.. _cli_walkthroughs:

CLI 
=======================================

These walkthroughs illustrate how to test your ML models using the different RIME modalities. Each walkthrough provides steps to run the examples using bundled sample data or your own models and data.

Ad-hoc model testing can be performed with the RIME Python Package, which exposes both a command-line interface and python modules.

Both ad-hoc model testing and programmatic interactions can be performed with the RIME SDK, which exposes a REST client that can be integrated in your existing ML pipelines. 

Tabular
---------------------------------------

The below will guide you through the two main RIME user flows: AI Stress Testing and AI Firewall Continuous Tests.

.. toctree::
   :maxdepth: 2

   cli/rime_ai_stress_testing.md
   cli/rime_ai_firewall_continuous_tests.md
   cli/specify_model.md

Next, the following tutorial will guide you through setting up the AI Firewall in a realtime setting:

.. toctree::
   :maxdepth: 2

   cli/rime_firewall_realtime.md

NLP
---------------------------------------

To learn how to use RIME to test NLP models, please reference the following tutorials:

.. toctree::
   :maxdepth: 2

   cli/rime_ai_stress_testing_nlp.md
   cli/rime_ai_firewall_continuous_tests_nlp.md
   cli/specify_model_nlp.md

Next, the following tutorial will guide you through setting up the AI Firewall for NLP in a realtime setting:

.. toctree::
   :maxdepth: 2

   cli/rime_firewall_realtime_nlp.md


Computer Vision
---------------------------------------

To learn how to use RIME to test CV models, please reference the following tutorials:

.. toctree::
   :maxdepth: 2

   cli/rime_ai_stress_testing_cv.md
   cli/rime_ai_firewall_continuous_tests_cv.md
   cli/specify_model_cv.md
   cli/specify_image_loading.md

Next, the following tutorial will guide you through setting up the AI Firewall for CV in a realtime setting:

.. toctree::
   :maxdepth: 2

   cli/rime_firewall_realtime_cv.md