}

    @Test
    public void test_constructorWithMessageAndErrorCode() {
        final LlmException exception = new LlmException("Rate limit exceeded", LlmException.ERROR_RATE_LIMIT);
        assertEquals("Rate limit exceeded", exception.getMessage());
        assertEquals(LlmException.ERROR_RATE_LIMIT, exception.getErrorCode());
        assertNull(exception.getCause());
    }

    @Test

do
đó
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không
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lên
lúc
mà
mỗi
một cách
này
nên
nếu
ngay
nhiều
như
nhưng
những
nơi
nữa
phải
qua
ra
rằng
rằng
rất
rất
rồi
sau
sẽ
so
sự
tại
theo
thì
trên
trước
từ
từng
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vẫn
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với

# https://github.com/apache/lucene-solr/blob/master/lucene/analysis/common/src/resources/org/apache/lucene/analysis/eu/stopwords.txt
al
anitz
arabera
asko
baina
bat
batean
batek
bati
batzuei
batzuek
batzuetan
batzuk
bera
beraiek
berau
berauek
bere
berori
beroriek
beste
bezala
da
dago
dira
ditu
du
dute
edo
egin
ere
eta
eurak
ez
gainera
gu
gutxi
guzti

    }

    /**
     * Increment error counter
     */
    public void incrementErrors() {
        errors.incrementAndGet();
    }

    /**
     * Get error rate (errors / total requests)
     *
     * @return error rate between 0.0 and 1.0
     */
    public double getErrorRate() {
        long total = requestsSent.get();
        if (total == 0)
            return 0.0;

    @Test
    void testFormatRateEdgeCases() {
        FileSizeFormat format = new FileSizeFormat();

        // Test zero rate
        MessageBuilder builder = new DefaultMessageBuilder();
        format.formatRate(builder, 0.0);
        assertEquals("0.0 B/s", builder.build());

        // Test rate at exactly 1000 (1 kB/s)
        builder = new DefaultMessageBuilder();
        format.formatRate(builder, 1000.0);

  int maximumSize;

  @Param("5000")
  int distinctKeys;

  @Param("4")
  int segments;

  // 1 means uniform likelihood of keys; higher means some keys are more popular
  // tweak this to control hit rate
  @Param("2.5")
  double concentration;

  Random random = new Random();

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);

     */
    int[] getSupportedAlgorithms();

    /**
     * Estimates the compression ratio for the given data and algorithm.
     * This can be used to decide whether compression is worthwhile.
     *
     * @param data the data to analyze
     * @param algorithm the compression algorithm
     * @return estimated compression ratio (0.0 to 1.0, where 0.5 means 50% size reduction)
     */

        now = datetime.now(tz=timezone.utc)

        # Handle primary rate limits
        primary_limit_wait_time = 0.0
        if self.remaining_points <= self.last_query_cost:
            primary_limit_wait_time = (self.reset_at - now).total_seconds() + 2
            logging.warning(
                f"Approaching GitHub API rate limit, remaining points: {self.remaining_points}, "

        cookey(kn, KnL);
    }

    private void cookey(final int[] raw, final int KnL[]) {
        int raw0, raw1;
        int rawi, KnLi;
        int i;

        for (i = 0, rawi = 0, KnLi = 0; i < 16; ++i) {
            raw0 = raw[rawi];
            rawi++;
            raw1 = raw[rawi++];
            KnL[KnLi] = (raw0 & 0x00fc0000) << 6;
            KnL[KnLi] |= (raw0 & 0x00000fc0) << 10;

	for i := 0; i < 2*b.N; i++ {
		if i%2 == 0 {
			l.Add(trace[i], trace[i])
		} else {
			if _, ok := l.Get(trace[i]); ok {
				hit++
			} else {
				miss++
			}
		}
	}
	b.Logf("hit: %d miss: %d ratio: %f", hit, miss, float64(hit)/float64(hit+miss))
}

func BenchmarkLRU_Freq_NoExpire(b *testing.B) {
	l := lru.NewLRU[int64, int64](8192, nil, 0)

	trace := make([]int64, b.N*2)
	for i := 0; i < b.N*2; i++ {