#!/usr/bin/env python3
"""AI Meter v1.4.9-compatible 1544-dimensional feature extraction."""
from __future__ import annotations
import re
from typing import Iterable
import numpy as np
import regex

WORD_BINS = 1024
CHAR_BINS = 512
NUMERIC_FEATURES = 8
INPUT_SIZE = WORD_BINS + CHAR_BINS + NUMERIC_FEATURES

TECH_RE = re.compile(r"[{}\[\]();=<>/]")
URL_RE = re.compile(r"https?://|www\.", re.I)
DOC_RE = re.compile(r"\b(pdf|document|dokument|file|súbor|attachment|príloha)\b", re.I)

def _utf16_units(text: str) -> Iterable[int]:
    raw = text.encode("utf-16-le", errors="surrogatepass")
    for index in range(0, len(raw), 2):
        yield raw[index] | (raw[index + 1] << 8)

def fnv1a_js(text: str) -> int:
    """32-bit FNV-1a over JavaScript-compatible UTF-16 code units."""
    value = 2166136261
    for unit in _utf16_units(text):
        value ^= unit
        value = (value * 16777619) & 0xFFFFFFFF
    return value

def build_features(text: str) -> np.ndarray:
    source = str(text or "")
    lower = source.lower()
    values = np.zeros(INPUT_SIZE, dtype=np.float32)
    words = regex.findall(r"[\p{L}\p{N}_]+", lower)
    grams = list(words)
    grams.extend(f"{words[i]}_{words[i + 1]}" for i in range(len(words) - 1))
    for gram in grams:
        values[fnv1a_js(gram) % WORD_BINS] += 1.0
    compact = regex.sub(r"\s+", " ", lower)
    for index in range(max(0, len(compact) - 2)):
        trigram = compact[index:index + 3]
        values[WORD_BINS + (fnv1a_js(trigram) % CHAR_BINS)] += 0.25
    sparse = values[:WORD_BINS + CHAR_BINS]
    norm = float(np.linalg.norm(sparse))
    if norm > 0:
        sparse /= norm
    base = WORD_BINS + CHAR_BINS
    values[base] = min(len(source), 4000) / 4000
    values[base + 1] = min(len(words), 800) / 800
    values[base + 2] = min(source.count("?"), 10) / 10
    values[base + 3] = min(source.count("\n"), 30) / 30
    values[base + 4] = min(len(TECH_RE.findall(source)), 100) / 100
    values[base + 5] = 1.0 if URL_RE.search(source) else 0.0
    values[base + 6] = 1.0 if DOC_RE.search(source) else 0.0
    values[base + 7] = 1.0
    return values