How to configure GreatAI

GreatAI aims to provide reasonable defaults wherever possible. The current configuration is always prominently displayed (and updated) on the dashboard and in the command-line start-up banner.

Using [great_ai.configure][]

You can override any of the default settings by calling [great_ai.configure][]. If you don't call configure, the default settings are applied on the first call to most great-ai functions.

!!! warning You must call [great_ai.configure][] before calling (or decorating with) any other great-ai function. However, importing other functions before calling [great_ai.configure][] is permitted.

from great_ai import configure, RouteConfig
import logging

configure(
    version='1.0.0',
    log_level=logging.INFO,
    seed=2,
    should_log_exception_stack=False, 
    prediction_cache_size=0,  #(1)
    disable_se4ml_banner=True,
    dashboard_table_size=200,
    route_config=RouteConfig(  #(2)
        feedback_endpoints_enabled=False,
        dashboard_enabled=False
    )
)

Completely disable caching.
The unspecified routes are enabled by default.

Using remote storage

The only aspect that cannot be automated is choosing the backing storage for the database and file storage.

Right now, you have 3 options for storing the models and large datasets: [LargeFileLocal][great_ai.large_file.LargeFileLocal], [LargeFileMongo][great_ai.large_file.LargeFileMongo], and [LargeFileS3][great_ai.large_file.LargeFileS3].

Without explicit configuration, [LargeFileLocal][great_ai.large_file.LargeFileLocal] is selected by default. This one still version-controls your files but it only stores them in a local path (which of course can be a remote volume attached by NFS{ target=_blank }, HDFS{ target=_blank }, etc.).

!!! important If your working directory contains a mongo.ini or s3.ini file, an attempt is made to auto-configure [LargeFileMongo][great_ai.large_file.LargeFileMongo] or [LargeFileS3][great_ai.large_file.LargeFileS3] respectively.

To use [LargeFileMongo][great_ai.large_file.LargeFileMongo] or [LargeFileS3][great_ai.large_file.LargeFileS3] explicitly, configure them before calling any other great-ai function.

S3-compatible

aws_region_name = eu-west-2
aws_access_key_id = MY_AWS_ACCESS_KEY  # ENV:MY_AWS_ACCESS_KEY would also work
aws_secret_access_key = MY_AWS_SECRET_KEY
large_files_bucket_name = bucket-for-models

from great_ai.large_file import LargeFileS3
from great_ai import save_model

LargeFileS3.configure_credentials_from_file('s3.ini') #(1)

model = [4, 3]
save_model(model, 'my-model')

This line isn't strictly necessary because if s3.ini (or mongo.ini) is available in the current working directory, they are automatically used to configure their respective LargeFile implementations/databases.

??? note "Departing from AWS" With the aws_endpoint_url argument, it is possible to use any other S3-compatible service such as Backblaze{ target=_blank }. In that case, it would be aws_endpoint_url=https://s3.us-west-002.backblazeb2.com.

GridFS

GridFS{ target=_blank } specifies how to store files in MongoDB. The official MongoDB server and many compatible implementations support it.

MONGO_CONNECTION_STRING=mongodb://localhost:27017  # this is the default value
# if `MONGO_CONNECTION_STRING` is specified, this default is overridden
MONGO_CONNECTION_STRING=ENV:MONGO_CONNECTION_STRING

MONGO_DATABASE=my-database  # it is automatically created if it doesn't exist

from great_ai.large_file import LargeFileMongo
from great_ai import save_model

LargeFileMongo.configure_credentials_from_file('mongo.ini')

model = [4, 3]
save_model(model, 'my-model')

!!! note "Simplifying config files" You can combine mongo.ini or s3.ini with your application's config file because the unneeded keys are ignored by the configure_credentials_from_file method.

Using a database

By default, a thread-safe version of TinyDB{ target=_blank } is utilised for saving the prediction traces into a local file. Unfortunately, for most production needs, this method is not suitable.

MongoDB

Currently, only MongoDB is supported as a production-ready TracingDatabase. In order to use it, you have to either place a file named mongo.ini in your working directory or explicitly call either [MongoDbDriver.configure_credentials_from_file][great_ai.MongoDbDriver] or [MongoDbDriver.configure_credentials][great_ai.MongoDbDriver.configure_credentials].

4.9 KiB Raw Blame History