Update README.md

docs/README.md

@@ -1,3 +1,15 @@
-Docs for setting up a demo cluster can be found under the demo directory
+Docs for setting up a demo cluster can be found ![here](https://github.com/opendatahub-io/caikit-tgis-serving/tree/main/demo/kserve)
 
-The cluster was set up using a single GPU, but could be set up in other configurations
+Caikit-tgis-serving is a combined image that allows users to perform LLM inference
+
+The architecture is shown here:
+
+![KServe+Knative+Istio+Caikit_TGIS Diagram](https://github.com/opendatahub-io/caikit-tgis-serving/assets/8479010/7009b95d-0f6f-4f18-b0e6-355f360a5ad1)
+
+There are several components:
+TGIS: Serving backend, loads the models and provides the inference engine
+Caikit: Wrapper layer, handles the lifecycle of the TGIS process, provides the inference endpoints, and has modules to handle different model types
+Caikit-nlp: Caikit module that handles NLP style models
+KServe: Orchestrates model serving for all types of models, servingruntimes implement loading given types of model servers. KServe handles the lifecycle of the deployment object, storage access, networking setup, etc
+Service Mesh (istio): Service mesh networking layer, manages traffic flows, enforces access policies, etc
+Serverless (knative): Allows for serverless deployments of models