trying new config

Dockerfile

@@ -1,28 +1,5 @@
 FROM python:3.10.9
-
-# Install git-lfs for downloading large files from Hugging Face
-RUN apt-get update && apt-get install -y git-lfs
-
-# Create a directory for your model inside the container's /app directory
-# This directory is typically writable during the build process
-RUN mkdir -p /app/models/sentence-transformers_all-MiniLM-L6-v2
-
-# Clone the specific SentenceTransformer model into the created directory
-# This downloads the model files as part of the image build
-RUN git clone https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2 /app/models/sentence-transformers_all-MiniLM-L6-v2
-
-# Set the SENTENCE_TRANSFORMERS_HOME environment variable
-# This tells the SentenceTransformer library where to look for pre-downloaded models
-ENV SENTENCE_TRANSFORMERS_HOME=/app/models
-
-# Copy your application code into the /app directory in the container
-COPY . /app
-
-# Set the working directory to /app
-WORKDIR /app
-
-# Install your Python dependencies
-RUN pip install --no-cache-dir --upgrade -r requirements.txt
-
-# Command to run your FastAPI application
+COPY . .
+WORKDIR /
+RUN pip install --no-cache-dir --upgrade -r /requirements.txt
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -40,7 +40,9 @@ user_interactions = defaultdict(set)
 post_features = {}
 post_metadata = {}
 
-sentence_model = SentenceTransformer('all-MiniLM-L6-v2')
+if not os.path.exists('/tmp/cache'):
+    os.makedirs('/tmp/cache')
+sentence_model = SentenceTransformer('all-MiniLM-L6-v2', cache_folder='/tmp/cache')
 
 SUPABASE_URL = os.getenv('supabaseUrl')
 SUPABASE_KEY = os.getenv('supabaseAnonKey')