#!/usr/bin/env python3
"""Speech-to-text transcription used by the gateway for voice messages.

Built-in providers: local (faster-whisper, default/free), local_command, groq,
openai (also serves the managed ``nous`` selection), mistral, xai, elevenlabs,
deepinfra; plus user-declared command providers and plugin providers.

    result = transcribe_audio("/path/to/audio.ogg")   # {"success", "transcript", "error"?, "provider"?}

This module owns provider resolution, the dispatcher, and the cached local
model + idle-unload state. Backends live in sibling modules
(``transcription_{common,audio,local,cloud,command}``) and are re-imported
here so ``tools.transcription_tools.<name>`` stays the patch/import surface.
"""

import logging
import os
import shutil
import subprocess  # noqa: F401  (tests patch tools.transcription_tools.subprocess.run)
import tempfile  # noqa: F401  (tests patch tools.transcription_tools.tempfile.TemporaryDirectory)
import threading
import time
import importlib.util as _ilu
from pathlib import Path
from typing import Optional, Dict, Any

from hermes_cli._subprocess_compat import windows_hide_flags  # noqa: F401  (imported by tests)
from utils import is_truthy_value
from tools.managed_tool_gateway import resolve_managed_tool_gateway  # noqa: F401  (patched by tests)
from tools.tool_backend_helpers import (  # noqa: F401  (patched by tests; read lazily by transcription_cloud)
    managed_nous_tools_enabled, nous_tool_gateway_unavailable_message, resolve_openai_audio_api_key,
)
from tools.transcription_common import (  # noqa: F401  (re-exported; tests patch tools.transcription_tools.<name>)
    BUILTIN_STT_PROVIDERS, CLOUD_STT_PROVIDERS, DEFAULT_ELEVENLABS_STT_MODEL,
    DEFAULT_GROQ_STT_MODEL, DEFAULT_LOCAL_MODEL, DEFAULT_MISTRAL_STT_MODEL, DEFAULT_PROVIDER,
    DEFAULT_STT_MODEL, ELEVENLABS_STT_BASE_URL, GROQ_MODELS, LOCAL_STT_COMMAND_ENV,
    LOCAL_STT_LANGUAGE_ENV, MAX_FILE_SIZE, OPENAI_MODELS, SUPPORTED_FORMATS, XAI_STT_BASE_URL,
    _error_result, _get_stt_section, _ok_result,
)
from tools.transcription_audio import (  # noqa: F401  (re-exported; tests patch tools.transcription_tools.<name>)
    _CLOUD_TRIM_KEEP_MS_DEFAULT, _CLOUD_TRIM_MIN_INPUT_SECONDS, _CLOUD_TRIM_THRESHOLD_DB_DEFAULT,
    _cloud_trim_settings, _convert_caf_to_wav, _find_ffmpeg_binary, _find_ffprobe_binary,
    _find_whisper_binary, _prepare_audio_for_transcription, _prepare_local_audio,
    _probe_audio_duration, _run_ffmpeg_stt_encode, _trim_silence_for_cloud_stt,
    _validate_audio_file, _validate_audio_file_size, _validate_audio_source_file,
)
from tools.transcription_local import (  # noqa: F401  (re-exported; tests patch tools.transcription_tools.<name>)
    _LOGPROB_THRESHOLD_DEFAULT, _NO_SPEECH_PROB_THRESHOLD_DEFAULT, _get_idle_unload_seconds,
    _get_local_command_template, _has_local_command, _is_hallucinated_segment,
    _join_confident_segments, _load_local_whisper_model, _looks_like_cuda_lib_error,
    _normalize_local_model, _transcribe_local_command, _try_lazy_install_stt,
    build_local_transcribe_kwargs,
)
from tools.transcription_cloud import (  # noqa: F401  (re-exported; tests patch tools.transcription_tools.<name>)
    _extract_transcript_text, _has_xai_stt_credentials, _is_local_or_private_url,
    _resolve_openai_audio_client_config, _transcribe_deepinfra, _transcribe_elevenlabs,
    _transcribe_groq, _transcribe_mistral, _transcribe_openai, _transcribe_xai,
)
from tools.transcription_command import (  # noqa: F401  (re-exported; tests patch tools.transcription_tools.<name>)
    COMMAND_STT_OUTPUT_FORMATS, DEFAULT_COMMAND_STT_LANGUAGE, DEFAULT_COMMAND_STT_OUTPUT_FORMAT,
    DEFAULT_COMMAND_STT_TIMEOUT_SECONDS, _PROMPT_CHARS_PER_TOKEN, _WHISPER_PROMPT_TOKEN_CAP,
    _apply_pre_transcription_hook, _dispatch_to_plugin_provider, _enforce_prompt_length_limit,
    _get_command_stt_output_format, _get_command_stt_timeout, _get_named_stt_provider_config,
    _render_command_stt_template, _resolve_command_stt_provider_config, _run_command_stt,
    _transcribe_command_stt, _unregistered_stt_provider_error,
)

logger = logging.getLogger(__name__)


def get_env_value(name, default=None):
    """Read env values through the live config module.

    Resolved at call time: tests monkeypatch/restore ``hermes_cli.config.get_env_value``
    around this module's import, so a cached import would go stale.
    """
    try:
        from hermes_cli.config import get_env_value as _get_env_value
    except ImportError:
        return os.getenv(name, default)
    value = _get_env_value(name)
    return default if value is None else value


def _resolve_provider_key(env_var: str, provider_id: str) -> str:
    """Resolve an STT API key via the shared voice-key resolver (config > env/.env > credential pool).

    Resolved at call time so tests that reload the helpers module see the live function.
    """
    try:
        from tools.tool_backend_helpers import resolve_provider_secret
    except ImportError:  # pragma: no cover — helpers are in-repo
        return str(get_env_value(env_var) or "").strip()
    return resolve_provider_secret(env_var, provider_id, env_getter=get_env_value)


def _safe_find_spec(module_name: str) -> bool:
    try:
        return _ilu.find_spec(module_name) is not None
    except (ImportError, ValueError):
        return module_name in globals() or module_name in os.sys.modules


_HAS_FASTER_WHISPER = _safe_find_spec("faster_whisper")
_HAS_OPENAI = _safe_find_spec("openai")
_HAS_MISTRAL = _safe_find_spec("mistralai")
_HAS_PILK = _safe_find_spec("pilk")


# Singleton for the local model — loaded once, reused across calls. The lock
# guards the check-then-load so two concurrent voice messages can't both
# download/load the model.
_local_model: Optional[object] = None
_local_model_name: Optional[str] = None
_local_model_lock = threading.Lock()

# Idle unload: a single daemon thread checks _last_transcription_time and
# releases the model (hundreds of MB of RAM/VRAM) after a configurable idle
# period, then exits; the next voice message reloads and restarts it.
# _idle_unload_mgmt_lock serializes the start check so two concurrent
# transcriptions can't both observe "no watcher alive" and spawn duplicates.
_last_transcription_time: float = 0.0
_idle_unload_thread: Optional[threading.Thread] = None
_idle_unload_stop = threading.Event()
_idle_unload_mgmt_lock = threading.Lock()

_IDLE_UNLOAD_CHECK_INTERVAL = 30  # seconds between idle checks


# ---- Config helpers -----------------------------------------------------


def _load_stt_config() -> dict:
    """Load the ``stt`` section from user config, falling back to defaults."""
    try:
        from hermes_cli.config import load_config
        return load_config().get("stt") or {}
    except Exception:
        return {}


def is_stt_enabled(stt_config: Optional[dict] = None) -> bool:
    """Return whether STT is enabled in config."""
    if stt_config is None:
        stt_config = _load_stt_config()
    return is_truthy_value(stt_config.get("enabled", True), default=True)


def _resolve_stt_language(
    provider_key: str,
    stt_config: Optional[Dict[str, Any]] = None,
    *,
    extra_keys: tuple = (),
) -> Optional[str]:
    """Resolve the language hint for an STT provider; first non-empty wins.

    Order: ``stt.<provider>.language`` (plus *extra_keys* aliases, e.g. ElevenLabs'
    ``language_code``) > ``stt.language`` > ``HERMES_LOCAL_STT_LANGUAGE`` env >
    None (provider auto-detects). Never returns "".
    """
    if stt_config is None:
        stt_config = _load_stt_config()
    provider_cfg = _get_stt_section(stt_config, provider_key)
    candidates = [provider_cfg.get(key) for key in ("language", *extra_keys)]
    if isinstance(stt_config, dict):
        candidates.append(stt_config.get("language"))
    candidates.append(os.getenv(LOCAL_STT_LANGUAGE_ENV))
    for candidate in candidates:
        if isinstance(candidate, str) and candidate.strip():
            return candidate.strip()
    return None


def _openai_audio_unavailable_reason() -> Optional[str]:
    """None when OpenAI audio has usable credentials (config, env, or managed gateway); else the reason."""
    try:
        _resolve_openai_audio_client_config()
        return None
    except ValueError as exc:
        return str(exc)


def _has_openai_audio_backend() -> bool:
    return _openai_audio_unavailable_reason() is None


def _is_local_stt_provider(provider: str, stt_config: Dict[str, Any]) -> bool:
    """Return whether *provider* is exempt from Hermes's remote upload cap."""
    return (provider or "").lower().strip() in {"local", "local_command"}


# ---- Provider resolution ------------------------------------------------


def _has_xai_stt_credentials_quietly() -> bool:
    try:
        return _has_xai_stt_credentials()
    except Exception:
        return False


def _has_key(env_var: str, provider: str, *, needs_openai: bool = False, needs_mistral: bool = False):
    """Availability probe factory: optional SDK flag AND a resolvable API key."""
    def probe() -> bool:
        if needs_openai and not _HAS_OPENAI:
            return False
        if needs_mistral and not _HAS_MISTRAL:
            return False
        return bool(_resolve_provider_key(env_var, provider))
    return probe


_has_groq_key = _has_key("GROQ_API_KEY", "groq", needs_openai=True)
_has_mistral_key = _has_key("MISTRAL_API_KEY", "mistral", needs_mistral=True)
_has_elevenlabs_key = _has_key("ELEVENLABS_API_KEY", "elevenlabs")
_has_deepinfra_key = _has_key("DEEPINFRA_API_KEY", "deepinfra", needs_openai=True)


def _resolve_explicit_openai() -> str:
    if not _HAS_OPENAI:
        logger.warning("STT provider 'openai' configured but no API key available")
        return "none"
    # Resolve directly rather than via the boolean probe so a managed
    # openai-audio gateway outage is logged with its real reason, not a
    # generic "no API key" hint.
    reason = _openai_audio_unavailable_reason()
    if reason is None:
        return "openai"
    logger.warning("STT provider 'openai' configured but unavailable: %s", reason)
    return "none"


def _detect_local_backend() -> Optional[str]:
    """faster-whisper > local whisper CLI > lazy-installed faster-whisper; None when nothing local works."""
    if _HAS_FASTER_WHISPER:
        return "local"
    if _has_local_command():
        return "local_command"
    if _try_lazy_install_stt():
        return "local"
    return None


def _resolve_explicit_local() -> str:
    backend = _detect_local_backend()
    if backend:
        return backend
    logger.warning(
        "STT provider 'local' configured but unavailable "
        "(install faster-whisper or set HERMES_LOCAL_STT_COMMAND)"
    )
    return "none"


def _resolve_explicit_local_command() -> str:
    if _has_local_command():
        return "local_command"
    if _HAS_FASTER_WHISPER:
        logger.info("Local STT command unavailable, using local faster-whisper")
        return "local"
    logger.warning("STT provider 'local_command' configured but unavailable")
    return "none"


# Cloud providers in AUTO-DETECT priority order:
#   name -> (explicit-selection probe, auto-detect probe, explicit warning, auto-detect log)
# The two probes differ only for openai (auto-detect additionally requires the
# SDK) and xai (auto-detect must never raise). DeepInfra is LAST so a
# DEEPINFRA_API_KEY set for the chat surface never displaces an existing
# xAI/ElevenLabs auto-selection. Mistral only auto-selects when the SDK is
# already present — no lazy-install during passive auto-detection (explicit
# ``provider: mistral`` installs on first use).
_CLOUD_PROVIDER_SPECS = {
    "groq": (
        _has_groq_key, _has_groq_key,
        "STT provider 'groq' configured but GROQ_API_KEY not set",
        "No local STT available, using Groq Whisper API",
    ),
    "openai": (
        None, lambda: _HAS_OPENAI and _has_openai_audio_backend(),
        None,  # explicit openai has its own resolver (logs the real gateway reason)
        "No local STT available, using OpenAI Whisper API",
    ),
    "mistral": (
        _has_mistral_key, _has_mistral_key,
        "STT provider 'mistral' configured but mistralai package "
        "not installed or MISTRAL_API_KEY not set",
        "No local STT available, using Mistral Voxtral Transcribe API",
    ),
    "xai": (
        _has_xai_stt_credentials, _has_xai_stt_credentials_quietly,
        "STT provider 'xai' configured but no xAI credentials are available",
        "No local STT available, using xAI Grok STT API",
    ),
    "elevenlabs": (
        _has_elevenlabs_key, _has_elevenlabs_key,
        "STT provider 'elevenlabs' configured but ELEVENLABS_API_KEY not set",
        "No local STT available, using ElevenLabs Scribe STT API",
    ),
    "deepinfra": (
        _has_deepinfra_key, _has_deepinfra_key,
        "STT provider 'deepinfra' configured but DEEPINFRA_API_KEY not set "
        "(or openai package missing)",
        "No local STT available, using DeepInfra Whisper API",
    ),
}


def _resolve_explicit_provider(provider: str) -> str:
    """Resolve an explicit ``stt.provider`` to a usable provider name or ``"none"``.

    Unknown names pass through untouched so the dispatcher can fail with the
    provider-not-registered message.
    """
    if provider == "local":
        return _resolve_explicit_local()
    if provider == "local_command":
        return _resolve_explicit_local_command()
    if provider == "openai":
        return _resolve_explicit_openai()
    spec = _CLOUD_PROVIDER_SPECS.get(provider)
    if spec is None:
        return provider
    probe, _auto, warning, _log = spec
    if probe():
        return provider
    logger.warning(warning)
    return "none"


def _get_provider(stt_config: dict) -> str:
    """Determine which STT provider to use.

    An explicit ``stt.provider`` is honoured — no silent cloud fallback. With no
    provider configured, auto-detect tries local > groq > openai > mistral > xai
    > elevenlabs > deepinfra.
    """
    if not is_stt_enabled(stt_config):
        return "none"

    explicit = "provider" in stt_config
    provider = stt_config.get("provider", DEFAULT_PROVIDER)

    # The managed "Nous Subscription" selection is serviced by the OpenAI
    # implementation, routed through the managed gateway by
    # _resolve_openai_audio_client_config.
    if isinstance(provider, str) and provider.strip().lower() == "nous":
        provider = "openai"

    if explicit and provider == "local":
        # Legacy DEFAULT_CONFIG seeded ``stt.provider: local`` on every install,
        # so a merged-config "local" is not proof of a user pick. Only a raw
        # config.yaml selection counts as explicit; otherwise autodetect (which
        # prefers local first anyway).
        try:
            from tools.tool_backend_helpers import read_selection

            if read_selection("stt") is None:
                explicit = False
        except Exception:  # pragma: no cover — helpers are in-repo
            pass

    if explicit:
        return _resolve_explicit_provider(provider)

    backend = _detect_local_backend()
    if backend:
        return backend
    for name, (_probe, available, _warning, message) in _CLOUD_PROVIDER_SPECS.items():
        if available():
            logger.info(message)
            return name
    return "none"


# ---- Provider: local (faster-whisper) -----------------------------------


def _unload_local_model() -> None:
    """Release the cached local whisper model. Thread-safe via the model lock."""
    global _local_model, _local_model_name
    with _local_model_lock:
        if _local_model is not None:
            logger.info(
                "Unloading local whisper model '%s' after idle timeout",
                _local_model_name or "unknown",
            )
            _local_model = None
            _local_model_name = None


def _start_idle_unload_watcher(timeout_seconds: int) -> None:
    """Ensure the single idle-unload watcher thread is running.

    Started only when none is alive (one lock + one ``is_alive()`` per
    transcription). The loop re-reads ``stt.local.unload_after_idle_seconds``
    every cycle so config edits apply within one interval; ``timeout_seconds``
    seeds the first cycle so a just-written config is honored even if a
    concurrent read races. After unloading, when the timeout becomes 0, or when
    the model is already gone, the thread exits; the next transcription restarts it.
    """
    global _idle_unload_thread
    with _idle_unload_mgmt_lock:
        if _idle_unload_thread is not None and _idle_unload_thread.is_alive():
            return

        def _watch(initial_timeout=timeout_seconds):
            timeout = initial_timeout
            while not _idle_unload_stop.is_set():
                if _idle_unload_stop.wait(_IDLE_UNLOAD_CHECK_INTERVAL):
                    break
                if _local_model is None:
                    break
                try:
                    timeout = _get_idle_unload_seconds(
                        _load_stt_config().get("local") or {}
                    )
                except Exception:  # noqa: BLE001 - keep the seed value
                    timeout = initial_timeout
                if timeout <= 0:
                    break  # unload disabled mid-flight — stand down
                if time.monotonic() - _last_transcription_time >= timeout:
                    _unload_local_model()
                    break

        _idle_unload_stop.clear()
        _idle_unload_thread = threading.Thread(
            target=_watch, name="hermes-stt-idle-unload", daemon=True
        )
        _idle_unload_thread.start()


def _touch_transcription_time() -> None:
    """Record transcription activity (resets the idle timer)."""
    global _last_transcription_time
    _last_transcription_time = time.monotonic()


def _get_or_load_local_model(model_name: str, local_cfg: Dict[str, Any]):
    """Return the cached faster-whisper model, (re)loading under the lock when needed.

    Double-checked lock: concurrent voice messages must not both download/load.
    The returned strong reference stays valid even if the idle watcher nulls the
    module global mid-transcription.
    """
    global _local_model, _local_model_name
    model = _local_model
    if model is None or _local_model_name != model_name:
        with _local_model_lock:
            if _local_model is None or _local_model_name != model_name:
                logger.info("Loading faster-whisper model '%s' (first load downloads the model)...", model_name)
                # stt.local.device / compute_type let users pin a configuration
                # where ``auto`` mis-detects; the loader keeps the CUDA→CPU fallback.
                _local_model = _load_local_whisper_model(
                    model_name,
                    device=local_cfg.get("device", "auto"),
                    compute_type=local_cfg.get("compute_type", "auto"),
                )
                _local_model_name = model_name
            model = _local_model
    return model


def _replace_cached_model_on_cpu(model_name: str):
    """Load *model_name* on CPU/int8 and make it the cached singleton."""
    global _local_model, _local_model_name
    from faster_whisper import WhisperModel
    model = WhisperModel(model_name, device="cpu", compute_type="int8")
    with _local_model_lock:
        _local_model = model
        _local_model_name = model_name
    return model


def _transcribe_local(
    file_path: str,
    model_name: str,
    *,
    language: Optional[str] = None,
    prompt: Optional[str] = None,
) -> Dict[str, Any]:
    """Transcribe using faster-whisper (local, free)."""
    if not _HAS_FASTER_WHISPER and not _try_lazy_install_stt():
        return _error_result("faster-whisper not installed")

    try:
        stt_config = _load_stt_config()
        local_cfg = stt_config.get("local") or {}
        # Reset the idle timer BEFORE loading/transcribing so the watcher can't
        # count a long in-flight transcription as idle time and unload mid-use.
        _touch_transcription_time()
        model = _get_or_load_local_model(model_name, local_cfg)
        if model is None:  # defensive: load failed without raising
            return _error_result("Local whisper model failed to load")

        transcribe_kwargs = build_local_transcribe_kwargs(stt_config)
        # pre_transcription hook overrides win over config-resolved values.
        if language:
            transcribe_kwargs["language"] = language
        if prompt:
            transcribe_kwargs["initial_prompt"] = prompt

        try:
            segments, info = model.transcribe(file_path, **transcribe_kwargs)
        except Exception as exc:
            # CUDA libs sometimes only fail at dlopen-on-first-use, AFTER the
            # model loaded. Evict the poisoned cached model, reload on CPU and
            # retry once — otherwise every later voice message fails until restart.
            if not _looks_like_cuda_lib_error(exc):
                raise
            logger.warning(
                "faster-whisper CUDA runtime failed mid-transcribe (%s) — "
                "evicting cached model and retrying on CPU (int8).",
                exc,
            )
            model = _replace_cached_model_on_cpu(model_name)
            segments, info = model.transcribe(file_path, **transcribe_kwargs)
        transcript = _join_confident_segments(segments, local_cfg)

        logger.info(
            "Transcribed %s via local whisper (%s, lang=%s, %.1fs audio)",
            Path(file_path).name, model_name, info.language, info.duration,
        )

        _touch_transcription_time()
        idle_timeout = _get_idle_unload_seconds(local_cfg)
        if idle_timeout > 0:
            _start_idle_unload_watcher(idle_timeout)

        return _ok_result(transcript, "local")

    except Exception as e:
        logger.error("Local transcription failed: %s", e, exc_info=True)
        return _error_result(f"Local transcription failed: {e}")


# ---- Public API ---------------------------------------------------------


def _read_block_error(file_path: str) -> Optional[Dict[str, Any]]:
    """Refuse to feed a credential / secret store (auth.json, .env, OAuth tokens, ...)
    to an STT provider, which would ship its plaintext to a third-party API.
    Mirrors the image-gen / video-gen read guards."""
    from agent.file_safety import get_read_block_error
    blocked = get_read_block_error(file_path)
    return _error_result(blocked) if blocked else None


def _transcribe_prepared_audio(
    file_path: str,
    model: Optional[str] = None,
    source: Optional[str] = None,
) -> Dict[str, Any]:
    """Transcribe a validated audio file with the configured STT provider.

    ``model`` overrides the config/provider default; ``source`` is a caller-surface
    label (``"gateway"``, ``"voice_mode"``) forwarded to the ``pre_transcription``
    hook for observability only. Returns the standard result envelope.
    """
    blocked = _read_block_error(file_path)
    if blocked:
        return blocked

    # Validate before provider resolution so invalid files cannot trigger
    # provider setup or lazy installation. The remote-upload size cap is
    # enforced below, only for non-local providers.
    error = _validate_audio_file(file_path, enforce_size_limit=False)
    if error:
        return error

    stt_config = _load_stt_config()
    if not is_stt_enabled(stt_config):
        return _error_result("STT is disabled in config.yaml (stt.enabled: false).")

    provider = _get_provider(stt_config)
    if not _is_local_stt_provider(provider, stt_config):
        error = _validate_audio_file_size(Path(file_path))
        if error:
            return error

    # Convert CAF (iMessage voice notes) to WAV for cloud STT providers.
    if Path(file_path).suffix.lower() == ".caf" and provider not in ("local", "local_command"):
        file_path = _convert_caf_to_wav(file_path)
        if not file_path:
            return _error_result("CAF audio could not be converted to WAV.")

    # Best-effort pre-upload silence trim for built-in cloud providers.
    trim_cleanup_dir: Optional[str] = None
    if provider in CLOUD_STT_PROVIDERS:
        trimmed = _trim_silence_for_cloud_stt(file_path, stt_config)
        if trimmed:
            file_path = trimmed
            trim_cleanup_dir = os.path.dirname(trimmed)

    try:
        return _dispatch_stt_provider(file_path, provider, stt_config, model, source)
    finally:
        if trim_cleanup_dir:
            shutil.rmtree(trim_cleanup_dir, ignore_errors=True)


# Built-in provider -> (stt section, config key, default, treat-empty-as-missing).
# "local_command" shares the ``stt.local`` section; xAI takes no model parameter
# (the name is logging-only); deepinfra resolves from the live catalog when empty.
_BUILTIN_MODEL_KEYS = {
    "local": ("local", "model", DEFAULT_LOCAL_MODEL, False),
    "local_command": ("local", "model", DEFAULT_LOCAL_MODEL, False),
    "groq": ("groq", "model", DEFAULT_GROQ_STT_MODEL, True),
    "openai": ("openai", "model", DEFAULT_STT_MODEL, False),
    "mistral": ("mistral", "model", DEFAULT_MISTRAL_STT_MODEL, False),
    "elevenlabs": ("elevenlabs", "model_id", DEFAULT_ELEVENLABS_STT_MODEL, False),
    "deepinfra": ("deepinfra", "model", "", True),
}


def _builtin_model_name(provider: str, stt_config: Dict[str, Any], model: Optional[str]) -> str:
    """Resolve the model for a built-in provider: caller override > ``stt.<provider>`` config > default."""
    if model:
        return model
    if provider == "xai":
        return "grok-stt"
    section, key, default, empty_is_missing = _BUILTIN_MODEL_KEYS[provider]
    cfg = _get_stt_section(stt_config, section)
    if empty_is_missing:
        return cfg.get(key) or default
    return cfg.get(key, default)


def _builtin_handler(provider: str):
    """Handler for a built-in provider, looked up in this module at call time so tests may patch ``_transcribe_*``."""
    if provider not in BUILTIN_STT_PROVIDERS:
        return None
    return globals()[f"_transcribe_{provider}"]


def _dispatch_stt_provider(
    file_path: str,
    provider: str,
    stt_config: Dict[str, Any],
    model: Optional[str] = None,
    source: Optional[str] = None,
) -> Dict[str, Any]:
    """Route *file_path* to the handler for *provider* (built-in > command > plugin)."""
    # Static ``stt.prompt`` is the base; pre_transcription hook results mutate
    # on top in registration order (last hook to set a field wins).
    prompt = stt_config.get("prompt")
    if not isinstance(prompt, str) or not prompt.strip():
        prompt = None

    # The hook fires after provider resolution and BEFORE any backend is
    # invoked; ``language`` stays None unless a hook overrides it.
    model, language, prompt = _apply_pre_transcription_hook(
        file_path=file_path, provider=provider, model=model,
        language=_get_stt_section(stt_config, provider).get("language"),
        prompt=prompt, source=source,
    )
    prompt = _enforce_prompt_length_limit(prompt, provider)

    handler = _builtin_handler(provider)
    if handler is not None:
        model_name = _builtin_model_name(provider, stt_config, model)
        if provider in ("local", "local_command"):
            model_name = _normalize_local_model(model_name)
        return handler(file_path, model_name, language=language, prompt=prompt)

    # User-declared command provider: after built-ins (so ``stt.providers.openai
    # .command`` can't override the real handler) and BEFORE plugins, because
    # config is more local than a plugin install (same precedence as TTS).
    command_provider_config = _resolve_command_stt_provider_config(provider, stt_config)
    if command_provider_config is not None:
        return _transcribe_command_stt(
            file_path, provider, command_provider_config, stt_config,
            model_override=model, language_override=language, prompt=prompt,
        )

    # Plugin-registered backend. Plugins read per-provider config under
    # ``stt.<provider>`` like built-ins; the ``model`` argument overrides it.
    plugin_cfg = _get_stt_section(stt_config, provider)
    plugin_result = _dispatch_to_plugin_provider(
        file_path, provider, stt_config,
        model=model or plugin_cfg.get("model"),
        language=language or _resolve_stt_language(provider, stt_config),
        prompt=prompt,
    )
    if plugin_result is not None:
        return plugin_result
    return _no_provider_error(provider, stt_config)


def _no_provider_error(provider: str, stt_config: Dict[str, Any]) -> Dict[str, Any]:
    """Error envelope when nothing claimed *provider*: unregistered name > openai selection reason > generic hint."""
    provider_key = str(provider or "").strip().lower()
    if "provider" in stt_config and provider_key and provider_key not in BUILTIN_STT_PROVIDERS and provider_key != "none":
        return _unregistered_stt_provider_error(provider_key)

    # An explicit openai selection flattened to "none" carries a
    # selection-specific reason (e.g. managed openai-audio gateway down);
    # surface it with its remediation instead of the all-provider hint.
    if provider_key == "none" and str(stt_config.get("provider") or "") == "openai" and _HAS_OPENAI:
        reason = _openai_audio_unavailable_reason()
        if reason is not None:
            return _error_result(reason)

    return _error_result(
        "No STT provider available. Install faster-whisper for free local "
        f"transcription, configure {LOCAL_STT_COMMAND_ENV} or install a local whisper CLI, "
        "set GROQ_API_KEY for free Groq Whisper, set MISTRAL_API_KEY for Mistral "
        "Voxtral Transcribe, configure xAI OAuth or set XAI_API_KEY for xAI Grok STT, "
        "set ELEVENLABS_API_KEY for ElevenLabs Scribe, or set VOICE_TOOLS_OPENAI_KEY "
        "or OPENAI_API_KEY for the OpenAI Whisper API."
    )


def transcribe_audio(
    file_path: str,
    model: Optional[str] = None,
    source: Optional[str] = None,
) -> Dict[str, Any]:
    """Safely validate, preprocess supported inputs, and dispatch transcription.

    ``source`` is an optional caller-surface label (``"gateway"``, ``"voice_mode"``)
    forwarded to the ``pre_transcription`` hook for observability only.
    """
    # Secret-store refusal runs before ANY validation so the error names the
    # real reason rather than a format error.
    blocked = _read_block_error(file_path)
    if blocked:
        return blocked

    # Cap .silk sources before the decoder runs (decoder safety); for all other
    # inputs the upload cap is provider-scoped in _transcribe_prepared_audio,
    # so local whisper can handle big files.
    is_silk = Path(file_path).suffix.lower() == ".silk"
    source_error = _validate_audio_source_file(file_path, enforce_size_limit=is_silk)
    if source_error:
        return source_error

    prepared_path, cleanup_dir, prep_error = _prepare_audio_for_transcription(file_path)
    if prep_error or prepared_path is None:
        return prep_error or _error_result("Audio preprocessing did not produce a file for transcription.")

    try:
        return (
            _validate_audio_file(prepared_path, enforce_size_limit=False)
            or _transcribe_prepared_audio(prepared_path, model, source)
        )
    finally:
        if cleanup_dir:
            shutil.rmtree(cleanup_dir, ignore_errors=True)


def transcribe_audio_local_fallback(
    file_path: str,
    model: Optional[str] = None,
) -> Dict[str, Any]:
    """Try an already-installed local STT backend without changing config.

    For passive inbound-media recovery after the configured provider failed:
    never lazy-installs or falls through to a cloud provider.
    """
    error = _validate_audio_file(file_path)
    if error:
        return error

    local_cfg = _load_stt_config().get("local") or {}
    local_model = model or local_cfg.get("model", DEFAULT_LOCAL_MODEL)

    if _HAS_FASTER_WHISPER:
        return _transcribe_local(file_path, _normalize_local_model(local_model))
    if _has_local_command():
        return _transcribe_local_command(file_path, _normalize_local_model(local_model))
    return _error_result("No installed local STT backend is available.", provider="local")