The server is configured via a file named server-config.toml. This file is included in the root of the distribution package that you have received and was automatically used when you started the server. You can, however, customize the values in this file and then restart the server. Below are the important configurations-
# The following line defines the API key to access the server end-points.
api_key = "mykey"
################################### Data Security Secret ####################################
# The following line defines a secret used to protect your data at rest and ensures
# there is no correlatability between your own data and someone else's who is using this
# product. Even if your database layer is compromised, protecting this secret will thwart
# many forms of attack vectors. This secret cannot be changed without re-enrolling all
# your data again. For secret rotation, it is suggested you re-enroll your entire data
# from time to time and point to a new instance while retiring the instance with the old
# secret.
#
# IMPORTANT NOTE: person_id and person_name are stored in plain text and are searchable.
# For full privacy, it is sugggested that you use UUIDs for person_id and skip storing
# the name where it is not neccessary. This is a trade-off between the convenience of
# search and the privacy of non-correlatibility that you can consider to suit your
# use-case. It is also suggested that you use UUIDs for collection names while
# maintaining a separate database that maps those UUIDs to meaningful groups.
#
# This product stores Renewable Biometric References as per the below standard:
# Biometric information protection - ISO/IEC 24745:2022:
# https://www.iso.org/standard/75302.html
#
# The secret that you are setting below corresponds to Auxiliary Data as per the
# standard.
data_security_secret = "changethis"
# Change the following line to define another interface for the server to listen on.
ip = "0.0.0.0"
# Max request size in MB. Change this to restrict request size.
max_payload_size = 5
# Uncomment one of the following lines to define the database to use.
# The default is "database/opencv-fr-database" (this uses the local file system).
# Local file system:
conn_str = "database/opencv-fr-database-new"
# AWS S3:
#conn_str = "s3://bucket/path"
# Uncomment and set the following lines if you are using AWS S3.
# aws_access_key_id = "my-access-key"
# aws_secret_access_key = "my-secret-key"
# aws_session_token = "my-session-token"
############################### Read consistency interval ###################################
# The interval at which to check for db updates from other instances. If more than this
# duration has passed since the last read, the read will check for updates from other
# instances.
# 0s (Strong consistency): The database checks for updates on every read.
# This provides the strongest consistency guarantees, ensuring that all instances see the
# latest committed data. However, it has the most overhead. This setting is suitable when
# consistency matters more than having high QPS.
# ns (Eventual consistency): The database checks for updates every n seconds. This
# provides eventual consistency, allowing for some lag between write and read operations.
# Changes made on one instance may not be immediately visible on another instance. This
# setting is suitable when having high QPS is more important than consistency.
# The default is "10s" which allows for new data inserted on one instance to be visible
# on other instances at most 10 seconds later. Change this value to suit your needs to
# balance consistency and performance.
conn_read_consistency_interval = "10s"
################################## Index retrieval tuning ###################################
# Indexing is recommended only when your collection is larger than 1,000,000 persons.
# When using an index, face search can miss some items. Having no index means the search
# will be slower but it will also be exhaustive and not miss any items. If you have more
# than a million items in a collection, you can create an index. When using an index,
# tuning the following will allow you to refine your search results according to your
# dataset distribution.
# The number of probes determines the distribution of vector space. While a higher number
# enhances search accuracy, it also results in slower performance. Typically, setting
# nprobes to cover 5–10% of the dataset proves effective in achieving high recall with
# minimal latency.
conn_n_probes_percentage = 10
# Refine the results by reading extra elements and re-ranking them in memory. A higher
# number makes the search more accurate but also slower. Please see:
# https://lancedb.github.io/lancedb/faq/#how-can-i-speed-up-data-inserts
conn_refine_factor = 50
# The time to wait before allowing another optimize or indexing job if one is currently
# running on a particular collection
conn_job_wait_time_sec = 3600
If you change the values in server-config.toml, you will need to stop the container and restart it again.
First list the containers:
> docker ps
After observing the value for CONTAINER ID, from the output of docker ps command, you can stop it using:
docker stop 336180357b1d
Once the docker is stopped, you can start it again using the process described in Starting the server.
