File size: 15,190 Bytes
b5b9c2e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
"""Tests for trajectory_compressor.py — config, metrics, and compression logic."""

import json
from types import SimpleNamespace
from unittest.mock import AsyncMock, patch, MagicMock

import pytest

from trajectory_compressor import (
    CompressionConfig,
    TrajectoryMetrics,
    AggregateMetrics,
    TrajectoryCompressor,
)


# ---------------------------------------------------------------------------
# CompressionConfig
# ---------------------------------------------------------------------------


class TestCompressionConfig:
    def test_defaults(self):
        config = CompressionConfig()
        assert config.target_max_tokens == 15250
        assert config.summary_target_tokens == 750
        assert config.protect_last_n_turns == 4
        assert config.skip_under_target is True

    def test_from_yaml(self, tmp_path):
        yaml_content = """\
tokenizer:
  name: custom-tokenizer
  trust_remote_code: false
compression:
  target_max_tokens: 10000
  summary_target_tokens: 500
protected_turns:
  first_system: true
  first_human: false
  last_n_turns: 6
summarization:
  model: gpt-4
  temperature: 0.5
  max_retries: 5
output:
  add_summary_notice: false
  output_suffix: _short
processing:
  num_workers: 8
  max_concurrent_requests: 100
  skip_under_target: false
  save_over_limit: false
metrics:
  enabled: false
  per_trajectory: false
  output_file: my_metrics.json
"""
        yaml_file = tmp_path / "config.yaml"
        yaml_file.write_text(yaml_content)
        config = CompressionConfig.from_yaml(str(yaml_file))
        assert config.tokenizer_name == "custom-tokenizer"
        assert config.trust_remote_code is False
        assert config.target_max_tokens == 10000
        assert config.summary_target_tokens == 500
        assert config.protect_first_human is False
        assert config.protect_last_n_turns == 6
        assert config.summarization_model == "gpt-4"
        assert config.temperature == 0.5
        assert config.max_retries == 5
        assert config.add_summary_notice is False
        assert config.output_suffix == "_short"
        assert config.num_workers == 8
        assert config.max_concurrent_requests == 100
        assert config.skip_under_target is False
        assert config.save_over_limit is False
        assert config.metrics_enabled is False
        assert config.metrics_output_file == "my_metrics.json"

    def test_from_yaml_partial(self, tmp_path):
        """Only specified sections override defaults."""
        yaml_file = tmp_path / "config.yaml"
        yaml_file.write_text("compression:\n  target_max_tokens: 8000\n")
        config = CompressionConfig.from_yaml(str(yaml_file))
        assert config.target_max_tokens == 8000
        # Other sections keep defaults
        assert config.protect_last_n_turns == 4
        assert config.num_workers == 4

    def test_from_yaml_empty(self, tmp_path):
        yaml_file = tmp_path / "config.yaml"
        yaml_file.write_text("{}\n")
        config = CompressionConfig.from_yaml(str(yaml_file))
        assert config.target_max_tokens == 15250  # all defaults


# ---------------------------------------------------------------------------
# TrajectoryMetrics
# ---------------------------------------------------------------------------


class TestTrajectoryMetrics:
    def test_to_dict(self):
        m = TrajectoryMetrics()
        m.original_tokens = 10000
        m.compressed_tokens = 5000
        m.tokens_saved = 5000
        m.compression_ratio = 0.5
        m.original_turns = 20
        m.compressed_turns = 10
        m.turns_removed = 10
        m.was_compressed = True
        d = m.to_dict()
        assert d["original_tokens"] == 10000
        assert d["compressed_tokens"] == 5000
        assert d["compression_ratio"] == 0.5
        assert d["was_compressed"] is True
        assert d["compression_region"]["start_idx"] == -1

    def test_default_values(self):
        m = TrajectoryMetrics()
        d = m.to_dict()
        assert d["original_tokens"] == 0
        assert d["was_compressed"] is False
        assert d["skipped_under_target"] is False


# ---------------------------------------------------------------------------
# AggregateMetrics
# ---------------------------------------------------------------------------


class TestAggregateMetrics:
    def test_empty_to_dict(self):
        agg = AggregateMetrics()
        d = agg.to_dict()
        assert d["summary"]["total_trajectories"] == 0
        assert d["averages"]["avg_compression_ratio"] == 1.0
        assert d["averages"]["avg_tokens_saved_per_compressed"] == 0

    def test_add_compressed_trajectory(self):
        agg = AggregateMetrics()
        m = TrajectoryMetrics()
        m.original_tokens = 20000
        m.compressed_tokens = 10000
        m.tokens_saved = 10000
        m.compression_ratio = 0.5
        m.original_turns = 30
        m.compressed_turns = 15
        m.turns_removed = 15
        m.was_compressed = True
        agg.add_trajectory_metrics(m)
        assert agg.total_trajectories == 1
        assert agg.trajectories_compressed == 1
        assert agg.total_tokens_saved == 10000
        assert len(agg.compression_ratios) == 1

    def test_add_skipped_trajectory(self):
        agg = AggregateMetrics()
        m = TrajectoryMetrics()
        m.original_tokens = 5000
        m.compressed_tokens = 5000
        m.skipped_under_target = True
        agg.add_trajectory_metrics(m)
        assert agg.trajectories_skipped_under_target == 1
        assert agg.trajectories_compressed == 0

    def test_add_over_limit_trajectory(self):
        agg = AggregateMetrics()
        m = TrajectoryMetrics()
        m.original_tokens = 20000
        m.compressed_tokens = 16000
        m.still_over_limit = True
        m.was_compressed = True
        m.compression_ratio = 0.8
        agg.add_trajectory_metrics(m)
        assert agg.trajectories_still_over_limit == 1

    def test_multiple_trajectories_aggregation(self):
        agg = AggregateMetrics()
        for i in range(3):
            m = TrajectoryMetrics()
            m.original_tokens = 10000
            m.compressed_tokens = 5000
            m.tokens_saved = 5000
            m.turns_removed = 5
            m.was_compressed = True
            m.compression_ratio = 0.5
            agg.add_trajectory_metrics(m)
        d = agg.to_dict()
        assert d["summary"]["total_trajectories"] == 3
        assert d["summary"]["trajectories_compressed"] == 3
        assert d["tokens"]["total_saved"] == 15000
        assert d["averages"]["avg_compression_ratio"] == 0.5

    def test_to_dict_no_division_by_zero(self):
        """Ensure no ZeroDivisionError with empty data."""
        agg = AggregateMetrics()
        d = agg.to_dict()
        assert d["summarization"]["success_rate"] == 1.0
        assert d["tokens"]["overall_compression_ratio"] == 0.0


# ---------------------------------------------------------------------------
# TrajectoryCompressor._find_protected_indices
# ---------------------------------------------------------------------------


def _make_compressor(config=None):
    """Create a TrajectoryCompressor with mocked tokenizer and summarizer."""
    if config is None:
        config = CompressionConfig()
    with patch.object(TrajectoryCompressor, '_init_tokenizer'), \
         patch.object(TrajectoryCompressor, '_init_summarizer'):
        compressor = TrajectoryCompressor(config)
    # Provide a simple token counter for tests (1 token per 4 chars)
    compressor.tokenizer = MagicMock()
    compressor.tokenizer.encode = lambda text: [0] * (len(text) // 4)
    return compressor


class TestFindProtectedIndices:
    def test_basic_trajectory(self):
        tc = _make_compressor()
        trajectory = [
            {"from": "system", "value": "You are an agent."},
            {"from": "human", "value": "Do something."},
            {"from": "gpt", "value": "I will use a tool."},
            {"from": "tool", "value": "Tool result."},
            {"from": "gpt", "value": "More work."},
            {"from": "tool", "value": "Another result."},
            {"from": "gpt", "value": "Work continues."},
            {"from": "tool", "value": "Result 3."},
            {"from": "gpt", "value": "Done."},
            {"from": "human", "value": "Thanks."},
        ]
        protected, start, end = tc._find_protected_indices(trajectory)
        # First system (0), human (1), gpt (2), tool (3) are protected
        assert 0 in protected
        assert 1 in protected
        assert 2 in protected
        assert 3 in protected
        # Last 4 turns (6,7,8,9) are protected
        assert 6 in protected
        assert 7 in protected
        assert 8 in protected
        assert 9 in protected
        # Compressible region should be between head and tail
        assert start >= 4
        assert end <= 6

    def test_short_trajectory_all_protected(self):
        tc = _make_compressor()
        trajectory = [
            {"from": "system", "value": "sys"},
            {"from": "human", "value": "hi"},
            {"from": "gpt", "value": "hello"},
        ]
        protected, start, end = tc._find_protected_indices(trajectory)
        # All 3 turns should be protected (first of each + last 4 covers all)
        assert len(protected) == 3
        assert start >= end  # Nothing to compress

    def test_protect_last_n_zero(self):
        config = CompressionConfig()
        config.protect_last_n_turns = 0
        tc = _make_compressor(config)
        trajectory = [
            {"from": "system", "value": "sys"},
            {"from": "human", "value": "q"},
            {"from": "gpt", "value": "a"},
            {"from": "tool", "value": "r"},
            {"from": "gpt", "value": "b"},
            {"from": "tool", "value": "r2"},
            {"from": "gpt", "value": "c"},
            {"from": "tool", "value": "r3"},
        ]
        protected, start, end = tc._find_protected_indices(trajectory)
        # Only first occurrences protected, no tail protection
        assert 0 in protected
        assert 1 in protected
        assert 2 in protected
        assert 3 in protected
        assert 7 not in protected

    def test_no_system_turn(self):
        tc = _make_compressor()
        trajectory = [
            {"from": "human", "value": "hi"},
            {"from": "gpt", "value": "hello"},
            {"from": "tool", "value": "data"},
            {"from": "gpt", "value": "result"},
            {"from": "human", "value": "thanks"},
        ]
        protected, start, end = tc._find_protected_indices(trajectory)
        assert 0 in protected  # first human

    def test_disable_protect_first_system(self):
        config = CompressionConfig()
        config.protect_first_system = False
        tc = _make_compressor(config)
        trajectory = [
            {"from": "system", "value": "sys"},
            {"from": "human", "value": "q"},
            {"from": "gpt", "value": "a"},
            {"from": "tool", "value": "r"},
            {"from": "gpt", "value": "b"},
            {"from": "tool", "value": "r2"},
            {"from": "gpt", "value": "c"},
            {"from": "tool", "value": "r3"},
        ]
        protected, _, _ = tc._find_protected_indices(trajectory)
        assert 0 not in protected  # system not protected


# ---------------------------------------------------------------------------
# TrajectoryCompressor._extract_turn_content_for_summary
# ---------------------------------------------------------------------------


class TestExtractTurnContent:
    def test_basic_extraction(self):
        tc = _make_compressor()
        trajectory = [
            {"from": "gpt", "value": "I will search."},
            {"from": "tool", "value": "Search result: found it."},
            {"from": "gpt", "value": "Great, done."},
        ]
        content = tc._extract_turn_content_for_summary(trajectory, 0, 2)
        assert "[Turn 0 - GPT]" in content
        assert "I will search." in content
        assert "[Turn 1 - TOOL]" in content
        assert "Search result: found it." in content
        # Turn 2 should NOT be included (end is exclusive)
        assert "[Turn 2" not in content

    def test_long_content_truncated(self):
        tc = _make_compressor()
        trajectory = [
            {"from": "tool", "value": "x" * 5000},
        ]
        content = tc._extract_turn_content_for_summary(trajectory, 0, 1)
        assert "...[truncated]..." in content
        assert len(content) < 5000

    def test_empty_range(self):
        tc = _make_compressor()
        trajectory = [{"from": "gpt", "value": "hello"}]
        content = tc._extract_turn_content_for_summary(trajectory, 0, 0)
        assert content == ""


# ---------------------------------------------------------------------------
# TrajectoryCompressor.count_tokens / count_trajectory_tokens
# ---------------------------------------------------------------------------


class TestTokenCounting:
    def test_count_tokens_empty(self):
        tc = _make_compressor()
        assert tc.count_tokens("") == 0

    def test_count_tokens_basic(self):
        tc = _make_compressor()
        # Our mock: 1 token per 4 chars
        assert tc.count_tokens("12345678") == 2

    def test_count_trajectory_tokens(self):
        tc = _make_compressor()
        trajectory = [
            {"from": "system", "value": "12345678"},   # 2 tokens
            {"from": "human", "value": "1234567890ab"}, # 3 tokens
        ]
        assert tc.count_trajectory_tokens(trajectory) == 5

    def test_count_turn_tokens(self):
        tc = _make_compressor()
        trajectory = [
            {"from": "system", "value": "1234"},     # 1 token
            {"from": "human", "value": "12345678"},  # 2 tokens
        ]
        result = tc.count_turn_tokens(trajectory)
        assert result == [1, 2]

    def test_count_tokens_fallback_on_error(self):
        tc = _make_compressor()
        tc.tokenizer.encode = MagicMock(side_effect=Exception("fail"))
        # Should fallback to len(text) // 4
        assert tc.count_tokens("12345678") == 2


class TestGenerateSummary:
    def test_generate_summary_handles_none_content(self):
        tc = _make_compressor()
        tc.client = MagicMock()
        tc.client.chat.completions.create.return_value = SimpleNamespace(
            choices=[SimpleNamespace(message=SimpleNamespace(content=None))]
        )
        metrics = TrajectoryMetrics()

        summary = tc._generate_summary("Turn content", metrics)

        assert summary == "[CONTEXT SUMMARY]:"

    @pytest.mark.asyncio
    async def test_generate_summary_async_handles_none_content(self):
        tc = _make_compressor()
        mock_client = MagicMock()
        mock_client.chat.completions.create = AsyncMock(
            return_value=SimpleNamespace(
                choices=[SimpleNamespace(message=SimpleNamespace(content=None))]
            )
        )
        tc._get_async_client = MagicMock(return_value=mock_client)
        metrics = TrajectoryMetrics()

        summary = await tc._generate_summary_async("Turn content", metrics)

        assert summary == "[CONTEXT SUMMARY]:"