Langchain

import { PineconeClient } from "@pinecone-database/pinecone";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";
import { PineconeStore } from "langchain/vectorstores/pinecone";
import { ChatCompletion, SystemMessage, UserMessage } from 'ai-jsx/completion-components';
 
function getVectorStore() {
  const client = new PineconeClient();
  await client.init({
    apiKey: process.env.PINECONE_API_KEY,
    environment: process.env.PINECONE_ENVIRONMENT,
  });
  const pineconeIndex = client.Index(process.env.PINECONE_INDEX);
 
  const vectorStore = await PineconeStore.fromExistingIndex(
    new OpenAIEmbeddings(),
    { pineconeIndex }
  );
}
 
function MyDocsFunction({query}: {query: string}) {
  const docs = await getVectorStore().similaritySearch(query);
  return <ChatCommpletion>
    <SystemMessage>
      You are a knowledge base agent who answers questions based on these docs: {JSON.stringify(docs)}
    </SystemMessage>
    <UserMessage>{query}</UserMessage>
  </ChatCompletion>
}