refactor: Single image serving both API (8081) and Streamlit (3000)

- Combine API and Streamlit into single Dockerfile
- Add entrypoint.sh to run both services in parallel
- Reduces Harbor storage from 2.66GB to 1.33GB
- Single build instead of two

Dockerfile

@@ -1,5 +1,5 @@
-# Reverse Image Search API
-# Multi-stage build for optimized image size
+# Visual Search Engine - API (8081) + Streamlit UI (3000)
+# Single image serving both endpoints
 
 FROM python:3.11-slim as builder
 
@@ -19,12 +19,12 @@ FROM python:3.11-slim
 
 WORKDIR /app
 
-# Install runtime dependencies (libgomp for OpenMP parallelism)
+# Install runtime dependencies
 RUN apt-get update && apt-get install -y --no-install-recommends \
     libgomp1 \
     && rm -rf /var/lib/apt/lists/*
 
-# FAISS uses OpenMP for parallel search - set threads for Xeon
+# FAISS OpenMP threads
 ENV OMP_NUM_THREADS=8
 
 # Copy installed packages from builder
@@ -36,29 +36,30 @@ COPY api/ ./api/
 COPY config.py .
 COPY reverse_icon_search.py .
 COPY run_api_server.py .
+COPY main_streamlit.py .
+COPY entrypoint.sh .
 
-# Copy pre-built index and filenames for inference
-# Option 1: Bundle in image (~530 MB)
+# Copy pre-built index and filenames
 COPY index.faiss .
 COPY filenames.pkl .
 
-# Option 2: Mount as volume at runtime (uncomment above, use docker run -v)
-
-# Create necessary directories
-RUN mkdir -p uploads logs
+# Create necessary directories and make entrypoint executable
+RUN mkdir -p uploads logs && chmod +x entrypoint.sh
 
 # Environment variables
 ENV PYTHONUNBUFFERED=1
 ENV PYTHONDONTWRITEBYTECODE=1
-ENV API_PORT=5002
+ENV API_PORT=8081
 ENV DEBUG=false
+ENV STREAMLIT_SERVER_PORT=3000
+ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
 
-# Expose port
-EXPOSE 5002
+# Expose both ports
+EXPOSE 8081 3000
 
-# Health check
-HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
-    CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:5002/api/health')" || exit 1
+# Health check on API
+HEALTHCHECK --interval=30s --timeout=10s --start-period=120s --retries=3 \
+    CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8081/api/health')" || exit 1
 
-# Run the application
-CMD ["python", "run_api_server.py"]
+# Run both services
+CMD ["./entrypoint.sh"]

Dockerfile.api

@@ -1,33 +0,0 @@
-# Reverse Image Search API
-# Uses pre-built base image with TensorFlow to avoid repeated downloads
-
-FROM harbor.armco.dev/library/visualsearch-base:latest
-
-WORKDIR /app
-
-# Copy application code
-COPY api/ ./api/
-COPY config.py .
-COPY reverse_icon_search.py .
-COPY run_api_server.py .
-
-# Copy pre-built index and filenames for inference
-COPY index.faiss .
-COPY filenames.pkl .
-
-# Create necessary directories
-RUN mkdir -p uploads logs
-
-# Environment variables
-ENV API_PORT=8081
-ENV DEBUG=false
-
-# Expose port
-EXPOSE 8081
-
-# Health check
-HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
-    CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8081/api/health')" || exit 1
-
-# Run the application
-CMD ["python", "run_api_server.py"]

Dockerfile.base

@@ -1,26 +0,0 @@
-# Base image with TensorFlow and heavy dependencies pre-installed
-# Build once, reuse for API and Streamlit builds
-# Tag: harbor.armco.dev/library/visualsearch-base:latest
-
-FROM python:3.11-slim
-
-WORKDIR /app
-
-# Install build dependencies
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential \
-    libgomp1 \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy and install requirements
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-# FAISS uses OpenMP for parallel search
-ENV OMP_NUM_THREADS=8
-ENV PATH=/root/.local/bin:$PATH
-ENV PYTHONUNBUFFERED=1
-ENV PYTHONDONTWRITEBYTECODE=1
-
-# Clean up build dependencies to reduce image size
-RUN apt-get purge -y build-essential && apt-get autoremove -y

Dockerfile.streamlit

@@ -1,32 +0,0 @@
-# Reverse Image Search Streamlit UI
-# Uses pre-built base image with TensorFlow to avoid repeated downloads
-
-FROM harbor.armco.dev/library/visualsearch-base:latest
-
-WORKDIR /app
-
-# Copy application code
-COPY config.py .
-COPY reverse_icon_search.py .
-COPY main_streamlit.py .
-
-# Copy pre-built index and filenames for inference
-COPY index.faiss .
-COPY filenames.pkl .
-
-# Create necessary directories
-RUN mkdir -p uploads logs
-
-# Environment variables
-ENV STREAMLIT_SERVER_PORT=3000
-ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
-
-# Expose port
-EXPOSE 3000
-
-# Health check
-HEALTHCHECK --interval=30s --timeout=10s --start-period=120s --retries=3 \
-    CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:3000/_stcore/health')" || exit 1
-
-# Run Streamlit
-CMD ["streamlit", "run", "main_streamlit.py", "--server.port=3000", "--server.address=0.0.0.0"]

Jenkinsfile

@@ -1,14 +1,11 @@
 @Library('jenkins-shared@main') _
 
-// NOTE: Build base image first when requirements.txt changes:
-//   [imageName: 'visualsearch-base', dockerfile: 'Dockerfile.base']
-// Then rebuild API and Streamlit images
+// Single image serves both API (8081) and Streamlit UI (3000)
 
 kanikoPipeline(
   repoName: 'visual-search-engine',
   branch: env.BRANCH_NAME ?: 'main',
   builds: [
-    [imageName: 'visualsearch', dockerfile: 'Dockerfile.api'],
-    [imageName: 'visualsearch-stl', dockerfile: 'Dockerfile.streamlit']
+    [imageName: 'visualsearch', dockerfile: 'Dockerfile']
   ]
 )

entrypoint.sh

@@ -0,0 +1,17 @@
+#!/bin/bash
+# Run both API server (8081) and Streamlit UI (3000) in parallel
+
+# Start API server in background
+python run_api_server.py &
+API_PID=$!
+
+# Start Streamlit in background
+streamlit run main_streamlit.py --server.port=3000 --server.address=0.0.0.0 &
+STL_PID=$!
+
+# Wait for either to exit
+wait -n $API_PID $STL_PID
+
+# If one exits, kill the other and exit
+kill $API_PID $STL_PID 2>/dev/null
+exit 1