PoturaevPetr
46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
import os
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from pathlib import Path
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# Базовые пути
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BASE_DIR = Path(__file__).resolve().parent.parent
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UPLOAD_FOLDER = BASE_DIR / "uploads"
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UPLOAD_FOLDER.mkdir(exist_ok=True)
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# Audio files path (shared with Calls_WEB_Client_main)
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AUDIOFILES_PATH = os.getenv("AUDIOFILES_PATH", "/app/audiofiles")
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# Database
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DATABASE_URL = os.getenv("DATABASE_URL", "sqlite:///./speech_analytics.db")
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# API Settings
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API_V1_PREFIX = "/api/v1"
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MAX_UPLOAD_SIZE = 100 * 1024 * 1024 # 100MB
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ALLOWED_AUDIO_EXTENSIONS = {".mp3", ".wav", ".ogg", ".flac", ".m4a", ".aac"}
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# Application
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APP_TITLE = "Speech Analytics API"
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APP_VERSION = "1.0.0"
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PORT = int(os.getenv("PORT", "5008"))
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HOST = os.getenv("HOST", "localhost")
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# GigaAM API Configuration
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GIGAAM_API_URL = os.getenv("GIGAAM_API_URL", "http://host.docker.internal:5002")
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AUDIOFILES_PATH = os.path.join(os.getcwd(), os.getenv("FILESAPTH", "audiofiles"))
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# Calls_WEB_Client_main Webhook Configuration
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CALLS_WEB_CLIENT_URL = os.getenv(
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"CALLS_WEB_CLIENT_URL",
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"http://host.docker.internal:8642"
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)
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WEBHOOK_ENDPOINT = f"{CALLS_WEB_CLIENT_URL}/api/transcription/webhook"
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WEBHOOK_API_KEY = os.getenv("WEBHOOK_API_KEY", "webhook_secret_key")
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# Auto-restore recognition on startup
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ENABLE_AUTO_RESTORE = os.getenv("ENABLE_AUTO_RESTORE", "true").lower() == "true"
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AUTO_RESTORE_LIMIT = int(os.getenv("AUTO_RESTORE_LIMIT", "100")) # Максимум файлов для восстановления
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AUTO_RESTORE_DELAY = int(os.getenv("AUTO_RESTORE_DELAY", "5")) # Задержка перед запуском (секунды)
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# Recognition retry policy (FileAudioAPI side)
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MAX_RECOGNITION_ATTEMPTS = int(os.getenv("MAX_RECOGNITION_ATTEMPTS", "3")) |