src/core/settings.py

import json
from pathlib import Path
from typing import Optional

from pydantic import Field, ValidationError
from pydantic_settings import BaseSettings, SettingsConfigDict
from dotenv import load_dotenv

from src.core.logger import logger

BASE_DIR = Path(__file__).parent.parent.parent
ENV_FILE = BASE_DIR / ".env"

load_dotenv(ENV_FILE, override=True)
logger.info(f"Loaded environment from: {ENV_FILE}")

SENSITIVE_KEY_MARKERS = ("key", "token", "secret", "password")


def _is_sensitive_key(key: str) -> bool:
    key_lower = key.lower()
    return any(marker in key_lower for marker in SENSITIVE_KEY_MARKERS)


def _redact_sensitive_value(value: object) -> str:
    if value is None:
        return "<not set>"
    if isinstance(value, str) and not value:
        return "<not set>"
    return "<redacted>"


def mask_sensitive_data(data: dict) -> dict:
    masked = {}

    for key, value in data.items():
        if _is_sensitive_key(key):
            masked[key] = _redact_sensitive_value(value)
            continue

        if isinstance(value, dict):
            masked[key] = mask_sensitive_data(value)
        else:
            masked[key] = value

    return masked


class CoreSettings(BaseSettings):
    model_config = SettingsConfigDict(
        env_file=str(ENV_FILE) if ENV_FILE.exists() else None,
        env_file_encoding="utf-8",
        case_sensitive=True,
        extra="ignore",
        protected_namespaces=(),
    )


class VoiceSettings(CoreSettings):
    POCKET_TTS_VOICE: str = Field(
        default="alba",
        description="Default voice (alba, marius, javert, jean, fantine, cosette, eponine, azelma) or path to audio file",
    )
    POCKET_TTS_TEMPERATURE: float = Field(
        default=0.7,
        ge=0.0,
        le=2.0,
        description="Sampling temperature for generation",
    )
    POCKET_TTS_LSD_DECODE_STEPS: int = Field(
        default=1,
        ge=1,
        description="LSD decoding steps (higher = better quality, slower)",
    )

    # LiveKit Audio Input Settings
    LIVEKIT_SAMPLE_RATE: int = Field(
        default=24000,
        description="Audio input sample rate (Hz)",
    )
    LIVEKIT_NUM_CHANNELS: int = Field(
        default=1,
        description="Number of audio input channels (1=mono)",
    )
    LIVEKIT_FRAME_SIZE_MS: int = Field(
        default=20,
        ge=10,
        le=100,
        description="Audio frame size in milliseconds (smaller = faster VAD response)",
    )
    LIVEKIT_PRE_CONNECT_AUDIO: bool = Field(
        default=True,
        description="Pre-connect audio before room join",
    )
    LIVEKIT_PRE_CONNECT_TIMEOUT: float = Field(
        default=3.0,
        ge=1.0,
        le=10.0,
        description="Timeout for pre-connect audio (seconds)",
    )

    # Voice Activity Detection Settings
    VAD_MIN_SPEECH_DURATION: float = Field(
        default=0.18,
        ge=0.1,
        le=1.0,
        description="Minimum speech duration (seconds) before VAD activation",
    )
    VAD_MIN_SILENCE_DURATION: float = Field(
        default=0.30,
        ge=0.1,
        le=2.0,
        description="Minimum silence duration (seconds) before VAD deactivation",
    )
    VAD_THRESHOLD: float = Field(
        default=0.6,
        ge=0.0,
        le=1.0,
        description="VAD activation threshold (higher = less sensitive, 0.5 is Silero default)",
    )
    MIN_ENDPOINTING_DELAY: float = Field(
        default=0.15,
        ge=0.0,
        le=10.0,
        description="Minimum endpointing delay (seconds) before committing user turn",
    )
    MAX_ENDPOINTING_DELAY: float = Field(
        default=1.0,
        ge=0.1,
        le=10.0,
        description="Maximum endpointing delay (seconds) when turn detector expects continuation",
    )
    PREEMPTIVE_GENERATION: bool = Field(
        default=True,
        description="Enable speculative LLM/TTS generation before final turn commit",
    )


class STTSettings(CoreSettings):
    # Provider selection
    STT_PROVIDER: str = Field(
        default="moonshine",
        description="STT provider: 'nvidia' or 'moonshine'"
    )

    # Moonshine STT settings
    MOONSHINE_MODEL_ID: str = Field(
        default="usefulsensors/moonshine-streaming-medium",
        description="Moonshine model size: tiny, base, small, or medium"
    )
    MOONSHINE_LANGUAGE: str = Field(
        default="en",
        description="Language code for Moonshine STT"
    )

    # NVIDIA STT settings
    NVIDIA_STT_API_KEY: Optional[str] = Field(
        default=None,
        description="NVIDIA API key for STT (falls back to NVIDIA_API_KEY if not set)"
    )
    NVIDIA_STT_MODEL: str = Field(
        default="parakeet-1.1b-en-US-asr-streaming-silero-vad-sortformer",
        description="NVIDIA STT model ID"
    )
    NVIDIA_STT_LANGUAGE_CODE: str = Field(
        default="en-US",
        description="Language code for NVIDIA STT"
    )


class LLMSettings(CoreSettings):
    # Provider selection
    LLM_PROVIDER: str = Field(
        default="huggingface",
        description="LLM provider: 'nvidia' or 'huggingface'"
    )

    # NVIDIA settings (existing)
    NVIDIA_API_KEY: Optional[str] = Field(default=None)
    NVIDIA_MODEL: str = Field(default="qwen/qwen2.5-7b-instruct")

    # HuggingFace settings (new)
    HUGGINGFACE_MODEL_ID: str = Field(
        default="Qwen/Qwen2.5-3B-Instruct",
        description="HuggingFace model repository ID"
    )
    HUGGINGFACE_DEVICE: Optional[str] = Field(
        default=None,
        description="Device for inference: 'cuda', 'cpu', or None for auto-detect"
    )

    # Common LLM parameters
    LLM_TEMPERATURE: float = Field(default=0.7, ge=0.0, le=2.0)
    LLM_MAX_TOKENS: int = Field(default=1024, gt=0)
    LLM_CONN_TIMEOUT_SEC: float = Field(
        default=12.0,
        gt=0.0,
        le=120.0,
        description="LLM API timeout in seconds for one request attempt",
    )
    LLM_CONN_MAX_RETRY: int = Field(
        default=1,
        ge=0,
        le=10,
        description="Maximum LLM retry attempts on transient failures",
    )
    LLM_CONN_RETRY_INTERVAL_SEC: float = Field(
        default=1.0,
        ge=0.0,
        le=30.0,
        description="Delay in seconds between LLM retries",
    )
    TURN_LLM_STALL_TIMEOUT_SEC: float = Field(
        default=8.0,
        gt=0.0,
        le=120.0,
        description="Warn when a finalized user turn does not reach LLM stage within this timeout",
    )


class LiveKitSettings(CoreSettings):
    LIVEKIT_URL: Optional[str] = Field(default=None)
    LIVEKIT_API_KEY: Optional[str] = Field(default=None)
    LIVEKIT_API_SECRET: Optional[str] = Field(default=None)
    LIVEKIT_AGENT_NAME: str = Field(default="open-voice-agent")
    LIVEKIT_NUM_IDLE_PROCESSES: int = Field(default=1, ge=0)
    LIVEKIT_JOB_MEMORY_WARN_MB: float = Field(
        default=6144,
        gt=0,
        description="Per-job memory warning threshold in MB",
    )


class LangfuseSettings(CoreSettings):
    LANGFUSE_ENABLED: bool = Field(
        default=False,
        description="Enable Langfuse tracing via OTEL exporter",
    )
    LANGFUSE_PUBLIC_KEY: Optional[str] = Field(default=None)
    LANGFUSE_SECRET_KEY: Optional[str] = Field(default=None)
    LANGFUSE_ENVIRONMENT: str = Field(default="development")
    LANGFUSE_HOST: Optional[str] = Field(
        default=None,
        description="Langfuse host URL, e.g. https://cloud.langfuse.com",
    )
    LANGFUSE_BASE_URL: Optional[str] = Field(
        default=None,
        description="Alternative to LANGFUSE_HOST",
    )
    LANGFUSE_TRACE_FINALIZE_TIMEOUT_MS: float = Field(
        default=8000.0,
        ge=0.0,
        le=10000.0,
        description="Timeout to wait for assistant text before force-finalizing trace",
    )
    LANGFUSE_MAX_PENDING_TRACE_TASKS: int = Field(
        default=200,
        ge=1,
        le=5000,
        description="Maximum queued background trace emission tasks",
    )
    LANGFUSE_TRACE_FLUSH_TIMEOUT_MS: float = Field(
        default=1000.0,
        ge=0.0,
        le=10000.0,
        description="Best-effort tracer flush timeout in milliseconds",
    )


class Settings(CoreSettings):
    voice: VoiceSettings = Field(default_factory=VoiceSettings)
    stt: STTSettings = Field(default_factory=STTSettings)
    llm: LLMSettings = Field(default_factory=LLMSettings)
    livekit: LiveKitSettings = Field(default_factory=LiveKitSettings)
    langfuse: LangfuseSettings = Field(default_factory=LangfuseSettings)


try:
    settings = Settings()

    settings_dict = settings.model_dump()
    masked_settings = mask_sensitive_data(settings_dict)
    logger.info(f"Settings loaded: {json.dumps(masked_settings, indent=2)}")

except ValidationError as e:
    safe_errors = e.errors(
        include_url=False,
        include_context=False,
        include_input=False,
    )
    logger.exception(
        "Error validating settings: %s",
        json.dumps(safe_errors),
    )
    raise