feat(landing): nouvelle animation d'accueil — une recette déclinée dans les quatre formats
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Le nouveau dessin montre une tarte aux pommes, comprise de tous, présentée successivement en document Word, tableau Excel, présentation PowerPoint et PDF : une onde de traduction traverse chaque document, la langue change, la mise en page reste rigoureusement identique. Contenu universel, plus aucun jargon de spécialiste. Également : deux nettoyages DeepL restés non envoyés (commentaires dans database/models.py et translators/word_translator.py). Vérifié : construction réussie, 14/14 tests, aucune erreur d'analyse, mode sombre et « réduire les animations » pris en charge.
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@@ -165,7 +165,7 @@ class Translation(Base):
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# Translation details
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# Translation details
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source_language = Column(String(10), default="auto")
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source_language = Column(String(10), default="auto")
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target_language = Column(String(10), nullable=False)
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target_language = Column(String(10), nullable=False)
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provider = Column(String(50), nullable=False) # google, deepl, ollama, etc.
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provider = Column(String(50), nullable=False) # google, ollama, etc.
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# Processing info
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# Processing info
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status = Column(
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status = Column(
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@@ -1378,7 +1378,7 @@ class WordTranslator:
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is translated whole — not fragment by fragment — and the result is
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is translated whole — not fragment by fragment — and the result is
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written into the first run while the sibling runs are blanked.
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written into the first run while the sibling runs are blanked.
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This is what keeps mid-sentence bold spans ("This is *very*
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This is what keeps mid-sentence bold spans ("This is *very*
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important") coherent in the target language, like DeepL's inline
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important") coherent in the target language, keeping inline
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tag handling.
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tag handling.
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Note: python-docx's `paragraph.runs` only returns DIRECT child <w:r>
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Note: python-docx's `paragraph.runs` only returns DIRECT child <w:r>
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