Spaces:
Sleeping
Sleeping
File size: 1,296 Bytes
2e94685 b5c921b 2e94685 82891c7 2e94685 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
import os
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
# Application Configuration
APP_TITLE = "Voice Analysis Toolkit"
APP_DESCRIPTION = (
"Upload an audio file to transcribe, summarize, analyze sentiment, "
"and ask questions about its content. All processing is done locally "
"and your data remains private."
)
# Model Configuration
MODEL_PROVIDER = "local" # Set to 'local' or 'openai'
# Local model settings (if MODEL_PROVIDER is 'local')
LOCAL_TRANSCRIPTION_MODEL = "openai/whisper-base.en"
LOCAL_ANALYSIS_MODEL = "HuggingFaceH4/zephyr-7b-beta"
# OpenAI API settings (if MODEL_PROVIDER is 'openai')
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
OPENAI_TRANSCRIPTION_MODEL = "whisper-1"
OPENAI_ANALYSIS_MODEL = "gpt-3.5-turbo"
# File Validation Configuration
# Maximum file size in megabytes (MB)
MAX_FILE_SIZE_MB = 25
# Maximum audio duration in minutes
MAX_FILE_LENGTH_MINS = 15
# List of allowed audio file extensions (add more as needed)
ALLOWED_FILE_EXTENSIONS = [".mp3", ".wav", ".m4a", ".flac", ".ogg"]
# Logging Configuration
LOG_FILE_PATH = os.path.join("/tmp", "logs", "app.log")
os.makedirs(os.path.dirname(LOG_FILE_PATH), exist_ok=True)
LOG_LEVEL = "INFO" # Can be "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"
|