Spaces:
Running
Running
updates
Browse files- Dockerfile +3 -4
- webchat.py +0 -9
Dockerfile
CHANGED
@@ -8,8 +8,6 @@ ENV PYTHONUNBUFFERED=1
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# Set the working directory in the container
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WORKDIR /app
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# Copy only the requirements file to leverage Docker cache
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COPY requirements.txt /app/requirements.txt
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@@ -19,8 +17,9 @@ RUN python -m pip install --upgrade pip && \
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python -m spacy download en_core_web_md
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# Create the cache directory and set permissions
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RUN mkdir -p /app/.cache && \
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chmod -R 777 /app
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# Copy the rest of the application code
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COPY app.py /app/app.py
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COPY webchat.py /app/webchat.py
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# Set the working directory in the container
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WORKDIR /app
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# Copy only the requirements file to leverage Docker cache
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COPY requirements.txt /app/requirements.txt
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python -m spacy download en_core_web_md
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# Create the cache directory and set permissions
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RUN mkdir -p /app/.cache && \
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chmod -R 777 /app && \
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chmod -R 777 /app/.cache
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ENV TRANSFORMERS_CACHE=/app/.cache
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# Copy the rest of the application code
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COPY app.py /app/app.py
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COPY webchat.py /app/webchat.py
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webchat.py
CHANGED
@@ -79,15 +79,6 @@ def get_model_test(model_type, max_tokens, min_tokens, decoding, temperature):
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return model
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# Set up cache directory
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current_dir = os.getcwd()
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cache_dir = os.path.join(current_dir, ".cache")
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if not os.path.exists(cache_dir):
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os.makedirs(cache_dir)
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# Set the TRANSFORMERS_CACHE environment variable
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os.environ['TRANSFORMERS_CACHE'] = cache_dir
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# Download the model first
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model = SentenceTransformer('all-MiniLM-L6-v2')
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return model
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# Download the model first
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model = SentenceTransformer('all-MiniLM-L6-v2')
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