290 lines
11 KiB
Plaintext
290 lines
11 KiB
Plaintext
# =============================================================================
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# Transcription Connector Configuration
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# =============================================================================
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#
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# DictIA supports multiple transcription providers through a connector-based
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# architecture. This file documents all available configuration options.
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#
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# Quick Start (Simplified):
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# 1. For OpenAI with diarization: Set TRANSCRIPTION_MODEL=gpt-4o-transcribe-diarize
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# 2. For self-hosted ASR: Set ASR_BASE_URL=http://your-asr:9000
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# 3. For legacy Whisper: Set TRANSCRIPTION_API_KEY and optionally TRANSCRIPTION_MODEL
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#
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# Auto-Detection Priority:
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# 1. TRANSCRIPTION_CONNECTOR - explicit connector name (if you need full control)
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# 2. ASR_BASE_URL - if set, uses ASR endpoint connector
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# 3. TRANSCRIPTION_MODEL contains 'gpt-4o' - uses OpenAI Transcribe connector
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# 4. Default - uses OpenAI Whisper connector with TRANSCRIPTION_MODEL or whisper-1
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# =============================================================================
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# TEXT GENERATION MODEL (REQUIRED for summaries, titles, chat)
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# =============================================================================
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# DictIA uses a text/LLM model for generating summaries, titles, and chat.
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# This is separate from the transcription model (STT).
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#
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# You can use OpenRouter (recommended - access to many models) or direct OpenAI API.
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# OpenRouter example (recommended - supports many models):
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TEXT_MODEL_BASE_URL=https://openrouter.ai/api/v1
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TEXT_MODEL_API_KEY=your_openrouter_api_key
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TEXT_MODEL_NAME=openai/gpt-4o-mini
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# OpenAI direct example:
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# TEXT_MODEL_BASE_URL=https://api.openai.com/v1
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# TEXT_MODEL_API_KEY=sk-your_openai_api_key
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# TEXT_MODEL_NAME=gpt-4o-mini
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# --- GPT-5 Specific Settings (only used with OpenAI API and GPT-5 models) ---
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# Reasoning effort: minimal, low, medium, high (default: medium)
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GPT5_REASONING_EFFORT=medium
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# Verbosity: low, medium, high (default: medium)
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GPT5_VERBOSITY=medium
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# --- Chat Model Configuration (Optional) ---
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# Configure a separate model for real-time chat interactions.
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# If not set, chat will use the TEXT_MODEL_* settings above.
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# CHAT_MODEL_API_KEY=your_chat_api_key
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# CHAT_MODEL_BASE_URL=https://openrouter.ai/api/v1
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# CHAT_MODEL_NAME=openai/gpt-4o
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# =============================================================================
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# CONNECTOR SELECTION (Auto-detected if not set)
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# =============================================================================
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# Options: openai_whisper, openai_transcribe, asr_endpoint
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# Leave empty to auto-detect based on other settings
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# TRANSCRIPTION_CONNECTOR=
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# Feature flag to enable/disable new connector architecture (default: true)
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# Set to false to use legacy code path for troubleshooting
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# USE_NEW_TRANSCRIPTION_ARCHITECTURE=true
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# =============================================================================
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# OPENAI CONFIGURATION (Required for openai_whisper and openai_transcribe)
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# =============================================================================
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TRANSCRIPTION_API_KEY=your_openai_api_key
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TRANSCRIPTION_BASE_URL=https://api.openai.com/v1
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# Model Selection - determines which connector is used:
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#
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# whisper-1 - Legacy Whisper model, no diarization, $0.006/min
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# Supports: srt, vtt, json, verbose_json output formats
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#
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# gpt-4o-transcribe - High quality transcription, no diarization, $0.006/min
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# Better accuracy than whisper-1, accepts prompts
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#
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# gpt-4o-mini-transcribe - Cost-effective option, no diarization, $0.003/min
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# Good for high-volume, budget-conscious use
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#
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# gpt-4o-transcribe-diarize - Speaker diarization!, $0.006/min
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# Identifies speakers as A, B, C, D...
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# Requires chunking_strategy for audio >30s
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#
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TRANSCRIPTION_MODEL=gpt-4o-transcribe-diarize
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# Legacy Whisper model name (used when TRANSCRIPTION_MODEL is not set)
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# WHISPER_MODEL=whisper-1
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# =============================================================================
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# ASR ENDPOINT CONFIGURATION (For self-hosted whisper services)
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# =============================================================================
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# Note: USE_ASR_ENDPOINT is deprecated. Just set ASR_BASE_URL instead.
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# The connector will auto-detect ASR mode when ASR_BASE_URL is set.
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# USE_ASR_ENDPOINT=true # Deprecated - kept for backwards compatibility
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# Base URL of your ASR service (required if USE_ASR_ENDPOINT=true)
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# Supports: whisper-asr-webservice, WhisperX, and compatible services
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# ASR_BASE_URL=http://whisper-asr:9000
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# Request timeout in seconds (default: 1800 = 30 minutes)
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# Increase for very long audio files
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# ASR_TIMEOUT=1800
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# Enable speaker diarization (default: true)
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# ASR_DIARIZE=true
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# Speaker count hints (optional, helps with diarization accuracy)
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# ASR_MIN_SPEAKERS=1
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# ASR_MAX_SPEAKERS=5
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# Return speaker embeddings for speaker identification (WhisperX only)
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# Enables automatic speaker matching across recordings
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# ASR_RETURN_SPEAKER_EMBEDDINGS=false
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# =============================================================================
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# CHUNKING CONFIGURATION (For large files)
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# =============================================================================
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# Chunking is now connector-aware with this priority:
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# 1. Connector handles internally (openai_transcribe, asr_endpoint) → No app chunking
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# 2. ENABLE_CHUNKING=false → Disable chunking (only affects openai_whisper)
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# 3. CHUNK_LIMIT set → Use your settings
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# 4. Connector defaults → Use connector's recommended limits
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# 5. App default → 20MB size-based
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#
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# For openai_transcribe/asr_endpoint: These settings are IGNORED (connector handles it)
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# For openai_whisper: These settings control chunking behavior
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# ENABLE_CHUNKING=false # Uncomment to disable chunking for openai_whisper
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# Chunk limit - supports size (20MB) or duration (600s, 10m)
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CHUNK_LIMIT=20MB
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# Overlap between chunks in seconds (helps with transcription accuracy at boundaries)
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CHUNK_OVERLAP_SECONDS=3
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# =============================================================================
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# EXAMPLE CONFIGURATIONS (Simplified)
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# =============================================================================
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#
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# --- OpenAI with Speaker Diarization (Recommended) ---
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# Just two environment variables needed:
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# TRANSCRIPTION_API_KEY=sk-xxx
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# TRANSCRIPTION_MODEL=gpt-4o-transcribe-diarize
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#
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# --- Self-hosted WhisperX (Best for privacy) ---
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# Just one environment variable needed (auto-detects ASR mode):
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# ASR_BASE_URL=http://whisper-asr:9000
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# Optional:
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# ASR_DIARIZE=true
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# ASR_RETURN_SPEAKER_EMBEDDINGS=true
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#
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# --- OpenAI Whisper (Legacy, no diarization) ---
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# TRANSCRIPTION_API_KEY=sk-xxx
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# TRANSCRIPTION_MODEL=whisper-1
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#
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# --- Custom Whisper model (local or compatible endpoint) ---
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# TRANSCRIPTION_API_KEY=not-needed
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# TRANSCRIPTION_BASE_URL=http://localhost:8080/v1
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# TRANSCRIPTION_MODEL=Systran/faster-distil-whisper-large-v3
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# =============================================================================
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# APPLICATION SETTINGS
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# =============================================================================
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# --- Admin User (created on first run) ---
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ADMIN_USERNAME=admin
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ADMIN_EMAIL=admin@example.com
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ADMIN_PASSWORD=changeme
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# --- Registration & Access ---
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ALLOW_REGISTRATION=false
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# Comma-separated list of allowed email domains for registration.
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# Leave empty to allow all domains. Example: company.com,subsidiary.org
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REGISTRATION_ALLOWED_DOMAINS=
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# --- Token Limits ---
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SUMMARY_MAX_TOKENS=8000
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CHAT_MAX_TOKENS=5000
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# --- Timezone ---
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# Use a valid TZ database name (e.g., "America/New_York", "Europe/London", "UTC")
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TIMEZONE="UTC"
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# --- Logging ---
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LOG_LEVEL="INFO"
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# =============================================================================
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# AUDIO PROCESSING
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# =============================================================================
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# --- Audio Compression ---
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# Automatically compress lossless uploads (WAV, AIFF) to save storage
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AUDIO_COMPRESS_UPLOADS=true
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# Target codec: mp3 (lossy, smallest), flac (lossless), opus (lossy, efficient)
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AUDIO_CODEC=mp3
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# Bitrate for lossy codecs (ignored for FLAC)
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AUDIO_BITRATE=128k
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# Unsupported codecs - comma-separated list of codecs to exclude
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# Example: AUDIO_UNSUPPORTED_CODECS=opus,vorbis
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# AUDIO_UNSUPPORTED_CODECS=
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# =============================================================================
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# OPTIONAL FEATURES
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# =============================================================================
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# --- Inquire Mode (AI search across all recordings) ---
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ENABLE_INQUIRE_MODE=false
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# --- Automated File Processing (Black Hole Directory) ---
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ENABLE_AUTO_PROCESSING=false
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# AUTO_PROCESS_MODE=admin_only
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# AUTO_PROCESS_WATCH_DIR=/data/auto-process
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# --- Automated Export ---
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ENABLE_AUTO_EXPORT=false
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# AUTO_EXPORT_DIR=/data/exports
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# --- Auto-Deletion & Retention ---
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ENABLE_AUTO_DELETION=false
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# GLOBAL_RETENTION_DAYS=90
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# DELETION_MODE=audio_only
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# --- Sharing Settings ---
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ENABLE_INTERNAL_SHARING=false
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ENABLE_PUBLIC_SHARING=true
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# SHOW_USERNAMES_IN_UI=false
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# --- Permission Controls ---
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USERS_CAN_DELETE=true
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# Delete speaker profiles when all their recordings are removed.
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# Default: false (speaker profiles and voice embeddings are preserved)
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# Set to true for privacy-sensitive deployments where biometric voice data
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# should not outlive the recordings it was derived from.
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# DELETE_ORPHANED_SPEAKERS=false
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# --- Video Retention ---
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# When enabled, uploaded video files keep their video stream for in-browser playback
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# The audio is extracted to a temp file for transcription, then cleaned up
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# Default: false (video uploads extract audio only, video stream is discarded)
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VIDEO_RETENTION=false
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# --- Video Passthrough to ASR ---
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# Send original video files directly to ASR without extracting audio.
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# Useful for custom ASR backends that handle video internally (e.g., multi-track audio extraction).
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# When enabled, video files bypass audio extraction, codec conversion, and chunking.
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# Only affects video files — audio uploads are processed normally.
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# Default: false
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# VIDEO_PASSTHROUGH_ASR=false
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# --- Concurrent Uploads ---
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# Maximum number of simultaneous file uploads (default: 3)
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MAX_CONCURRENT_UPLOADS=3
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# =============================================================================
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# BACKGROUND PROCESSING
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# =============================================================================
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# Transcription queue workers (default: 2)
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JOB_QUEUE_WORKERS=2
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# Summary queue workers (default: 2)
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SUMMARY_QUEUE_WORKERS=2
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# Maximum retry attempts for failed jobs (default: 3)
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JOB_MAX_RETRIES=3
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# =============================================================================
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# DOCKER/DATABASE SETTINGS
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# =============================================================================
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# Database URI - SQLite (default) or PostgreSQL
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SQLALCHEMY_DATABASE_URI=sqlite:////data/instance/transcriptions.db
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# For PostgreSQL: postgresql://username:password@hostname:5432/database_name
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UPLOAD_FOLDER=/data/uploads
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# =============================================================================
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# FUTURE: Additional Provider Notes
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# =============================================================================
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# The connector architecture is designed to support additional providers.
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# Future connectors may include:
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#
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# - Deepgram: Known for excellent diarization and real-time transcription
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# - AssemblyAI: Strong diarization with speaker labels
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# - Google Cloud Speech-to-Text: Enterprise-grade with speaker diarization
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#
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# To request a new connector, please open an issue on GitHub.
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