From 6fcac7bfec7f0d144d64dd5d4eb9562219ae8537 Mon Sep 17 00:00:00 2001
From: Enkidu93 <lowryec17@gcc.edu>
Date: Wed, 21 Oct 2026 11:23:59 -0400
Subject: [PATCH 1/2] Add example retrieval code

Remove example pool; add lock and tests; fix condition

Update scikit version

Explicitly cast

Fix circular import

Address Claude comments

Fix formatting
---
 machine/translation/llm/__init__.py           | 17 ++++
 .../llm/coverage_example_retriever.py         | 95 +++++++++++++++++++
 machine/translation/llm/example.py            |  7 ++
 .../llm/example_retriever_factory.py          | 19 ++++
 .../llm/example_retriever_method.py           |  6 ++
 .../translation/llm/lazy_example_retriever.py | 43 +++++++++
 .../llm/tfidf_example_retriever.py            | 44 +++++++++
 .../llm/top_k_example_retriever.py            | 27 ++++++
 pyproject.toml                                |  1 +
 tests/testutils/mock_example_retriever.py     | 11 +++
 .../llm/test_coverage_example_retriever.py    | 76 +++++++++++++++
 .../llm/test_lazy_example_retriever.py        | 68 +++++++++++++
 .../llm/test_tfidf_example_retriever.py       | 56 +++++++++++
 13 files changed, 470 insertions(+)
 create mode 100644 machine/translation/llm/__init__.py
 create mode 100644 machine/translation/llm/coverage_example_retriever.py
 create mode 100644 machine/translation/llm/example.py
 create mode 100644 machine/translation/llm/example_retriever_factory.py
 create mode 100644 machine/translation/llm/example_retriever_method.py
 create mode 100644 machine/translation/llm/lazy_example_retriever.py
 create mode 100644 machine/translation/llm/tfidf_example_retriever.py
 create mode 100644 machine/translation/llm/top_k_example_retriever.py
 create mode 100644 tests/testutils/mock_example_retriever.py
 create mode 100644 tests/translation/llm/test_coverage_example_retriever.py
 create mode 100644 tests/translation/llm/test_lazy_example_retriever.py
 create mode 100644 tests/translation/llm/test_tfidf_example_retriever.py

diff --git a/machine/translation/llm/__init__.py b/machine/translation/llm/__init__.py
new file mode 100644
index 00000000..355048d9
--- /dev/null
+++ b/machine/translation/llm/__init__.py
@@ -0,0 +1,17 @@
+from .coverage_example_retriever import CoverageExampleRetriever
+from .example import Example
+from .example_retriever_factory import ExampleRetrieverFactory
+from .example_retriever_method import ExampleRetrievalMethod
+from .lazy_example_retriever import LazyExampleRetriever
+from .tfidf_example_retriever import TfidfExampleRetriever
+from .top_k_example_retriever import TopKExampleRetriever
+
+__all__ = [
+    "CoverageExampleRetriever",
+    "Example",
+    "ExampleRetrieverFactory",
+    "ExampleRetrievalMethod",
+    "LazyExampleRetriever",
+    "TfidfExampleRetriever",
+    "TopKExampleRetriever",
+]
diff --git a/machine/translation/llm/coverage_example_retriever.py b/machine/translation/llm/coverage_example_retriever.py
new file mode 100644
index 00000000..90866c7d
--- /dev/null
+++ b/machine/translation/llm/coverage_example_retriever.py
@@ -0,0 +1,95 @@
+from typing import Iterable, List, Optional, cast
+
+import numpy as np
+from scipy.sparse import csr_matrix
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.metrics.pairwise import linear_kernel
+
+from .example import Example
+from .lazy_example_retriever import LazyExampleRetriever
+
+
+class CoverageExampleRetriever(LazyExampleRetriever):
+    # Benchmarked as a set; the measured gain says nothing about other values.
+    _ANCHORS = 20
+    _CANDIDATE_MULTIPLE = 4
+    _MIN_CANDIDATES = 100
+    _RELEVANCE_WEIGHT = 0.7
+
+    def __init__(self, examples: Iterable[Example]) -> None:
+        super().__init__(examples)
+        self._vectorizer: Optional[TfidfVectorizer] = None
+        self._matrix: Optional[csr_matrix] = None
+
+    def _fit(self) -> None:
+        # TfidfVectorizer rejects a corpus with nothing to put in its vocabulary.
+        sources = [ex.source for ex in self.examples]
+        if not any(source.strip() for source in sources):
+            self._vectorizer = None
+            self._matrix = None
+            return
+        self._vectorizer = TfidfVectorizer(analyzer="char_wb", ngram_range=(2, 5))
+        self._matrix = cast(csr_matrix, self._vectorizer.fit_transform(sources))
+
+    def _rank(self, query: str, k: int, exclude_index: Optional[int] = None) -> List[Example]:
+        if self._vectorizer is None or self._matrix is None:
+            return []
+        vector = cast(csr_matrix, self._vectorizer.transform([query]))
+        similarities = linear_kernel(vector, self._matrix).ravel()
+        ranked = similarities.argsort()[::-1]
+        if exclude_index is not None:
+            ranked = ranked[ranked != exclude_index]
+        k = min(k, len(ranked))
+        if k == 0:
+            return []
+        if vector.nnz == 0:
+            return [self.examples[i] for i in ranked[:k].tolist()]
+        candidates = self._distinct_candidates(
+            ranked, k, None if exclude_index is None else self.examples[exclude_index]
+        )
+        if len(candidates) == 0:
+            return []
+        chosen = self._choose_for_coverage(vector, self._matrix[candidates], similarities[candidates], k)
+        # Ties are broken by position so that the same corpus always yields the same prompt.
+        return [
+            self.examples[example_index]
+            for example_index in sorted(
+                (int(candidates[i]) for i in chosen), key=lambda i: (similarities[i], i), reverse=True
+            )
+        ]
+
+    def _distinct_candidates(self, ranked: np.ndarray, k: int, excluded: Optional[Example]) -> np.ndarray:
+        limit = max(self._CANDIDATE_MULTIPLE * k, self._MIN_CANDIDATES)
+        candidates: List[int] = []
+        # A copy of the excluded example would show the answer to the row it is excluded for.
+        seen = set() if excluded is None else {excluded}
+        for index in ranked:
+            example = self.examples[index]
+            if example not in seen:
+                candidates.append(int(index))
+                seen.add(example)
+            if len(candidates) >= limit:
+                break
+        return np.asarray(candidates)
+
+    def _choose_for_coverage(self, vector, candidate_matrix, similarities: np.ndarray, k: int) -> List[int]:
+        features = candidate_matrix[:, vector.indices].toarray() > 0
+        weights = vector.data / vector.data.sum()
+        relevance = similarities / max(float(similarities.max()), 1e-12)
+        # The closest few are kept outright, so that strong whole-sentence analogues survive the balancing.
+        anchor_count = min(self._ANCHORS, max(1, k // 2), len(features))
+        chosen = list(range(anchor_count))
+        available = np.ones(len(features), dtype=bool)
+        available[chosen] = False
+        counts = features[chosen].sum(axis=0).astype(float)
+        while len(chosen) < min(k, len(features)):
+            # Each n-gram counts for less the more of the chosen examples already demonstrate it.
+            gain = features @ (weights / (1.0 + counts))
+            gain /= max(float(gain[available].max()), 1e-12)
+            utility = self._RELEVANCE_WEIGHT * relevance + (1 - self._RELEVANCE_WEIGHT) * gain
+            utility[~available] = -np.inf
+            best = int(np.argmax(utility))
+            chosen.append(best)
+            available[best] = False
+            counts += features[best]
+        return chosen
diff --git a/machine/translation/llm/example.py b/machine/translation/llm/example.py
new file mode 100644
index 00000000..f22b55c0
--- /dev/null
+++ b/machine/translation/llm/example.py
@@ -0,0 +1,7 @@
+from dataclasses import dataclass
+
+
+@dataclass(frozen=True)
+class Example:
+    source: str
+    target: str
diff --git a/machine/translation/llm/example_retriever_factory.py b/machine/translation/llm/example_retriever_factory.py
new file mode 100644
index 00000000..2a2ed92b
--- /dev/null
+++ b/machine/translation/llm/example_retriever_factory.py
@@ -0,0 +1,19 @@
+from typing import Iterable
+
+from .coverage_example_retriever import CoverageExampleRetriever
+from .example import Example
+from .example_retriever_method import ExampleRetrievalMethod
+from .lazy_example_retriever import LazyExampleRetriever
+from .tfidf_example_retriever import TfidfExampleRetriever
+
+
+class ExampleRetrieverFactory:
+    @staticmethod
+    def create_example_retriever(method: ExampleRetrievalMethod, examples: Iterable[Example]) -> LazyExampleRetriever:
+        match method:
+            case ExampleRetrievalMethod.TFIDF:
+                return TfidfExampleRetriever(examples)
+            case ExampleRetrievalMethod.COVERAGE:
+                return CoverageExampleRetriever(examples)
+            case _:
+                raise ValueError(f"Unable to create example retriever with method {method}")
diff --git a/machine/translation/llm/example_retriever_method.py b/machine/translation/llm/example_retriever_method.py
new file mode 100644
index 00000000..b93b3791
--- /dev/null
+++ b/machine/translation/llm/example_retriever_method.py
@@ -0,0 +1,6 @@
+from enum import Enum, auto
+
+
+class ExampleRetrievalMethod(Enum):
+    TFIDF = auto()
+    COVERAGE = auto()
diff --git a/machine/translation/llm/lazy_example_retriever.py b/machine/translation/llm/lazy_example_retriever.py
new file mode 100644
index 00000000..339dd577
--- /dev/null
+++ b/machine/translation/llm/lazy_example_retriever.py
@@ -0,0 +1,43 @@
+import threading
+from abc import ABC, abstractmethod
+from typing import Iterable, List, Optional, Union
+
+from .example import Example
+
+
+class LazyExampleRetriever(ABC):
+
+    def __init__(self, examples: Iterable[Example]) -> None:
+        self._examples = examples
+        self._fitted = False
+        self._lock = threading.RLock()
+
+    @property
+    def examples(self) -> List[Example]:
+        with self._lock:
+            if not isinstance(self._examples, List):
+                self._examples = list(self._examples)
+            return self._examples
+
+    @abstractmethod
+    def _fit(self) -> None: ...
+
+    def rank(self, query: str, k: int, exclude: Optional[Union[int, Example]] = None) -> List[Example]:
+        if k <= 0:
+            return []
+        num_examples = len(self.examples)
+        exclude_index = (
+            exclude
+            if isinstance(exclude, int) or exclude is None
+            else (self.examples.index(exclude) if exclude in self.examples else None)
+        )
+        if k >= num_examples:
+            return [example for index, example in enumerate(self.examples) if index != exclude_index]
+        with self._lock:
+            if not self._fitted:
+                self._fit()
+                self._fitted = True
+        return self._rank(query, k, exclude_index)
+
+    @abstractmethod
+    def _rank(self, query: str, k: int, exclude_index: Optional[int] = None) -> List[Example]: ...
diff --git a/machine/translation/llm/tfidf_example_retriever.py b/machine/translation/llm/tfidf_example_retriever.py
new file mode 100644
index 00000000..dfb1b76e
--- /dev/null
+++ b/machine/translation/llm/tfidf_example_retriever.py
@@ -0,0 +1,44 @@
+from typing import Iterable, List, Optional, cast
+
+import numpy as np
+from scipy.sparse import csr_matrix
+from sklearn.feature_extraction.text import TfidfVectorizer
+
+from ...tokenization.latin_word_tokenizer import LatinWordTokenizer
+from .example import Example
+from .top_k_example_retriever import TopKExampleRetriever
+
+
+class TfidfExampleRetriever(TopKExampleRetriever):
+
+    def __init__(self, examples: Iterable[Example]) -> None:
+        super().__init__(examples)
+        self._latin_tokenizer = LatinWordTokenizer()
+        self._vectorizer: Optional[TfidfVectorizer] = None
+        self._matrix: Optional[csr_matrix] = None
+
+    def _fit(self) -> None:
+        # TfidfVectorizer rejects a corpus with nothing to put in its vocabulary.
+        sources = [ex.source for ex in self.examples]
+        if not any(self._tokenize(source) for source in sources):
+            self._vectorizer = None
+            self._matrix = None
+            return
+        self._vectorizer = TfidfVectorizer(
+            lowercase=False, tokenizer=self._tokenize, token_pattern=None  # pyright: ignore[reportArgumentType]
+        )
+        self._matrix = cast(csr_matrix, self._vectorizer.fit_transform(sources))
+
+    def _score_examples(self, query: str) -> np.ndarray:
+        if self._matrix is None or self._vectorizer is None:
+            return np.array([])
+        index_of_query = next((i for i, ex in enumerate(self.examples) if ex.source == query), -1)
+        if index_of_query != -1:
+            vector: csr_matrix = self._matrix[index_of_query]
+        else:
+            vector = cast(csr_matrix, self._vectorizer.transform([query]))
+        return (self._matrix @ vector.T).toarray().ravel()
+
+    def _tokenize(self, text: str) -> List[str]:
+        # Strip all punctuation-only tokens
+        return [token for token in self._latin_tokenizer.tokenize(text.lower()) if any(c.isalnum() for c in token)]
diff --git a/machine/translation/llm/top_k_example_retriever.py b/machine/translation/llm/top_k_example_retriever.py
new file mode 100644
index 00000000..c7f76906
--- /dev/null
+++ b/machine/translation/llm/top_k_example_retriever.py
@@ -0,0 +1,27 @@
+from abc import ABC, abstractmethod
+from typing import List, Optional
+
+import numpy as np
+
+from machine.translation.llm.example import Example
+
+from .lazy_example_retriever import LazyExampleRetriever
+
+
+class TopKExampleRetriever(LazyExampleRetriever, ABC):
+    @abstractmethod
+    def _score_examples(self, query: str) -> np.ndarray: ...
+
+    def _rank(self, query: str, k: int, exclude_index: Optional[int] = None) -> List[Example]:
+        scores = self._score_examples(query)
+        n = scores.shape[0]
+        available = n - 1 if exclude_index is not None else n
+        k = min(k, available)
+        if k <= 0:
+            return []
+        if exclude_index is not None:
+            scores = scores.copy()
+            scores[exclude_index] = -np.inf
+        top = np.argpartition(-scores, k - 1)[:k] if k < n else np.arange(n)
+        top_indices: List[int] = top[np.argsort(-scores[top])].tolist()
+        return [self.examples[i] for i in top_indices]
diff --git a/pyproject.toml b/pyproject.toml
index 8105c060..203885e7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -54,6 +54,7 @@ jobs = [
     "dynaconf>=3.2.5,<4.0",
     "pydantic>=2.13.4,<3.0",
 ]
+llm = ["scikit-learn>=1.6,<2.0"]
 
 [build-system]
 requires = ["uv_build>=0.12.17,<0.13"]
diff --git a/tests/testutils/mock_example_retriever.py b/tests/testutils/mock_example_retriever.py
new file mode 100644
index 00000000..10b11897
--- /dev/null
+++ b/tests/testutils/mock_example_retriever.py
@@ -0,0 +1,11 @@
+import numpy as np
+
+from machine.translation.llm.top_k_example_retriever import TopKExampleRetriever
+
+
+class MockExampleRetriever(TopKExampleRetriever):
+    def _fit(self) -> None:
+        pass
+
+    def _score_examples(self, query: str) -> np.ndarray:
+        return np.array([0 if query == e.source else (1 if query > e.source else -1) for e in self.examples])
diff --git a/tests/translation/llm/test_coverage_example_retriever.py b/tests/translation/llm/test_coverage_example_retriever.py
new file mode 100644
index 00000000..b9583da6
--- /dev/null
+++ b/tests/translation/llm/test_coverage_example_retriever.py
@@ -0,0 +1,76 @@
+from machine.translation.llm import Example
+from machine.translation.llm.coverage_example_retriever import CoverageExampleRetriever
+
+
+def test_coverage_retriever_prefers_an_uncovered_clause_to_a_near_duplicate():
+    sources = [
+        "the shepherd counted his sheep in the green field",
+        "the shepherd counted his sheep in the green field again",
+        "the shepherd counted all his sheep in the green field",
+        "fishermen mended nets",
+        "a woman drew water from the well",
+    ]
+    query = "the shepherd counted his sheep in the green field while fishermen mended nets"
+
+    retriever = CoverageExampleRetriever([Example(source, "") for source in sources])
+
+    assert [example.source for example in retriever.rank(query, 2)] == [sources[0], sources[3]]
+
+
+def test_coverage_retriever_keeps_the_closest_example():
+    sources = ["the shepherd counted his sheep in the green field", "fishermen mended nets"]
+    query = "the shepherd counted his sheep in the green field while fishermen mended nets"
+
+    retriever = CoverageExampleRetriever([Example(source, "") for source in sources])
+
+    assert [example.source for example in retriever.rank(query, 1)] == [sources[0]]
+
+
+def test_coverage_retriever_selects_an_exact_duplicate_pair_only_once():
+    examples = [Example("apple pie", "tarte"), Example("apple pie", "tarte"), Example("banana split", "banane")]
+    retriever = CoverageExampleRetriever(examples)
+
+    selected = retriever.rank("apple pie", 2)
+
+    assert examples[2] in selected
+    assert len([example for example in selected if example == examples[0]]) == 1
+
+
+def test_coverage_retriever_keeps_repeated_sources_with_different_targets():
+    examples = [Example("apple pie", "tarte"), Example("apple pie", "tourte"), Example("banana split", "banane")]
+
+    assert set(CoverageExampleRetriever(examples).rank("apple pie", 2)) == set(examples[:2])
+
+
+def test_coverage_retriever_excludes_copies_of_the_excluded_example():
+    examples = [Example("apple pie", "tarte"), Example("apple pie", "tarte"), Example("banana split", "banane")]
+
+    assert CoverageExampleRetriever(examples).rank("apple pie", 2, exclude=0) == [examples[2]]
+
+
+def test_coverage_retriever_finds_nothing_when_all_remaining_examples_are_copies():
+    examples = [Example("apple pie", "tarte"), Example("apple pie", "tarte")]
+
+    assert CoverageExampleRetriever(examples).rank("apple pie", 1, exclude=0) == []
+
+
+def test_coverage_retriever_matches_a_script_without_spaces():
+    sources = ["他们在家里吃饭", "我们去学校", "明天下雨"]
+
+    retriever = CoverageExampleRetriever([Example(source, "") for source in sources])
+
+    assert retriever.rank("我们明天去学校吗", 1)[0].source == sources[1]
+
+
+def test_coverage_retriever_fills_k_when_the_query_has_no_known_ngrams():
+    retriever = CoverageExampleRetriever(
+        [Example("apple pie", ""), Example("banana split", ""), Example("cherry tart", "")]
+    )
+
+    assert len(set(retriever.rank("zzzz", 2))) == 2
+
+
+def test_coverage_retriever_handles_a_corpus_with_no_text():
+    retriever = CoverageExampleRetriever([Example("", ""), Example("  ", "")])
+
+    assert retriever.rank("anything", 1) == []
diff --git a/tests/translation/llm/test_lazy_example_retriever.py b/tests/translation/llm/test_lazy_example_retriever.py
new file mode 100644
index 00000000..249bbdc5
--- /dev/null
+++ b/tests/translation/llm/test_lazy_example_retriever.py
@@ -0,0 +1,68 @@
+import threading
+from concurrent.futures import ThreadPoolExecutor
+
+from testutils.mock_example_retriever import MockExampleRetriever
+
+from machine.translation.llm.example import Example
+
+
+class _BlockingFitExampleRetriever(MockExampleRetriever):
+    def __init__(self, examples):
+        super().__init__(examples)
+        self.fit_calls = 0
+        self.fit_started = threading.Event()
+        self.release_fit = threading.Event()
+        self.second_fit_started = threading.Event()
+        self._fit_counter_lock = threading.Lock()
+
+    def _fit(self) -> None:
+        with self._fit_counter_lock:
+            self.fit_calls += 1
+            if self.fit_calls == 2:
+                self.second_fit_started.set()
+        self.fit_started.set()
+        self.release_fit.wait(timeout=5)
+
+
+def test_lazy_example_retriever_fits_once_when_threads_rank_together():
+    retriever = _BlockingFitExampleRetriever([Example("a", "1"), Example("b", "2"), Example("c", "3")])
+    with ThreadPoolExecutor(max_workers=2) as executor:
+        first = executor.submit(retriever.rank, "a", 1)
+        assert retriever.fit_started.wait(timeout=1)
+        second = executor.submit(retriever.rank, "b", 1)
+        try:
+            assert not retriever.second_fit_started.wait(timeout=0.2)
+        finally:
+            retriever.release_fit.set()
+        assert first.result(timeout=1)
+        assert second.result(timeout=1)
+
+    assert retriever.fit_calls == 1
+
+
+def test_lazy_example_retriever_k_greater_than_n():
+    examples = [Example("a", "1"), Example("b", "2")]
+    retriever = MockExampleRetriever(examples)
+    retrieved_examples = retriever.rank("query", 3)
+    assert retrieved_examples == examples
+
+
+def test_lazy_example_retriever_no_such_exclude():
+    examples = [Example("a", "1"), Example("b", "2")]
+    retriever = MockExampleRetriever(examples)
+    retrieved_examples = retriever.rank("query", 2, Example("c", "3"))
+    assert retrieved_examples == examples
+
+
+def test_lazy_example_retriever_exclude_index():
+    examples = [Example("a", "1"), Example("b", "2")]
+    retriever = MockExampleRetriever(examples)
+    retrieved_examples = retriever.rank("query", 2, 0)
+    assert retrieved_examples == examples[1:]
+
+
+def test_lazy_example_retriever_exclude_example():
+    examples = [Example("a", "1"), Example("b", "2")]
+    retriever = MockExampleRetriever(examples)
+    retrieved_examples = retriever.rank("query", 2, Example("a", "1"))
+    assert retrieved_examples == examples[1:]
diff --git a/tests/translation/llm/test_tfidf_example_retriever.py b/tests/translation/llm/test_tfidf_example_retriever.py
new file mode 100644
index 00000000..8b8b3f32
--- /dev/null
+++ b/tests/translation/llm/test_tfidf_example_retriever.py
@@ -0,0 +1,56 @@
+from machine.translation.llm import Example
+from machine.translation.llm.tfidf_example_retriever import TfidfExampleRetriever
+
+
+def test_tfidf_retriever_ranks_most_similar_source_first():
+    examples = [
+        Example("the cat sat on the mat", "0"),
+        Example("completely unrelated sentence", "1"),
+        Example("a cat sat here", "2"),
+    ]
+
+    assert TfidfExampleRetriever(examples).rank("the cat sat", 2) == [examples[0], examples[2]]
+
+
+def test_tfidf_retriever_respects_k():
+    examples = [Example("apple pie", str(index)) for index in range(3)]
+
+    assert len(TfidfExampleRetriever(examples).rank("apple pie", 2)) == 2
+
+
+def test_tfidf_retriever_excludes_its_own_position():
+    examples = [Example("the cat sat", "0"), Example("the cat sat", "1"), Example("totally different words", "2")]
+
+    assert TfidfExampleRetriever(examples).rank("the cat sat", 2, exclude=0) == [examples[1], examples[2]]
+
+
+def test_tfidf_retriever_k_larger_than_the_corpus_returns_every_example():
+    examples = [Example("apple pie", "0"), Example("banana split", "1")]
+
+    assert TfidfExampleRetriever(examples).rank("apple pie", 10) == examples
+
+
+def test_tfidf_retriever_empty_corpus_returns_no_examples():
+    assert TfidfExampleRetriever([]).rank("anything", 5) == []
+
+
+def test_tfidf_retriever_handles_a_corpus_with_no_word_tokens():
+    examples = [Example("!!!", "0"), Example("...", "1")]
+
+    assert TfidfExampleRetriever(examples).rank("anything", 1) == []
+
+
+def test_tfidf_retriever_indexes_a_corpus_where_only_some_sources_have_words():
+    examples = [Example("!!!", "0"), Example("let there be light", "1")]
+
+    assert TfidfExampleRetriever(examples).rank("light", 1) == [examples[1]]
+
+
+def test_punctuation_carries_no_tfidf_retrieval_signal():
+    examples = [
+        Example("the cat sat", "0"),
+        Example("!!! !!! !!! ???", "1"),
+        Example("something else entirely", "2"),
+    ]
+
+    assert TfidfExampleRetriever(examples).rank("!!! !!! !!! cat", 1) == [examples[0]]

From 9125975ae5c897a42c8973712207d74ffb4dec9f Mon Sep 17 00:00:00 2001
From: Enkidu93 <lowryec17@gcc.edu>
Date: Tue, 27 Oct 2026 21:19:18 -0400
Subject: [PATCH 2/2] Update uv lock

---
 uv.lock | 395 ++++++++++++++++++++++++++++++++++++++++++++++++++------
 1 file changed, 353 insertions(+), 42 deletions(-)

diff --git a/uv.lock b/uv.lock
index c017e097..22f39bfe 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 5
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@@ -816,7 +816,7 @@ name = "exceptiongroup"
 version = "1.3.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
+    { name = "typing-extensions" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219", size = 30371, upload-time = "2025-11-21T23:01:54.787Z" }
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-    { name = "traitlets", marker = "python_full_version < '3.11'" },
-    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "decorator" },
+    { name = "exceptiongroup" },
+    { name = "jedi" },
+    { name = "matplotlib-inline" },
+    { name = "pexpect", marker = "sys_platform != 'emscripten' and sys_platform != 'win32'" },
+    { name = "prompt-toolkit" },
+    { name = "pygments" },
+    { name = "stack-data" },
+    { name = "traitlets" },
+    { name = "typing-extensions" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/40/18/f8598d287006885e7136451fdea0755af4ebcbfe342836f24deefaed1164/ipython-8.39.0.tar.gz", hash = "sha256:4110ae96012c379b8b6db898a07e186c40a2a1ef5d57a7fa83166047d9da7624", size = 5513971, upload-time = "2026-03-27T10:02:13.94Z" }
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-    { name = "traitlets", marker = "python_full_version >= '3.11'" },
-    { name = "typing-extensions", marker = "python_full_version == '3.11.*'" },
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "ipython-pygments-lexers" },
+    { name = "jedi" },
+    { name = "matplotlib-inline" },
+    { name = "pexpect", marker = "sys_platform != 'emscripten' and sys_platform != 'win32'" },
+    { name = "prompt-toolkit" },
+    { name = "psutil", marker = "sys_platform != 'cygwin' and sys_platform != 'emscripten'" },
+    { name = "pygments" },
+    { name = "stack-data" },
+    { name = "traitlets" },
+    { name = "typing-extensions", marker = "python_full_version < '3.12'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/b9/32/99451b1283ec5d92ad77073f12e1c667dc10775384d8f15c2914207149dd/ipython-9.17.1.tar.gz", hash = "sha256:8919be8c27f20a6f4423145028063f6637b42a03ce57665bb12015ee1f073529", size = 4539289, upload-time = "2026-09-01T08:29:32.6Z" }
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 version = "1.1.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "pygments", marker = "python_full_version >= '3.11'" },
+    { name = "pygments" },
 ]
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 ]
 
+[[package]]
+name = "narwhals"
+version = "2.28.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/67/43/e11d75a7fb635c6f63dd6e176cb3e050ec2fee35f2f2267b332a6ad351ec/narwhals-2.28.0.tar.gz", hash = "sha256:2d9860c80d6610820826e94c6e42ce4b1d92d89cdd479586e652a8d211dab345", size = 754977, upload-time = "2026-10-27T12:19:33.777Z" }
+wheels = [
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+
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 name = "nbclient"
 version = "0.11.0"
@@ -3745,6 +3754,293 @@ wheels = [
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 ]
 
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+version = "1.7.2"
+source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
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+]
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+    { name = "joblib" },
+    { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" } },
+    { name = "scipy", version = "1.15.3", source = { registry = "https://pypi.org/simple" } },
+    { name = "threadpoolctl" },
+]
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+    { url = "https://files.pythonhosted.org/packages/ee/16/e79e0d1c63ef698879d85439d37e9fb434e3b804e506a6991038d086ebd9/scipy-1.18.1-cp314-cp314t-win_arm64.whl", hash = "sha256:9f2897bf7737392ad0d5213ea7b6add72a4edf5679b3153106aeb88b6507b3b9", size = 25331848, upload-time = "2026-08-21T23:27:05.884Z" },
+]
+
 [[package]]
 name = "send2trash"
 version = "2.1.0"
@@ -3833,6 +4129,7 @@ wheels = [
 name = "sil-machine"
 version = "1.9.2"
 source = { editable = "." }
+default-groups = "all"
 dependencies = [
     { name = "boto3" },
     { name = "botocore" },
@@ -3860,6 +4157,10 @@ jobs = [
     { name = "json-stream" },
     { name = "pydantic" },
 ]
+llm = [
+    { name = "scikit-learn", version = "1.7.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
+    { name = "scikit-learn", version = "1.9.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
+]
 sentencepiece = [
     { name = "sentencepiece" },
 ]
@@ -3901,13 +4202,14 @@ requires-dist = [
     { name = "pydantic", marker = "extra == 'jobs'", specifier = ">=2.13.4,<3.0" },
     { name = "regex", specifier = ">=2021.7.6" },
     { name = "sacremoses", marker = "extra == 'huggingface'", specifier = ">=0.0.53,<1" },
+    { name = "scikit-learn", marker = "extra == 'llm'", specifier = ">=1.6,<2.0" },
     { name = "sentencepiece", marker = "extra == 'sentencepiece'", specifier = "~=0.2" },
     { name = "sil-thot", marker = "extra == 'thot'", specifier = "~=3.5.2" },
     { name = "sortedcontainers", specifier = "~=2.4" },
     { name = "transformers", marker = "extra == 'huggingface'", specifier = "==5.14.1" },
     { name = "urllib3", specifier = "<2.0" },
 ]
-provides-extras = ["sentencepiece", "thot", "huggingface", "jobs"]
+provides-extras = ["sentencepiece", "thot", "huggingface", "jobs", "llm"]
 
 [package.metadata.requires-dev]
 dev = [
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 ]
 
+[[package]]
+name = "threadpoolctl"
+version = "3.7.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/00/dc/6c58154c1c65f758ea979e7139cb76993a9cfc662d14e9be3c4a667cfb77/threadpoolctl-3.7.0.tar.gz", hash = "sha256:61348cfb77d53b9242e0017029244b559b810c142ced65b4e21eeca1843959a7", size = 31961, upload-time = "2026-09-15T15:46:20.263Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/43/3f/f88a53f60a472b46f4023f56d204dd7de33d34c5d2acbfa0d70a674e639e/threadpoolctl-3.7.0-py3-none-any.whl", hash = "sha256:cd8b60b5641b45c67bbf73c64c843235fc2d8a480c87389f52f5dbee893b86be", size = 26362, upload-time = "2026-09-15T15:46:19.168Z" },
+]
+
 [[package]]
 name = "tinycss2"
 version = "1.5.1"
@@ -4140,24 +4451,24 @@ dependencies = [
     { name = "networkx", version = "3.4.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
     { name = "networkx", version = "3.6.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.11.*'" },
     { name = "networkx", version = "3.7", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
-    { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cufile-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cusparselt-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nvjitlink-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nvshmem-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
+    { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cufile-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-cusparselt-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-nvjitlink-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-nvshmem-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
+    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
     { name = "setuptools", marker = "python_full_version >= '3.12'" },
     { name = "sympy" },
-    { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
+    { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform != 'win32'" },
     { name = "typing-extensions" },
 ]
 wheels = [