hold-slayer/docs/configuration.md

Configuration

All configuration is via environment variables, loaded through Pydantic Settings. Copy .env.example to .env and edit.

Environment Variables

Auth (Casdoor SSO + owner)

The gateway is owner-only: the browser signs in via Casdoor (JWT), MCP/CLI clients use owner-minted PATs, and only OWNER_NAME may use any surface. With CASDOOR_ENABLED=false the gateway runs in dev-owner mode — permitted only on a loopback HOST. Startup refuses SSO-enabled-with-missing-config and SSO-disabled-off-loopback.

Variable	Description	Default	Required
CASDOOR_ENABLED	Enable Casdoor SSO	false	No
CASDOOR_ENDPOINT	Casdoor base URL	https://id.ouranos.helu.ca	If SSO on
CASDOOR_CLIENT_ID	Casdoor application client ID	—	If SSO on
CASDOOR_CLIENT_SECRET	Casdoor application client secret	—	If SSO on
CASDOOR_ORG_NAME	Casdoor organization	heluca	No
CASDOOR_APP_NAME	Casdoor application name	—	No
OWNER_NAME	Casdoor username of the single operator	—	If SSO on
PUBLIC_BASE_URL	Public base URL for OAuth discovery (else derived)	—	No

SIP Trunk

Variable	Description	Default	Required
SIP_TRUNK_HOST	Your SIP provider hostname	—	Yes
SIP_TRUNK_PORT	SIP signaling port	5060	No
SIP_TRUNK_USERNAME	SIP auth username	—	Yes
SIP_TRUNK_PASSWORD	SIP auth password	—	Yes
SIP_TRUNK_DID	Your phone number (E.164)	—	Yes
SIP_TRUNK_TRANSPORT	Transport protocol (udp, tcp, tls)	udp	No

Gateway

Variable	Description	Default	Required
GATEWAY_SIP_PORT	Port for device SIP registration	5080	No
GATEWAY_RTP_PORT_MIN	Minimum RTP port	10000	No
GATEWAY_RTP_PORT_MAX	Maximum RTP port	20000	No
GATEWAY_HOST	Bind address	0.0.0.0	No

LLM

Variable	Description	Default	Required
LLM_BASE_URL	OpenAI-compatible API endpoint	http://localhost:11434/v1	No
LLM_MODEL	Model name for IVR analysis	llama3	No
LLM_API_KEY	API key (if required)	not-needed	No
LLM_TIMEOUT	Request timeout in seconds	30.0	No
LLM_MAX_TOKENS	Max tokens per response	1024	No
LLM_TEMPERATURE	Sampling temperature	0.3	No

Speech-to-Text

Variable	Description	Default	Required
SPEACHES_URL	Speaches/Whisper STT endpoint	http://localhost:22070	No
SPEACHES_MODEL	Whisper model name	whisper-large-v3	No

Database

Variable	Description	Default	Required
DATABASE_URL	PostgreSQL or SQLite connection string	sqlite+aiosqlite:///./hold_slayer.db	No

Notifications

Variable	Description	Default	Required
NOTIFY_SMS_NUMBER	Phone number for SMS alerts (E.164)	—	No

Audio Classifier

Variable	Description	Default	Required
CLASSIFIER_WINDOW_SECONDS	Audio window size for classification	3.0	No
CLASSIFIER_SILENCE_THRESHOLD	RMS below this = silence	0.85	No
CLASSIFIER_MUSIC_THRESHOLD	Spectral flatness below this = music	0.7	No
CLASSIFIER_SPEECH_THRESHOLD	Spectral flatness above this = speech	0.6	No

Hold Slayer

Variable	Description	Default	Required
MAX_HOLD_TIME	Maximum seconds to wait on hold	7200	No
HOLD_CHECK_INTERVAL	Seconds between audio checks	2.0	No
DEFAULT_TRANSFER_DEVICE	Device to transfer to	sip_phone	No

Recording

Variable	Description	Default	Required
RECORDING_DIR	Directory for WAV recordings	recordings	No
RECORDING_MAX_SECONDS	Maximum recording duration	7200	No
RECORDING_SAMPLE_RATE	Audio sample rate	16000	No

Settings Architecture

Configuration is managed by Pydantic Settings in config.py:

from config import get_settings

settings = get_settings()
settings.sip_trunk_host      # "sip.provider.com"
settings.llm.base_url        # "http://localhost:11434/v1"
settings.llm.model           # "llama3"
settings.speaches_url        # "http://localhost:22070"
settings.database_url        # "sqlite+aiosqlite:///./hold_slayer.db"

LLM settings are nested under settings.llm as a LLMSettings sub-model.

Deployment

Development

# 1. Clone and install
git clone <repo-url>
cd hold-slayer
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

# 2. Configure
cp .env.example .env
# Edit .env

# 3. Start Ollama (for LLM)
ollama serve
ollama pull llama3

# 4. Start Speaches (for STT)
docker run -p 22070:8000 ghcr.io/speaches-ai/speaches

# 5. Run
uvicorn main:app --host 0.0.0.0 --port 8000 --reload

Production

# PostgreSQL is required (no SQLite fallback)
DATABASE_URL=postgresql+asyncpg://user:pass@localhost/hold_slayer

# Use vLLM for faster inference
LLM_BASE_URL=http://localhost:8000/v1
LLM_MODEL=meta-llama/Llama-3-8B-Instruct

# Run with multiple workers (note: each worker is independent)
uvicorn main:app --host 0.0.0.0 --port 8000 --workers 1

Note: Hold Slayer is designed as a single-process application. Multiple workers would each have their own SIP engine and call state. For high availability, run behind a load balancer with sticky sessions.

Docker

FROM python:3.13-slim

# Install system dependencies for PJSUA2 and Sippy
RUN apt-get update && apt-get install -y \
    build-essential \
    libpjproject-dev \
    && rm -rf /var/lib/apt/lists/*

WORKDIR /app
COPY . .
RUN pip install -e .

EXPOSE 8000 5080/udp 10000-20000/udp

CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

Port mapping:

• 8000 — HTTP API + WebSocket + MCP
• 5080/udp — SIP device registration
• 10000-20000/udp — RTP media ports