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Prerequisites

  • Docker installed and running
  • 8 GB RAM (16 GB+ recommended)
  • 10 GB disk space (100 GB+ recommended)

Run VectorAI DB

docker pull actian/vectorai:latest
docker run -d --name vectorai \
  -v ./local_data:/var/lib/actian-vectorai \
  -p 6573-6575:6573-6575 \
  -e ACTIAN_VECTORAI_ACCEPT_EULA=YES \
  actian/vectorai:latest
The gRPC server is available at localhost:6574. The Local UI is available at localhost:6575.
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Using Docker Compose

Create a docker-compose.yml file:
services:
  vectorai:
    image: actian/vectorai:latest
    container_name: vectorai
    ports:
      - "6573:6573"
      - "6574:6574"
      - "6575:6575"
    volumes:
      - ./local_data:/var/lib/actian-vectorai
    environment:
      - ACTIAN_VECTORAI_ACCEPT_EULA=YES
    restart: unless-stopped
Start the service:
docker-compose up -d
Stop the service:
docker-compose down

Verify installation

Python SDK required: Run pip install actian-vectorai-client first, or see the Python SDK installation guide.
from actian_vectorai import VectorAIClient

with VectorAIClient("localhost:6574") as client:
    info = client.health_check()
    print(f"Connected to {info['title']} v{info['version']}")

Troubleshooting

IssueSolution
Connection failedEnsure the container is running: docker ps
Port already in useStop services using port 6574 or remap: -p 6576:6574
Permission deniedRun Docker with appropriate permissions or add your user to the docker group
Container exits immediatelyCheck logs: docker logs <container-id>
Container exits (Linux / WSL2)Volume mount permission mismatch: the container runs as UID 999. Run chown -R 999:999 ./local_data on the host, then restart.

View Docker logs

# List running containers
docker ps

# View logs
docker logs <container-id>

# Follow logs in real-time
docker logs -f <container-id>

Next steps

Quickstart

Create your first collection, insert vectors, and run a search.

Core concepts

Understand the data model, architecture, and how search works.

Python SDK

Install and configure the Python SDK.