"""Shared helpers for skill classification output."""

from __future__ import annotations

import json
import re

VALID_SKILLS: frozenset[str] = frozenset(
    {
        "bluetooth_enable",
        "calendar_create_event",
        "camera_take_photo",
        "contacts_search",
        "create_alarm",
        "gmail_send_email",
        "linkedin_search_person",
        "slack_open_channel",
        "spotify_pause",
        "spotify_play_playlist",
        "spotify_search_play",
        "uber_request_ride",
        "whatsapp_send_message",
        "wifi_enable",
        "youtube_search",
    }
)

# Model sometimes invents close-but-wrong skill names.
SKILL_ALIASES: dict[str, str] = {
    "alarm_set": "create_alarm",
    "set_alarm": "create_alarm",
    "alarm_create": "create_alarm",
    "create_alarms": "create_alarm",
    "wake_up_alarm": "create_alarm",
    "send_message": "whatsapp_send_message",
    "send_whatsapp": "whatsapp_send_message",
    "whatsapp_message": "whatsapp_send_message",
    "send_email": "gmail_send_email",
    "compose_email": "gmail_send_email",
    "open_slack": "slack_open_channel",
    "slack_channel": "slack_open_channel",
    "search_contacts": "contacts_search",
    "contact_search": "contacts_search",
    "spotify_create_playlist": "spotify_play_playlist",
}


def extract_skill(text: str) -> str | None:
    """Extract the skill name from model output JSON."""
    text = text.strip()
    if not text:
        return None

    match = re.search(r'\{[^{}]*"skill"\s*:\s*"([^"]+)"[^{}]*\}', text)
    if match:
        return match.group(1)

    start = text.find("{")
    end = text.rfind("}")
    if start == -1 or end == -1 or end <= start:
        return None

    try:
        payload = json.loads(text[start : end + 1])
    except json.JSONDecodeError:
        return None

    skill = payload.get("skill")
    return skill if isinstance(skill, str) and skill else None


def normalize_skill(raw_skill: str | None) -> str | None:
    """Map a raw model skill label to a known skill, if possible."""
    if not raw_skill or not isinstance(raw_skill, str):
        return None

    skill = raw_skill.strip().lower().replace("-", "_").replace(" ", "_")
    if skill in VALID_SKILLS:
        return skill
    if skill in SKILL_ALIASES:
        return SKILL_ALIASES[skill]
    return None


def infer_skill_from_prompt(prompt: str) -> str | None:
    """Keyword fallback when the model returns an unknown skill."""
    text = prompt.lower().strip()
    if not text:
        return None

    if re.search(r"gmail|@\w+\.\w+|send\s+(an?\s+)?email|compose\s+email|write\s+mail", text):
        return "gmail_send_email"

    if "whatsapp" in text or re.search(
        r"\b(send|message|text)\s+\w+\s+a\s+message\b", text
    ):
        return "whatsapp_send_message"

    rules: list[tuple[str, re.Pattern[str]]] = [
        ("contacts_search", re.compile(r"\bcontacts\b|phone book|address book")),
        ("slack_open_channel", re.compile(r"slack.*channel|channel.*slack|#\w+.*slack")),
        ("youtube_search", re.compile(r"youtube")),
        ("linkedin_search_person", re.compile(r"linkedin")),
        (
            "spotify_search_play",
            re.compile(r"spotify.*(search|find).*(play|and play)|search.*spotify.*play"),
        ),
        (
            "spotify_play_playlist",
            re.compile(r"playlist|liked songs|discover weekly|daily mix"),
        ),
        ("spotify_pause", re.compile(r"pause.*spotify|stop.*spotify|hold spotify")),
        ("uber_request_ride", re.compile(r"\buber\b|book.*ride|get.*ride")),
        ("create_alarm", re.compile(r"\balarm\b|wake me up|wake up at|wake up tomorrow")),
        (
            "calendar_create_event",
            re.compile(r"calendar|appointment|schedule.*meeting|book.*appointment"),
        ),
        ("bluetooth_enable", re.compile(r"bluetooth")),
        ("wifi_enable", re.compile(r"\bwifi\b|wlan")),
        ("camera_take_photo", re.compile(r"camera|take a photo|take a picture|selfie|snap a")),
    ]

    for skill, pattern in rules:
        if pattern.search(text):
            return skill

    if "spotify" in text:
        return "spotify_play_playlist"

    return None


def resolve_skill(raw_skill: str | None, prompt: str) -> str | None:
    """Return a valid skill from model output, aliases, or prompt keywords."""
    inferred = infer_skill_from_prompt(prompt)
    normalized = normalize_skill(raw_skill)

    text = prompt.lower()
    bare_message = re.search(r"\b(send|message|text)\s+\w+\s+a\s+message\b", text)
    if (
        inferred == "whatsapp_send_message"
        and bare_message
        and "gmail" not in text
        and "email" not in text
        and "@" not in prompt
        and normalized == "gmail_send_email"
    ):
        return inferred

    if normalized:
        return normalized
    return inferred


def _parse_json_payload(text: str) -> dict | None:
    text = text.strip()
    if not text:
        return None

    start = text.find("{")
    end = text.rfind("}")
    if start == -1 or end == -1 or end <= start:
        return None

    try:
        payload = json.loads(text[start : end + 1])
    except json.JSONDecodeError:
        return None

    return payload if isinstance(payload, dict) else None


def extract_intent(text: str) -> dict | None:
    """Extract skill and parameters from model output JSON."""
    payload = _parse_json_payload(text)
    if not payload:
        return None

    skill = payload.get("skill")
    if not isinstance(skill, str) or not skill:
        return None

    parameters = payload.get("parameters", {})
    if parameters is None:
        parameters = {}
    if not isinstance(parameters, dict):
        return None

    return {"skill": skill, "parameters": parameters}


def format_intent_json(skill: str, parameters: dict | None = None) -> str:
    payload: dict = {"skill": skill, "parameters": parameters or {}}
    return json.dumps(payload, separators=(",", ":"))


def normalize_param(value: str) -> str:
    return " ".join(value.lower().strip().split())


def parameters_match(
    predicted: dict,
    expected: dict,
    *,
    required_only: bool = True,
) -> bool:
    """Compare parameter dicts with normalized lowercase string matching."""
    for key, expected_value in expected.items():
        if required_only and expected_value is None:
            continue
        predicted_value = predicted.get(key)
        if predicted_value is None:
            return False
        if normalize_param(str(predicted_value)) != normalize_param(str(expected_value)):
            return False
    return True


def intent_matches(
    predicted: dict | None,
    expected_skill: str,
    expected_parameters: dict | None = None,
) -> bool:
    """Check if predicted intent matches expected skill and parameters."""
    if not predicted:
        return False

    predicted_skill = normalize_skill(predicted.get("skill")) or predicted.get("skill")
    if predicted_skill != expected_skill:
        return False
    if not expected_parameters:
        return True
    return parameters_match(
        predicted.get("parameters", {}),
        expected_parameters,
    )


def format_skill_json(skill: str) -> str:
    return json.dumps({"skill": skill}, separators=(",", ":"))