headroom/tests/test_quality_retention.py
chopratejas 1601591900 feat(rust): SmartCrusher PR4 — lossless-first default + CCR-Dropped restoration
Stage 3c.2 PR4. Restores Python's CCR-Dropped semantics on the lossy
path (the cornerstone reversibility guarantee that the port had
silently dropped) and flips the OSS default to lossless-first with a
configurable savings threshold.

# The user-visible behavior

Default `SmartCrusher::new()` now runs:

  1. Try lossless compaction.
  2. If savings >= `lossless_min_savings_ratio` (default 0.30), ship
     it — `compacted` populated, `ccr_hash = None`, nothing dropped.
  3. Otherwise fall through to the lossy path — drop rows AND
     populate `ccr_hash` so the runtime can cache the full original
     for tool-call retrieval.

**No data is ever lost.** "Lossy" means "compressed view inline; full
payload retrievable via CCR cache" — same semantics as Python's
SmartCrusher with CCR enabled. The runtime (PyO3 bridge / proxy
server) owns the cache; this crate computes the hash and emits a
marker so the prompt knows where to look.

# What changed

- `SmartCrusherConfig.lossless_min_savings_ratio: f64` (default 0.30).
  Single configurable knob — Enterprise overrides as needed. Below
  the threshold, lossless declines and lossy + CCR runs.

- `SmartCrusher::new(cfg)` flips to include the compaction stage by
  default. `SmartCrusher::without_compaction(cfg)` is the explicit
  opt-out for callers / fixtures that depend on pre-PR4 behavior.

- `crush_array` rewritten:
  - Lossless-first dispatch with savings-ratio gate
  - Lossy path now hashes the full original (12-char SHA-256 prefix)
    and emits a CCR-Dropped marker in `dropped_summary` whenever
    rows are dropped
  - `ccr_hash` field populated whenever rows were dropped
  - `process_value` substitutes the compacted string into the JSON
    tree when lossless wins, so `crush()` output reflects the win

- PyO3 bridge: `SmartCrusher.without_compaction()` static method;
  `SmartCrusherConfig` exposes the new `lossless_min_savings_ratio`
  field; Python `SmartCrusher` wrapper accepts `with_compaction=True`
  (default) and routes to the right Rust constructor.

- Parity harness: legacy 17 fixtures use `without_compaction()` so
  byte-equal coverage of the lossy path is preserved.

# Tests

- Rust: 281/281 smart_crusher unit tests pass (was 277). Six new
  tests cover: lossless wins above threshold, lossy falls through
  below threshold, CCR hash deterministic + input-dependent, lossy
  without compaction emits CCR, passthrough paths don't emit CCR,
  without_compaction yields no compacted field.
- Python parity: 21/21 (legacy fixtures via without_compaction).
- Python lossless default smoke: 3/3 new tests in
  test_smart_crusher_lossless_default.py.
- Python retention: 21/21 (updated to opt into the lossy path
  explicitly since their semantics target row-level retention).
- make ci-precheck green.

Modules:
  crates/headroom-core/src/transforms/smart_crusher/{config,crusher}.rs
  crates/headroom-parity/src/lib.rs
  crates/headroom-py/src/lib.rs
  headroom/transforms/smart_crusher.py
  tests/test_quality_retention.py
  tests/test_transforms/test_smart_crusher_{lossless_default,rust_parity}.py
2026-04-27 16:30:22 -07:00

398 lines
15 KiB
Python

"""Formal evals for SmartCrusher quality retention.
These tests verify that SmartCrusher GUARANTEES 100% retention of critical items:
1. Error items: Items containing error keywords
2. Anomaly items: Items with values > 2 std from mean
3. Relevance items: Items matching user query context
This is a FORMAL EVAL - any failure here is a CRITICAL BUG.
"""
import json
import pytest
from headroom.providers.anthropic import AnthropicTokenCounter
from headroom.tokenizer import Tokenizer
from headroom.transforms.smart_crusher import (
SmartCrusher,
SmartCrusherConfig,
smart_crush_tool_output,
)
class TestErrorRetention:
"""Verify 100% retention of error items."""
ERROR_KEYWORDS = ["error", "exception", "failed", "failure", "critical", "fatal"]
@pytest.fixture
def large_dataset(self):
"""Create large dataset with known errors."""
items = []
error_indices = []
for i in range(1000):
items.append(
{
"id": f"item_{i}",
"value": i,
"status": "ok",
"message": f"Normal operation {i}",
}
)
# Insert errors at specific positions
for idx in [10, 50, 100, 250, 500, 750, 999]:
items[idx]["status"] = "failed"
items[idx]["error"] = f"Error at position {idx}"
error_indices.append(idx)
return items, error_indices
def test_all_error_items_retained(self, large_dataset):
"""CRITICAL: Every item with error keywords MUST be retained."""
items, error_indices = large_dataset
config = SmartCrusherConfig(max_items_after_crush=20)
content = json.dumps(items)
compressed_str, _, _ = smart_crush_tool_output(content, config, with_compaction=False)
compressed = json.loads(compressed_str)
# Count errors before and after
errors_before = len(error_indices)
errors_after = sum(1 for x in compressed if x.get("error"))
assert errors_after == errors_before, (
f"QUALITY FAILURE: Lost {errors_before - errors_after} error items! "
f"Expected {errors_before}, got {errors_after}"
)
@pytest.mark.parametrize("keyword", ERROR_KEYWORDS)
def test_each_error_keyword_detected(self, keyword):
"""Each error keyword must trigger retention."""
items = [{"id": f"item_{i}", "msg": f"Normal {i}"} for i in range(100)]
items[50]["msg"] = f"This contains {keyword} keyword"
config = SmartCrusherConfig(max_items_after_crush=15)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
matching = [x for x in compressed if keyword in str(x).lower()]
assert len(matching) >= 1, f"Item with '{keyword}' keyword was dropped!"
def test_error_in_nested_structure(self):
"""Errors in nested objects must be detected."""
items = [{"id": i, "data": {"status": "ok"}} for i in range(100)]
items[50]["data"]["status"] = "failed"
items[50]["data"]["error"] = "Nested error"
config = SmartCrusherConfig(max_items_after_crush=15)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
nested_errors = [x for x in compressed if x.get("data", {}).get("error")]
assert len(nested_errors) >= 1, "Nested error item was dropped!"
def test_multiple_errors_all_retained(self):
"""When errors exceed max_items, ALL errors must still be retained."""
# Create 100 items where 30 are errors (more than max_items_after_crush)
items = []
for i in range(100):
item = {"id": i, "value": i}
if i % 3 == 0: # Every 3rd item is an error (33 total)
item["error"] = f"Error {i}"
item["status"] = "failed"
items.append(item)
error_count_before = sum(1 for x in items if x.get("error"))
assert error_count_before == 34 # 0,3,6,...,99 = 34 items
# Compress with max 20 items
config = SmartCrusherConfig(max_items_after_crush=20)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
error_count_after = sum(1 for x in compressed if x.get("error"))
# When errors > max_items, we should keep ALL errors (errors take priority)
# This tests the _prioritize_indices logic
assert error_count_after == error_count_before, (
f"CRITICAL: Errors were dropped! "
f"Before: {error_count_before}, After: {error_count_after}"
)
class TestAnomalyRetention:
"""Verify 100% retention of anomalous numeric values."""
def test_numeric_anomalies_retained(self):
"""Items with values > 2 std from mean must be retained."""
items = []
anomaly_indices = []
# Create items with normal values around mean=100, std=10
for i in range(1000):
items.append(
{
"id": f"item_{i}",
"value": 100 + (i % 20) - 10, # Values 90-110
"name": f"Normal item {i}",
}
)
# Insert anomalies (> 2 std = > 120 or < 80)
for idx in [100, 300, 500, 700, 900]:
items[idx]["value"] = 999999 # Extreme anomaly
items[idx]["is_anomaly"] = True # Mark for verification
anomaly_indices.append(idx)
config = SmartCrusherConfig(max_items_after_crush=20)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
anomalies_after = sum(1 for x in compressed if x.get("is_anomaly"))
assert anomalies_after == len(anomaly_indices), (
f"QUALITY FAILURE: Lost anomaly items! "
f"Expected {len(anomaly_indices)}, got {anomalies_after}"
)
def test_negative_anomalies_retained(self):
"""Negative outliers must also be retained."""
items = [{"id": i, "value": 100} for i in range(100)]
items[50]["value"] = -999 # Negative anomaly
items[50]["is_anomaly"] = True
config = SmartCrusherConfig(max_items_after_crush=15)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
anomalies = [x for x in compressed if x.get("is_anomaly")]
assert len(anomalies) == 1, "Negative anomaly was dropped!"
class TestRelevanceRetention:
"""Verify retention of items matching query context."""
def test_relevance_with_query_context(self):
"""Items matching query should be retained when context is provided."""
items = [{"id": i, "content": f"Generic content about topic {i}"} for i in range(100)]
# Insert a specific item that matches our query
# Note: This also contains "error" keyword which will trigger error retention
items[50]["content"] = "Authentication error: invalid JWT token expired"
items[50]["is_target"] = True
# Use SmartCrusher with query context (via message-based API)
config = SmartCrusherConfig(max_items_after_crush=15)
crusher = SmartCrusher(config, with_compaction=False)
# Create tokenizer with proper counter
model = "claude-3-5-sonnet-20241022"
token_counter = AnthropicTokenCounter(model)
tokenizer = Tokenizer(token_counter, model)
# Create messages with query context
messages = [
{"role": "user", "content": "Why is JWT authentication failing?"},
{"role": "tool", "tool_call_id": "call_1", "content": json.dumps(items)},
]
result = crusher.apply(messages, tokenizer)
tool_msg = next(m for m in result.messages if m.get("role") == "tool")
compressed = json.loads(tool_msg["content"].split("\n")[0]) # Remove marker
targets = [x for x in compressed if x.get("is_target")]
assert len(targets) >= 1, "Target item was dropped despite matching query context!"
class TestFirstLastRetention:
"""Verify first K and last K items are always retained."""
def test_first_items_retained(self):
"""First 3 items must always be retained."""
items = [{"id": i, "value": i} for i in range(100)]
config = SmartCrusherConfig(max_items_after_crush=15)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
ids = [x["id"] for x in compressed]
assert 0 in ids, "First item (id=0) was dropped!"
assert 1 in ids, "Second item (id=1) was dropped!"
assert 2 in ids, "Third item (id=2) was dropped!"
def test_last_items_retained(self):
"""Last 2 items must always be retained."""
items = [{"id": i, "value": i} for i in range(100)]
config = SmartCrusherConfig(max_items_after_crush=15)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
ids = [x["id"] for x in compressed]
assert 98 in ids, "Second-to-last item (id=98) was dropped!"
assert 99 in ids, "Last item (id=99) was dropped!"
class TestCombinedRetention:
"""Test retention when multiple preservation criteria apply."""
def test_error_and_anomaly_both_retained(self):
"""Items that are both errors AND anomalies must be retained."""
items = [{"id": i, "value": 100} for i in range(100)]
# Item is both an error AND an anomaly
items[50]["value"] = 999999
items[50]["error"] = "Critical failure"
items[50]["is_both"] = True
config = SmartCrusherConfig(max_items_after_crush=10)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
both = [x for x in compressed if x.get("is_both")]
assert len(both) == 1, "Item with both error and anomaly was dropped!"
def test_high_volume_critical_items(self):
"""Even with many critical items, none should be dropped."""
items = []
critical_count = 0
for i in range(500):
item = {"id": i, "value": 100}
# Make every 5th item an error
if i % 5 == 0:
item["error"] = f"Error {i}"
critical_count += 1
# Make every 7th item an anomaly (some overlap)
if i % 7 == 0:
item["value"] = 999999
if "error" not in item:
critical_count += 1
items.append(item)
config = SmartCrusherConfig(max_items_after_crush=30)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
# Count retained critical items
errors_retained = sum(1 for x in compressed if x.get("error"))
sum(1 for x in compressed if x.get("value", 0) > 900000)
# All errors should be retained
errors_original = sum(1 for x in items if x.get("error"))
assert errors_retained == errors_original, (
f"Some errors dropped: {errors_original} -> {errors_retained}"
)
class TestCompressionRatio:
"""Verify compression achieves target while preserving quality."""
def test_compression_with_quality(self):
"""Compression should reduce size significantly while keeping critical items."""
# Create realistic large dataset
items = []
for i in range(1000):
items.append(
{
"id": f"doc_{i}",
"score": 0.5,
"title": f"Document {i} about various topics",
"snippet": "Lorem ipsum " * 20,
"metadata": {"source": "web", "date": "2024-01-01"},
}
)
# Add some critical items
items[100]["error"] = "Parse error"
items[500]["value"] = 999999 # Add numeric field for anomaly
original_size = len(json.dumps(items))
config = SmartCrusherConfig(max_items_after_crush=50)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
compressed_size = len(json.dumps(compressed))
# Should achieve significant compression
compression_ratio = 1 - (compressed_size / original_size)
assert compression_ratio > 0.9, f"Compression too low: {compression_ratio:.1%}"
# But critical items must be preserved
assert any(x.get("error") for x in compressed), "Error item lost during compression!"
class TestEdgeCases:
"""Test edge cases and boundary conditions."""
def test_empty_array(self):
"""Empty array should return empty."""
compressed_str, was_modified, _ = smart_crush_tool_output("[]", with_compaction=False)
assert compressed_str == "[]"
assert not was_modified
def test_small_array_unchanged(self):
"""Arrays smaller than min_items_to_analyze should be unchanged."""
items = [{"id": i} for i in range(3)]
original = json.dumps(items)
compressed_str, was_modified, _ = smart_crush_tool_output(original, with_compaction=False)
# Small arrays shouldn't be modified
assert json.loads(compressed_str) == items
def test_all_items_are_errors(self):
"""When all items are errors, all should be retained."""
items = [{"id": i, "error": f"Error {i}"} for i in range(50)]
config = SmartCrusherConfig(max_items_after_crush=20)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
# All 50 errors should be retained (errors override max_items)
assert len(compressed) == 50, (
f"Some errors dropped when all items are errors! Expected 50, got {len(compressed)}"
)
def test_unicode_content(self):
"""Unicode content should not break error detection."""
items = [{"id": i, "content": f"内容 {i}"} for i in range(100)]
items[50]["error"] = "错误: Unicode error message"
config = SmartCrusherConfig(max_items_after_crush=15)
compressed_str, _, _ = smart_crush_tool_output(
json.dumps(items), config, with_compaction=False
)
compressed = json.loads(compressed_str)
errors = [x for x in compressed if x.get("error")]
assert len(errors) == 1, "Unicode error item was dropped!"