diff --git a/apps/simple/pinecone-vector-store/README.md b/apps/simple/pinecone-vector-store/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..b0576bc26c4a6a8b4cff0a74150190f48acffe6e
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+# Pinecone Vector Store
+
+There are two scripts available here: load-docs.ts and query.ts
+
+## Prerequisites
+
+You'll need a Pinecone account, project, and index. Pinecone does not allow automatic creation of indexes on the free plan,
+so this vector store does not check and create the index (unlike, e.g., the PGVectorStore)
+
+Set the **PINECONE_API_KEY** and **PINECONE_ENVIRONMENT** environment variables to match your specific values. You will likely also need to set **PINECONE_INDEX_NAME**, unless your
+index is the default value "llama".
+
+You'll also need a value for OPENAI_API_KEY in your environment.
+
+## 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 pinecone-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.
+
+**NOTE**: Sending text chunks as part of the Pinecone metadata means that upsert API calls can get arbitrarily large. Set the **PINECONE_CHUNK_SIZE** environment variable to a smaller value if the load script fails
+
+## RAG Querying
+
+To query using the resulting vector store:
+
+> `npx ts-node pinecone-vector-store/query.ts`
+
+The script will prompt for a question, then process and present the answer using the PineconeVectorStore data and your OpenAI API key. It will continue to prompt until you enter `q`, `quit` or `exit` as the next query.
diff --git a/apps/simple/pinecone-vector-store/load-docs.ts b/apps/simple/pinecone-vector-store/load-docs.ts
new file mode 100755
index 0000000000000000000000000000000000000000..f3ebb3dd360cd03877ae0017cf1b6a3711b55884
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+++ b/apps/simple/pinecone-vector-store/load-docs.ts
@@ -0,0 +1,66 @@
+// load-docs.ts
+import fs from "fs/promises";
+import {
+ SimpleDirectoryReader,
+ storageContextFromDefaults,
+ VectorStoreIndex,
+} from "llamaindex";
+import { PineconeVectorStore } from "../../../packages/core/src/storage/vectorStore/PineconeVectorStore";
+
+async function getSourceFilenames(sourceDir: string) {
+ return await fs
+ .readdir(sourceDir)
+ .then((fileNames) => fileNames.map((file) => sourceDir + "/" + file));
+}
+
+function callback(
+ category: string,
+ name: string,
+ status: any,
+ message: string = "",
+): boolean {
+ console.log(category, name, status, message);
+ return true;
+}
+
+async function main(args: any) {
+ const sourceDir: string = args.length > 2 ? args[2] : "../data";
+
+ console.log(`Finding documents in ${sourceDir}`);
+ const fileList = await getSourceFilenames(sourceDir);
+ const count = fileList.length;
+ console.log(`Found ${count} files`);
+
+ console.log(`Importing contents from ${count} files in ${sourceDir}`);
+ 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 pcvs = new PineconeVectorStore();
+
+ const ctx = await storageContextFromDefaults({ vectorStore: pcvs });
+
+ 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 PineconeVectorStore connection failed, make sure to set env vars for PINECONE_API_KEY and PINECONE_ENVIRONMENT. If the upserts failed, try setting PINECONE_CHUNK_SIZE to limit the content sent per chunk",
+ );
+ process.exit(1);
+ }
+
+ console.log(
+ "Done. Try running query.ts to ask questions against the imported embeddings.",
+ );
+ process.exit(0);
+}
+
+main(process.argv).catch((err) => console.error(err));
diff --git a/apps/simple/pinecone-vector-store/query.ts b/apps/simple/pinecone-vector-store/query.ts
new file mode 100755
index 0000000000000000000000000000000000000000..513f2fc7151be1c25f8836db99995e87d0602e0c
--- /dev/null
+++ b/apps/simple/pinecone-vector-store/query.ts
@@ -0,0 +1,65 @@
+import { VectorStoreIndex } from "../../../packages/core/src/indices/vectorStore/VectorStoreIndex";
+import { serviceContextFromDefaults } from "../../../packages/core/src/ServiceContext";
+import { PineconeVectorStore } from "../../../packages/core/src/storage/vectorStore/PineconeVectorStore";
+
+async function main() {
+ const readline = require("readline").createInterface({
+ input: process.stdin,
+ output: process.stdout,
+ });
+
+ try {
+ const pcvs = new PineconeVectorStore();
+
+ const ctx = serviceContextFromDefaults();
+ const index = await VectorStoreIndex.fromVectorStore(pcvs, ctx);
+
+ // Query the index
+ const queryEngine = await index.asQueryEngine();
+
+ let question = "";
+ while (!isQuit(question)) {
+ question = await getUserInput(readline);
+
+ if (isQuit(question)) {
+ readline.close();
+ process.exit(0);
+ }
+
+ try {
+ const answer = await queryEngine.query(question);
+ console.log(answer.response);
+ } catch (error) {
+ console.error("Error:", error);
+ }
+ }
+ } catch (err) {
+ console.error(err);
+ console.log(
+ "If your PineconeVectorStore connection failed, make sure to set env vars for PINECONE_API_KEY and PINECONE_ENVIRONMENT.",
+ );
+ process.exit(1);
+ }
+}
+
+function isQuit(question: string) {
+ return ["q", "quit", "exit"].includes(question.trim().toLowerCase());
+}
+
+// Function to get user input as a promise
+function getUserInput(readline: any): Promise<string> {
+ return new Promise((resolve) => {
+ readline.question(
+ "What would you like to know?\n>",
+ (userInput: string) => {
+ resolve(userInput);
+ },
+ );
+ });
+}
+
+main()
+ .catch(console.error)
+ .finally(() => {
+ process.exit(1);
+ });