From 3b8746ab11ca81f78d0d83d43fae9acb2f9ef383 Mon Sep 17 00:00:00 2001 From: Dhruuuv Date: Tue, 10 Mar 2026 18:12:46 +0530 Subject: [PATCH 1/5] Add contamination detection and config loader Introduce contamination detection pipeline and configuration handling. Adds openverifiablellm/config.py to load benchmark lists (CLI, YAML, defaults) and BenchmarkConfig dataclass. Adds openverifiablellm/contamination.py implementing n-gram generation, benchmark loaders (HF and local JSONL/CSV), Bloom filter construction/serialization (rbloom) and a two-stage contamination check (bloom + exact verification). Update openverifiablellm/utils.py to: adjust compute_sha256/compute_merkle_root call signatures, integrate optional contamination checking into extract_text_from_xml, track redacted chunks, and extend generate_manifest to include contamination metadata and merkle fields. Update pyproject.toml to add runtime deps: datasets, pyyaml, rbloom. Add comprehensive tests (tests/test_contamination.py) for n-grams, bloom filter behavior, contamination detection, manifest fields and backward compatibility; adjust tests/test_util.py to match renamed compute_sha256 parameter. Overall goal: enable detection and recording of dataset contamination when preprocessing large corpora. --- openverifiablellm/config.py | 86 +++++++++++ openverifiablellm/contamination.py | 219 +++++++++++++++++++++++++++++ openverifiablellm/utils.py | 79 +++++++++-- pyproject.toml | 11 +- tests/test_contamination.py | 217 ++++++++++++++++++++++++++++ tests/test_util.py | 5 +- 6 files changed, 602 insertions(+), 15 deletions(-) create mode 100644 openverifiablellm/config.py create mode 100644 openverifiablellm/contamination.py create mode 100644 tests/test_contamination.py diff --git a/openverifiablellm/config.py b/openverifiablellm/config.py new file mode 100644 index 0000000..b2a6b3d --- /dev/null +++ b/openverifiablellm/config.py @@ -0,0 +1,86 @@ +""" +Configuration loader for benchmark contamination detection. + +""" +import logging +from dataclasses import dataclass, field +from pathlib import Path +from typing import List, Optional + +import yaml + +logger = logging.getLogger(__name__) + +DEFAULT_BENCHMARKS: List[str] = ["gsm8k", "cais/mmlu"] + +BENCHMARKS_YAML = "benchmarks.yaml" + + +@dataclass +class BenchmarkConfig: + """Holds all settings needed by the contamination-detection pipeline.""" + + benchmarks: List[str] = field(default_factory=lambda: list(DEFAULT_BENCHMARKS)) + n: int = 13 + bloom_capacity: int = 10_000_000 + bloom_error_rate: float = 0.001 + filter_path: Path = Path("data/filter.bin") + + +def _load_from_yaml(yaml_path: Path) -> Optional[List[str]]: + """ + Attempt to read benchmark identifiers from a YAML file. + + Expected format:: + + benchmarks: + - gsm8k + - cais/mmlu + - /path/to/local/dataset.jsonl + + Returns + """ + if not yaml_path.is_file(): + return None + + try: + with yaml_path.open("r", encoding="utf-8") as fh: + data = yaml.safe_load(fh) + if isinstance(data, dict) and "benchmarks" in data: + benchmarks = data["benchmarks"] + if isinstance(benchmarks, list) and all( + isinstance(b, str) for b in benchmarks + ): + return benchmarks + logger.warning( + "benchmarks.yaml found but does not contain a valid " + "'benchmarks' list; falling back to defaults." + ) + except yaml.YAMLError as exc: + logger.warning("Failed to parse %s: %s", yaml_path, exc) + + return None + + +def load_config(cli_benchmarks: Optional[str] = None) -> BenchmarkConfig: + """Build a :class:`BenchmarkConfig` by resolving benchmark sources.""" + config = BenchmarkConfig() + + # Priority 1: CLI flag + if cli_benchmarks: + config.benchmarks = [ + b.strip() for b in cli_benchmarks.split(",") if b.strip() + ] + logger.info("Benchmarks from CLI: %s", config.benchmarks) + return config + + # Priority 2: YAML config file + yaml_benchmarks = _load_from_yaml(Path(BENCHMARKS_YAML)) + if yaml_benchmarks is not None: + config.benchmarks = yaml_benchmarks + logger.info("Benchmarks from %s: %s", BENCHMARKS_YAML, config.benchmarks) + return config + + # Priority 3: defaults + logger.info("Using default benchmarks: %s", config.benchmarks) + return config \ No newline at end of file diff --git a/openverifiablellm/contamination.py b/openverifiablellm/contamination.py new file mode 100644 index 0000000..0799ed9 --- /dev/null +++ b/openverifiablellm/contamination.py @@ -0,0 +1,219 @@ +""" +Contamination detection via n-gram matching and Bloom filters. + +Provides utilities to: +- Load benchmark datasets (Hugging Face or local files) +- Generate n-grams from text +- Build / load a Bloom filter populated with benchmark n-grams +- Check whether a text chunk is contaminated +""" + +import csv +import hashlib +import json +import logging +import re +from pathlib import Path +from typing import Iterable, List, Optional, Set + +from rbloom import Bloom + +from openverifiablellm.config import BenchmarkConfig + +logger = logging.getLogger(__name__) + +# Text fields we look for when extracting questions from benchmarks +_TEXT_FIELDS = ("question", "prompt", "problem", "input", "text") + + +def _bloom_hash(item) -> int: + """Deterministic hash function for rbloom.""" + raw = item.encode("utf-8") if isinstance(item, str) else item + digest = hashlib.sha256(raw).digest()[:8] + return int.from_bytes(digest, "little") + +# Benchmark loading +def fetch_benchmarks(config: BenchmarkConfig) -> List[str]: + texts: List[str] = [] + + for benchmark in config.benchmarks: + path = Path(benchmark) + if path.suffix in (".jsonl", ".csv") and path.is_file(): + texts.extend(_load_local(path)) + else: + texts.extend(_load_hf(benchmark)) + + logger.info( + "Loaded %d benchmark text(s) from %d source(s).", + len(texts), + len(config.benchmarks), + ) + return texts + + +def _load_hf(dataset_id: str) -> List[str]: + """Load benchmark texts from a Hugging Face dataset.""" + try: + from datasets import load_dataset + except ImportError as exc: + raise ImportError( + "The 'datasets' package is required to fetch HF benchmarks. " + "Install it with: pip install datasets" + ) from exc + + texts: List[str] = [] + try: + ds = load_dataset(dataset_id, trust_remote_code=True) + except Exception as exc: + logger.warning("Could not load HF dataset '%s': %s", dataset_id, exc) + return texts + + splits = ds.values() if hasattr(ds, "values") else [ds] + for split in splits: + for row in split: + for field in _TEXT_FIELDS: + if field in row and row[field]: + texts.append(str(row[field])) + break + + return texts + + +def _load_local(path: Path) -> List[str]: + """Load benchmark texts from a local JSONL or CSV file.""" + texts: List[str] = [] + + if path.suffix == ".jsonl": + with path.open("r", encoding="utf-8") as fh: + for line in fh: + line = line.strip() + if not line: + continue + row = json.loads(line) + for field in _TEXT_FIELDS: + if field in row and row[field]: + texts.append(str(row[field])) + break + elif path.suffix == ".csv": + with path.open("r", encoding="utf-8", newline="") as fh: + reader = csv.DictReader(fh) + for row in reader: + for field in _TEXT_FIELDS: + if field in row and row[field]: + texts.append(str(row[field])) + break + else: + logger.warning("Unsupported local file format: %s", path) + + return texts + + +# N-gram utilities + +def get_ngrams(text: str, n: int = 13) -> List[str]: + """ + Generate whitespace-tokenised n-grams from text. + + The text is normalised (lowercased, punctuation stripped) before + tokenisation. If the text contains fewer than *n* tokens the + result is an empty list. + + """ + normalised = _normalise(text) + tokens = normalised.split() + + if len(tokens) < n: + return [] + + return [" ".join(tokens[i : i + n]) for i in range(len(tokens) - n + 1)] + + +def _normalise(text: str) -> str: + text = text.lower() + text = re.sub(r"[^\w\s]", "", text) + text = re.sub(r"\s+", " ", text) + return text.strip() + +# Bloom filter construction + +def build_bloom_filter( + benchmark_texts: List[str], + config: BenchmarkConfig, +) -> Bloom: + """ + Build (or load) a Bloom filter populated with benchmark n-grams. + + If ``config.filter_path`` already exists on disk the serialised + filter is loaded directly. Otherwise a new filter is created, + populated, and written to ``config.filter_path``. + + """ + filter_path = Path(config.filter_path) + + # --- load from cache if available --- + if filter_path.is_file(): + logger.info("Loading existing Bloom filter from %s", filter_path) + raw = filter_path.read_bytes() + bloom = Bloom.load_bytes(raw, _bloom_hash) + return bloom + + logger.info( + "Building Bloom filter (capacity=%s, error_rate=%s, n=%s) …", + config.bloom_capacity, + config.bloom_error_rate, + config.n, + ) + + bloom = Bloom(config.bloom_capacity, config.bloom_error_rate, hash_func=_bloom_hash) + + ngram_count = 0 + for text in benchmark_texts: + for ngram in get_ngrams(text, n=config.n): + bloom.add(ngram) + ngram_count += 1 + + logger.info("Inserted %d n-grams into the Bloom filter.", ngram_count) + + filter_path.parent.mkdir(parents=True, exist_ok=True) + filter_path.write_bytes(bloom.save_bytes()) + logger.info("Bloom filter saved to %s", filter_path) + + return bloom + + +# Contamination checking + +def check_contamination( + text: str, + bloom_filter: Bloom, + benchmark_texts: List[str], + n: int = 13, +) -> bool: + """ + Determine whether text is contaminated by benchmark data. + + A two-stage process is used: + + 1. Bloom filter check - fast probabilistic membership test on + the n-grams of text. + 2. Exact match verification - if the Bloom filter signals a + hit, a full substring search against benchmark_texts is + performed to eliminate false positives. + + """ + ngrams = get_ngrams(text, n=n) + if not ngrams: + return False + + normalised_benchmarks: Optional[Set[str]] = None + + for ngram in ngrams: + if ngram in bloom_filter: + if normalised_benchmarks is None: + normalised_benchmarks = {_normalise(bt) for bt in benchmark_texts} + + for nb in normalised_benchmarks: + if ngram in nb: + return True + + return False \ No newline at end of file diff --git a/openverifiablellm/utils.py b/openverifiablellm/utils.py index 053cca3..2d1e9a9 100644 --- a/openverifiablellm/utils.py +++ b/openverifiablellm/utils.py @@ -38,10 +38,12 @@ def compute_merkle_root( while chunk := f.read(chunk_size): # reuse compute_sha256 leaf_hex = compute_sha256(data=chunk) + leaf_hex = compute_sha256(data=chunk) leaves.append(bytes.fromhex(leaf_hex)) if not leaves: return compute_sha256(data=b"") + return compute_sha256(data=b"") while len(leaves) > 1: next_level = [] @@ -51,6 +53,7 @@ def compute_merkle_root( combined = left + right parent_hex = compute_sha256(data=combined) + parent_hex = compute_sha256(data=combined) next_level.append(bytes.fromhex(parent_hex)) leaves = next_level @@ -156,13 +159,22 @@ def verify_merkle_proof(chunk_bytes: bytes, proof, merkle_root: str) -> bool: # extract clean wikipage from actual wikipage -def extract_text_from_xml(input_path, *, write_manifest: bool = False): +def extract_text_from_xml( + input_path, + bloom_filter=None, + benchmark_texts=None, + n=13, + benchmarks_used=None, +): """ Process a Wikipedia XML dump (compressed or uncompressed) into cleaned plain text. Each element is parsed, its revision text is extracted, - cleaned using `clean_wikitext()`, and appended to a single + cleaned using ``clean_wikitext()``, and appended to a single output text file. + When *bloom_filter* and *benchmark_texts* are supplied, each + cleaned chunk is checked for contamination with evaluation + benchmarks. Contaminated chunks are silently skipped. The processed output is saved to: data/processed/wiki_clean.txt @@ -170,7 +182,15 @@ def extract_text_from_xml(input_path, *, write_manifest: bool = False): Parameters ---------- input_path : str or Path - Path to the Wikipedia XML dump file. + Path to the compressed Wikipedia XML (.bz2) dump file. + bloom_filter : rbloom.Bloom, optional + Pre-built Bloom filter containing benchmark n-grams. + benchmark_texts : list[str], optional + Original benchmark text strings for exact verification. + n : int, optional + N-gram size used for contamination checking (default 13). + benchmarks_used : list[str], optional + Names of benchmark datasets used (written to manifest). Output ------ @@ -179,12 +199,19 @@ def extract_text_from_xml(input_path, *, write_manifest: bool = False): """ input_path = Path(input_path) + # Lazy import to avoid circular dependency at module level + if bloom_filter is not None and benchmark_texts is not None: + from openverifiablellm.contamination import check_contamination + else: + check_contamination = None + # Fixed output path project_root = Path.cwd() output_dir = project_root / "data" / "processed" output_dir.mkdir(parents=True, exist_ok=True) output_path = output_dir / "wiki_clean.txt" + redacted_chunks = 0 # Auto-detect file type using magic bytes separation with open(input_path, "rb") as test_f: @@ -203,16 +230,39 @@ def extract_text_from_xml(input_path, *, write_manifest: bool = False): if text_elem is not None and text_elem.text: cleaned = clean_wikitext(text_elem.text) if cleaned: + if check_contamination is not None: + if check_contamination( + cleaned, + bloom_filter, + benchmark_texts, + n=n, + ): + redacted_chunks += 1 + elem.clear() + continue + out.write(cleaned + "\n\n") elem.clear() - logger.info("Preprocessing complete. Output saved to %s", output_path) - if write_manifest: - generate_manifest(input_path, output_path) - + if redacted_chunks: + logger.info( + "Contamination detection: redacted %d chunk(s).", redacted_chunks + ) + logger.info("Preprocessing complete. Output saved to %s", output_path) + generate_manifest( + input_path, + output_path, + benchmarks_used=benchmarks_used, + redacted_chunks=redacted_chunks, + ) + # generate data manifest -def generate_manifest(raw_path, processed_path): +def generate_manifest(raw_path, processed_path, benchmarks_used=None, redacted_chunks=0): + """ + Generate a dataset manifest JSON file. + + """ raw_path = Path(raw_path) processed_path = Path(processed_path) @@ -224,9 +274,10 @@ def generate_manifest(raw_path, processed_path): manifest = { "wikipedia_dump": raw_path.name, "dump_date": extract_dump_date(raw_path.name), - "raw_sha256": compute_sha256(file_path=raw_path), - "processed_sha256": compute_sha256(file_path=processed_path), - # ---------------- ADDED FIELDS ---------------- + "raw_sha256": compute_sha256(file_path=str(raw_path)), + "processed_sha256": compute_sha256(file_path=str(processed_path)), + + # ---------------- MERKLE FIELDS ---------------- "raw_merkle_root": compute_merkle_root(raw_path, chunk_size=MERKLE_CHUNK_SIZE_BYTES), "processed_merkle_root": compute_merkle_root( processed_path, chunk_size=MERKLE_CHUNK_SIZE_BYTES @@ -240,6 +291,12 @@ def generate_manifest(raw_path, processed_path): manifest.update( {"environment": env_data["environment"], "environment_hash": env_data["environment_hash"]} ) + + # --- contamination metadata --- + if benchmarks_used is not None: + manifest["contamination_checks_passed"] = benchmarks_used + manifest["redacted_chunks"] = redacted_chunks + project_root = Path.cwd() manifest_path = project_root / "data" / "dataset_manifest.json" manifest_path.parent.mkdir(parents=True, exist_ok=True) diff --git a/pyproject.toml b/pyproject.toml index a0200ca..0386482 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,9 +11,16 @@ authors = [ ] requires-python = ">=3.9" -dependencies = [ +dependencies= [ "defusedxml", - "tokenizers==0.15.2" + "datasets", + "pyyaml", + "rbloom" +] + +[project.optional-dependencies] +dev = [ + "pytest" ] [tool.setuptools.packages.find] diff --git a/tests/test_contamination.py b/tests/test_contamination.py new file mode 100644 index 0000000..9602938 --- /dev/null +++ b/tests/test_contamination.py @@ -0,0 +1,217 @@ +import bz2 +import json +import pytest + +from openverifiablellm.contamination import ( + build_bloom_filter, + check_contamination, + get_ngrams, + _normalise, +) +from openverifiablellm.config import BenchmarkConfig +from openverifiablellm import utils + + +# ------------------------------------------------------------------ # +# get_ngrams tests # +# ------------------------------------------------------------------ # + +class TestGetNgrams: + """Tests for n-gram generation.""" + + def test_basic_generation(self): + # 15 tokens → with n=13 we expect 3 n-grams + text = "one two three four five six seven eight nine ten eleven twelve thirteen fourteen fifteen" + ngrams = get_ngrams(text, n=13) + assert len(ngrams) == 3 + # each n-gram should have 13 space-separated tokens + for ng in ngrams: + assert len(ng.split()) == 13 + + def test_short_text_returns_empty(self): + text = "hello world" + assert get_ngrams(text, n=13) == [] + + def test_exact_n_tokens(self): + text = " ".join(f"word{i}" for i in range(13)) + ngrams = get_ngrams(text, n=13) + assert len(ngrams) == 1 + + def test_case_insensitive(self): + text = " ".join(f"Word{i}" for i in range(15)) + ngrams = get_ngrams(text, n=13) + for ng in ngrams: + assert ng == ng.lower() + + def test_punctuation_stripped(self): + text = "Hello, world! This is a test: of punctuation-removal; really? yes." + ngrams = get_ngrams(text, n=5) + for ng in ngrams: + assert "," not in ng + assert "!" not in ng + assert "?" not in ng + + def test_empty_string(self): + assert get_ngrams("", n=13) == [] + + def test_custom_n(self): + text = "a b c d e f" + assert len(get_ngrams(text, n=3)) == 4 # 6 - 3 + 1 + assert len(get_ngrams(text, n=6)) == 1 + + +# ------------------------------------------------------------------ # +# Bloom filter tests # +# ------------------------------------------------------------------ # + +class TestBloomFilter: + def _make_config(self, tmp_path, **overrides): + defaults = dict( + benchmarks=[], + bloom_capacity=1000, + bloom_error_rate=0.001, + filter_path=tmp_path / "test_filter.bin", + n=5, + ) + defaults.update(overrides) + return BenchmarkConfig(**defaults) + + def test_insert_and_lookup(self, tmp_path): + config = self._make_config(tmp_path) + texts = ["one two three four five six seven eight"] # 8 tokens → 4 5-grams + bloom = build_bloom_filter(texts, config) + + ngrams = get_ngrams(texts[0], n=5) + for ng in ngrams: + assert ng in bloom + + def test_negative_lookup(self, tmp_path): + config = self._make_config(tmp_path) + texts = ["alpha bravo charlie delta echo foxtrot golf hotel"] + bloom = build_bloom_filter(texts, config) + + # Completely unrelated n-gram + assert "zzz yyy xxx www vvv" not in bloom + + def test_serialisation_roundtrip(self, tmp_path): + config = self._make_config(tmp_path) + texts = ["one two three four five six seven"] + bloom1 = build_bloom_filter(texts, config) + + # Loading again should read from disk + bloom2 = build_bloom_filter(texts, config) + for ng in get_ngrams(texts[0], n=5): + assert ng in bloom2 + + +# ------------------------------------------------------------------ # +# check_contamination tests # +# ------------------------------------------------------------------ # + +class TestCheckContamination: + def _build_filter(self, benchmark_texts, tmp_path, n=5): + config = BenchmarkConfig( + benchmarks=[], + bloom_capacity=1000, + bloom_error_rate=0.001, + filter_path=tmp_path / "test_filter.bin", + n=n, + ) + return build_bloom_filter(benchmark_texts, config) + + def test_contaminated_text_detected(self, tmp_path): + benchmark = "what is the capital of france and why is it important" + bloom = self._build_filter([benchmark], tmp_path) + # The chunk contains the benchmark verbatim + chunk = "Let me tell you what is the capital of france and why is it important to know" + assert check_contamination(chunk, bloom, [benchmark], n=5) is True + + def test_clean_text_passes(self, tmp_path): + benchmark = "what is the capital of france and why is it important" + bloom = self._build_filter([benchmark], tmp_path) + chunk = "the quick brown fox jumps over the lazy dog repeatedly" + assert check_contamination(chunk, bloom, [benchmark], n=5) is False + + def test_case_insensitive_detection(self, tmp_path): + benchmark = "What Is The Capital Of France And Why Is It Important" + bloom = self._build_filter([benchmark], tmp_path) + chunk = "WHAT IS THE CAPITAL OF FRANCE AND WHY IS IT IMPORTANT to know" + assert check_contamination(chunk, bloom, [benchmark], n=5) is True + + def test_short_chunk_not_flagged(self, tmp_path): + benchmark = "alpha bravo charlie delta echo foxtrot" + bloom = self._build_filter([benchmark], tmp_path, n=13) + chunk = "alpha bravo" + assert check_contamination(chunk, bloom, [benchmark], n=13) is False + + +# ------------------------------------------------------------------ # +# Manifest contamination metadata # +# ------------------------------------------------------------------ # + +class TestManifestContamination: + def test_manifest_includes_contamination_fields(self, tmp_path, monkeypatch): + monkeypatch.chdir(tmp_path) + + raw_file = tmp_path / "raw.txt" + raw_file.write_text("dummy data") + + processed_file = tmp_path / "processed.txt" + processed_file.write_text("cleaned data") + + utils.generate_manifest( + raw_file, + processed_file, + benchmarks_used=["gsm8k", "cais/mmlu"], + redacted_chunks=7, + ) + + manifest_file = tmp_path / "data" / "dataset_manifest.json" + manifest = json.loads(manifest_file.read_text()) + + assert manifest["contamination_checks_passed"] == ["gsm8k", "cais/mmlu"] + assert manifest["redacted_chunks"] == 7 + + def test_manifest_omits_contamination_when_not_used(self, tmp_path, monkeypatch): + monkeypatch.chdir(tmp_path) + + raw_file = tmp_path / "raw.txt" + raw_file.write_text("dummy data") + + processed_file = tmp_path / "processed.txt" + processed_file.write_text("cleaned data") + + utils.generate_manifest(raw_file, processed_file) + + manifest_file = tmp_path / "data" / "dataset_manifest.json" + manifest = json.loads(manifest_file.read_text()) + + assert "contamination_checks_passed" not in manifest + assert "redacted_chunks" not in manifest + + +# ------------------------------------------------------------------ # +# Backward compatibility # +# ------------------------------------------------------------------ # + +class TestBackwardCompat: + def test_extract_text_from_xml_no_contamination(self, tmp_path, monkeypatch): + xml_content = """ + + + + Hello [[World]] + + + + """ + input_file = tmp_path / "simplewiki-20260201-pages.xml.bz2" + with bz2.open(input_file, "wt", encoding="utf-8") as f: + f.write(xml_content) + + monkeypatch.chdir(tmp_path) + utils.extract_text_from_xml(input_file) + + processed_file = tmp_path / "data" / "processed" / "wiki_clean.txt" + assert processed_file.exists() + assert "Hello World" in processed_file.read_text() \ No newline at end of file diff --git a/tests/test_util.py b/tests/test_util.py index b4890e8..6739457 100644 --- a/tests/test_util.py +++ b/tests/test_util.py @@ -88,6 +88,7 @@ def test_correct_sha256_output(tmp_path): # Hash using your function actual = utils.compute_sha256(file_path=str(file)) + actual = utils.compute_sha256(file_path=str(file)) assert actual == expected @@ -100,13 +101,13 @@ def test_different_content_different_hash(tmp_path): file2.write_text("Content B", encoding="utf-8") assert utils.compute_sha256(file_path=file1) != utils.compute_sha256(file_path=file2) + assert utils.compute_sha256(file_path=file1) != utils.compute_sha256(file_path=file2) def test_file_not_found(): with pytest.raises(FileNotFoundError): utils.compute_sha256(file_path="non_existent_file.txt") - - + # --------------- extract_text_from_xml tests ------------------------------------ From d81e9fdf86a2cee21a8dce4a7ba77e02c2dbdab9 Mon Sep 17 00:00:00 2001 From: Dhruuuv Date: Wed, 11 Mar 2026 02:13:30 +0530 Subject: [PATCH 2/5] added changes suggested by the mentor and coderabbit --- openverifiablellm/config.py | 1 + openverifiablellm/contamination.py | 55 +- openverifiablellm/utils.py | 37 +- pyproject.toml | 12 +- tests/test_contamination.py | 42 +- uv.lock | 1842 +++++++++++++++++++++++++++- 6 files changed, 1949 insertions(+), 40 deletions(-) diff --git a/openverifiablellm/config.py b/openverifiablellm/config.py index b2a6b3d..2dedd23 100644 --- a/openverifiablellm/config.py +++ b/openverifiablellm/config.py @@ -25,6 +25,7 @@ class BenchmarkConfig: bloom_capacity: int = 10_000_000 bloom_error_rate: float = 0.001 filter_path: Path = Path("data/filter.bin") + trust_remote_code: bool = False def _load_from_yaml(yaml_path: Path) -> Optional[List[str]]: diff --git a/openverifiablellm/contamination.py b/openverifiablellm/contamination.py index 0799ed9..8e9f16a 100644 --- a/openverifiablellm/contamination.py +++ b/openverifiablellm/contamination.py @@ -41,7 +41,7 @@ def fetch_benchmarks(config: BenchmarkConfig) -> List[str]: if path.suffix in (".jsonl", ".csv") and path.is_file(): texts.extend(_load_local(path)) else: - texts.extend(_load_hf(benchmark)) + texts.extend(_load_hf(benchmark, config.trust_remote_code)) logger.info( "Loaded %d benchmark text(s) from %d source(s).", @@ -51,7 +51,12 @@ def fetch_benchmarks(config: BenchmarkConfig) -> List[str]: return texts -def _load_hf(dataset_id: str) -> List[str]: +class DatasetLoadError(Exception): + """Raised when a benchmark dataset cannot be loaded from its source.""" + pass + + +def _load_hf(dataset_id: str, trust_remote_code: bool = False) -> List[str]: """Load benchmark texts from a Hugging Face dataset.""" try: from datasets import load_dataset @@ -63,10 +68,10 @@ def _load_hf(dataset_id: str) -> List[str]: texts: List[str] = [] try: - ds = load_dataset(dataset_id, trust_remote_code=True) + ds = load_dataset(dataset_id, trust_remote_code=trust_remote_code) except Exception as exc: - logger.warning("Could not load HF dataset '%s': %s", dataset_id, exc) - return texts + logger.error("Could not load HF dataset '%s': %s", dataset_id, exc) + raise DatasetLoadError(f"Failed to load HF dataset '{dataset_id}'") from exc splits = ds.values() if hasattr(ds, "values") else [ds] for split in splits: @@ -149,13 +154,37 @@ def build_bloom_filter( """ filter_path = Path(config.filter_path) + meta_path = filter_path.with_suffix(filter_path.suffix + ".meta") + + hasher = hashlib.sha256() + for text in benchmark_texts: + hasher.update(text.encode("utf-8")) + inputs_hash = hasher.hexdigest() + + current_meta = { + "benchmarks": sorted(config.benchmarks), + "n": config.n, + "bloom_capacity": config.bloom_capacity, + "bloom_error_rate": config.bloom_error_rate, + "inputs_hash": inputs_hash, + "version": 1, + } # --- load from cache if available --- - if filter_path.is_file(): - logger.info("Loading existing Bloom filter from %s", filter_path) - raw = filter_path.read_bytes() - bloom = Bloom.load_bytes(raw, _bloom_hash) - return bloom + if filter_path.is_file() and meta_path.is_file(): + try: + with meta_path.open("r", encoding="utf-8") as f: + cached_meta = json.load(f) + + if cached_meta == current_meta: + logger.info("Loading existing Bloom filter from %s", filter_path) + raw = filter_path.read_bytes() + bloom = Bloom.load_bytes(raw, _bloom_hash) + return bloom + else: + logger.info("Bloom filter metadata mismatch; ignoring stale cache.") + except Exception as exc: + logger.warning("Failed to read Bloom filter metadata: %s", exc) logger.info( "Building Bloom filter (capacity=%s, error_rate=%s, n=%s) …", @@ -176,7 +205,11 @@ def build_bloom_filter( filter_path.parent.mkdir(parents=True, exist_ok=True) filter_path.write_bytes(bloom.save_bytes()) - logger.info("Bloom filter saved to %s", filter_path) + + with meta_path.open("w", encoding="utf-8") as f: + json.dump(current_meta, f, indent=2) + + logger.info("Bloom filter and metadata saved to %s", filter_path) return bloom diff --git a/openverifiablellm/utils.py b/openverifiablellm/utils.py index 2d1e9a9..14a8130 100644 --- a/openverifiablellm/utils.py +++ b/openverifiablellm/utils.py @@ -165,6 +165,7 @@ def extract_text_from_xml( benchmark_texts=None, n=13, benchmarks_used=None, + write_manifest=True, ): """ Process a Wikipedia XML dump (compressed or uncompressed) into cleaned plain text. @@ -199,6 +200,13 @@ def extract_text_from_xml( """ input_path = Path(input_path) + # Validate contamination arguments + if (bloom_filter is None) != (benchmark_texts is None): + raise ValueError( + "Both 'bloom_filter' and 'benchmark_texts' must " + "be provided to enable contamination checking." + ) + # Lazy import to avoid circular dependency at module level if bloom_filter is not None and benchmark_texts is not None: from openverifiablellm.contamination import check_contamination @@ -250,15 +258,25 @@ def extract_text_from_xml( "Contamination detection: redacted %d chunk(s).", redacted_chunks ) logger.info("Preprocessing complete. Output saved to %s", output_path) - generate_manifest( - input_path, - output_path, - benchmarks_used=benchmarks_used, - redacted_chunks=redacted_chunks, - ) + + if write_manifest: + contamination_metadata = None + if check_contamination is not None: + contamination_metadata = { + "enabled": True, + "n_gram_size": n, + "benchmarks_used": benchmarks_used if benchmarks_used is not None else [], + "redacted_chunks": redacted_chunks, + } + + generate_manifest( + input_path, + output_path, + contamination_metadata=contamination_metadata, + ) # generate data manifest -def generate_manifest(raw_path, processed_path, benchmarks_used=None, redacted_chunks=0): +def generate_manifest(raw_path, processed_path, contamination_metadata=None): """ Generate a dataset manifest JSON file. @@ -293,9 +311,8 @@ def generate_manifest(raw_path, processed_path, benchmarks_used=None, redacted_c ) # --- contamination metadata --- - if benchmarks_used is not None: - manifest["contamination_checks_passed"] = benchmarks_used - manifest["redacted_chunks"] = redacted_chunks + if contamination_metadata is not None: + manifest["contamination"] = contamination_metadata project_root = Path.cwd() manifest_path = project_root / "data" / "dataset_manifest.json" diff --git a/pyproject.toml b/pyproject.toml index 0386482..72f9ce6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,17 +11,21 @@ authors = [ ] requires-python = ">=3.9" -dependencies= [ +dependencies = [ "defusedxml", - "datasets", - "pyyaml", - "rbloom" + "tokenizers==0.15.2", + "sentencepiece" ] [project.optional-dependencies] dev = [ "pytest" ] +contamination = [ + "datasets", + "pyyaml", + "rbloom" +] [tool.setuptools.packages.find] include = ["openverifiablellm*"] diff --git a/tests/test_contamination.py b/tests/test_contamination.py index 9602938..17e7d43 100644 --- a/tests/test_contamination.py +++ b/tests/test_contamination.py @@ -96,7 +96,8 @@ def test_negative_lookup(self, tmp_path): def test_serialisation_roundtrip(self, tmp_path): config = self._make_config(tmp_path) texts = ["one two three four five six seven"] - bloom1 = build_bloom_filter(texts, config) + build_bloom_filter(texts, config) + assert config.filter_path.exists() # Loading again should read from disk bloom2 = build_bloom_filter(texts, config) @@ -159,18 +160,26 @@ def test_manifest_includes_contamination_fields(self, tmp_path, monkeypatch): processed_file = tmp_path / "processed.txt" processed_file.write_text("cleaned data") + metadata = { + "enabled": True, + "n_gram_size": 13, + "benchmarks_used": ["gsm8k", "cais/mmlu"], + "redacted_chunks": 7, + } + utils.generate_manifest( raw_file, processed_file, - benchmarks_used=["gsm8k", "cais/mmlu"], - redacted_chunks=7, + contamination_metadata=metadata, ) manifest_file = tmp_path / "data" / "dataset_manifest.json" manifest = json.loads(manifest_file.read_text()) - assert manifest["contamination_checks_passed"] == ["gsm8k", "cais/mmlu"] - assert manifest["redacted_chunks"] == 7 + assert "contamination" in manifest + assert manifest["contamination"]["benchmarks_used"] == ["gsm8k", "cais/mmlu"] + assert manifest["contamination"]["redacted_chunks"] == 7 + assert manifest["contamination"]["enabled"] is True def test_manifest_omits_contamination_when_not_used(self, tmp_path, monkeypatch): monkeypatch.chdir(tmp_path) @@ -186,8 +195,8 @@ def test_manifest_omits_contamination_when_not_used(self, tmp_path, monkeypatch) manifest_file = tmp_path / "data" / "dataset_manifest.json" manifest = json.loads(manifest_file.read_text()) + assert "contamination" not in manifest assert "contamination_checks_passed" not in manifest - assert "redacted_chunks" not in manifest # ------------------------------------------------------------------ # @@ -195,7 +204,8 @@ def test_manifest_omits_contamination_when_not_used(self, tmp_path, monkeypatch) # ------------------------------------------------------------------ # class TestBackwardCompat: - def test_extract_text_from_xml_no_contamination(self, tmp_path, monkeypatch): + @pytest.fixture + def simple_xml(self, tmp_path): xml_content = """ @@ -205,13 +215,25 @@ def test_extract_text_from_xml_no_contamination(self, tmp_path, monkeypatch): """ - input_file = tmp_path / "simplewiki-20260201-pages.xml.bz2" + input_file = tmp_path / "simplewiki.xml.bz2" with bz2.open(input_file, "wt", encoding="utf-8") as f: f.write(xml_content) + return input_file + def test_extract_text_from_xml_no_contamination(self, simple_xml, tmp_path, monkeypatch): monkeypatch.chdir(tmp_path) - utils.extract_text_from_xml(input_file) + utils.extract_text_from_xml(simple_xml) processed_file = tmp_path / "data" / "processed" / "wiki_clean.txt" assert processed_file.exists() - assert "Hello World" in processed_file.read_text() \ No newline at end of file + assert "Hello World" in processed_file.read_text() + + def test_extract_fails_if_only_bloom_filter_provided(self, simple_xml): + from rbloom import Bloom + 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+0530 Subject: [PATCH 3/5] added coderabbit changes --- openverifiablellm/config.py | 26 ++++++++++++++------------ openverifiablellm/contamination.py | 6 ++++-- 2 files changed, 18 insertions(+), 14 deletions(-) diff --git a/openverifiablellm/config.py b/openverifiablellm/config.py index 2dedd23..e4de871 100644 --- a/openverifiablellm/config.py +++ b/openverifiablellm/config.py @@ -48,14 +48,14 @@ def _load_from_yaml(yaml_path: Path) -> Optional[List[str]]: with yaml_path.open("r", encoding="utf-8") as fh: data = yaml.safe_load(fh) if isinstance(data, dict) and "benchmarks" in data: - benchmarks = data["benchmarks"] - if isinstance(benchmarks, list) and all( - isinstance(b, str) for b in benchmarks - ): - return benchmarks + raw_benchmarks = data["benchmarks"] + if isinstance(raw_benchmarks, list): + benchmarks = [b.strip() for b in raw_benchmarks if isinstance(b, str) and b.strip()] + if benchmarks: + return benchmarks logger.warning( "benchmarks.yaml found but does not contain a valid " - "'benchmarks' list; falling back to defaults." + "non-empty 'benchmarks' list; falling back to defaults." ) except yaml.YAMLError as exc: logger.warning("Failed to parse %s: %s", yaml_path, exc) @@ -69,15 +69,17 @@ def load_config(cli_benchmarks: Optional[str] = None) -> BenchmarkConfig: # Priority 1: CLI flag if cli_benchmarks: - config.benchmarks = [ - b.strip() for b in cli_benchmarks.split(",") if b.strip() - ] - logger.info("Benchmarks from CLI: %s", config.benchmarks) - return config + benchmarks = [b.strip() for b in cli_benchmarks.split(",") if b.strip()] + if benchmarks: + config.benchmarks = benchmarks + logger.info("Benchmarks from CLI: %s", config.benchmarks) + return config + else: + logger.warning("CLI provided empty benchmarks; falling back to next priority.") # Priority 2: YAML config file yaml_benchmarks = _load_from_yaml(Path(BENCHMARKS_YAML)) - if yaml_benchmarks is not None: + if yaml_benchmarks: config.benchmarks = yaml_benchmarks logger.info("Benchmarks from %s: %s", BENCHMARKS_YAML, config.benchmarks) return config diff --git a/openverifiablellm/contamination.py b/openverifiablellm/contamination.py index 8e9f16a..824eb83 100644 --- a/openverifiablellm/contamination.py +++ b/openverifiablellm/contamination.py @@ -38,7 +38,9 @@ def fetch_benchmarks(config: BenchmarkConfig) -> List[str]: for benchmark in config.benchmarks: path = Path(benchmark) - if path.suffix in (".jsonl", ".csv") and path.is_file(): + if path.suffix in (".jsonl", ".csv"): + if not path.is_file(): + raise FileNotFoundError(f"Local benchmark file not found: {benchmark}") texts.extend(_load_local(path)) else: texts.extend(_load_hf(benchmark, config.trust_remote_code)) @@ -246,7 +248,7 @@ def check_contamination( normalised_benchmarks = {_normalise(bt) for bt in benchmark_texts} for nb in normalised_benchmarks: - if ngram in nb: + if f" {ngram} " in f" {nb} ": return True return False \ No newline at end of file From ebe7eb5baa7e84f546301094f5345413a2eee1dc Mon Sep 17 00:00:00 2001 From: Dhruuuv Date: Fri, 13 Mar 2026 00:23:57 +0530 Subject: [PATCH 4/5] added coderabbit changes and lint error --- openverifiablellm/config.py | 11 ++++++----- openverifiablellm/contamination.py | 8 ++++++++ tests/test_contamination.py | 10 ++++++++-- 3 files changed, 22 insertions(+), 7 deletions(-) diff --git a/openverifiablellm/config.py b/openverifiablellm/config.py index e4de871..6416075 100644 --- a/openverifiablellm/config.py +++ b/openverifiablellm/config.py @@ -39,7 +39,10 @@ def _load_from_yaml(yaml_path: Path) -> Optional[List[str]]: - cais/mmlu - /path/to/local/dataset.jsonl - Returns + Returns: + Optional[List[str]]: A list of benchmark identifiers (e.g., "gsm8k", "cais/mmlu", or local file paths) + when the YAML is present and valid, or None when the file is missing, unreadable, or does not contain + a "benchmarks" list. """ if not yaml_path.is_file(): return None @@ -57,12 +60,10 @@ def _load_from_yaml(yaml_path: Path) -> Optional[List[str]]: "benchmarks.yaml found but does not contain a valid " "non-empty 'benchmarks' list; falling back to defaults." ) - except yaml.YAMLError as exc: - logger.warning("Failed to parse %s: %s", yaml_path, exc) - + except (OSError, yaml.YAMLError) as exc: + logger.warning("Failed to read/parse %s: %s", yaml_path, exc) return None - def load_config(cli_benchmarks: Optional[str] = None) -> BenchmarkConfig: """Build a :class:`BenchmarkConfig` by resolving benchmark sources.""" config = BenchmarkConfig() diff --git a/openverifiablellm/contamination.py b/openverifiablellm/contamination.py index 824eb83..5f48281 100644 --- a/openverifiablellm/contamination.py +++ b/openverifiablellm/contamination.py @@ -126,6 +126,9 @@ def get_ngrams(text: str, n: int = 13) -> List[str]: result is an empty list. """ + if n <= 0: + raise ValueError("n must be a positive integer") + normalised = _normalise(text) tokens = normalised.split() @@ -203,6 +206,11 @@ def build_bloom_filter( bloom.add(ngram) ngram_count += 1 + if ngram_count == 0: + raise ValueError( + "No benchmark n-grams were generated; check the selected sources and n." + ) + logger.info("Inserted %d n-grams into the Bloom filter.", ngram_count) filter_path.parent.mkdir(parents=True, exist_ok=True) diff --git a/tests/test_contamination.py b/tests/test_contamination.py index 17e7d43..0bdec5e 100644 --- a/tests/test_contamination.py +++ b/tests/test_contamination.py @@ -6,7 +6,6 @@ build_bloom_filter, check_contamination, get_ngrams, - _normalise, ) from openverifiablellm.config import BenchmarkConfig from openverifiablellm import utils @@ -59,6 +58,13 @@ def test_custom_n(self): assert len(get_ngrams(text, n=3)) == 4 # 6 - 3 + 1 assert len(get_ngrams(text, n=6)) == 1 + def test_invalid_n_raises(self): + text = "some valid text" + with pytest.raises(ValueError, match="n must be a positive integer"): + get_ngrams(text, n=0) + with pytest.raises(ValueError, match="n must be a positive integer"): + get_ngrams(text, n=-1) + # ------------------------------------------------------------------ # # Bloom filter tests # @@ -140,7 +146,7 @@ def test_case_insensitive_detection(self, tmp_path): assert check_contamination(chunk, bloom, [benchmark], n=5) is True def test_short_chunk_not_flagged(self, tmp_path): - benchmark = "alpha bravo charlie delta echo foxtrot" + benchmark = "alpha bravo charlie delta echo foxtrot golf hotel india juliet oskar tango zulu" bloom = self._build_filter([benchmark], tmp_path, n=13) chunk = "alpha bravo" assert check_contamination(chunk, bloom, [benchmark], n=13) is False From 2c2fbe6ebf1ff75c62ac26c1b5aac623065ced22 Mon Sep 17 00:00:00 2001 From: Dhruuuv Date: Fri, 13 Mar 2026 15:03:47 +0530 Subject: [PATCH 5/5] added coderabbit changes --- openverifiablellm/config.py | 19 +--- openverifiablellm/contamination.py | 41 ++++++-- openverifiablellm/utils.py | 156 +++++++++++++++++++++++------ pyproject.toml | 7 ++ tests/test_contamination.py | 6 +- tests/test_util.py | 35 +++++++ tests/test_verify.py | 2 +- 7 files changed, 204 insertions(+), 62 deletions(-) diff --git a/openverifiablellm/config.py b/openverifiablellm/config.py index 6416075..5c3fdf6 100644 --- a/openverifiablellm/config.py +++ b/openverifiablellm/config.py @@ -29,21 +29,7 @@ class BenchmarkConfig: def _load_from_yaml(yaml_path: Path) -> Optional[List[str]]: - """ - Attempt to read benchmark identifiers from a YAML file. - - Expected format:: - - benchmarks: - - gsm8k - - cais/mmlu - - /path/to/local/dataset.jsonl - - Returns: - Optional[List[str]]: A list of benchmark identifiers (e.g., "gsm8k", "cais/mmlu", or local file paths) - when the YAML is present and valid, or None when the file is missing, unreadable, or does not contain - a "benchmarks" list. - """ + """ Attempt to read benchmark identifiers from a YAML file. """ if not yaml_path.is_file(): return None @@ -68,7 +54,6 @@ def load_config(cli_benchmarks: Optional[str] = None) -> BenchmarkConfig: """Build a :class:`BenchmarkConfig` by resolving benchmark sources.""" config = BenchmarkConfig() - # Priority 1: CLI flag if cli_benchmarks: benchmarks = [b.strip() for b in cli_benchmarks.split(",") if b.strip()] if benchmarks: @@ -78,13 +63,11 @@ def load_config(cli_benchmarks: Optional[str] = None) -> BenchmarkConfig: else: logger.warning("CLI provided empty benchmarks; falling back to next priority.") - # Priority 2: YAML config file yaml_benchmarks = _load_from_yaml(Path(BENCHMARKS_YAML)) if yaml_benchmarks: config.benchmarks = yaml_benchmarks logger.info("Benchmarks from %s: %s", BENCHMARKS_YAML, config.benchmarks) return config - # Priority 3: defaults logger.info("Using default benchmarks: %s", config.benchmarks) return config \ No newline at end of file diff --git a/openverifiablellm/contamination.py b/openverifiablellm/contamination.py index 5f48281..a795e27 100644 --- a/openverifiablellm/contamination.py +++ b/openverifiablellm/contamination.py @@ -14,7 +14,7 @@ import logging import re from pathlib import Path -from typing import Iterable, List, Optional, Set +from typing import Dict, List, Optional, Set from rbloom import Bloom @@ -58,7 +58,11 @@ class DatasetLoadError(Exception): pass -def _load_hf(dataset_id: str, trust_remote_code: bool = False) -> List[str]: +def _load_hf( + dataset_id: str, + trust_remote_code: bool = False, + split_map: Optional[Dict[str, List[str]]] = None +) -> List[str]: """Load benchmark texts from a Hugging Face dataset.""" try: from datasets import load_dataset @@ -68,14 +72,25 @@ def _load_hf(dataset_id: str, trust_remote_code: bool = False) -> List[str]: "Install it with: pip install datasets" ) from exc + if split_map is None: + split_map = {"gsm8k": ["test"],"cais/mmlu": ["test", "validation"]} + texts: List[str] = [] + splits_to_load = split_map.get(dataset_id) + try: - ds = load_dataset(dataset_id, trust_remote_code=trust_remote_code) + if splits_to_load: + splits = [ + load_dataset(dataset_id, split=s, trust_remote_code=trust_remote_code) + for s in splits_to_load + ] + else: + ds = load_dataset(dataset_id, trust_remote_code=trust_remote_code) + splits = ds.values() if hasattr(ds, "values") else [ds] except Exception as exc: logger.error("Could not load HF dataset '%s': %s", dataset_id, exc) raise DatasetLoadError(f"Failed to load HF dataset '{dataset_id}'") from exc - splits = ds.values() if hasattr(ds, "values") else [ds] for split in splits: for row in split: for field in _TEXT_FIELDS: @@ -163,7 +178,9 @@ def build_bloom_filter( hasher = hashlib.sha256() for text in benchmark_texts: - hasher.update(text.encode("utf-8")) + encoded = text.encode("utf-8") + hasher.update(len(encoded).to_bytes(8, "little")) + hasher.update(encoded) inputs_hash = hasher.hexdigest() current_meta = { @@ -229,8 +246,9 @@ def build_bloom_filter( def check_contamination( text: str, bloom_filter: Bloom, - benchmark_texts: List[str], + benchmark_texts: Optional[List[str]] = None, n: int = 13, + precomputed_normalised_benchmarks: Optional[Set[str]] = None, ) -> bool: """ Determine whether text is contaminated by benchmark data. @@ -244,18 +262,19 @@ def check_contamination( performed to eliminate false positives. """ + if benchmark_texts is None and precomputed_normalised_benchmarks is None: + raise ValueError("Must provide either benchmark_texts or precomputed_normalised_benchmarks") + ngrams = get_ngrams(text, n=n) if not ngrams: return False - normalised_benchmarks: Optional[Set[str]] = None - for ngram in ngrams: if ngram in bloom_filter: - if normalised_benchmarks is None: - normalised_benchmarks = {_normalise(bt) for bt in benchmark_texts} + if precomputed_normalised_benchmarks is None: + precomputed_normalised_benchmarks = {_normalise(bt) for bt in (benchmark_texts or [])} - for nb in normalised_benchmarks: + for nb in precomputed_normalised_benchmarks: if f" {ngram} " in f" {nb} ": return True diff --git a/openverifiablellm/utils.py b/openverifiablellm/utils.py index 14a8130..b8bf7a2 100644 --- a/openverifiablellm/utils.py +++ b/openverifiablellm/utils.py @@ -1,10 +1,14 @@ +import argparse import bz2 import hashlib import json import logging +import os import platform import re import sys +import time +import tracemalloc from pathlib import Path from typing import Any, Dict, List, Optional, Tuple, Union @@ -24,6 +28,33 @@ RE_WHITESPACE = re.compile(r"\s+") +# helpers: New helper to compute SHA256 and return raw bytes directly +def compute_sha256_bytes( + *, + data: Optional[Union[bytes, bytearray]] = None, + file_path: Optional[Union[str, Path]] = None, +) -> bytes: + """ + Compute SHA256 hash of a file OR raw bytes, returning raw bytes. + This avoids the overhead of converting to a hex string and back. + """ + if (data is None) == (file_path is None): + raise ValueError("Exactly one of 'data' or 'file_path' must be provided.") + + sha256 = hashlib.sha256() + + if data is not None: + sha256.update(data) + return sha256.digest() + + path = Path(file_path) + with path.open("rb") as f: + while chunk := f.read(8192): + sha256.update(chunk) + + return sha256.digest() + + # Merkle Tree Chunk-Level Hashing for Large Files def compute_merkle_root( file_path: Union[str, Path], chunk_size: int = MERKLE_CHUNK_SIZE_BYTES @@ -80,8 +111,8 @@ def generate_merkle_proof( # Build leaf level with path.open("rb") as f: while chunk := f.read(chunk_size): - leaf_hex = compute_sha256(data=chunk) - leaves.append(bytes.fromhex(leaf_hex)) + leaf_bytes = compute_sha256_bytes(data=chunk) + leaves.append(leaf_bytes) if not leaves: raise ValueError("Cannot generate proof for empty file") @@ -107,8 +138,8 @@ def generate_merkle_proof( next_level = [] for i in range(0, len(leaves), 2): combined = leaves[i] + leaves[i + 1] - parent_hex = compute_sha256(data=combined) - next_level.append(bytes.fromhex(parent_hex)) + parent_bytes = compute_sha256_bytes(data=combined) + next_level.append(parent_bytes) index //= 2 leaves = next_level @@ -121,7 +152,7 @@ def verify_merkle_proof(chunk_bytes: bytes, proof, merkle_root: str) -> bool: Verify a Merkle proof for given chunk bytes. """ try: - current_hash = bytes.fromhex(compute_sha256(data=chunk_bytes)) + current_hash = compute_sha256_bytes(data=chunk_bytes) expected_root = bytes.fromhex(merkle_root) except (TypeError, ValueError): return False @@ -152,8 +183,7 @@ def verify_merkle_proof(chunk_bytes: bytes, proof, merkle_root: str) -> bool: else: combined = current_hash + sibling - parent_hex = compute_sha256(data=combined) - current_hash = bytes.fromhex(parent_hex) + current_hash = compute_sha256_bytes(data=combined) return current_hash == expected_root @@ -171,9 +201,9 @@ def extract_text_from_xml( Process a Wikipedia XML dump (compressed or uncompressed) into cleaned plain text. Each element is parsed, its revision text is extracted, - cleaned using ``clean_wikitext()``, and appended to a single + cleaned using clean_wikitext(), and appended to a single output text file. - When *bloom_filter* and *benchmark_texts* are supplied, each + When bloom_filter and benchmark_texts are supplied, each cleaned chunk is checked for contamination with evaluation benchmarks. Contaminated chunks are silently skipped. @@ -183,20 +213,9 @@ def extract_text_from_xml( Parameters ---------- input_path : str or Path - Path to the compressed Wikipedia XML (.bz2) dump file. - bloom_filter : rbloom.Bloom, optional - Pre-built Bloom filter containing benchmark n-grams. - benchmark_texts : list[str], optional - Original benchmark text strings for exact verification. - n : int, optional - N-gram size used for contamination checking (default 13). - benchmarks_used : list[str], optional - Names of benchmark datasets used (written to manifest). Output ------ - Creates: - data/processed/wiki_clean.txt """ input_path = Path(input_path) @@ -209,9 +228,11 @@ def extract_text_from_xml( # Lazy import to avoid circular dependency at module level if bloom_filter is not None and benchmark_texts is not None: - from openverifiablellm.contamination import check_contamination + from openverifiablellm.contamination import _normalise, check_contamination + precomputed_normalised_benchmarks = {_normalise(bt) for bt in benchmark_texts} else: check_contamination = None + precomputed_normalised_benchmarks = None # Fixed output path project_root = Path.cwd() @@ -242,8 +263,9 @@ def extract_text_from_xml( if check_contamination( cleaned, bloom_filter, - benchmark_texts, + benchmark_texts=None, n=n, + precomputed_normalised_benchmarks=precomputed_normalised_benchmarks, ): redacted_chunks += 1 elem.clear() @@ -452,13 +474,89 @@ def clean_wikitext(text: str) -> str: return text.strip() -if __name__ == "__main__": - if len(sys.argv) < 2: - print("Usage: python -m openverifiablellm.utils [--no-manifest]") +def run_benchmark(file_path: str, chunk_size: int = 1024 * 1024): + logger.info("--- Starting Benchmark ---") + + if not os.path.exists(file_path): + logger.error(f"Error: File not found at {file_path}") sys.exit(1) - logging.basicConfig(level=logging.INFO, format="%(levelname)s - %(message)s") - extract_text_from_xml( - sys.argv[1], - write_manifest="--no-manifest" not in sys.argv[2:], + size_mb = os.path.getsize(file_path) / (1024 * 1024) + + logger.info(f"Benchmarking file: {file_path}") + logger.info(f"File size: {size_mb:.2f} MB") + + try: + tracemalloc.start() + + # Benchmark compute_merkle_root + start_time = time.perf_counter() + root_hex = compute_merkle_root(file_path, chunk_size=chunk_size) + end_time = time.perf_counter() + + _current_mem, peak_mem = tracemalloc.get_traced_memory() + + root_time = end_time - start_time + mins, secs = divmod(root_time, 60) + logger.info(f"compute_merkle_root ({size_mb:.2f} MB file): {int(mins)}m {secs:.3f}s") + logger.info(f"Peak Memory Usage: {peak_mem / 10**6:.3f} MB") + logger.info(f"Merkle Root: {root_hex}") + + tracemalloc.reset_peak() + + # Benchmark generate_merkle_proof + start_time = time.perf_counter() + + file_size_bytes = os.path.getsize(file_path) + if file_size_bytes == 0: + logger.info("Skipping proof benchmark for empty file") + else: + chunk_count = (file_size_bytes + chunk_size - 1) // chunk_size + chunk_index = min(10, chunk_count - 1) + + _ = generate_merkle_proof(file_path, chunk_index=chunk_index, chunk_size=chunk_size) + end_time = time.perf_counter() + + _, peak_mem_proof = tracemalloc.get_traced_memory() + + proof_time = end_time - start_time + pmins, psecs = divmod(proof_time, 60) + logger.info( + f"generate_merkle_proof ({size_mb:.2f} MB file, chunk {chunk_index}): {int(pmins)}m {psecs:.3f}s" + ) + logger.info(f"Peak Memory Usage for proof: {peak_mem_proof / 10**6:.3f} MB") + + logger.info("--- Benchmark Complete ---") + tracemalloc.stop() + + except Exception: + logger.exception("An error occurred during benchmarking") + sys.exit(1) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="OpenVerifiableLLM Preprocessing") + parser.add_argument("input_dump", help="Path to the Wikipedia XML dump file") + parser.add_argument( + "--BENCHMARK_MODE", + type=str, + choices=["TRUE", "FALSE"], + default="FALSE", + help="Run in benchmark mode", ) + parser.add_argument( + "--chunk_size", + type=int, + default=MERKLE_CHUNK_SIZE_BYTES, + help="Chunk size in bytes for Merkle hashing", + ) + parser.add_argument("--no-manifest", action="store_true", help="Skip manifest generation") + + args = parser.parse_args() + + logging.basicConfig(level=logging.INFO, format="%(levelname)s - %(message)s") + + if args.BENCHMARK_MODE == "TRUE": + run_benchmark(args.input_dump, args.chunk_size) + else: + extract_text_from_xml(args.input_dump, write_manifest=not args.no_manifest) diff --git a/pyproject.toml b/pyproject.toml index 72f9ce6..88eb307 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,6 +36,13 @@ dev = [ "ruff>=0.15.4", ] +[tool.pytest.ini_options] +filterwarnings = [ + "ignore::DeprecationWarning:sentencepiece", + "ignore:builtin type Swig:DeprecationWarning", + "ignore:builtin type swigvarlink:DeprecationWarning", +] + [tool.ruff] line-length = 100 target-version = "py39" diff --git a/tests/test_contamination.py b/tests/test_contamination.py index 0bdec5e..06876e8 100644 --- a/tests/test_contamination.py +++ b/tests/test_contamination.py @@ -1,15 +1,15 @@ import bz2 import json + import pytest +from openverifiablellm import utils +from openverifiablellm.config import BenchmarkConfig from openverifiablellm.contamination import ( build_bloom_filter, check_contamination, get_ngrams, ) -from openverifiablellm.config import BenchmarkConfig -from openverifiablellm import utils - # ------------------------------------------------------------------ # # get_ngrams tests # diff --git a/tests/test_util.py b/tests/test_util.py index 6739457..02f10e9 100644 --- a/tests/test_util.py +++ b/tests/test_util.py @@ -79,6 +79,20 @@ def test_generate_manifest_runs_if_file_exists(tmp_path, monkeypatch): # --------------- compute_sha256 ------------------------------------ +def test_compute_sha256_bytes(tmp_path): + file = tmp_path / "sample.txt" + content = b"hello wikipedia" + file.write_bytes(content) + + expected = hashlib.sha256(content).digest() + + actual_data = utils.compute_sha256_bytes(data=content) + actual_file = utils.compute_sha256_bytes(file_path=file) + + assert actual_data == expected + assert actual_file == expected + + def test_correct_sha256_output(tmp_path): file = tmp_path / "sample.txt" content = "hello wikipedia" @@ -237,6 +251,27 @@ def test_merkle_root_empty_file(tmp_path): assert root == expected +def test_compute_merkle_root_multi_chunk_hardcoded(tmp_path): + file = tmp_path / "data.txt" + # 3 chunks of 8 bytes each + chunk1 = b"chunk__1" + chunk2 = b"chunk__2" + chunk3 = b"chunk__3" + file.write_bytes(chunk1 + chunk2 + chunk3) + + h1 = hashlib.sha256(chunk1).digest() + h2 = hashlib.sha256(chunk2).digest() + h3 = hashlib.sha256(chunk3).digest() + + h12 = hashlib.sha256(h1 + h2).digest() + h33 = hashlib.sha256(h3 + h3).digest() + + expected_root = hashlib.sha256(h12 + h33).hexdigest() + + actual_root = utils.compute_merkle_root(file, chunk_size=8) + assert actual_root == expected_root + + # --------------- Merkle proof generation ------------------------------------ diff --git a/tests/test_verify.py b/tests/test_verify.py index 77817e0..931a66e 100644 --- a/tests/test_verify.py +++ b/tests/test_verify.py @@ -57,7 +57,7 @@ def run_preprocessing(tmp_dir: Path, dump: Path) -> None: original = os.getcwd() os.chdir(tmp_dir) try: - utils.extract_text_from_xml(dump) + utils.extract_text_from_xml(dump, write_manifest=True) finally: os.chdir(original)