fix(HuggingFaceLocalGenerator): remove stop_words cross-product in reply post-processing

[alvinttang]

Refs #11409.

HuggingFaceLocalGenerator.run post-processes replies with a nested list comprehension:

replies = [reply.replace(stop_word, '').rstrip()
           for reply in replies
           for stop_word in self.stop_words]

That's a cross-product. With N replies and M stop words it emits N*M replies, and only every M-th one has every stop word removed. Half the output silently still contains a stop word.

The chat sibling at chat/hugging_face_local.py:660 already does this correctly with a sequential loop, so this PR aligns the non-chat path with the same pattern.

RED

Two new regression tests on main:

FAILED test_run_stop_words_removal_with_multiple_stop_words
  assert {'replies': [...4 entries...]} == {'replies': ['Paris is the capital.', 'France is in Europe.']}

FAILED test_run_stop_words_removal_all_stop_words_removed_from_each_reply
  assert {'replies': ['Hello STOP world']} == {'replies': ['Hello  world']}

The original test_run_stop_words_removal (single stop word) keeps passing.

GREEN

test_run_stop_words_removal                                              PASSED
test_run_stop_words_removal_with_multiple_stop_words                     PASSED
test_run_stop_words_removal_all_stop_words_removed_from_each_reply       PASSED

Full file: 28 passed, 1 deselected (integration, model download), 6 warnings in 140.60s. No regression elsewhere.

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[anakin87]

Thank you for this PR.

Please sign the CLA, then ping me and I'll proceed with the actual review.