deploy

Dockerfile

@@ -1,5 +1,5 @@
 # Use an official Python image
-FROM python:3.9
+FROM python:3.9-slim
 
 # Set environment variables for cache location
 ENV HF_HOME="/app/cache"
@@ -8,23 +8,26 @@ ENV TRANSFORMERS_CACHE="/app/cache"
 # Create the cache directory and set permissions
 RUN mkdir -p /app/cache && chmod -R 777 /app/cache
 
-# Install required Python packages
-RUN pip install --no-cache-dir uvicorn fastapi sentence-transformers
-
-# Pre-download the model and set proper permissions
-RUN python -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('sentence-transformers/clip-ViT-B-32-multilingual-v1')" && chmod -R 777 /app/cache
-
 # Set working directory
 WORKDIR /app
 
-# Copy application code
+# Copy the requirements file first (to leverage Docker's layer caching)
+COPY requirements.txt /app/
+
+# Install dependencies from requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application code
 COPY . /app
 
-# Ensure the app runs with correct permissions
+# Ensure all files are accessible
 RUN chmod -R 777 /app
 
-# Expose port for FastAPI
+# Pre-download the model (to avoid runtime downloading issues)
+RUN python -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('sentence-transformers/clip-ViT-B-32-multilingual-v1')" && chmod -R 777 /app/cache
+
+# Expose FastAPI port
 EXPOSE 7860
 
-# Start the FastAPI app
+# Start FastAPI application
 CMD ["python", "-m", "uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]