Improve docs. (#1096)

docs/use-cases/chatbots.mdx

@@ -1,5 +1,5 @@
 ---
-title: 'Chatbots'
+title: '🤖 Chatbots'
 ---
 
 Chatbots, especially those powered by Large Language Models (LLMs), have a wide range of use cases, significantly enhancing various aspects of business, education, and personal assistance. Here are some key applications:

docs/use-cases/introduction.mdx

@@ -0,0 +1,11 @@
+---
+title: 🧱 Introduction
+---
+
+## Overview
+
+You can use embedchain to create the following usecases:
+
+* [Chatbots](/use-cases/chatbots)
+* [Question Answering](/use-cases/question-answering)
+* [Semantic Search](/use-cases/semantic-search)

docs/use-cases/question-answering.mdx

@@ -1,5 +1,5 @@
 ---
-title: 'Question Answering'
+title: '❓ Question Answering'
 ---
 
 Utilizing large language models (LLMs) for question answering is a transformative application, bringing significant benefits to various real-world situations. Embedchain extensively supports tasks related to question answering, including summarization, content creation, language translation, and data analysis. The versatility of question answering with LLMs enables solutions for numerous practical applications such as:

docs/use-cases/semantic-search.mdx

@@ -1,3 +1,7 @@
+---
+title: '🔍 Semantic Search'
+---
+
 Semantic searching, which involves understanding the intent and contextual meaning behind search queries, is yet another popular use-case of RAG. It has several popular use cases across various domains:
 
 - **Information Retrieval**: Enhances search accuracy in databases and websites