Documentation fixes

search/retrieval-augmented-generation-llm.ipynb

@@ -11,9 +11,9 @@
     "tags": []
    },
    "source": [
-    "# Retrieval-augmented Generation (RAG) Using LLMs \n",
+    "# Retrieval-augmented Generation (RAG)\n",
     "\n",
-    "This notebook provides several prototypes of a Retrieval-Augmented Generation (RAG) system. \n",
+    "This notebook provides several prototypes of a Retrieval-Augmented Generation (RAG) system. We use product data analytics use cases as a running example.\n",
     "\n",
     "### Use Case\n",
     "We have a large collection of documents and want to use LLM to summarize these documents, answer standalone questions based on the document content, or answer questions in a conversational mode. Examples include a sales assistant that answers customers' questions about company's products, coding assistant that answers developers' questions about the codebase, and legal assistant that answers questions about regulations.   \n",