diff --git a/README.md b/README.md
index d15d55e..e20c783 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,11 @@
 # Pinecone + OpenAI Scala Client - Demo/Seed Project
-[![version](https://img.shields.io/badge/version-0.0.1-green.svg)](https://cequence.io) [![License](https://img.shields.io/badge/License-MIT-lightgrey.svg)](https://opensource.org/licenses/MIT) [![Twitter Follow](https://img.shields.io/twitter/follow/0xbnd?style=social)](https://twitter.com/0xbnd)
+[![version](https://img.shields.io/badge/version-0.1.0-green.svg)](https://cequence.io) [![License](https://img.shields.io/badge/License-MIT-lightgrey.svg)](https://opensource.org/licenses/MIT) [![Twitter Follow](https://img.shields.io/twitter/follow/0xbnd?style=social)](https://twitter.com/0xbnd)
+
+---
+
+### This project is archived! It has been moved to the main Pinecone Scala Client repository as a module [openai-examples](https://github.com/cequence-io/pinecone-scala/tree/master/openai-examples)
+
+---
 
 This is a ready-to-fork, example/demo project demonstrating how to use [Pinecone](https://pinecone.io) vector database with [OpenAI](https://openai.com) embeddings in Scala using [Pinecone Scala Client](https://github.com/cequence-io/pinecone-scala) and [OpenAI Scala Client](https://github.com/cequence-io/openai-scala-client).
 
diff --git a/build.sbt b/build.sbt
index 43864c8..2a0d09e 100644
--- a/build.sbt
+++ b/build.sbt
@@ -2,7 +2,7 @@ organization := "io.cequence"
 
 name := "pinecone-openai-scala-demo"
 
-version := "0.0.1"
+version := "0.1.0"
 
 // Supported Scala versions
 val scala212 = "2.12.15"
diff --git a/src/main/scala/io/cequence/pineconeopenai/demo/PineconeOpenAIDemo.scala b/src/main/scala/io/cequence/pineconeopenai/demo/PineconeOpenAIDemo.scala
index 9ebd36d..7eb55c7 100644
--- a/src/main/scala/io/cequence/pineconeopenai/demo/PineconeOpenAIDemo.scala
+++ b/src/main/scala/io/cequence/pineconeopenai/demo/PineconeOpenAIDemo.scala
@@ -74,7 +74,7 @@ object PineconeOpenAIDemo extends PineconeOpenAIDemoApp {
       // create a service for a given index name
       pineconeVectorService <- createPineconeVectorService(indexName)
 
-      // take the first 1000 entries and extract text, result is an iterator
+      // take the first 1000 entries and extract the text. the result is an iterator
       trecTextsIterator = scala.io.Source.fromFile("src/main/resources/trec-train.json")
         .getLines()
         .take(1000)