Added trained model

Dockerfile

@@ -1,19 +1,22 @@
-FROM python:3.9
+# Use official Python base image
+FROM python:3.11-slim
 
+# Set the working directory
 WORKDIR /app
+
+# Copy all files to the container
 COPY . /app
 
-ENV HF_HOME=/app/.cache
 
-RUN mkdir -p /app/.cache/huggingface/hub && \
-    chmod -R 777 /app/.cache && \
-    chmod -R 777 /app/.cache/huggingface
+# Set HF_HOME to use an accessible cache directory
+ENV HF_HOME=/app/.cache
+RUN mkdir -p /app/.cache && chmod -R 777 /app/.cache
 
-RUN pip install --upgrade pip
-RUN pip install --no-cache-dir -r requirements.txt
-RUN pip install uvicorn
-RUN uvicorn --version
+# Install dependencies
+RUN pip install --no-cache-dir -r Requirements.txt
 
+# Expose port (Hugging Face uses port 7860 by default)
 EXPOSE 7860
 
-CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]
+# Run the FastAPI server using uvicorn
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

requirements.txt

@@ -0,0 +1,10 @@
+fastapi
+uvicorn
+sentence-transformers
+torch
+scikit-learn
+numpy
+pandas
+openpyxl
+numpy
+huggingface-hub