diff --git a/apps/web/app/(dash)/chat/chatWindow.tsx b/apps/web/app/(dash)/chat/chatWindow.tsx
index b631c835..bb6a0be1 100644
--- a/apps/web/app/(dash)/chat/chatWindow.tsx
+++ b/apps/web/app/(dash)/chat/chatWindow.tsx
@@ -201,6 +201,7 @@ function ChatWindow({
+
))}
diff --git a/apps/web/app/(dash)/chat/page.tsx b/apps/web/app/(dash)/chat/page.tsx
index fd4de826..f98c761f 100644
--- a/apps/web/app/(dash)/chat/page.tsx
+++ b/apps/web/app/(dash)/chat/page.tsx
@@ -1,5 +1,6 @@
import ChatWindow from "./chatWindow";
import { chatSearchParamsCache } from "../../helpers/lib/searchParams";
+import { ChevronDownIcon, ClipboardIcon, SpeakerWaveIcon } from '@heroicons/react/24/outline'
// @ts-expect-error
await import("katex/dist/katex.min.css");
@@ -12,7 +13,85 @@ function Page({
console.log(spaces);
- return
What is RAG? - Retrieval-Augmented Generation Explained - AWS
++ Retrieval-Augmented Generation is crucial because it combines the strengths of retrieval-based methods, ensuring relevance and accuracy, with generation-based models, enabling creativity and flexibility. By integrating retrieval mechanisms, it addresses data sparsity issues, improves content relevance, offers fine-tuned control over output, handles ambiguity, and allows for continual learning, making it highly adaptable and effective across various natural language processing tasks and domains. +
+ + {/* response actions */} +