description: Learn how to configure environment variables for AiMicromind

Environment Variables

aimicromind support different environment variables to configure your instance. You can specify the following variables in the .env file inside packages/server folder. Refer to .env.example file.

Variable	Description	Type	Default
PORT	The HTTP port aimicromind runs on	Number	3000
AIMICROMIND_USERNAME	Username to login	String
AIMICROMIND_PASSWORD	Password to login	String
AIMICROMIND_FILE_SIZE_LIMIT	Maximum file size when uploading	String	`50mb`
NUMBER_OF_PROXIES	Rate Limit Proxy	Number
CORS_ORIGINS	The allowed origins for all cross-origin HTTP calls	String
IFRAME_ORIGINS	The allowed origins for iframe src embedding	String
SHOW_COMMUNITY_NODES	Display nodes that are created by community	Boolean: `true` or `false`
DISABLED_NODES	Comma separated list of node names to disable	String

For Database

Variable	Description	Type	Default
DATABASE_TYPE	Type of database to store the aimicromind data	Enum String: `sqlite`, `mysql`, `postgres`	`sqlite`
DATABASE_PATH	Location where database is saved (When DATABASE_TYPE is sqlite)	String	`your-home-dir/.aimicromind`
DATABASE_HOST	Host URL or IP address (When DATABASE_TYPE is not sqlite)	String
DATABASE_PORT	Database port (When DATABASE_TYPE is not sqlite)	String
DATABASE_USER	Database username (When DATABASE_TYPE is not sqlite)	String
DATABASE_PASSWORD	Database password (When DATABASE_TYPE is not sqlite)	String
DATABASE_NAME	Database name (When DATABASE_TYPE is not sqlite)	String
DATABASE_SSL	Database SSL is required (When DATABASE_TYPE is not sqlite)	Boolean: `true` or `false`	`false`

For Storage

aimicromind store the following files under a local path folder by default.

Files uploaded on Document Loaders/Document Store
Image/Audio uploads from chat
Images/Files from Assistant
Files from Vector Upsert API

User can specify STORAGE_TYPE to use AWS S3, Google Cloud Storage or local path

Variable	Description	Type	Default
STORAGE_TYPE	Type of storage for uploaded files. default is `local`	Enum String: `s3`, `gcs`, `local`	`local`
BLOB_STORAGE_PATH	Local folder path where uploaded files are stored when `STORAGE_TYPE` is `local`	String	`your-home-dir/.aimicromind/storage`
S3_STORAGE_BUCKET_NAME	Bucket name to hold the uploaded files when `STORAGE_TYPE` is `s3`	String
S3_STORAGE_ACCESS_KEY_ID	AWS Access Key	String
S3_STORAGE_SECRET_ACCESS_KEY	AWS Secret Key	String
S3_STORAGE_REGION	Region for S3 bucket	String
S3_ENDPOINT_URL	Custom S3 endpoint (optional)	String
S3_FORCE_PATH_STYLE	Force S3 path style (optional)	Boolean	false
GOOGLE_CLOUD_STORAGE_CREDENTIAL	Google Cloud Service Account Key	String
GOOGLE_CLOUD_STORAGE_PROJ_ID	Google Cloud Project ID	String
GOOGLE_CLOUD_STORAGE_BUCKET_NAME	Google Cloud Storage Bucket Name	String
GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS	Type of Access	Boolean	true

For Debugging and Logs

Variable	Description	Type
DEBUG	Print logs from components	Boolean
LOG_PATH	Location where log files are stored	String	`AiMicromind/packages/server/logs`
LOG_LEVEL	Different levels of logs	Enum String: `error`, `info`, `verbose`, `debug`	`info`

DEBUG: if set to true, will print logs to terminal/console:

LOG_LEVEL: Different log levels for loggers to be saved. Can be error, info, verbose, or debug. By default it is set to info, only logger.info will be saved to the log files. If you want to have complete details, set to debug.

**server-requests.log.jsonl - logs every request sent to AiMicromind**

**server.log - logs general actions on AiMicromind**

**server-error.log - logs error with stack trace**

Logs Streaming S3

When STORAGE_TYPE env variable is set to s3 , logs will be automatically streamed and stored to S3. New log file will be created hourly, enabling easier debugging.

Logs Streaming GCS

When STORAGE_TYPE env variable is set to gcs , logs will be automatically streamed to Google Cloud Logging.

For Credentials

AiMicromind store your third party API keys as encrypted credentials using an encryption key.

By default, a random encryption key will be generated when starting up the application and stored under a file path. This encryption key is then retrieved everytime to decrypt the credentials used within a chatflow. For example, your OpenAI API key, Pinecone API key, etc.

You can configure to use AWS Secret Manager to store the encryption key instead.

Variable	Description	Type	Default
SECRETKEY_STORAGE_TYPE	How to store the encryption key	Enum String: `local`, `aws`	`local`
SECRETKEY_PATH	Local file path where encryption key is saved	String	`AiMicromind/packages/server`
AIMICROMIND_SECRETKEY_OVERWRITE	Encryption key to be used instead of the existing key	String
SECRETKEY_AWS_ACCESS_KEY		String
SECRETKEY_AWS_SECRET_KEY		String
SECRETKEY_AWS_REGION		String

For some reasons, sometimes encryption key might be re-generated or the stored path was changed, this will cause errors like - Credentials could not be decrypted.

To avoid this, you can set your own encryption key as AIMICROMIND_SECRETKEY_OVERWRITE, so that the same encryption key will be used everytime. There is no restriction on the format, you can set it as any text that you want, or the same as your AIMICROMIND_PASSWORD.

{% hint style="info" %} Credential API Key returned from the UI is not the same length as your original Api Key that you have set. This is a fake prefix string that prevents network spoofing, that's why we are not returning the Api Key back to UI. However, the correct Api Key will be retrieved and used during your interaction with the chatflow. {% endhint %}

For Models

In some cases, you might want to use custom model on the existing Chat Model and LLM nodes, or restrict access to only certain models.

By default, aimicromindpulls the model list from here. However user can create their own models.json file and specify the file path:

Variable	Description	Type	Default
MODEL_LIST_CONFIG_JSON	Link to load list of models from your `models.json` config file	String	https://github.com/operativestech/AiMicroMind_Platform_2025/main/packages/components/models.json

For API Keys

Users can create multiple API keys within aimicromind in order to authenticate with the APIs. By default, keys get stored as a JSON file to your local file path. User can change the behavior by using the below env variable.

Variable	Description	Type	Default
APIKEY_STORAGE_TYPE	Method to store API keys	Enum string: `json`, `db`	`json`
APIKEY_PATH	Location where the API keys are stored when `APIKEY_STORAGE_TYPE` is unspecified or `json`	String	`AiMicromind/packages/server`

Using db as storage type will store the API keys to database instead of a local JSON file.

For Built-In and External Dependencies

There are certain nodes/features within aimicromind that allow user to run Javascript code. For security reasons, by default it only allow certain dependencies. It's possible to lift that restriction for built-in and external modules by setting the following environment variables:

Variable	Description
TOOL_FUNCTION_BUILTIN_DEP	NodeJS built-in modules to be used for Tool Function	String
TOOL_FUNCTION_EXTERNAL_DEP	External modules to be used for Tool Function	String

{% code title=".env" %}

# Allows usage of all builtin modules
TOOL_FUNCTION_BUILTIN_DEP=*

# Allows usage of only fs
TOOL_FUNCTION_BUILTIN_DEP=fs

# Allows usage of only crypto and fs
TOOL_FUNCTION_BUILTIN_DEP=crypto,fs

# Allow usage of external npm modules.
TOOL_FUNCTION_EXTERNAL_DEP=axios,moment

{% endcode %}

Examples of how to set environment variables

NPM

You can set all these variables when running aimicromind using npx. For example:

npx aimicromind start --PORT=3000 --DEBUG=true

Docker

docker run -d -p 5678:5678 aimicromind\
 -e DATABASE_TYPE=postgresdb \
 -e DATABASE_PORT=<POSTGRES_PORT> \
 -e DATABASE_HOST=<POSTGRES_HOST> \
 -e DATABASE_NAME=<POSTGRES_DATABASE_NAME> \
 -e DATABASE_USER=<POSTGRES_USER> \
 -e DATABASE_PASSWORD=<POSTGRES_PASSWORD> \

Docker Compose

You can set all these variables in the .env file inside docker folder. Refer to .env.example file.

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