Add Python TrustyAI library and update documentation

trustyai-explainability · Dec 11, 2023 · 7b584d4 · 7b584d4
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diff --git a/docs/modules/ROOT/pages/python-trustyai.adoc b/docs/modules/ROOT/pages/python-trustyai.adoc
@@ -1 +1,17 @@
-= Python TrustyAI
+= Python TrustyAI
+
+Python TrustyAI is a Python library for explainable AI. It is a wrapper around the xref:trustyai-core.adoc[TrustyAI core] explainability library.
+
+== Setup
+
+The library is available on PyPi and can be installed with pip.
+
+```bash
+pip install trustyai
+```
+
+To install additional experimental features, the following command can be used:
+
+```bash
+pip install trustyai[extras]
+```
diff --git a/docs/modules/ROOT/pages/trustyai-core.adoc b/docs/modules/ROOT/pages/trustyai-core.adoc
@@ -1 +1,3 @@
-= TrustyAI core
+= TrustyAI core
+
+The TrustyAI core is a Java library that provides the core functionality of the TrustyAI framework. It is used by the xref:trustyai-service.adoc[TrustyAI service] and the xref:python-trustyai.adoc[Python TrustyAI library].
diff --git a/docs/modules/ROOT/pages/trustyai-operator.adoc b/docs/modules/ROOT/pages/trustyai-operator.adoc
@@ -1 +1,5 @@
-= TrustyAI operator
+= TrustyAI operator
+
+The TrustyAI Kubernetes Operator aims at simplifying the deployment and management of the xref:trustyai-service.adoc[TrustyAI service] on Kubernetes and OpenShift clusters by watching for custom resources of kind `TrustyAIService` in the `trustyai.opendatahub.io` API group and manages deployments, services, and optionally, routes and `ServiceMonitors` corresponding to these resources.
+
+The operator ensures the service is properly configured, is discoverable by Prometheus for metrics scraping (on both Kubernetes and OpenShift), and is accessible via a `Route` on OpenShift.
diff --git a/docs/modules/ROOT/pages/trustyai-service.adoc b/docs/modules/ROOT/pages/trustyai-service.adoc
@@ -1,5 +1,15 @@
 = TrustyAI service
 
+The TrustyAI service is a REST service that provides the integration between XAI and metrics algorithms provided by the xref:trustyai-core.adoc[TrustyAI core] and external models.
+
+[NOTE]
+====
+Although it can be used as a standalone service, it is designed to be used as part of Open Data Hub, deployed in OpenShift/Kubernetes and managed by the xref:trustyai-operator.adoc[TrustyAI operator].
+====
+
+The main functionality of the service is to provide a REST API to calculate metrics and explainability. The service can consume model data (inputs and outputs) for metrics calculation either via a consumer endpoint, or cloud events.
+
+To provide explanations, the service performs inferences to a ModelMesh/KServe-deployed model using gRPC.
 
 == External endpoints