.env.example

# FastFlowLM-Docker Configuration
# Copy this file to .env and adjust values as needed

# ── Mode Selection ──────────────────────────────────────────
# Enable/disable individual Wyoming services
FLM_ASR_ENABLED=true
FLM_LLM_ENABLED=true

# ── Model Configuration ────────────────────────────────────
# LLM model to load for conversation (any FLM-supported model)
FLM_LLM_MODEL=llama3.2:1b

# Whisper model for ASR (speech-to-text)
FLM_ASR_MODEL=whisper-v3:turbo

# ── Network Ports ──────────────────────────────────────────
# FastFlowLM internal API port
FLM_SERVER_PORT=52625

# Wyoming protocol listening ports
WYOMING_ASR_PORT=10300
WYOMING_LLM_PORT=10400

# ── ASR Settings ───────────────────────────────────────────
# Default language for speech recognition
FLM_ASR_LANGUAGE=en

# ── LLM Settings ──────────────────────────────────────────
# System prompt for the LLM conversation handler
FLM_LLM_SYSTEM_PROMPT=You are a helpful voice assistant for a smart home. Keep responses concise and conversational. When asked to control devices, describe what you would do.

# ── Storage ────────────────────────────────────────────────
# Model storage path inside container
FLM_MODEL_PATH=/data/models

# ── Logging ────────────────────────────────────────────────
FLM_LOG_LEVEL=INFO