120 lines
4.4 KiB
Python
120 lines
4.4 KiB
Python
from unittest.mock import patch
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from agent.context_compressor import ContextCompressor, _estimate_msg_budget_tokens
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from agent.model_metadata import (
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_is_cjk_token_dense_char,
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estimate_messages_tokens_rough,
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estimate_tokens_rough,
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)
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def test_message_estimate_counts_korean_content_as_token_dense():
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messages = [{"role": "user", "content": "압축 테스트 " + ("가" * 1000)}]
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assert estimate_messages_tokens_rough(messages) >= 1000
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def test_cjk_tail_does_not_expand_to_english_char_budget():
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with patch("agent.context_compressor.get_model_context_length", return_value=65536):
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compressor = ContextCompressor(
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"test/model",
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protect_first_n=3,
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protect_last_n=20,
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summary_target_ratio=0.2,
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quiet_mode=True,
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)
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# Resolve while the mock is active (lazy init, #32221).
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_ = compressor.context_length
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messages = [
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{"role": "user", "content": "head 1"},
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{"role": "assistant", "content": "head 2"},
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{"role": "user", "content": "head 3"},
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]
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for idx in range(40):
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role = "assistant" if idx % 2 else "user"
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messages.append({"role": role, "content": "가" * 1200})
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compress_start = compressor._align_boundary_forward(
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messages,
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compressor._protect_head_size(messages),
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)
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compress_end = compressor._find_tail_cut_by_tokens(messages, compress_start)
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assert len(messages) - compress_end < 31
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def _reference_per_char_estimate(text: str) -> int:
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"""Per-character reference: CJK ~1 token/char, everything else UTF-8
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bytes/4 (the byte width corrects Cyrillic/Greek/Arabic under-counting)."""
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dense = 0
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sparse_bytes = 0
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for ch in text:
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if _is_cjk_token_dense_char(ch):
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dense += 1
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else:
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sparse_bytes += len(ch.encode("utf-8"))
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return dense + ((sparse_bytes + 3) // 4)
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def test_perf_gated_estimator_matches_per_char_reference():
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samples = [
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"",
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"ab",
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"a" * 400,
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"가" * 400,
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"압축 테스트 " + ("가" * 1000),
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"café résumé naïve", # non-ASCII, no CJK
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"hello 안녕 world",
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"ｱｲｳｴｵ ﾃｽﾄ", # halfwidth kana (fullwidth-forms block)
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"漢字とかな交じり文です。",
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"русский текст", # Cyrillic — non-ASCII, non-CJK
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]
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for text in samples:
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assert estimate_tokens_rough(text) == _reference_per_char_estimate(text), repr(text)
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def test_cyrillic_counts_by_utf8_bytes():
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# «русский текст» = 12 Cyrillic chars (2 bytes each) + 1 ASCII space:
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# 25 bytes -> ceil(25/4) = 7 tokens; the old chars/4 rule said 4 —
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# the ~2x under-count that let real prompts ride the context ceiling.
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from agent.model_metadata import estimate_tokens_rough
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assert estimate_tokens_rough("русский текст") == 7
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# Pure ASCII unchanged.
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assert estimate_tokens_rough("a" * 400) == 100
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def test_accented_latin_is_not_inflated_by_byte_counting():
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# Byte-counting must not punish Western-European text: only the accented
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# chars are 2 bytes, so the estimate moves by a few percent, not 2x.
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from agent.model_metadata import estimate_tokens_rough
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fr = "La compression du contexte permet aux longues sessions de rester dans la fenêtre du fournisseur sans perdre le fil de la tâche."
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ascii_rule = (len(fr) + 3) // 4
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est = estimate_tokens_rough(fr)
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assert ascii_rule <= est <= int(ascii_rule * 1.10), (ascii_rule, est)
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def test_mixed_cyrillic_and_ascii_code_counts_ascii_at_one_byte():
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from agent.model_metadata import estimate_tokens_rough
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code = "def compress(ctx):\n # Сжимаем контекст\n return summarize(ctx)\n"
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ascii_part = "def compress(ctx):\n # \n return summarize(ctx)\n"
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cyr = "Сжимаем контекст"
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expected = (len(ascii_part.encode()) + len(cyr.encode()) + 3) // 4
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assert estimate_tokens_rough(code) == expected
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# and strictly more than the old chars/4 rule for the same text
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assert estimate_tokens_rough(code) > (len(code) + 3) // 4
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def test_lone_surrogates_do_not_raise():
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# main's estimator was total (len/regex never raise); byte-counting must
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# stay total too — tool output routinely carries unpaired surrogates.
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from agent.model_metadata import estimate_tokens_rough
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assert estimate_tokens_rough("abc\ud800def") >= 2
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assert estimate_tokens_rough("漢字\udfff") >= 2
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