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Ported Example, ExampleRetriever, TopKExampleRetriever, TfidfExampleRetriever, CoverageExampleRetriever, ExampleRetrieverFactory and ExampleRetrievalMethod to SIL.Machine.Translation.Llm, plus an internal TfidfIndex
There is no scikit-learn or numpy equivalent here, so TF-IDF is a small internal sparse implementation that follows TfidfVectorizer defaults. It adds no new dependency.
Ties in ranking are broken by corpus order, because numpy leaves tie order unspecified.
Subclasses call Fit() at the end of their own constructor, because derived fields are not initialized yet when the base constructor runs.
Not ported:pyproject.toml, uv.lock, the llm extra, __init__.py and the sklearn availability check. These are Python packaging only.
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claude commentedon Nov 12, 2026
Claude finished @Enkidu93's task in 3m 54s —— View job •
claude/issue-641-20261112-1529• [Create PR ➔](https://github.com/sillsdev/machine/compare/master...claude/issue-641-20261112-1529?quick_pull=1&title=Issue%20%23641%3A%20Changes%20from%20Claude&body=This%20PR%20addresses%20issue%20%23641%0A%0AGenerated%20with%20%5BClaude%20Code%5D(https%3A%2F%2Fclaude.ai%2Fcode)Ported machine.py PR #412 (LLM example retrieval)
Example,ExampleRetriever,TopKExampleRetriever,TfidfExampleRetriever,CoverageExampleRetriever,ExampleRetrieverFactoryandExampleRetrievalMethodtoSIL.Machine.Translation.Llm, plus an internalTfidfIndex./local_check.sh --agent-strict:local_check: PASSEDPR: #642 (closes #641)
Differences from the Python version
TfidfVectorizerdefaults. It adds no new dependency.Fit()at the end of their own constructor, because derived fields are not initialized yet when the base constructor runs.Not ported:
pyproject.toml,uv.lock, thellmextra,__init__.pyand the sklearn availability check. These are Python packaging only.· Branch