkSttBatchDone();
|
||||||
|
if(sttQueue.filter(i=>i.status!=='waiting'&&i.status!=='done'&&i.status!=='failed').length===0&&
|
||||||
|
sttQueue.filter(i=>i.status==='done').length===1) showSttResult(d);
|
||||||
|
} else if(d.state==='failure'){
|
||||||
|
clearInterval(t);sttQueue[qi].status='failed';renderSttQueue();checkSttBatchDone();
|
||||||
|
} else {
|
||||||
|
const done=sttQueue.filter(i=>i.status==='done').length;
|
||||||
|
setProg('stt',20+Math.round((done/sttQueue.length)*75),d.message||'처리 중...');
|
||||||
|
}
|
||||||
|
}catch{}
|
||||||
|
},1800);
|
||||||
|
}
|
||||||
|
|
||||||
|
function checkSttBatchDone(){
|
||||||
|
if(sttQueue.every(i=>['done','failed','waiting'].includes(i.status))){
|
||||||
|
const done=sttQueue.filter(i=>i.status==='done').length;
|
||||||
|
setProg('stt',100,`완료 ${done}/${sttQueue.length}개`);
|
||||||
|
setTimeout(()=>document.getElementById('stt-prog').style.display='none',2000);
|
||||||
|
document.getElementById('stt-btn').disabled=false;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
function setSttLoading(on){document.getElementById('stt-btn').disabled=on;document.getElementById('stt-prog').style.display=on?'block':'none';if(on)setProg('stt',0,'준비 중...')}
|
function setSttLoading(on){document.getElementById('stt-btn').disabled=on;document.getElementById('stt-prog').style.display=on?'block':'none';if(on)setProg('stt',0,'준비 중...')}
|
||||||
|
|
||||||
function showSttResult(d){
|
function showSttResult(d){
|
||||||
sttOutputFile=d.output_file;
|
sttOutputFile=d.output_file;
|
||||||
document.getElementById('stt-mlang').textContent=(d.language||'').toUpperCase();
|
document.getElementById('stt-mlang').textContent=((d.language||'')+( d.translated?' → '+d.translate_to:'')).toUpperCase();
|
||||||
document.getElementById('stt-mdur').textContent=fmtDur(d.duration);
|
document.getElementById('stt-mdur').textContent=fmtDur(d.duration);
|
||||||
document.getElementById('stt-msegs').textContent=(d.segments||[]).length+'개';
|
document.getElementById('stt-msegs').textContent=(d.segments||[]).length+'개';
|
||||||
const chip=document.getElementById('stt-mollama-chip');if(d.ollama_used){chip.style.display='block';document.getElementById('stt-mollama').textContent=d.ollama_model}else chip.style.display='none';
|
const chip=document.getElementById('stt-mollama-chip');
|
||||||
|
if(d.ollama_used){chip.style.display='block';document.getElementById('stt-mollama').textContent=d.ollama_model}else chip.style.display='none';
|
||||||
document.getElementById('stt-meta').style.display='flex';document.getElementById('stt-tabs').style.display='flex';
|
document.getElementById('stt-meta').style.display='flex';document.getElementById('stt-tabs').style.display='flex';
|
||||||
document.getElementById('stt-empty').style.display='none';document.getElementById('stt-result').style.display='block';document.getElementById('stt-result').value=d.text||'';
|
document.getElementById('stt-empty').style.display='none';document.getElementById('stt-result').style.display='block';document.getElementById('stt-result').value=d.text||'';
|
||||||
const sl=document.getElementById('stt-seglist');sl.innerHTML='';
|
const sl=document.getElementById('stt-seglist');sl.innerHTML='';
|
||||||
(d.segments||[]).forEach(s=>{const row=document.createElement('div');row.className='seg-item';row.innerHTML=`<div class="seg-time">${fmtTime(s.start)}<br>→${fmtTime(s.end)}</div><div class="seg-text">${esc(s.text)}</div>`;sl.appendChild(row)});
|
(d.segments||[]).forEach(s=>{const row=document.createElement('div');row.className='seg-item';row.innerHTML=`<div class="seg-time">${fmtTime(s.start)}<br>→${fmtTime(s.end)}</div><div class="seg-text">${esc(s.text)}</div>`;sl.appendChild(row)});
|
||||||
document.getElementById('stt-actions').style.display='flex';setSttLoading(false);
|
document.getElementById('stt-actions').style.display='flex';
|
||||||
|
// 자막 다운로드 버튼
|
||||||
|
const srtBtn=document.getElementById('stt-dl-srt'),vttBtn=document.getElementById('stt-dl-vtt'),origBtn=document.getElementById('stt-dl-srt-orig');
|
||||||
|
srtBtn.style.display=d.srt_file?'flex':'none';if(d.srt_file)srtBtn.onclick=()=>dlFile(d.srt_file);
|
||||||
|
vttBtn.style.display=d.vtt_file?'flex':'none';if(d.vtt_file)vttBtn.onclick=()=>dlFile(d.vtt_file);
|
||||||
|
origBtn.style.display=d.srt_original_file?'flex':'none';if(d.srt_original_file)origBtn.onclick=()=>dlFile(d.srt_original_file);
|
||||||
|
setSttLoading(false);
|
||||||
}
|
}
|
||||||
document.getElementById('stt-copy').addEventListener('click',()=>copyText(document.getElementById('stt-result').value,document.getElementById('stt-copy')));
|
document.getElementById('stt-copy').addEventListener('click',()=>copyText(document.getElementById('stt-result').value,document.getElementById('stt-copy')));
|
||||||
document.getElementById('stt-dl').addEventListener('click',()=>dlFile(sttOutputFile));
|
document.getElementById('stt-dl').addEventListener('click',()=>dlFile(sttOutputFile));
|
||||||
document.getElementById('stt-new').addEventListener('click',()=>{sttFile=null;sttInput.value='';sttOutputFile=null;['stt-info','stt-prog','stt-err','stt-meta','stt-tabs','stt-actions'].forEach(id=>document.getElementById(id).style.display='none');document.getElementById('stt-empty').style.display='flex';document.getElementById('stt-result').style.display='none';document.getElementById('stt-result').value='';document.getElementById('stt-seglist').innerHTML='';document.getElementById('stt-btn').disabled=true;resetTabs('stt-tabs')});
|
document.getElementById('stt-new').addEventListener('click',()=>{
|
||||||
|
sttQueue=[];sttInput.value='';sttOutputFile=null;renderSttQueue();
|
||||||
|
['stt-prog','stt-err','stt-meta','stt-tabs','stt-actions'].forEach(id=>document.getElementById(id).style.display='none');
|
||||||
|
document.getElementById('stt-empty').style.display='flex';
|
||||||
|
document.getElementById('stt-result').style.display='none';document.getElementById('stt-result').value='';
|
||||||
|
document.getElementById('stt-seglist').innerHTML='';document.getElementById('stt-btn').disabled=true;resetTabs('stt-tabs');
|
||||||
|
['stt-dl-srt','stt-dl-vtt','stt-dl-srt-orig'].forEach(id=>document.getElementById(id).style.display='none');
|
||||||
|
});
|
||||||
|
|
||||||
// ══ OCR ══
|
// ══ OCR — 배치 ══
|
||||||
const ocrDrop=document.getElementById('ocr-drop'),ocrInput=document.getElementById('ocr-input');
|
const ocrDrop=document.getElementById('ocr-drop'),ocrInput=document.getElementById('ocr-input');
|
||||||
ocrInput.addEventListener('change',()=>setOcrFile(ocrInput.files[0]));
|
let ocrQueue=[];
|
||||||
|
|
||||||
|
function addOcrFiles(fileList){
|
||||||
|
const IMG=['jpg','jpeg','png','bmp','tiff','tif','webp','gif'];
|
||||||
|
const files=Array.from(fileList).filter(f=>IMG.includes(f.name.split('.').pop().toLowerCase()));
|
||||||
|
if(!files.length)return;
|
||||||
|
files.forEach(f=>ocrQueue.push({file:f,taskId:null,txtFile:null,xlsxFile:null,status:'waiting',el:null}));
|
||||||
|
renderOcrQueue();document.getElementById('ocr-btn').disabled=false;
|
||||||
|
}
|
||||||
|
ocrInput.addEventListener('change',()=>addOcrFiles(ocrInput.files));
|
||||||
ocrDrop.addEventListener('dragover',e=>{e.preventDefault();ocrDrop.classList.add('dragover')});
|
ocrDrop.addEventListener('dragover',e=>{e.preventDefault();ocrDrop.classList.add('dragover')});
|
||||||
ocrDrop.addEventListener('dragleave',()=>ocrDrop.classList.remove('dragover'));
|
ocrDrop.addEventListener('dragleave',()=>ocrDrop.classList.remove('dragover'));
|
||||||
ocrDrop.addEventListener('drop',e=>{e.preventDefault();ocrDrop.classList.remove('dragover');setOcrFile(e.dataTransfer.files[0])});
|
ocrDrop.addEventListener('drop',e=>{e.preventDefault();ocrDrop.classList.remove('dragover');addOcrFiles(e.dataTransfer.files)});
|
||||||
function setOcrFile(f){if(!f)return;ocrFile=f;showFileInfo('ocr',f);document.getElementById('ocr-btn').disabled=false;document.getElementById('ocr-err').style.display='none';const p=document.getElementById('ocr-preview'),w=document.getElementById('ocr-preview-wrap');p.src=URL.createObjectURL(f);w.style.display='block'}
|
document.getElementById('ocr-queue-clear').addEventListener('click',()=>{ocrQueue=[];renderOcrQueue();document.getElementById('ocr-btn').disabled=true});
|
||||||
document.querySelectorAll('#page-ocr .engine-btn').forEach(btn=>{btn.addEventListener('click',()=>{document.querySelectorAll('#page-ocr .engine-btn').forEach(b=>b.classList.remove('active'));btn.classList.add('active');ocrEngine=btn.dataset.engine;document.getElementById('ocr-ollama-opts').classList.toggle('visible',ocrEngine==='ollama');document.getElementById('ocr-or-opts').classList.toggle('visible',ocrEngine==='openrouter');const isOr=ocrEngine==='openrouter',isOllama=ocrEngine==='ollama';document.getElementById('ocr-btn').className='btn-start '+(isOr||isOllama?'purple':'green')})});
|
|
||||||
document.getElementById('cprompt-toggle').addEventListener('click',()=>{const ta=document.getElementById('custom-prompt');const open=ta.style.display!=='block';ta.style.display=open?'block':'none';document.getElementById('cprompt-toggle').textContent=(open?'▼':'▶')+' 커스텀 프롬프트'});
|
function renderOcrQueue(){
|
||||||
document.getElementById('cprompt-toggle-or').addEventListener('click',()=>{const ta=document.getElementById('custom-prompt-or');const open=ta.style.display!=='block';ta.style.display=open?'block':'none';document.getElementById('cprompt-toggle-or').textContent=(open?'▼':'▶')+' 커스텀 프롬프트'});
|
const qEl=document.getElementById('ocr-queue'),list=document.getElementById('ocr-queue-list'),sum=document.getElementById('ocr-queue-summary');
|
||||||
document.querySelectorAll('.mode-btn').forEach(btn=>{btn.addEventListener('click',()=>{document.querySelectorAll('.mode-btn').forEach(b=>b.classList.remove('active'));btn.classList.add('active');ocrMode=btn.dataset.mode;document.getElementById('mode-desc').textContent=ocrMode==='structure'?'표 구조를 감지하고 Excel로 저장합니다':'일반 텍스트와 글자를 인식합니다'})});
|
if(!ocrQueue.length){qEl.style.display='none';return}
|
||||||
document.getElementById('ocr-btn').addEventListener('click',async()=>{
|
qEl.style.display='block';list.innerHTML='';
|
||||||
if(!ocrFile)return;document.getElementById('ocr-err').style.display='none';setOcrLoading(true);
|
ocrQueue.forEach((item,i)=>{
|
||||||
const fd=new FormData();
|
const div=document.createElement('div');div.className='batch-item '+item.status;
|
||||||
fd.append('file',ocrFile);
|
div.innerHTML=`<div><div class="bi-name">${esc(item.file.name)}</div><div class="bi-prog" id="ocr-bp-${i}" style="width:0%;display:${item.status==='running'?'block':'none'}"></div></div><span class="bi-status ${item.status}">${{waiting:'대기',running:'인식중',done:'완료',failed:'실패'}[item.status]}</span><span style="display:flex;gap:3px">${item.status==='done'?[item.txtFile?`<button class="bi-dl" onclick="dlFile('${esc(item.txtFile)}')">TXT</button>`:'',item.xlsxFile?`<button class="bi-dl" onclick="dlFile('${esc(item.xlsxFile)}')">XLS</button>`:''].filter(Boolean).join(''):''}</span>`;
|
||||||
fd.append('mode',ocrMode);
|
item.el=div;list.appendChild(div);
|
||||||
fd.append('backend',ocrEngine);
|
});
|
||||||
// Ollama 모델
|
const done=ocrQueue.filter(i=>i.status==='done').length,failed=ocrQueue.filter(i=>i.status==='failed').length,running=ocrQueue.filter(i=>i.status==='running').length;
|
||||||
fd.append('ollama_model', ocrEngine==='ollama' ? (document.getElementById('ocr-ollama-model').value||'') : '');
|
sum.innerHTML=`전체 <span>${ocrQueue.length}</span>개 · 완료 <span>${done}</span> · 실패 <span>${failed}</span>${running?` · 진행중 <span>${running}</span>`:''}`;
|
||||||
// OpenRouter 모델
|
}
|
||||||
fd.append('openrouter_model', ocrEngine==='openrouter' ? (document.getElementById('ocr-or-model').value||'') : '');
|
|
||||||
// 커스텀 프롬프트 (엔진별)
|
document.querySelectorAll('#page-ocr .engine-btn').forEach(btn=>{
|
||||||
const cp = ocrEngine==='openrouter'
|
btn.addEventListener('click',()=>{
|
||||||
? (document.getElementById('custom-prompt-or').value||'')
|
document.querySelectorAll('#page-ocr .engine-btn').forEach(b=>b.classList.remove('active'));
|
||||||
: (document.getElementById('custom-prompt').value||'');
|
btn.classList.add('active');ocrEngine=btn.dataset.engine;
|
||||||
fd.append('custom_prompt', cp);
|
document.getElementById('ocr-ollama-opts').classList.toggle('visible',ocrEngine==='ollama');
|
||||||
try{const r=await api('POST','/api/ocr',fd);const d=await r.json();if(!r.ok)throw new Error(d.detail||'업로드 실패');pollTask(d.task_id,dt=>setProg('ocr',dt.progress||0,dt.message||'처리 중...'),showOcrResult,e=>{showErr('ocr-err',e);setOcrLoading(false)})}
|
document.getElementById('ocr-or-opts').classList.toggle('visible',ocrEngine==='openrouter');
|
||||||
catch(e){showErr('ocr-err',e.message);setOcrLoading(false)}
|
document.getElementById('ocr-btn').className='btn-start '+(ocrEngine!=='paddle'?'purple':'green');
|
||||||
|
});
|
||||||
});
|
});
|
||||||
function setOcrLoading(on){const io=(ocrEngine==='ollama'||ocrEngine==='openrouter'),c=io?'var(--purple)':'var(--accent)';document.getElementById('ocr-btn').disabled=on;document.getElementById('ocr-prog').style.display=on?'block':'none';document.getElementById('ocr-wave').style.display=on?'flex':'none';document.getElementById('ocr-pfill').style.background=c;document.getElementById('ocr-ppct').style.color=c;document.querySelectorAll('#ocr-wave .wave-bar').forEach(b=>b.style.background=c);if(on)setProg('ocr',0,'준비 중...')}
|
document.getElementById('cprompt-toggle').addEventListener('click',()=>{const ta=document.getElementById('custom-prompt');const open=ta.style.display!=='block';ta.style.display=open?'block':'none';document.getElementById('cprompt-toggle').textContent=(open?'▼':'▶')+' 커스텀 프롬프트'});
|
||||||
|
document.querySelectorAll('.mode-btn').forEach(btn=>{btn.addEventListener('click',()=>{document.querySelectorAll('.mode-btn').forEach(b=>b.classList.remove('active'));btn.classList.add('active');ocrMode=btn.dataset.mode;document.getElementById('mode-desc').textContent=ocrMode==='structure'?'표 구조를 감지하고 Excel로 저장합니다':'일반 텍스트와 글자를 인식합니다'})});
|
||||||
|
|
||||||
|
document.getElementById('ocr-btn').addEventListener('click',async()=>{
|
||||||
|
const pending=ocrQueue.filter(i=>i.status==='waiting');
|
||||||
|
if(!pending.length){showErr('ocr-err','인식할 파일이 없습니다');return}
|
||||||
|
document.getElementById('ocr-err').style.display='none';
|
||||||
|
document.getElementById('ocr-btn').disabled=true;
|
||||||
|
document.getElementById('ocr-prog').style.display='block';
|
||||||
|
setProg('ocr',0,`${pending.length}개 업로드 중...`);
|
||||||
|
const fd=new FormData();
|
||||||
|
pending.forEach(item=>fd.append('files',item.file));
|
||||||
|
fd.append('mode',ocrMode);fd.append('backend',ocrEngine);
|
||||||
|
fd.append('ollama_model',ocrEngine==='ollama'?(document.getElementById('ocr-ollama-model').value||''):'');
|
||||||
|
fd.append('openrouter_model',ocrEngine==='openrouter'?(document.getElementById('ocr-or-model')?.value||''):'');
|
||||||
|
const cp=ocrEngine==='openrouter'?(document.getElementById('custom-prompt-or')?.value||''):(document.getElementById('custom-prompt').value||'');
|
||||||
|
fd.append('custom_prompt',cp);
|
||||||
|
try{
|
||||||
|
const url=pending.length===1?'/api/ocr':'/api/ocr/batch';
|
||||||
|
const r=await api('POST',url,fd);const d=await r.json();if(!r.ok)throw new Error(d.detail||'업로드 실패');
|
||||||
|
const items=pending.length===1?[d]:(d.items||[]);
|
||||||
|
let pi=0;
|
||||||
|
ocrQueue.forEach((qItem,qi)=>{
|
||||||
|
if(qItem.status!=='waiting')return;
|
||||||
|
const taskItem=items[pi++];if(!taskItem)return;
|
||||||
|
if(taskItem.error){qItem.status='failed';return}
|
||||||
|
qItem.status='running';qItem.taskId=taskItem.task_id;renderOcrQueue();
|
||||||
|
const t=setInterval(async()=>{
|
||||||
|
try{
|
||||||
|
const r2=await api('GET','/api/status/'+taskItem.task_id);if(r2.status===401){clearInterval(t);showLogin();return}
|
||||||
|
const d2=await r2.json();
|
||||||
|
if(d2.state==='success'){clearInterval(t);qItem.txtFile=d2.txt_file||null;qItem.xlsxFile=d2.xlsx_file||null;qItem.status='done';renderOcrQueue();
|
||||||
|
if(ocrQueue.filter(i=>i.status==='done').length===1&&ocrQueue.filter(i=>i.status==='running').length===0)showOcrResult(d2);
|
||||||
|
if(ocrQueue.every(i=>['done','failed','waiting'].includes(i.status))){const done=ocrQueue.filter(i=>i.status==='done').length;setProg('ocr',100,`완료 ${done}/${ocrQueue.length}개`);setTimeout(()=>document.getElementById('ocr-prog').style.display='none',2000);document.getElementById('ocr-btn').disabled=false;}
|
||||||
|
} else if(d2.state==='failure'){clearInterval(t);qItem.status='failed';renderOcrQueue();}
|
||||||
|
else{const done=ocrQueue.filter(i=>i.status==='done').length;setProg('ocr',20+Math.round((done/ocrQueue.length)*75),d2.message||'처리중...')}
|
||||||
|
}catch{}
|
||||||
|
},1800);
|
||||||
|
});
|
||||||
|
}catch(e){showErr('ocr-err',e.message);document.getElementById('ocr-btn').disabled=false;document.getElementById('ocr-prog').style.display='none'}
|
||||||
|
});
|
||||||
|
function setOcrLoading(on){const isAI=ocrEngine!=='paddle',c=isAI?'var(--purple)':'var(--accent)';document.getElementById('ocr-btn').disabled=on;document.getElementById('ocr-prog').style.display=on?'block':'none';document.getElementById('ocr-wave').style.display=on?'flex':'none';document.getElementById('ocr-pfill').style.background=c;document.getElementById('ocr-ppct').style.color=c;document.querySelectorAll('#ocr-wave .wave-bar').forEach(b=>b.style.background=c);if(on)setProg('ocr',0,'준비 중...')}
|
||||||
function showOcrResult(d){
|
function showOcrResult(d){
|
||||||
ocrOutputTxt=d.txt_file||null;ocrOutputXlsx=d.xlsx_file||null;const io=d.backend==='ollama';
|
ocrOutputTxt=d.txt_file||null;ocrOutputXlsx=d.xlsx_file||null;const io=d.backend!=='paddle';
|
||||||
document.getElementById('ocr-mlines').textContent=(d.line_count||0)+'줄';document.getElementById('ocr-mmode').textContent=d.mode==='structure'?'구조분석':'텍스트';document.getElementById('ocr-mbackend').textContent=io?`Ollama`:'Paddle';document.getElementById('ocr-mtables').textContent=(d.tables||[]).length+'개';
|
document.getElementById('ocr-mlines').textContent=(d.line_count||0)+'줄';document.getElementById('ocr-mmode').textContent=d.mode==='structure'?'구조분석':'텍스트';document.getElementById('ocr-mbackend').textContent=d.backend==='openrouter'?'OpenRouter':d.backend==='ollama'?'Ollama':'Paddle';document.getElementById('ocr-mtables').textContent=(d.tables||[]).length+'개';
|
||||||
document.getElementById('ocr-meta').style.display='flex';document.getElementById('ocr-tabs').style.display='flex';document.getElementById('ocr-empty').style.display='none';document.getElementById('ocr-result').style.display='block';document.getElementById('ocr-result').value=d.full_text||'';
|
document.getElementById('ocr-meta').style.display='flex';document.getElementById('ocr-tabs').style.display='flex';document.getElementById('ocr-empty').style.display='none';document.getElementById('ocr-result').style.display='block';document.getElementById('ocr-result').value=d.full_text||'';
|
||||||
const ll=document.getElementById('ocr-linelist');ll.innerHTML='';(d.lines||[]).forEach(line=>{const c=line.confidence||0,cls=c>=.9?'high':c>=.7?'mid':'low';const row=document.createElement('div');row.className='line-item';row.innerHTML=`<div class="line-conf ${cls}">${io?'AI':Math.round(c*100)+'%'}</div><div class="line-text">${esc(line.text)}</div>`;ll.appendChild(row)});
|
const ll=document.getElementById('ocr-linelist');ll.innerHTML='';(d.lines||[]).forEach(line=>{const c=line.confidence||0,cls=c>=.9?'high':c>=.7?'mid':'low';const row=document.createElement('div');row.className='line-item';row.innerHTML=`<div class="line-conf ${cls}">${io?'AI':Math.round(c*100)+'%'}</div><div class="line-text">${esc(line.text)}</div>`;ll.appendChild(row)});
|
||||||
const tl=document.getElementById('ocr-tablelist'),te=document.getElementById('ocr-tableempty');tl.innerHTML='';const tables=d.tables||[];te.style.display=tables.length?'none':'flex';tables.forEach((t,i)=>{const w=document.createElement('div');w.innerHTML=`<div class="table-title">표 ${i+1} — ${t.rows||0}행 × ${t.cols||0}열</div><div class="table-wrapper">${(t.html||'').replace(/<table/g,'<table class="ocr-table"')}</div>`;tl.appendChild(w)});
|
const tl=document.getElementById('ocr-tablelist'),te=document.getElementById('ocr-tableempty');tl.innerHTML='';const tables=d.tables||[];te.style.display=tables.length?'none':'flex';tables.forEach((t,i)=>{const w=document.createElement('div');w.innerHTML=`<div class="table-title">표 ${i+1} — ${t.rows||0}행 × ${t.cols||0}열</div><div class="table-wrapper">${(t.html||'').replace(/<table/g,'<table class="ocr-table"')}</div>`;tl.appendChild(w)});
|
||||||
@@ -898,7 +1128,12 @@ function showOcrResult(d){
|
|||||||
document.getElementById('ocr-copy').addEventListener('click',()=>copyText(document.getElementById('ocr-result').value,document.getElementById('ocr-copy')));
|
document.getElementById('ocr-copy').addEventListener('click',()=>copyText(document.getElementById('ocr-result').value,document.getElementById('ocr-copy')));
|
||||||
document.getElementById('ocr-dl-txt').addEventListener('click',()=>dlFile(ocrOutputTxt));
|
document.getElementById('ocr-dl-txt').addEventListener('click',()=>dlFile(ocrOutputTxt));
|
||||||
document.getElementById('ocr-dl-xlsx').addEventListener('click',()=>dlFile(ocrOutputXlsx));
|
document.getElementById('ocr-dl-xlsx').addEventListener('click',()=>dlFile(ocrOutputXlsx));
|
||||||
document.getElementById('ocr-new').addEventListener('click',()=>{ocrFile=null;ocrInput.value='';ocrOutputTxt=null;ocrOutputXlsx=null;['ocr-info','ocr-preview-wrap','ocr-prog','ocr-err','ocr-meta','ocr-tabs','ocr-actions'].forEach(id=>document.getElementById(id).style.display='none');document.getElementById('ocr-empty').style.display='flex';document.getElementById('ocr-result').style.display='none';document.getElementById('ocr-result').value='';document.getElementById('ocr-linelist').innerHTML='';document.getElementById('ocr-tablelist').innerHTML='';document.getElementById('ocr-btn').disabled=true;resetTabs('ocr-tabs')});
|
document.getElementById('ocr-new').addEventListener('click',()=>{
|
||||||
|
ocrQueue=[];ocrInput.value='';ocrOutputTxt=null;ocrOutputXlsx=null;renderOcrQueue();
|
||||||
|
['ocr-prog','ocr-err','ocr-meta','ocr-tabs','ocr-actions'].forEach(id=>document.getElementById(id).style.display='none');
|
||||||
|
document.getElementById('ocr-empty').style.display='flex';document.getElementById('ocr-result').style.display='none';document.getElementById('ocr-result').value='';document.getElementById('ocr-linelist').innerHTML='';document.getElementById('ocr-tablelist').innerHTML='';document.getElementById('ocr-btn').disabled=true;resetTabs('ocr-tabs');
|
||||||
|
});
|
||||||
|
|
||||||
|
|
||||||
// ══ HISTORY ══
|
// ══ HISTORY ══
|
||||||
document.querySelectorAll('.hist-filter-btn').forEach(btn=>{btn.addEventListener('click',()=>{document.querySelectorAll('.hist-filter-btn').forEach(b=>b.classList.remove('active'));btn.classList.add('active');histType=btn.dataset.type;histPage=1;loadHistory()})});
|
document.querySelectorAll('.hist-filter-btn').forEach(btn=>{btn.addEventListener('click',()=>{document.querySelectorAll('.hist-filter-btn').forEach(b=>b.classList.remove('active'));btn.classList.add('active');histType=btn.dataset.type;histPage=1;loadHistory()})});
|
||||||
@@ -1153,70 +1388,36 @@ async function copyText(text,btn){try{await navigator.clipboard.writeText(text);
|
|||||||
|
|
||||||
// ══ OPENROUTER ══
|
// ══ OPENROUTER ══
|
||||||
async function loadOrModels(){
|
async function loadOrModels(){
|
||||||
try{
|
try{const r=await api('GET','/api/openrouter/models');const d=await r.json();
|
||||||
const r=await api('GET','/api/openrouter/models');const d=await r.json();
|
|
||||||
const wrap=document.getElementById('or-models-wrap');
|
const wrap=document.getElementById('or-models-wrap');
|
||||||
if(d.connected){
|
if(d.connected){orModels=d.models||[];orVisionModels=d.vision_models||[];
|
||||||
orModels=d.models||[];orVisionModels=d.vision_models||[];orTextModels=d.text_models||[];
|
wrap.style.display='block';document.getElementById('or-connected-badge').textContent=`✓ 연결됨 — Vision ${orVisionModels.length}개 / 전체 ${orModels.length}개`;populateOrSelects('vision');}
|
||||||
wrap.style.display='block';
|
else wrap.style.display='none';
|
||||||
document.getElementById('or-connected-badge').textContent=`✓ 연결됨 — Vision ${orVisionModels.length}개 / 전체 ${orModels.length}개`;
|
|
||||||
populateOrSelects('vision');
|
|
||||||
} else {
|
|
||||||
wrap.style.display='none';
|
|
||||||
}
|
|
||||||
}catch{}
|
}catch{}
|
||||||
}
|
}
|
||||||
|
|
||||||
let orFilter='vision';
|
let orFilter='vision';
|
||||||
document.querySelectorAll('.or-model-tab').forEach(btn=>{
|
document.querySelectorAll('.or-model-tab').forEach(btn=>{btn.addEventListener('click',()=>{document.querySelectorAll('.or-model-tab').forEach(b=>b.classList.remove('active'));btn.classList.add('active');orFilter=btn.dataset.filter;populateOrSelects(orFilter)})});
|
||||||
btn.addEventListener('click',()=>{
|
|
||||||
document.querySelectorAll('.or-model-tab').forEach(b=>b.classList.remove('active'));
|
|
||||||
btn.classList.add('active');orFilter=btn.dataset.filter;populateOrSelects(orFilter);
|
|
||||||
});
|
|
||||||
});
|
|
||||||
|
|
||||||
function populateOrSelects(filter){
|
function populateOrSelects(filter){
|
||||||
filter=filter||orFilter;
|
filter=filter||orFilter;const list=filter==='vision'?orVisionModels:filter==='text'?orTextModels:orModels;
|
||||||
const list = filter==='vision'?orVisionModels:filter==='text'?orTextModels:orModels;
|
const fillOr=(sel,def)=>{if(!sel)return;const cur=sel.value||def||'';sel.innerHTML='<option value="">(없음)</option>';list.forEach(m=>{const o=document.createElement('option');o.value=m;o.textContent=m;if(m===cur)o.selected=true;sel.appendChild(o)})};
|
||||||
const fillOr=(sel,def)=>{
|
fillOr(document.getElementById('setting-or-stt-model'),appSettings.openrouter_stt_model);
|
||||||
const cur=sel.value||def||'';
|
|
||||||
sel.innerHTML='<option value="">(없음)</option>';
|
|
||||||
list.forEach(m=>{const o=document.createElement('option');o.value=m;o.textContent=m;if(m===cur)o.selected=true;sel.appendChild(o)});
|
|
||||||
};
|
|
||||||
const sttSel=document.getElementById('setting-or-stt-model');
|
|
||||||
const ocrSel=document.getElementById('setting-or-ocr-model');
|
const ocrSel=document.getElementById('setting-or-ocr-model');
|
||||||
const sttPage=document.getElementById('stt-or-model');
|
if(ocrSel){const cur=ocrSel.value||appSettings.openrouter_ocr_model||'';ocrSel.innerHTML='<option value="">(없음)</option>';orVisionModels.forEach(m=>{const o=document.createElement('option');o.value=m;o.textContent=m;if(m===cur)o.selected=true;ocrSel.appendChild(o)})}
|
||||||
const ocrPage=document.getElementById('ocr-or-model');
|
fillOr(document.getElementById('stt-or-model'),appSettings.openrouter_stt_model);
|
||||||
if(sttSel)fillOr(sttSel,appSettings.openrouter_stt_model);
|
const ocrPage=document.getElementById('ocr-or-model');if(ocrPage){const cur=ocrPage.value||appSettings.openrouter_ocr_model||'';ocrPage.innerHTML='<option value="">설정 기본 모델 사용</option>';orVisionModels.forEach(m=>{const o=document.createElement('option');o.value=m;o.textContent=m;if(m===cur)o.selected=true;ocrPage.appendChild(o)})}
|
||||||
if(ocrSel){
|
|
||||||
// OCR은 Vision만
|
|
||||||
const vlist=filter==='text'?[]:orVisionModels;
|
|
||||||
const cur=ocrSel.value||appSettings.openrouter_ocr_model||'';
|
|
||||||
ocrSel.innerHTML='<option value="">(없음)</option>';
|
|
||||||
vlist.forEach(m=>{const o=document.createElement('option');o.value=m;o.textContent=m;if(m===cur)o.selected=true;ocrSel.appendChild(o)});
|
|
||||||
}
|
|
||||||
if(sttPage)fillOr(sttPage,appSettings.openrouter_stt_model);
|
|
||||||
if(ocrPage){
|
|
||||||
const cur=ocrPage.value||appSettings.openrouter_ocr_model||'';
|
|
||||||
ocrPage.innerHTML='<option value="">설정 기본 모델 사용</option>';
|
|
||||||
orVisionModels.forEach(m=>{const o=document.createElement('option');o.value=m;o.textContent=m;if(m===cur)o.selected=true;ocrPage.appendChild(o)});
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
|
document.getElementById('btn-or-test')?.addEventListener('click',async()=>{
|
||||||
document.getElementById('btn-or-test').addEventListener('click',async()=>{
|
const key=document.getElementById('or-api-key').value.trim(),url=document.getElementById('or-url').value.trim()||'https://openrouter.ai/api/v1';
|
||||||
const key=document.getElementById('or-api-key').value.trim();
|
|
||||||
const url=document.getElementById('or-url').value.trim()||'https://openrouter.ai/api/v1';
|
|
||||||
const result=document.getElementById('or-test-result');
|
const result=document.getElementById('or-test-result');
|
||||||
if(!key){result.style.display='block';result.style.color='var(--warn)';result.textContent='API 키를 입력하세요';return}
|
if(!key){result.style.display='block';result.style.color='var(--warn)';result.textContent='API 키를 입력하세요';return}
|
||||||
result.style.display='block';result.style.color='var(--muted)';result.textContent='연결 중...';
|
result.style.display='block';result.style.color='var(--muted)';result.textContent='연결 중...';
|
||||||
try{
|
try{const fd=new FormData();fd.append('api_key',key);fd.append('base_url',url);
|
||||||
const fd=new FormData();fd.append('api_key',key);fd.append('base_url',url);
|
|
||||||
const r=await api('POST','/api/openrouter/test',fd);const d=await r.json();
|
const r=await api('POST','/api/openrouter/test',fd);const d=await r.json();
|
||||||
result.style.color=d.ok?'var(--accent)':'var(--warn)';result.textContent=d.message;
|
result.style.color=d.ok?'var(--accent)':'var(--warn)';result.textContent=d.message;if(d.ok)loadOrModels();}
|
||||||
if(d.ok)loadOrModels();
|
catch{result.style.color='var(--warn)';result.textContent='요청 실패'}
|
||||||
}catch{result.style.color='var(--warn)';result.textContent='요청 실패'}
|
|
||||||
});
|
});
|
||||||
|
|
||||||
|
loadLanguages();
|
||||||
checkAuth();
|
checkAuth();
|
||||||
</script>
|
</script>
|
||||||
</body>
|
</body>
|
||||||
|
|||||||
322
app/tasks.py
322
app/tasks.py
@@ -1,4 +1,10 @@
|
|||||||
import os
|
"""
|
||||||
|
STT Celery Tasks
|
||||||
|
- faster-whisper 변환
|
||||||
|
- Ollama / OpenRouter 후처리 (교정 또는 번역)
|
||||||
|
- SRT / VTT / TXT 자막 파일 생성
|
||||||
|
"""
|
||||||
|
import os, json
|
||||||
import httpx
|
import httpx
|
||||||
from celery import Celery
|
from celery import Celery
|
||||||
from ocr_tasks import ocr_task # noqa: F401
|
from ocr_tasks import ocr_task # noqa: F401
|
||||||
@@ -31,13 +37,144 @@ def get_model():
|
|||||||
from faster_whisper import WhisperModel
|
from faster_whisper import WhisperModel
|
||||||
kwargs = dict(device=DEVICE, compute_type=COMPUTE_TYPE)
|
kwargs = dict(device=DEVICE, compute_type=COMPUTE_TYPE)
|
||||||
if CPU_THREADS is not None: kwargs["cpu_threads"] = CPU_THREADS
|
if CPU_THREADS is not None: kwargs["cpu_threads"] = CPU_THREADS
|
||||||
print(f"[Whisper] 로딩: {MODEL_SIZE} / {DEVICE} / {COMPUTE_TYPE} / threads={CPU_THREADS or 'auto'}")
|
print(f"[Whisper] 로딩: {MODEL_SIZE}/{DEVICE}/{COMPUTE_TYPE}/threads={CPU_THREADS or 'auto'}")
|
||||||
_model = WhisperModel(MODEL_SIZE, **kwargs)
|
_model = WhisperModel(MODEL_SIZE, **kwargs)
|
||||||
print("[Whisper] 로드 완료")
|
print("[Whisper] 로드 완료")
|
||||||
return _model
|
return _model
|
||||||
|
|
||||||
|
|
||||||
# ── 후처리: Ollama ────────────────────────────────────────────
|
# ══════════════════════════════════════════════════════════════
|
||||||
|
# 언어 코드 매핑
|
||||||
|
# ══════════════════════════════════════════════════════════════
|
||||||
|
LANG_NAMES = {
|
||||||
|
"ko":"한국어","en":"English","ja":"日本語","zh":"中文","fr":"Français",
|
||||||
|
"de":"Deutsch","es":"Español","it":"Italiano","pt":"Português","ru":"Русский",
|
||||||
|
"ar":"العربية","vi":"Tiếng Việt","th":"ไทย","id":"Bahasa Indonesia",
|
||||||
|
"nl":"Nederlands","pl":"Polski","tr":"Türkçe","sv":"Svenska","uk":"Українська",
|
||||||
|
}
|
||||||
|
|
||||||
|
def _lang_name(code: str) -> str:
|
||||||
|
return LANG_NAMES.get(code, code)
|
||||||
|
|
||||||
|
|
||||||
|
# ══════════════════════════════════════════════════════════════
|
||||||
|
# 자막 포맷 생성
|
||||||
|
# ══════════════════════════════════════════════════════════════
|
||||||
|
def _fmt_srt_time(s: float) -> str:
|
||||||
|
"""초 → SRT 시간 포맷 00:00:00,000"""
|
||||||
|
ms = int(round(s * 1000))
|
||||||
|
h, rem = divmod(ms, 3600000)
|
||||||
|
m, rem = divmod(rem, 60000)
|
||||||
|
sec, ms = divmod(rem, 1000)
|
||||||
|
return f"{h:02d}:{m:02d}:{sec:02d},{ms:03d}"
|
||||||
|
|
||||||
|
def _fmt_vtt_time(s: float) -> str:
|
||||||
|
"""초 → VTT 시간 포맷 00:00:00.000"""
|
||||||
|
return _fmt_srt_time(s).replace(",", ".")
|
||||||
|
|
||||||
|
def _make_srt(segments: list) -> str:
|
||||||
|
lines = []
|
||||||
|
for i, seg in enumerate(segments, 1):
|
||||||
|
lines.append(str(i))
|
||||||
|
lines.append(f"{_fmt_srt_time(seg['start'])} --> {_fmt_srt_time(seg['end'])}")
|
||||||
|
lines.append(seg["text"].strip())
|
||||||
|
lines.append("")
|
||||||
|
return "\n".join(lines)
|
||||||
|
|
||||||
|
def _make_vtt(segments: list) -> str:
|
||||||
|
lines = ["WEBVTT", ""]
|
||||||
|
for i, seg in enumerate(segments, 1):
|
||||||
|
lines.append(f"{i}")
|
||||||
|
lines.append(f"{_fmt_vtt_time(seg['start'])} --> {_fmt_vtt_time(seg['end'])}")
|
||||||
|
lines.append(seg["text"].strip())
|
||||||
|
lines.append("")
|
||||||
|
return "\n".join(lines)
|
||||||
|
|
||||||
|
|
||||||
|
# ══════════════════════════════════════════════════════════════
|
||||||
|
# 번역 (Ollama / OpenRouter)
|
||||||
|
# ══════════════════════════════════════════════════════════════
|
||||||
|
def _translate_segments(segments: list, target_lang: str,
|
||||||
|
use_openrouter: bool, model: str,
|
||||||
|
openrouter_url: str, openrouter_key: str,
|
||||||
|
task_self=None) -> list:
|
||||||
|
"""세그먼트 텍스트를 target_lang으로 번역해서 새 세그먼트 리스트 반환"""
|
||||||
|
if not model or not target_lang:
|
||||||
|
return segments
|
||||||
|
|
||||||
|
lang_name = _lang_name(target_lang)
|
||||||
|
translated = []
|
||||||
|
|
||||||
|
# 세그먼트를 청크로 묶어서 번역 (API 호출 최소화)
|
||||||
|
# 최대 20개씩 묶음
|
||||||
|
CHUNK = 20
|
||||||
|
chunks = [segments[i:i+CHUNK] for i in range(0, len(segments), CHUNK)]
|
||||||
|
|
||||||
|
for ci, chunk in enumerate(chunks):
|
||||||
|
if task_self:
|
||||||
|
pct = 85 + int((ci / len(chunks)) * 10)
|
||||||
|
task_self.update_state(state="PROGRESS",
|
||||||
|
meta={"progress": pct,
|
||||||
|
"message": f"번역 중... ({ci*CHUNK+1}/{len(segments)})"})
|
||||||
|
|
||||||
|
# JSON 배열로 텍스트만 전달
|
||||||
|
texts = [seg["text"].strip() for seg in chunk]
|
||||||
|
prompt = (
|
||||||
|
f"다음 문장들을 {lang_name}로 번역해줘.\n"
|
||||||
|
f"JSON 배열 형식으로만 답해줘. 설명 없이 번역된 문장 배열만 출력해.\n"
|
||||||
|
f"입력 배열과 동일한 개수, 동일한 순서로 출력해.\n\n"
|
||||||
|
f"입력: {json.dumps(texts, ensure_ascii=False)}"
|
||||||
|
)
|
||||||
|
|
||||||
|
try:
|
||||||
|
if use_openrouter and openrouter_key:
|
||||||
|
resp = httpx.post(
|
||||||
|
f"{openrouter_url.rstrip('/')}/chat/completions",
|
||||||
|
headers={"Authorization": f"Bearer {openrouter_key}",
|
||||||
|
"HTTP-Referer": "https://voicescript.local",
|
||||||
|
"Content-Type": "application/json"},
|
||||||
|
json={"model": model,
|
||||||
|
"messages": [{"role":"user","content":prompt}],
|
||||||
|
"temperature": 0.2},
|
||||||
|
timeout=float(OLLAMA_TIMEOUT),
|
||||||
|
)
|
||||||
|
resp.raise_for_status()
|
||||||
|
raw = resp.json()["choices"][0]["message"]["content"].strip()
|
||||||
|
else:
|
||||||
|
resp = httpx.post(f"{OLLAMA_URL}/api/chat",
|
||||||
|
json={"model": model,
|
||||||
|
"messages": [{"role":"user","content":prompt}],
|
||||||
|
"stream": False, "options": {"temperature": 0.2}},
|
||||||
|
timeout=float(OLLAMA_TIMEOUT))
|
||||||
|
resp.raise_for_status()
|
||||||
|
raw = resp.json().get("message",{}).get("content","").strip()
|
||||||
|
|
||||||
|
# JSON 파싱
|
||||||
|
# 코드블록 제거
|
||||||
|
if "```" in raw:
|
||||||
|
raw = raw.split("```")[1].lstrip("json").strip()
|
||||||
|
trans_texts = json.loads(raw)
|
||||||
|
if not isinstance(trans_texts, list):
|
||||||
|
trans_texts = texts # 파싱 실패 시 원본 유지
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
print(f"[번역 실패 chunk {ci}] {e}")
|
||||||
|
trans_texts = texts # 실패 시 원본 유지
|
||||||
|
|
||||||
|
# 번역된 텍스트를 세그먼트에 결합
|
||||||
|
for seg, t_text in zip(chunk, trans_texts):
|
||||||
|
translated.append({**seg, "text": t_text})
|
||||||
|
# 남은 세그먼트 (번역 누락)
|
||||||
|
if len(trans_texts) < len(chunk):
|
||||||
|
for seg in chunk[len(trans_texts):]:
|
||||||
|
translated.append(seg)
|
||||||
|
|
||||||
|
return translated
|
||||||
|
|
||||||
|
|
||||||
|
# ══════════════════════════════════════════════════════════════
|
||||||
|
# Ollama 텍스트 후처리 (교정)
|
||||||
|
# ══════════════════════════════════════════════════════════════
|
||||||
def _ollama_postprocess(text: str, model: str) -> str:
|
def _ollama_postprocess(text: str, model: str) -> str:
|
||||||
if not model or not text.strip(): return text
|
if not model or not text.strip(): return text
|
||||||
prompt = (
|
prompt = (
|
||||||
@@ -46,19 +183,16 @@ def _ollama_postprocess(text: str, model: str) -> str:
|
|||||||
"결과 텍스트만 출력하고 설명은 하지 마.\n\n" + text
|
"결과 텍스트만 출력하고 설명은 하지 마.\n\n" + text
|
||||||
)
|
)
|
||||||
try:
|
try:
|
||||||
resp = httpx.post(f"{OLLAMA_URL}/api/chat", json={
|
resp = httpx.post(f"{OLLAMA_URL}/api/chat",
|
||||||
"model": model,
|
json={"model":model,"messages":[{"role":"user","content":prompt}],
|
||||||
"messages": [{"role":"user","content":prompt}],
|
"stream":False,"options":{"temperature":0.1}},
|
||||||
"stream": False, "options": {"temperature": 0.1},
|
timeout=float(OLLAMA_TIMEOUT))
|
||||||
}, timeout=float(OLLAMA_TIMEOUT))
|
|
||||||
resp.raise_for_status()
|
resp.raise_for_status()
|
||||||
result = resp.json().get("message",{}).get("content","").strip()
|
result = resp.json().get("message",{}).get("content","").strip()
|
||||||
return result if result else text
|
return result if result else text
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
print(f"[Ollama 후처리 실패] {e}"); return text
|
print(f"[Ollama 후처리 실패] {e}"); return text
|
||||||
|
|
||||||
|
|
||||||
# ── 후처리: OpenRouter (OpenAI 호환) ─────────────────────────
|
|
||||||
def _openrouter_postprocess(text: str, model: str, base_url: str, api_key: str) -> str:
|
def _openrouter_postprocess(text: str, model: str, base_url: str, api_key: str) -> str:
|
||||||
if not model or not api_key or not text.strip(): return text
|
if not model or not api_key or not text.strip(): return text
|
||||||
prompt = (
|
prompt = (
|
||||||
@@ -67,21 +201,10 @@ def _openrouter_postprocess(text: str, model: str, base_url: str, api_key: str)
|
|||||||
"결과 텍스트만 출력하고 설명은 하지 마.\n\n" + text
|
"결과 텍스트만 출력하고 설명은 하지 마.\n\n" + text
|
||||||
)
|
)
|
||||||
try:
|
try:
|
||||||
resp = httpx.post(
|
resp = httpx.post(f"{base_url.rstrip('/')}/chat/completions",
|
||||||
f"{base_url.rstrip('/')}/chat/completions",
|
headers={"Authorization":f"Bearer {api_key}","HTTP-Referer":"https://voicescript.local","Content-Type":"application/json"},
|
||||||
headers={
|
json={"model":model,"messages":[{"role":"user","content":prompt}],"temperature":0.1},
|
||||||
"Authorization": f"Bearer {api_key}",
|
timeout=float(OLLAMA_TIMEOUT))
|
||||||
"HTTP-Referer": "https://voicescript.local",
|
|
||||||
"X-Title": "VoiceScript",
|
|
||||||
"Content-Type": "application/json",
|
|
||||||
},
|
|
||||||
json={
|
|
||||||
"model": model,
|
|
||||||
"messages": [{"role":"user","content":prompt}],
|
|
||||||
"temperature": 0.1,
|
|
||||||
},
|
|
||||||
timeout=float(OLLAMA_TIMEOUT),
|
|
||||||
)
|
|
||||||
resp.raise_for_status()
|
resp.raise_for_status()
|
||||||
result = resp.json()["choices"][0]["message"]["content"].strip()
|
result = resp.json()["choices"][0]["message"]["content"].strip()
|
||||||
return result if result else text
|
return result if result else text
|
||||||
@@ -89,30 +212,44 @@ def _openrouter_postprocess(text: str, model: str, base_url: str, api_key: str)
|
|||||||
print(f"[OpenRouter 후처리 실패] {e}"); return text
|
print(f"[OpenRouter 후처리 실패] {e}"); return text
|
||||||
|
|
||||||
|
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ══════════════════════════════════════════════════════════════
|
||||||
# STT Task
|
# 메인 STT Task
|
||||||
# ════════════════════════════════════════════════════════════════
|
# ══════════════════════════════════════════════════════════════
|
||||||
@celery_app.task(bind=True, name="tasks.transcribe_task", queue="stt")
|
@celery_app.task(bind=True, name="tasks.transcribe_task", queue="stt")
|
||||||
def transcribe_task(
|
def transcribe_task(
|
||||||
self,
|
self,
|
||||||
file_id: str,
|
file_id: str,
|
||||||
audio_path: str,
|
audio_path: str,
|
||||||
|
# 후처리
|
||||||
use_ollama: bool = False,
|
use_ollama: bool = False,
|
||||||
ollama_model: str = "",
|
ollama_model: str = "",
|
||||||
use_openrouter: bool = False,
|
use_openrouter: bool = False,
|
||||||
openrouter_model: str = "",
|
openrouter_model: str = "",
|
||||||
openrouter_url: str = "",
|
openrouter_url: str = "",
|
||||||
openrouter_key: str = "",
|
openrouter_key: str = "",
|
||||||
|
# 자막
|
||||||
|
subtitle_mode: bool = False, # True → 자막 파일 생성
|
||||||
|
subtitle_format: str = "srt", # srt | vtt | both
|
||||||
|
translate_to: str = "", # 번역 대상 언어 코드 (없으면 원어 자막)
|
||||||
|
translate_model: str = "", # 번역에 쓸 모델
|
||||||
|
translate_via: str = "ollama",# ollama | openrouter
|
||||||
|
# 원본 언어 강제 지정 (없으면 auto)
|
||||||
|
force_language: str = "",
|
||||||
):
|
):
|
||||||
self.update_state(state="PROGRESS", meta={"progress":5,"message":"모델 준비 중..."})
|
self.update_state(state="PROGRESS", meta={"progress":5,"message":"모델 준비 중..."})
|
||||||
try:
|
try:
|
||||||
model = get_model()
|
model = get_model()
|
||||||
self.update_state(state="PROGRESS", meta={"progress":15,"message":"오디오 분석 중..."})
|
self.update_state(state="PROGRESS", meta={"progress":15,"message":"오디오 분석 중..."})
|
||||||
|
|
||||||
|
lang = force_language.strip() or LANGUAGE
|
||||||
segments_gen, info = model.transcribe(
|
segments_gen, info = model.transcribe(
|
||||||
audio_path, language=LANGUAGE, beam_size=BEAM_SIZE,
|
audio_path,
|
||||||
initial_prompt=INITIAL_PROMPT, vad_filter=True,
|
language=lang,
|
||||||
vad_parameters=dict(min_silence_duration_ms=500), word_timestamps=False,
|
beam_size=BEAM_SIZE,
|
||||||
|
initial_prompt=INITIAL_PROMPT,
|
||||||
|
vad_filter=True,
|
||||||
|
vad_parameters=dict(min_silence_duration_ms=500),
|
||||||
|
word_timestamps=False,
|
||||||
)
|
)
|
||||||
|
|
||||||
self.update_state(state="PROGRESS", meta={"progress":30,"message":"텍스트 변환 중..."})
|
self.update_state(state="PROGRESS", meta={"progress":30,"message":"텍스트 변환 중..."})
|
||||||
@@ -120,63 +257,126 @@ def transcribe_task(
|
|||||||
duration = info.duration
|
duration = info.duration
|
||||||
|
|
||||||
for seg in segments_gen:
|
for seg in segments_gen:
|
||||||
segments.append({"start":round(seg.start,2),"end":round(seg.end,2),"text":seg.text.strip()})
|
segments.append({"start":round(seg.start,3),"end":round(seg.end,3),"text":seg.text.strip()})
|
||||||
parts.append(seg.text.strip())
|
parts.append(seg.text.strip())
|
||||||
if duration > 0:
|
if duration > 0:
|
||||||
pct = 30 + int((seg.end/duration)*50)
|
pct = 30 + int((seg.end/duration)*45)
|
||||||
self.update_state(state="PROGRESS",
|
self.update_state(state="PROGRESS",
|
||||||
meta={"progress":min(pct,80),"message":f"변환 중... {seg.end:.0f}s / {duration:.0f}s"})
|
meta={"progress":min(pct,75),
|
||||||
|
"message":f"변환 중... {seg.end:.0f}s / {duration:.0f}s"})
|
||||||
|
|
||||||
raw_text = "\n".join(parts)
|
raw_text = "\n".join(parts)
|
||||||
full_text = raw_text
|
full_text = raw_text
|
||||||
|
detected_lang = info.language
|
||||||
|
|
||||||
# Ollama 후처리
|
# ── 텍스트 후처리 (교정) ──────────────────────────────
|
||||||
if use_ollama and ollama_model:
|
if use_ollama and ollama_model and not subtitle_mode:
|
||||||
self.update_state(state="PROGRESS",
|
self.update_state(state="PROGRESS",
|
||||||
meta={"progress":85,"message":f"Ollama({ollama_model}) 후처리 중..."})
|
meta={"progress":80,"message":f"Ollama({ollama_model}) 교정 중..."})
|
||||||
full_text = _ollama_postprocess(raw_text, ollama_model)
|
full_text = _ollama_postprocess(raw_text, ollama_model)
|
||||||
|
|
||||||
# OpenRouter 후처리
|
elif use_openrouter and openrouter_model and openrouter_key and not subtitle_mode:
|
||||||
elif use_openrouter and openrouter_model and openrouter_key:
|
|
||||||
self.update_state(state="PROGRESS",
|
self.update_state(state="PROGRESS",
|
||||||
meta={"progress":85,"message":f"OpenRouter({openrouter_model}) 후처리 중..."})
|
meta={"progress":80,"message":f"OpenRouter({openrouter_model}) 교정 중..."})
|
||||||
full_text = _openrouter_postprocess(raw_text, openrouter_model, openrouter_url, openrouter_key)
|
full_text = _openrouter_postprocess(raw_text, openrouter_model, openrouter_url, openrouter_key)
|
||||||
|
|
||||||
self.update_state(state="PROGRESS", meta={"progress":95,"message":"파일 저장 중..."})
|
# ── 자막 모드: 번역 ──────────────────────────────────
|
||||||
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
translated_segments = segments
|
||||||
output_filename = f"{file_id}.txt"
|
is_translated = False
|
||||||
|
|
||||||
with open(os.path.join(OUTPUT_DIR, output_filename), "w", encoding="utf-8") as f:
|
if subtitle_mode and translate_to and translate_to != detected_lang:
|
||||||
f.write(f"# 변환 결과\n# 언어: {info.language} | 재생 시간: {duration:.1f}초")
|
t_model = translate_model or (ollama_model if translate_via=="ollama" else openrouter_model)
|
||||||
if use_ollama and ollama_model:
|
t_via_or = (translate_via == "openrouter" and bool(openrouter_key))
|
||||||
f.write(f" | Ollama: {ollama_model}")
|
self.update_state(state="PROGRESS",
|
||||||
elif use_openrouter and openrouter_model:
|
meta={"progress":82,
|
||||||
f.write(f" | OpenRouter: {openrouter_model}")
|
"message":f"{_lang_name(translate_to)}로 번역 중..."})
|
||||||
f.write("\n\n## 전체 텍스트\n\n" + full_text + "\n\n")
|
translated_segments = _translate_segments(
|
||||||
f.write("## 타임스탬프별 세그먼트\n\n")
|
segments, translate_to,
|
||||||
for seg in segments:
|
use_openrouter=t_via_or,
|
||||||
f.write(f"[{_fmt(seg['start'])} → {_fmt(seg['end'])}] {seg['text']}\n")
|
model=t_model,
|
||||||
|
openrouter_url=openrouter_url,
|
||||||
|
openrouter_key=openrouter_key,
|
||||||
|
task_self=self,
|
||||||
|
)
|
||||||
|
is_translated = True
|
||||||
|
# 번역된 전체 텍스트
|
||||||
|
full_text = "\n".join(s["text"] for s in translated_segments)
|
||||||
|
|
||||||
|
self.update_state(state="PROGRESS", meta={"progress":93,"message":"파일 저장 중..."})
|
||||||
|
os.makedirs(OUTPUT_DIR, exist_ok=True)
|
||||||
|
|
||||||
|
result_files = {}
|
||||||
|
|
||||||
|
# ── TXT 저장 ─────────────────────────────────────────
|
||||||
|
txt_filename = f"{file_id}.txt"
|
||||||
|
with open(os.path.join(OUTPUT_DIR, txt_filename), "w", encoding="utf-8") as f:
|
||||||
|
f.write(f"# 변환 결과\n")
|
||||||
|
f.write(f"# 언어: {detected_lang} | 재생 시간: {duration:.1f}초\n")
|
||||||
|
if is_translated:
|
||||||
|
f.write(f"# 번역: {_lang_name(translate_to)}\n")
|
||||||
|
f.write(f"\n## 전체 텍스트\n\n{full_text}\n\n")
|
||||||
|
f.write(f"## 타임스탬프별 세그먼트\n\n")
|
||||||
|
for seg in (translated_segments if is_translated else segments):
|
||||||
|
f.write(f"[{_fmt_ts(seg['start'])} → {_fmt_ts(seg['end'])}] {seg['text']}\n")
|
||||||
|
result_files["txt"] = txt_filename
|
||||||
|
|
||||||
|
# ── 자막 파일 저장 ────────────────────────────────────
|
||||||
|
if subtitle_mode:
|
||||||
|
sub_segs = translated_segments if is_translated else segments
|
||||||
|
lang_suffix = f".{translate_to}" if is_translated else f".{detected_lang}"
|
||||||
|
|
||||||
|
if subtitle_format in ("srt", "both"):
|
||||||
|
srt_fn = f"{file_id}{lang_suffix}.srt"
|
||||||
|
with open(os.path.join(OUTPUT_DIR, srt_fn), "w", encoding="utf-8") as f:
|
||||||
|
f.write(_make_srt(sub_segs))
|
||||||
|
result_files["srt"] = srt_fn
|
||||||
|
|
||||||
|
if subtitle_format in ("vtt", "both"):
|
||||||
|
vtt_fn = f"{file_id}{lang_suffix}.vtt"
|
||||||
|
with open(os.path.join(OUTPUT_DIR, vtt_fn), "w", encoding="utf-8") as f:
|
||||||
|
f.write(_make_vtt(sub_segs))
|
||||||
|
result_files["vtt"] = vtt_fn
|
||||||
|
|
||||||
|
# 원본 언어 SRT도 함께 (번역 시)
|
||||||
|
if is_translated and subtitle_format in ("srt","both"):
|
||||||
|
orig_fn = f"{file_id}.{detected_lang}.srt"
|
||||||
|
with open(os.path.join(OUTPUT_DIR, orig_fn), "w", encoding="utf-8") as f:
|
||||||
|
f.write(_make_srt(segments))
|
||||||
|
result_files["srt_original"] = orig_fn
|
||||||
|
|
||||||
try: os.remove(audio_path)
|
try: os.remove(audio_path)
|
||||||
except: pass
|
except: pass
|
||||||
|
|
||||||
return {
|
return {
|
||||||
|
# 기본 STT 결과
|
||||||
"text": full_text,
|
"text": full_text,
|
||||||
"raw_text": raw_text,
|
"raw_text": raw_text,
|
||||||
"segments": segments,
|
"segments": translated_segments if is_translated else segments,
|
||||||
"language": info.language,
|
"orig_segments": segments,
|
||||||
|
"language": detected_lang,
|
||||||
"duration": round(duration, 1),
|
"duration": round(duration, 1),
|
||||||
"output_file": output_filename,
|
# 후처리
|
||||||
"ollama_used": use_ollama and bool(ollama_model),
|
"ollama_used": use_ollama and bool(ollama_model) and not subtitle_mode,
|
||||||
"ollama_model": ollama_model if (use_ollama and ollama_model) else "",
|
"ollama_model": ollama_model if (use_ollama and not subtitle_mode) else "",
|
||||||
"openrouter_used": use_openrouter and bool(openrouter_model) and bool(openrouter_key),
|
"openrouter_used": use_openrouter and bool(openrouter_model) and not subtitle_mode,
|
||||||
"openrouter_model": openrouter_model if (use_openrouter and openrouter_model) else "",
|
"openrouter_model": openrouter_model if (use_openrouter and not subtitle_mode) else "",
|
||||||
|
# 자막
|
||||||
|
"subtitle_mode": subtitle_mode,
|
||||||
|
"subtitle_format": subtitle_format,
|
||||||
|
"translated": is_translated,
|
||||||
|
"translate_to": translate_to if is_translated else "",
|
||||||
|
"translate_model": translate_model if is_translated else "",
|
||||||
|
# 파일
|
||||||
|
"output_file": result_files.get("txt",""),
|
||||||
|
"srt_file": result_files.get("srt",""),
|
||||||
|
"vtt_file": result_files.get("vtt",""),
|
||||||
|
"srt_original_file": result_files.get("srt_original",""),
|
||||||
}
|
}
|
||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
raise Exception(f"변환 실패: {str(e)}")
|
raise Exception(f"변환 실패: {str(e)}")
|
||||||
|
|
||||||
|
|
||||||
def _fmt(s):
|
def _fmt_ts(s: float) -> str:
|
||||||
m, sec = divmod(int(s), 60)
|
m, sec = divmod(int(s), 60)
|
||||||
return f"{m:02d}:{sec:02d}"
|
return f"{m:02d}:{sec:02d}"
|
||||||
|
|||||||
Reference in New Issue
Block a user