The easiest and quickest way to run AI Studio is via docker-compose.
Create `docker-compose.yml`
version: '3.8'
services:
postgres:
image: postgres:13
environment:
- POSTGRES_DB=aistudio
- POSTGRES_USER=aistudio
- POSTGRES_HOST_AUTH_METHOD=trust
volumes:
- postgres:/var/lib/postgresql/data
ports:
- 5432:5432
healthcheck:
test: [ "CMD-SHELL", "pg_isready -U aistudio" ]
interval: 30s
timeout: 30s
retries: 3
restart: always
redis:
image: redis:7.2-alpine
ports:
- 6379:6379
command: redis-server --save 20 1 --loglevel warning
volumes:
- redis:/data
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 1s
timeout: 3s
retries: 30
restart: always
clickhouse:
image: clickhouse/clickhouse-server:24.1.5
volumes:
- clickhouse:/var/lib/clickhouse
ports:
- 9000:9000
- 8123:8123
restart: always
migrate:
image: missingstudio/ai:dev
command: ["migrate"]
environment:
- GATEWAY_POSTGRES_URL=postgres://aistudio@postgres:5432/aistudio?sslmode=disable
depends_on:
- postgres
aistudio:
image: missingstudio/ai:dev
environment:
- GATEWAY_APP_HOST=0.0.0.0
- GATEWAY_APP_PORT=8080
- GATEWAY_REDIS_HOST=redis
- GATEWAY_REDIS_PORT=6379
- GATEWAY_POSTGRES_URL=postgres://aistudio@postgres:5432/aistudio?sslmode=disable
command: ["start"]
ports:
- 8080:8080
depends_on:
- redis
- postgres
- clickhouse
- migrate
volumes:
redis: {}
postgres: {}
clickhouse: {}
You’re geared up and ready to go! 🚀
Following these steps should have you AI studio up and running to power up LLMOps for your LLM appplications.
If you have any questions or need support, reach out to our Discord Community.
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