RHOAIENG-37346:Refactor Guardrails for Safety JTBD

Author: skrthomas

assemblies/configuring-the-guardrails-orchestrator-service.adoc

@@ -1,45 +1,61 @@
 :_module-type: ASSEMBLY
 
 ifdef::context[:parent-context: {context}]
-[id="configuring-the-guardrails-orchestrator-service_{context}"]
-= Configuring the Guardrails Orchestrator service
+[id="enable-ai-safety-with-guardrails_{context}"]
+= Enabling AI safety with Guardrails
 
 The TrustyAI Guardrails Orchestrator service is a tool to invoke detections on text generation inputs and outputs, as well as standalone detections.
 
 It is underpinned by the open-source project link:https://github.com/foundation-model-stack/fms-guardrails-orchestrator[FMS-Guardrails Orchestrator] from IBM. You can deploy the Guardrails Orchestrator service through a Custom Resource Definition (CRD) that is managed by the TrustyAI Operator.
 
-You can use the following detectors with trustyai_fms:
+The following sections describe the Guardrails components, how to deploy them and provide example use cases of how to protect your AI applications using these tools:
 
+Deploy a Guardrails Orchestrator instance:: 
+The guardrails orchestrator is the main networking layer of the guardrails ecosystem, and “orchestrates” the network requests between the user, generative models, and detector servers. 
+
+Configure and use the built-in detectors:: 
+The Guardrails framework provides a set of “built-in” detectors out-of-the-box, that provides a number of simple detection algorithms. You can use the following detector with trustyai_fms:
++
 * *Regex Detectors*: Pattern-based content detection for structured rule enforcement. These are the built-in detectors in the Guardrails Orchestrator service. Learn more about the link:https://github.com/trustyai-explainability/guardrails-regex-detector[guardrails-regex-detector].
 
-* *Hugging Face Detectors*: Compatible with most Hugging Face `AutoModelForSequenceClassification` models, such as `granite-guardian-hap-38m` or `deberta-v3-base-prompt-injection-v2`. Learn more about the detector algorithms for the link:https://github.com/trustyai-explainability/guardrails-detectors[FMS Guardrails Orchestrator].
 
+Use Hugging Face models as detectors in Guardrails Orchestrator::
+Any text classification model from link:https://huggingface.co/ibm-granite/granite-guardian-hap-38m[Huggingface] can be used as a detector model within the Guardrails ecosystem.
++
+* *Hugging Face Detectors*: Compatible with most Hugging Face `AutoModelForSequenceClassification` models, such as `granite-guardian-hap-38m` or `deberta-v3-base-prompt-injection-v2`. Learn more about the detector algorithms for the link:https://github.com/trustyai-explainability/guardrails-detectors[FMS Guardrails Orchestrator].
 * *vLLM Detector Adapter*: Content detection compatible with Hugging Face `AutoModelForCausalLM` models, for example `ibm-granite/granite-guardian-3.1-2b`. Learn more about link:https://github.com/foundation-model-stack/vllm-detector-adapter[vllm-detector-adapter].
 
-The following sections describe how to deploy Guardrails Orchestrator and provide example use cases:
+Configure and use the guardrails gateway:: 
+The optional Guardrails Gateway lets you create preset guardrailing pipelines that can be interacted with via /chat/completions endpoints.
 
-* Deploy a Guardrails Orchestrator instance
-* Monitor user-inputs to your LLM
-* Configure and use the built-in detectors
-* Configure and use the guardrails gateway
-* Enable the OpenTelemetry exporter for metrics and tracing
-* Use Hugging Face models as detectors in Guardrails Orchestrator
+*Monitor user-inputs to your LLM* 
+Enable a safer LLM by filtering hateful, profane, or toxic inputs.
 
+*Enable the OpenTelemetry exporter for metrics and tracing* 
+Provide observability for the security and governance mechanisms of AI applications.
 
+== Deploying and Configuring Guardrails components
+Set up the Orchestrator, Detectors, and Gateway. 
 
 include::modules/deploying-the-guardrails-orchestrator-service.adoc[leveloffset=+1]
 include::modules/auto-configuring-guardrails.adoc[leveloffset=+1]
 include::modules/guardrails-orchestrator-parameters.adoc[leveloffset=+1]
-include::modules/guardrails-orchestrator-hap-scenario.adoc[leveloffset=+1]
 include::modules/guardrails-detectors.adoc[leveloffset=+1]
+include::modules/configuring-the-built-in-detector-and-guardrails-gateway.adoc[leveloffset=+2]
 include::modules/configuring-the-guardrails-detector-hugging-face-serving-runtime.adoc[leveloffset=+2]
-include::modules/using-a-hugging-face-prompt-injection-detector-with-the-guardrails-orchestrator.adoc[leveloffset=+2]
 include::modules/using-hugging-face-models-with-guardrails-orchestrator.adoc[leveloffset=+2]
-include::modules/configuring-the-built-in-detector-and-guardrails-gateway.adoc[leveloffset=+2]
-include::modules/sending-requests-to-the-regex-detector.adoc[leveloffset=+2]
-include::modules/guardrails-orchestrator-querying-using-guardrails-gateway.adoc[leveloffset=+2]
 include::modules/configuring-the-opentelemetry-exporter.adoc[leveloffset=+1]
 
+== Using Guardrails for AI Safety
+Use the Guardrails tools to ensure the safety and security of your generative AI applications in production.
+
+include::modules/guardrails-orchestrator-hap-scenario.adoc[leveloffset=+1]
+include::modules/using-a-hugging-face-prompt-injection-detector-with-the-guardrails-orchestrator.adoc[leveloffset=+1]
+include::modules/filtering-flagged-content-by-sending-requests-to-the-regex-detector.adoc[leveloffset=+2]
+include::modules/enforcing-configured-safety-pipelines-for-llm-inference-using-guardrails-gateway.adoc[leveloffset=+1]
+
+
+
 
 ifdef::parent-context[:context: {parent-context}]
 ifndef::parent-context[:!context:]

modules/guardrails-orchestrator-querying-using-guardrails-gateway.adoc renamed to modules/enforcing-configured-safety-pipelines-for-llm-inference-using-guardrails-gateway.adoc

@@ -1,11 +1,11 @@
 :_module-type: PROCEDURE
 
 ifdef::context[:parent-context: {context}]
-[id="querying-using-guardrails-gateway_{context}"]
-= Querying using guardrails gateway
+[id="enforcing-configured-safety-pipelines-for-LLM-inference-using-guardrails-gateway_{context}"]
+= Enforcing configured safety pipelines for LLM inference by using Guardrails Gateway
 [role='_abstract']
 
-Guardrails gateway is a sidecar image that you can use with the `GuardrailsOrchestrator` service. It provides the OpenAI `v1/chat/completions` API and allows you to specify which detectors and endpoints you want to use to access the service. 
+The Guardrails Gateway is a sidecar image that you can use with the `GuardrailsOrchestrator` service. When running your AI application in production, you can use the Guardrails Gateway to enforce a consistent, custom set of safety policies using a preset guardrail pipeline. For example, you can create a preset guardrail pipeline for PII detection and language moderation. You can then send chat completions requests to the preset pipeline endpoints without needing to alter my existing inference API calls. It provides the OpenAI `v1/chat/completions` API and allows you to specify which detectors and endpoints you want to use to access the service. 
 
 .Prerequisites
 * You have configured the guardrails gateway image.

modules/sending-requests-to-the-regex-detector.adoc renamed to modules/filtering-flagged-content-by-sending-requests-to-the-regex-detector.adoc

@@ -1,8 +1,8 @@
 :_module-type: PROCEDURE
 
 ifdef::context[:parent-context: {context}]
-[id="sending-requests-to-the-regex-detector_{context}"]
-= Sending requests to the regex detector
+[id="filtering-flagged-content-by-sending-requests-to-the-regex-detector_{context}"]
+= Filtering flagged content by sending requests to the regex detector
 [role='_abstract']
 
 You can use the Guardrails Orchestrator API to send requests to the regex detector. The regex detector filters conversations by flagging content that matches specified regular expression patterns. 

modules/using-a-hugging-face-prompt-injection-detector-with-the-guardrails-orchestrator.adoc

@@ -2,7 +2,7 @@
 
 ifdef::context[:parent-context: {context}]
 [id="using-a-hugging-face-prompt-injection-detector-with-guardrails-orchestrator_{context}"]
-= Using a Hugging Face Prompt Injection detector with the Guardrails Orchestrator
+= Preventing Prompt Injection by using a Hugging Face Prompt Injection detector
 
 [role='_abstract']