#!/usr/bin/env python3
"""Extract common CS entity identifiers from ticket text (pattern-based MVP).

Does not call NMI. Purpose: surface tracking numbers / order-like IDs / SKUs
so humans and agents can jump systems without copy-paste gymnastics.

Patterns are conservative heuristics — false positives are possible; treat hits
as hints, not ground truth.
"""

from __future__ import annotations

import re
from typing import Any, Iterable


# USPS: 20–22 digit, or 420… + 26 digits, or 13-char ending US
_USPS = re.compile(
    r"\b("
    r"9[0-9]{19,21}"
    r"|420\d{5}\d{20,26}"
    r"|[A-Z]{2}\d{9}US"
    r")\b",
    re.I,
)
_UPS = re.compile(r"\b(1Z[0-9A-Z]{16})\b", re.I)
_FEDEX = re.compile(r"\b(\d{12}|\d{15})\b")
_AMZ_ORDER = re.compile(r"\b(\d{3}-\d{7}-\d{7})\b")
# Prefer digit-heavy order captures; reject pure alpha HTML fragments
_ORDER_LABEL = re.compile(
    r"(?:order\s*(?:id|#|number|no\.?)|po\s*(?:#|number)?)\s*[:=\s#]*([A-Z0-9][A-Z0-9\-_/]{3,32})",
    re.I,
)
_ITEM_LABEL = re.compile(
    r"(?:item\s*(?:#|no\.?|number)|sku|merchant\s*sku)\s*[:=\s#]*([A-Z0-9][A-Z0-9\-_/]{2,40})",
    re.I,
)
_ACCOUNT = re.compile(r"\baccount\s*[#:]?\s*([A-Z0-9]{4,20})\b", re.I)
# LDR unit item numbers: 9 digits starting with 2
_ITEM_NO_BARE = re.compile(r"\b(2\d{8})\b")

_ORDER_STOP = {
    "number",
    "id",
    "no",
    "none",
    "null",
    "true",
    "false",
    "class",
    "style",
    "mode",
    "text",
    "title",
    "guide",
    "html",
    "body",
    "rted",
    "rtal",
    "licy",
    "lation-mode",
    "rtant",
    "nsive",
    "nsive-text",
    "nsive-title",
    "nsive-h2",
    "ints",
}


def _text_from_issue(issue: dict[str, Any]) -> str:
    chunks: list[str] = []
    for key in ("subject", "description"):
        val = issue.get(key)
        if val:
            chunks.append(str(val))
    helpdesk = issue.get("helpdesk_ticket")
    if isinstance(helpdesk, dict):
        for key in ("from_address", "to_address", "message_id"):
            if helpdesk.get(key):
                chunks.append(str(helpdesk[key]))
        contact = helpdesk.get("contact")
        if isinstance(contact, dict):
            for key in ("email", "company", "name", "first_name", "last_name"):
                if contact.get(key):
                    chunks.append(str(contact[key]))
    journals = issue.get("journals")
    if isinstance(journals, list):
        for j in journals[-15:]:
            if isinstance(j, dict) and j.get("notes"):
                chunks.append(str(j["notes"]))
    return "\n".join(chunks)


def extract_entities(text: str) -> list[dict[str, str]]:
    """Return unique {type, value, confidence} hits from free text."""
    hits: list[dict[str, str]] = []
    seen: set[tuple[str, str]] = set()

    def add(kind: str, value: str, confidence: str = "high") -> None:
        value = value.strip()
        if not value:
            return
        key = (kind, value.upper())
        if key in seen:
            return
        seen.add(key)
        hits.append({"type": kind, "value": value, "confidence": confidence})

    for m in _UPS.finditer(text):
        add("tracking_ups", m.group(1).upper())
    for m in _USPS.finditer(text):
        add("tracking_usps", m.group(1).upper())
    for m in _AMZ_ORDER.finditer(text):
        add("order_amazon", m.group(1))
    for m in _ORDER_LABEL.finditer(text):
        val = m.group(1)
        if re.fullmatch(r"\d{3}-\d{7}-\d{7}", val):
            add("order_amazon", val)
            continue
        if not re.search(r"\d", val):
            continue
        if val.lower() in _ORDER_STOP:
            continue
        # Require at least 5 chars and a digit; reject long alpha+token noise
        if len(val) < 5:
            continue
        if re.search(r"[a-zA-Z]{6,}", val) and not re.search(r"\d{4,}", val):
            continue  # e.g. MGdHZfSeDzi_BhM6 without enough digits
        conf = "high" if re.fullmatch(r"\d{5,12}", val) else "medium"
        add("order_id", val, confidence=conf)
    for m in _ITEM_LABEL.finditer(text):
        val = m.group(1)
        if re.fullmatch(r"2\d{8}", val):
            add("item_no", val, confidence="high")
        elif re.search(r"\d", val) or re.search(r"[A-Z]{2,}", val, re.I):
            add("item_or_sku", val, confidence="medium")
    for m in _ITEM_NO_BARE.finditer(text):
        add("item_no", m.group(1), confidence="medium")
    for m in _ACCOUNT.finditer(text):
        val = m.group(1)
        if val.lower() in {"within", "number", "setup", "your", "the"}:
            continue
        if not re.search(r"\d", val) and len(val) < 6:
            continue
        add("account_ref", val, confidence="medium")

    if re.search(r"\b(fedex|tracking|shipment|shipped|carrier)\b", text, re.I):
        for m in _FEDEX.finditer(text):
            # skip USPS/item_no already captured lengths that are tracking
            val = m.group(1)
            if val.startswith("9") and len(val) >= 20:
                continue
            if re.fullmatch(r"2\d{8}", val):
                continue
            add("tracking_fedex_candidate", val, confidence="low")

    return hits


def extract_entities_from_issue(issue: dict[str, Any]) -> list[dict[str, str]]:
    return extract_entities(_text_from_issue(issue))


def format_entities_line(entities: Iterable[dict[str, str]]) -> str:
    parts = []
    for e in entities:
        conf = e.get("confidence") or "high"
        if conf == "high":
            parts.append(f"{e['type']}:{e['value']}")
        else:
            parts.append(f"{e['type']}:{e['value']}({conf})")
    return "; ".join(parts)