add -hf token

Dockerfile

@@ -1,39 +1,38 @@
-# Use official NVIDIA CUDA base image with Ubuntu
 FROM nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04
-
-# Set working directory
 WORKDIR /app
 
-# Install system dependencies
 RUN apt-get update && apt-get install -y \
-    python3-pip \
-    python3-dev \
+    python3 \
+    python3-pip python3-distutils python3-dev python3-venv\
     git \
+    ffmpeg \
+    sudo wget curl software-properties-common build-essential gcc g++ \   
+    && ln -s /usr/bin/python3 /usr/bin/python \
     && rm -rf /var/lib/apt/lists/*
 
-# Set Python 3 as default
-RUN ln -s /usr/bin/python3 /usr/bin/python
+RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
+ENV PATH="/root/.cargo/bin:${PATH}"
 
-# Install PyTorch with CUDA support
-RUN pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu121
+RUN export CC=/usr/bin/gcc
+RUN export CXX=/usr/bin/g++
 
-# Install other Python dependencies
-RUN pip3 install \
-    fastapi \
-    uvicorn \
-    diffusers \
-    huggingface_hub \
-    safetensors
+RUN pip install --upgrade pip setuptools setuptools-rust torch
+RUN pip install flash-attn --no-build-isolation
 
-# Copy the FastAPI server code
-COPY server.py .
+COPY requirements.txt .
+#RUN pip install --no-cache-dir torch==2.6.0 torchvision
+#RUN pip install --no-cache-dir transformers
+RUN pip install --no-cache-dir -r requirements.txt
+#RUN pip install git+https://github.com/ai4bharat/IndicF5.git
 
-# Expose port
-EXPOSE 7860
+COPY . .
+
+RUN useradd -ms /bin/bash appuser \
+    && chown -R appuser:appuser /app
 
-# Set environment variables
-ENV PYTHONUNBUFFERED=1
-ENV CUDA_HOME=/usr/local/cuda
+USER appuser
+
+EXPOSE 7860
 
 # Run the server
 CMD ["uvicorn", "server.py:app", "--host", "0.0.0.0", "--port", "7860"]