feat: Optimize Dockerfile configuration for production deployment

Dockerfile

@@ -1,4 +1,3 @@
-# Hugging Face Spaces Docker SDK Image
 FROM python:3.11-slim
 
 # Set environment variables
@@ -6,10 +5,16 @@ ENV PYTHONUNBUFFERED=1 \
     PYTHONDONTWRITEBYTECODE=1 \
     PORT=7860 \
     HOST=0.0.0.0 \
+    OMP_NUM_THREADS=1 \
+    MKL_NUM_THREADS=1 \
+    OPENBLAS_NUM_THREADS=1 \
+    VECLIB_MAXIMUM_THREADS=1 \
+    NUMEXPR_NUM_THREADS=1 \
+    TOKENIZERS_PARALLELISM=false \
     DATA_DIR=/app/knowledge_base \
     INDEX_DIR=/app/knowledge_base/indexes \
     PROCESSED_DIR=/app/knowledge_base/processed \
-    HF_HOME=/app/.cache/huggingface
+    HF_HOME=/tmp/.cache/huggingface
 
 WORKDIR /app
 
@@ -27,30 +32,11 @@ COPY requirements.txt .
 RUN pip install --no-cache-dir --upgrade pip && \
     pip install --no-cache-dir -r requirements.txt
 
-# Pre-cache embedding model weights into Docker image at build time
-RUN python -c "from transformers import AutoTokenizer, AutoModel; AutoTokenizer.from_pretrained('intfloat/multilingual-e5-small'); AutoModel.from_pretrained('intfloat/multilingual-e5-small')"
+# Copy application source code
+COPY . .
 
-# Copy application source code and pre-built index/processed artifacts
-COPY config.py .
-COPY main.py .
-COPY knowledge_base/ ./knowledge_base/
-COPY doc_chunking/ ./doc_chunking/
-COPY vector_search/ ./vector_search/
-COPY voice_stt/ ./voice_stt/
-COPY safety_guardrails/ ./safety_guardrails/
-COPY llm_synthesis/ ./llm_synthesis/
-COPY rag_pipeline/ ./rag_pipeline/
-COPY api_endpoints/ ./api_endpoints/
-COPY latency_benchmarks/ ./latency_benchmarks/
-COPY web_ui/ ./web_ui/
-
-# Create user for Hugging Face Spaces security
-RUN useradd -m -u 1000 user && \
-    chown -R user:user /app
-USER user
-
-# Expose default Hugging Face Spaces port
+# Expose default port
 EXPOSE 7860
 
 # Launch FastAPI server
-CMD ["python", "main.py"]
+CMD ["sh", "-c", "python main.py"]