diff --git a/apps/simple/pg-vector-store/README.md b/apps/simple/pg-vector-store/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..7bcf6a854430165398eafdb80159d769645e4715
--- /dev/null
+++ b/apps/simple/pg-vector-store/README.md
@@ -0,0 +1,28 @@
+# Postgres Vector Store
+There are two scripts available here: load-docs.ts and query.ts
+
+## Prerequisites
+You'll need a postgres database instance against which to run these scripts.  A simple docker command would look like this:
+
+>`docker run -d --rm --name vector-db -p 5432:5432 -e "POSTGRES_HOST_AUTH_METHOD=trust" ankane/pgvector`
+
+Set the PGHOST and PGUSER (and PGPASSWORD) environment variables to match your database setup.
+
+You'll also need a value for OPENAI_API_KEY in your environment.
+
+**NOTE:** Using `--rm` in the example docker command above means that the vector store will be deleted every time the container is stopped.  For production purposes, use a volume to ensure persistence across restarts.
+
+## Setup and Loading Docs
+Read and follow the instructions in the README.md file located one directory up to make sure your JS/TS dependencies are set up.  The commands listed below are also run from that parent directory.
+
+To import documents and save the embedding vectors to your database:
+>`npx ts-node pg-vector-store/load-docs.ts data`
+
+where data is the directory containing your input files.  Using the *data* directory in the example above will read all of the files in that directory using the llamaindexTS default readers for each file type.
+
+## RAG Querying
+To query using the resulting vector store:
+
+>`npx ts-node pg-vector-store/query.ts`
+
+The script will prompt for a question, then process and present the answer using the PGVectorStore data and your OpenAI API key.  It will continue to prompt until you enter `q`, `quit` or `exit` as the next query.
\ No newline at end of file
diff --git a/apps/simple/pg-vector-store/load-docs.ts b/apps/simple/pg-vector-store/load-docs.ts
index 7baca34b78becb6cada2a16e2cac282709b6adbd..2a5eb863b3035287549d1faa08a94170b13cd9f1 100755
--- a/apps/simple/pg-vector-store/load-docs.ts
+++ b/apps/simple/pg-vector-store/load-docs.ts
@@ -1,11 +1,7 @@
 // load-docs.ts
 import fs from 'fs/promises';
 import { SimpleDirectoryReader, storageContextFromDefaults, VectorStoreIndex } from 'llamaindex';
-// import { VectorStoreIndex } from "../../../packages/core/src/indices/vectorStore/VectorStoreIndex";
-// import { SimpleDirectoryReader } from "../../../packages/core/src/readers/SimpleDirectoryReader";
 import { PGVectorStore } from "../../../packages/core/src/storage/vectorStore/PGVectorStore";
-// import { storageContextFromDefaults } from '../../../packages/core/src/storage';
-
 
 async function getSourceFilenames(sourceDir: string) {
     return await fs.readdir(sourceDir)
@@ -25,7 +21,6 @@ async function main(args: any) {
 
     const sourceDir: string = args.length > 2 ? args[2] : '../data';
 
-    // Create Document object with essay
     console.log(`Finding documents in ${sourceDir}`);
     const fileList = await getSourceFilenames(sourceDir);
     const count = fileList.length;
@@ -35,24 +30,23 @@ async function main(args: any) {
     var fileName = '';
     try {
 
-      // Passing callback fn to the ctor here
-      // will enable looging to console.
-      // See callback fn, defined above.
-      const rdr = new SimpleDirectoryReader(callback);
-      const docs = await rdr.loadData({ directoryPath: sourceDir });
-
-      const pgvs = new PGVectorStore();
-      pgvs.setCollection(sourceDir);
-      pgvs.clearCollection();
+        // Passing callback fn to the ctor here
+        // will enable looging to console.
+        // See callback fn, defined above.
+        const rdr = new SimpleDirectoryReader(callback);
+        const docs = await rdr.loadData({ directoryPath: sourceDir });
 
-      const ctx = await storageContextFromDefaults(
-          { vectorStore: pgvs }
-      );
+        const pgvs = new PGVectorStore();
+        pgvs.setCollection(sourceDir);
+        pgvs.clearCollection();
 
-      console.debug('  - creating vector store');
-      const index = await VectorStoreIndex.fromDocuments(docs, { storageContext: ctx });
-      console.debug('  - done.');
+        const ctx = await storageContextFromDefaults(
+            { vectorStore: pgvs }
+        );
 
+        console.debug('  - creating vector store');
+        const index = await VectorStoreIndex.fromDocuments(docs, { storageContext: ctx });
+        console.debug('  - done.');
     } catch (err) {
         console.error(fileName, err);
         console.log("If your PGVectorStore init failed, make sure to set env vars for PGUSER or USER, PGHOST, PGPORT and PGPASSWORD as needed.");