Advanced Settings#

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

Build Local Image#

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).

Configuration Options#

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#

  1. Add Images: Place food tray/plate images in images/ folder

    • Supported formats: .jpg, .jpeg, .png

    • Images should clearly show food items on the plate

  2. 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)

  3. 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

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

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

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

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