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added docu for installing default models (#393)
* added docu for installing default models Co-authored-by: Christoph Kuhnke <github@kuhnke.net>
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.github/workflows/saas-integration-tests.yml

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required: true
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jobs:
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run-saas-integration-tests:
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permissions:
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contents: read
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continue-on-error: true # Allow this job to fail
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strategy:
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fail-fast: false
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matrix:
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- name: Run test saas_integration_tests
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run: poetry run -- nox -s saas_integration_tests
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env: # Set the secret as an input
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env:
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DOCKER_USER: ${{ secrets.DOCKER_USER }}
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DOCKER_PASSWD: ${{ secrets.DOCKER_PASSWORD }}
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SAAS_HOST: ${{ secrets.INTEGRATION_TEAM_SAAS_STAGING_HOST }}
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SAAS_ACCOUNT_ID: ${{ secrets.INTEGRATION_TEAM_SAAS_STAGING_ACCOUNT_ID }}
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SAAS_PAT: ${{ secrets.INTEGRATION_TEAM_SAAS_STAGING_PAT }}
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handle-test-result:
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needs: [run-saas-integration-tests]
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runs-on: ubuntu-latest
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if: always() # Run regardless of whether previous job failed
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steps:
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- name: Check test result
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run: |
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echo "Tests passed!"

doc/changes/unreleased.md

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* #204: Split the user_guide into multiple files
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* #253, #341, #342: Fixed links and improved parameter description in user guide
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* #363: Added documentation for installing default models.
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## Refactorings
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doc/user_guide/manage_models.md

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### Table of Contents
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* [Store Models in BucketFS](#store-models-in-bucketfs)
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* [Install the Default Models](#install-the-default-models)
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* [Manually Store Models in BucketFS](#manually-store-models-in-bucketfs)
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* [Model Downloader UDF](#model-downloader-udf)
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* [Name Server](#name-server)
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* [Running the UDF](#running-the-udf)
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* [Delete model via a Python Function](#delete-model-via-a-python-function)
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* [List Models UDF](#list-models-udf)
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## Install the Default Models
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Some of our UDF's use preselected models, so you do not need to
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configure the UDF's in order to run them.
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However, you do need to install these default models before using the UDf's.
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We provide two options for you to install these default models. You can use the
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`install_default_models`- command
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or the `INSTALL_AI_DEFAULT_MODEL_UDF`.
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Both versions will install all needed default models in the BucketFS.
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They will use a predefined BucketFS location to install the models into.
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You can call the `INSTALL_AI_DEFAULT_MODEL_UDF` like this:
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```sql
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SELECT INSTALL_AI_DEFAULT_MODEL_UDF()
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```
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It will return a table with a `model_path_in_udfs` column and
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a `model_path_of_tar_file_in_bucketfs` column.
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Or you can call the `install_default_models`- command:
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```shell
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python -m exasol_transformers_extension.install_default_models <options>
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```
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For information about the available options common to all Exasol extensions,
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please refer to the [documentation][pec-user-guide] in the Exasol Python Extension Common package.
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## Store Models in BucketFS
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## Manually Store Models in BucketFS
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Before you can use pre-trained models, the models must be stored in the BucketFS.
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doc/user_guide/user_guide.md

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These UDFs call a model stored in the BucketFS and use it to make predictions on the given input data.
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We have selected a curated list of models, which are used in our UDFs.
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You can install these models using the `install_default_models`- command
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or the `INSTALL_AI_DEFAULT_MODEL_UDF`.
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These UDFs require only minimal configuation to use:
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