Advanced Settings

Configuration Options

Local Image Building

By default, the application uses pre-built Docker images for faster setup. If you need to build images locally (for customization or development):

# Build and run locally instead of using pre-built images
make build REGISTRY=false
make up

# Examples for both applications:
# Dine-In
cd dine-in && make build REGISTRY=false && make up

# Take-Away
cd take-away && make build REGISTRY=false && make up

When to use local building: - Modifying source code or configurations - Development and testing changes - Air-gapped environments without internet access - Custom hardware optimizations

Note: Local building takes significantly longer (15-30 minutes) compared to pre-built images (2-5 minutes).

Dine-In Configuration

Environment Configuration (.env)

# =============================================================================
# Logging
# =============================================================================
LOG_LEVEL=INFO

# =============================================================================
# Service Endpoints
# =============================================================================
OVMS_ENDPOINT=http://ovms-vlm:8000
OVMS_MODEL_NAME=Qwen/Qwen2.5-VL-7B-Instruct
SEMANTIC_SERVICE_ENDPOINT=http://semantic-service:8080
API_TIMEOUT=60

Test Data Configuration

Add Images: Place food tray/plate images in images/ folder
Supported formats: .jpg, .jpeg, .png
Images should clearly show food items on the plate
Update Orders: Edit configs/orders.json with test orders
Each order needs image_id and list of items_ordered
Image IDs should match filenames (without extension)
Update Inventory: Edit configs/inventory.json with menu items
Define all possible food items
Include item names, categories, and metadata

Dine-In Docker Services

Container	Ports	Description
`dinein_app`	7861, 8083	Main application (Gradio + FastAPI)
`dinein_ovms_vlm`	8002	Vision-Language Model server
`dinein_semantic_service`	8081, 9091	Semantic text matching
`metrics-collector`	8084	System metrics aggregation

Take-Away Configuration

Environment Configuration (.env)

# =============================================================================
# VLM Backend
# =============================================================================
VLM_BACKEND=ovms
OVMS_ENDPOINT=http://ovms-vlm:8000
OVMS_MODEL_NAME=Qwen/Qwen2.5-VL-7B-Instruct
OPENVINO_DEVICE=GPU          # 'GPU', 'CPU', or 'AUTO'

# =============================================================================
# Semantic Service
# =============================================================================
SEMANTIC_VLM_BACKEND=ovms
DEFAULT_MATCHING_STRATEGY=hybrid   # 'exact', 'semantic', or 'hybrid'
SIMILARITY_THRESHOLD=0.85
OVMS_TIMEOUT=60

# =============================================================================
# MinIO Storage
# =============================================================================
MINIO_ROOT_USER=minioadmin
MINIO_ROOT_PASSWORD=minioadmin
MINIO_ENDPOINT=minio:9000

Service Modes

Mode	Configuration	Use Case
Single	`SERVICE_MODE=single`	Development, testing
Parallel	`SERVICE_MODE=parallel WORKERS=4`	Production deployment

Start in Different Modes:

# Single mode (default)
make up

# Parallel mode with 4 workers
make up-parallel WORKERS=4

# Parallel mode with auto-scaling
make up-parallel WORKERS=4 SCALING_MODE=auto

Take-Away Docker Services

Container	Ports	Description
`takeaway_app`	7860, 8080	Main application (Gradio + FastAPI)
`ovms-vlm`	8001	Vision-Language Model server
`frame-selector`	8085	YOLO-based frame selection
`semantic-service`	8081, 9091	Semantic text matching
`minio`	9000, 9001	S3-compatible storage

Benchmarking

Dine-In Benchmarking

Initialize Performance Tools:

cd dine-in
make update-submodules

Run Benchmark:

make benchmark

Stream Density Test:

make benchmark-density

View Results:

make benchmark-density-results
cat results/benchmark_results.json

Take-Away Benchmarking

Initialize Performance Tools:

cd take-away
make update-submodules

Single Video Benchmark:

make benchmark

Fixed Workers Benchmark:

make benchmark-oa BENCHMARK_WORKERS=4 BENCHMARK_DURATION=300

Stream Density Benchmark:

make benchmark-stream-density \
  BENCHMARK_TARGET_LATENCY_MS=25000 \
  BENCHMARK_MIN_TRANSACTIONS=3 \
  BENCHMARK_WORKER_INCREMENT=1

Benchmark Configuration Variables

Variable	Default	Description
`TARGET_LATENCY_MS`	25000	Target latency threshold (ms)
`LATENCY_METRIC`	avg	'avg', 'p95', or 'max'
`WORKER_INCREMENT`	1	Workers added per iteration
`INIT_DURATION`	10	Warmup time (seconds)
`MIN_TRANSACTIONS`	3	Min transactions before measuring
`MAX_ITERATIONS`	50	Max scaling iterations
`RESULTS_DIR`	./results	Results output directory

System Requirements

Minimum Configuration

Component	Specification
CPU	Intel Xeon 8+ cores
RAM	16 GB
GPU	Intel Arc A770 8GB / NVIDIA RTX 3060
Storage	50 GB SSD
Docker	24.0+ with Compose V2

Recommended Configuration

Component	Specification
CPU	Intel Xeon 16+ cores
RAM	32 GB
GPU	NVIDIA RTX 3080+ / Intel Data Center GPU
Storage	200 GB NVMe SSD
Network	10 Gbps (for Take-Away RTSP)

Useful Make Commands

Dine-In Commands

make build                  # Build Docker images
make up                     # Start services
make down                   # Stop services
make logs                   # View logs
make update-submodules      # Initialize performance-tools
make benchmark              # Run benchmark
make benchmark-density      # Run stream density test

Take-Away Commands

make build                  # Build Docker images
make up                     # Start (single mode)
make up-parallel WORKERS=4  # Start (parallel mode)
make down                   # Stop services
make logs                   # View logs
make update-submodules      # Initialize performance-tools
make benchmark              # Run benchmark
make benchmark-stream-density  # Stream density test

Common Commands

make clean-images — Remove dangling Docker images
make clean-all — Remove all unused Docker resources
make check-env — Verify configuration
make show-config — Display current configuration

Configure System Proxy

Please follow these steps to configure proxy settings:

1. Configure Proxy for Current Shell Session

export http_proxy=http://<proxy-host>:<port>
export https_proxy=http://<proxy-host>:<port>
export HTTP_PROXY=http://<proxy-host>:<port>
export HTTPS_PROXY=http://<proxy-host>:<port>
export NO_PROXY=localhost,127.0.0.1,::1
export no_proxy=localhost,127.0.0.1,::1

2. Docker Daemon Proxy Configuration

Create directory if missing:

sudo mkdir -p /etc/systemd/system/docker.service.d
sudo nano /etc/systemd/system/docker.service.d/http-proxy.conf

Add configuration:

[Service]
Environment="http_proxy=http://<proxy-host>:<port>"
Environment="https_proxy=http://<proxy-host>:<port>"
Environment="no_proxy=localhost,127.0.0.1,::1"

Reload and restart:

sudo systemctl daemon-reload
sudo systemctl restart docker

Troubleshooting

Common Issues

OVMS Not Loading: - Ensure GPU drivers are installed - Check model files exist in ovms-service/models/ - Verify OVMS endpoint in .env

VLM Timeout Errors: - Increase API_TIMEOUT in .env - Check GPU memory utilization - Consider using a smaller model precision (INT8)

Stream Processing Issues (Take-Away): - Verify RTSP stream URLs are accessible - Check network bandwidth - Consider reducing number of parallel workers

Debug Commands

# Check container logs
docker logs <container_name>

# Check GPU utilization
nvidia-smi -l 1

# Check network connectivity
curl http://localhost:8001/v2/models

# Verify service health
curl http://localhost:8083/health