Update Dockerfile

Dockerfile

@@ -1,48 +1,49 @@
-# syntax=docker/dockerfile:1
-FROM python:3.11-slim
-
-# Install build dependencies for llama-cpp-python
-RUN apt-get update && apt-get install -y \
-    cmake \
-    g++ \
-    gcc \
-    libopenblas-dev \
-    && rm -rf /var/lib/apt/lists/*
-
-# Set working directory
-WORKDIR /app
-
-# Set environment variables for CPU optimization
-# GGML_BLAS enables BLAS acceleration
-# GGML_OPENBLAS uses OpenBLAS library for matrix operations (2-3x faster)
-ENV CMAKE_ARGS="-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS"
-ENV FORCE_CMAKE=1
-
-# Copy requirements first for better Docker layer caching
-COPY requirements.txt .
-
-# Install Python dependencies
-# llama-cpp-python will compile from source with CPU optimizations
-RUN pip install --no-cache-dir -r requirements.txt
-
-# Copy application code
-COPY main.py .
-
-# Create cache directory for models
-RUN mkdir -p /app/models
-
-# Expose port 7860 (HuggingFace Space default)
-EXPOSE 7860
-
-# Set environment variables
-ENV HOST=0.0.0.0
-ENV PORT=7860
-
-# Health check for HuggingFace monitoring
-HEALTHCHECK --interval=30s --timeout=10s --start-period=120s --retries=3 \
-    CMD python -c "import requests; requests.get('http://localhost:7860/health')"
-
-# Run the FastAPI application with Uvicorn
-# workers=1 ensures single process (important for model memory management)
-# log-level=info provides detailed logging for debugging
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1", "--log-level", "info"]
+# syntax=docker/dockerfile:1
+FROM python:3.11-slim
+
+# Install build dependencies for llama-cpp-python
+RUN apt-get update && apt-get install -y \
+    cmake \
+    g++ \
+    gcc \
+    pkg-config \
+    libopenblas-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /app
+
+# Set environment variables for CPU optimization
+# GGML_BLAS enables BLAS acceleration
+# GGML_OPENBLAS uses OpenBLAS library for matrix operations (2-3x faster)
+ENV CMAKE_ARGS="-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS"
+ENV FORCE_CMAKE=1
+
+# Copy requirements first for better Docker layer caching
+COPY requirements.txt .
+
+# Install Python dependencies
+# llama-cpp-python will compile from source with CPU optimizations
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY main.py .
+
+# Create cache directory for models
+RUN mkdir -p /app/models
+
+# Expose port 7860 (HuggingFace Space default)
+EXPOSE 7860
+
+# Set environment variables
+ENV HOST=0.0.0.0
+ENV PORT=7860
+
+# Health check for HuggingFace monitoring
+HEALTHCHECK --interval=30s --timeout=10s --start-period=120s --retries=3 \
+    CMD python -c "import requests; requests.get('http://localhost:7860/health')"
+
+# Run the FastAPI application with Uvicorn
+# workers=1 ensures single process (important for model memory management)
+# log-level=info provides detailed logging for debugging
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1", "--log-level", "info"]