dockerfile-fix
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14fc115e0f
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@ -5,8 +5,10 @@ WORKDIR /app
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COPY requirements.txt .
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COPY requirements.txt .
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# Install system dependencies required for building Python packages
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RUN apt-get update && apt-get install -y --no-install-recommends gcc libffi-dev libssl-dev
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RUN apt-get update && apt-get install -y --no-install-recommends gcc libffi-dev libssl-dev
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RUN pip install asyncio aiohttp redis[hiredis]
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# Install Python dependencies including redis with hiredis support
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RUN pip install --no-cache-dir -r requirements.txt
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RUN pip install --no-cache-dir -r requirements.txt
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# Stage 2: Final stage
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# Stage 2: Final stage
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@ -15,7 +17,10 @@ FROM python:slim
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WORKDIR /app
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WORKDIR /app
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# Copy only necessary files from the builder stage
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# Copy only necessary files from the builder stage
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COPY --from=builder /usr/local/lib/python/dist-packages /usr/local/lib/python/dist-packages
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COPY --from=builder /usr/local/lib/python3/dist-packages /usr/local/lib/python3/dist-packages
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COPY --from=builder /usr/local/lib/python3.*/dist-packages /usr/local/lib/python3.*/dist-packages
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COPY --from=builder /usr/local/lib/python3.*/dist-packages /usr/local/lib/python3.*/dist-packages
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COPY . .
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COPY . .
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EXPOSE 8080
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EXPOSE 8080
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@ -8,11 +8,14 @@ model = T5ForConditionalGeneration.from_pretrained("google/byt5-small")
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def is_russian_wording(text):
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def is_russian_wording(text):
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"""
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"""
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Check if the text contains any Russian characters by checking
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Check if the text contains more than one Russian characters by checking
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each character against the Unicode range for Cyrillic.
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each character against the Unicode range for Cyrillic.
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"""
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"""
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counter = 0
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for char in text:
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for char in text:
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if "\u0400" <= char <= "\u04ff": # Unicode range for Cyrillic characters
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if "\u0400" <= char <= "\u04ff": # Unicode range for Cyrillic characters
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counter += 1
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if counter > 1:
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return True
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return True
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return False
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return False
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@ -39,17 +42,15 @@ def normalize(text):
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Normalize English text to resemble Russian characters.
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Normalize English text to resemble Russian characters.
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"""
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"""
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# Segment the text first
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# Segment the text first
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segmented_text = segment_text(
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t = segment_text(
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text.replace(" ", " ").replace(" ", " ").replace(" ", " ")
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text.replace(" ", " ").replace(" ", " ").replace(" ", " ")
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)
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)
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# Normalize after segmentation
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if is_russian_wording(t):
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segmented_text = segmented_text.lower()
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if is_russian_wording(segmented_text):
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# Normalize the text by replacing characters
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# Normalize the text by replacing characters
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normalized_text = (
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normalized_text = (
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segmented_text.replace("e", "е")
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t.lower()
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.replace("e", "е")
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.replace("o", "о")
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.replace("o", "о")
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.replace("x", "х")
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.replace("x", "х")
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.replace("a", "а")
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.replace("a", "а")
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@ -74,7 +75,7 @@ def normalize(text):
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return normalized_text
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return normalized_text
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return segmented_text
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return t
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# Example usage
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# Example usage
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