Environment Variables
To change environment variables, you must recreate the Immich containers. Just restarting the containers does not replace the environment within the container!
In order to recreate the container using docker compose, run docker compose up -d.
In most cases docker will recognize that the .env file has changed and recreate the affected containers.
If this should not work, try running docker compose up -d --force-recreate.
Docker Compose
| Variable | Description | Default | Services |
|---|---|---|---|
IMMICH_VERSION | Image tags | release | server, microservices, machine learning, web, proxy |
UPLOAD_LOCATION | Host Path for uploads | server, microservices |
These environment variables are used by the docker-compose.yml file and do NOT affect the containers directly.
General
| Variable | Description | Default | Services |
|---|---|---|---|
TZ | Timezone | microservices | |
NODE_ENV | Environment (production, development) | production | server, microservices, machine learning, web |
LOG_LEVEL | Log Level (verbose, debug, log, warn, error) | log | server, microservices |
IMMICH_MEDIA_LOCATION | Media Location | ./upload | server, microservices |
IMMICH_CONFIG_FILE | Path to config file | server | |
IMMICH_WEB_ROOT | Path of root index.html | /usr/src/app/www | server |
IMMICH_REVERSE_GEOCODING_ROOT | Path of reverse geocoding dump directory | /usr/src/resources | microservices |
TZ is only used by the exiftool as a fallback in case the timezone cannot be determined from the image metadata.
exiftool is only present in the microservices container.
Ports
| Variable | Description | Default | Services |
|---|---|---|---|
PORT | Web Port | 3000 | web |
SERVER_PORT | Server Port | 3001 | server |
MICROSERVICES_PORT | Microservices Port | 3002 | microservices |
MACHINE_LEARNING_HOST | Machine Learning Host | 0.0.0.0 | machine learning |
MACHINE_LEARNING_PORT | Machine Learning Port | 3003 | machine learning |
Database
| Variable | Description | Default | Services |
|---|---|---|---|
DB_URL | Database URL | server, microservices | |
DB_HOSTNAME | Database Host | localhost | server, microservices |
DB_PORT | Database Port | 5432 | server, microservices |
DB_USERNAME | Database User | postgres | server, microservices |
DB_PASSWORD | Database Password | postgres | server, microservices |
DB_DATABASE | Database Name | immich | server, microservices |
When DB_URL is defined, the other database (DB_*) variables are ignored.
Redis
| Variable | Description | Default | Services |
|---|---|---|---|
REDIS_URL | Redis URL | server, microservices | |
REDIS_HOSTNAME | Redis Host | immich_redis | server, microservices |
REDIS_PORT | Redis Port | 6379 | server, microservices |
REDIS_DBINDEX | Redis DB Index | 0 | server, microservices |
REDIS_USERNAME | Redis Username | server, microservices | |
REDIS_PASSWORD | Redis Password | server, microservices | |
REDIS_SOCKET | Redis Socket | server, microservices |
REDIS_URL must start with ioredis:// and then include a base64 encoded JSON string for the configuration.
More info can be found in the upstream ioredis documentation.
- When
REDIS_URLis defined, the other redis (REDIS_*) variables are ignored. - When
REDIS_SOCKETis defined, the other redis (REDIS_*) variables are ignored.
Redis (Sentinel) URL example JSON before encoding:
{
"sentinels": [
{
"host": "redis-sentinel-node-0",
"port": 26379
},
{
"host": "redis-sentinel-node-1",
"port": 26379
},
{
"host": "redis-sentinel-node-2",
"port": 26379
}
],
"name": "redis-sentinel"
}
Machine Learning
| Variable | Description | Default | Services |
|---|---|---|---|
MACHINE_LEARNING_MODEL_TTL | Inactivity time (s) before a model is unloaded (disabled if <= 0) | 300 | machine learning |
MACHINE_LEARNING_MODEL_TTL_POLL_S | Interval (s) between checks for the model TTL (disabled if <= 0) | 10 | machine learning |
MACHINE_LEARNING_CACHE_FOLDER | Directory where models are downloaded | /cache | machine learning |
MACHINE_LEARNING_REQUEST_THREADS*1 | Thread count of the request thread pool (disabled if <= 0) | number of CPU cores | machine learning |
MACHINE_LEARNING_MODEL_INTER_OP_THREADS | Number of parallel model operations | 1 | machine learning |
MACHINE_LEARNING_MODEL_INTRA_OP_THREADS | Number of threads for each model operation | 2 | machine learning |
MACHINE_LEARNING_WORKERS*2 | Number of worker processes to spawn | 1 | machine learning |
MACHINE_LEARNING_WORKER_TIMEOUT | Maximum time (s) of unresponsiveness before a worker is killed | 120 | machine learning |
*1: It is recommended to begin with this parameter when changing the concurrency levels of the machine learning service and then tune the other ones.
*2: Since each process duplicates models in memory, changing this is not recommended unless you have abundant memory to go around.
Other machine learning parameters can be tuned from the admin UI.
Docker Secrets
The following variables support the use of Docker secrets for additional security.
To use any of these, replace the regular environment variable with the equivalent _FILE environment variable. The value of
the _FILE variable should be set to the path of a file containing the variable value.
| Regular Variable | Equivalent Docker Secrets '_FILE' Variable |
|---|---|
DB_HOSTNAME | DB_HOSTNAME_FILE*1 |
DB_DATABASE_NAME | DB_DATABASE_NAME_FILE*1 |
DB_USERNAME | DB_USERNAME_FILE*1 |
DB_PASSWORD | DB_PASSWORD_FILE*1 |
REDIS_PASSWORD | REDIS_PASSWORD_FILE*2 |
*1: See the official documentation for details on how to use Docker Secrets in the Postgres image.
*2: See this comment for an example of how to use use a Docker secret for the password in the Redis container.