parts for clarity

jac/support/jac-lang.org/docs/learn/tutorial/1_setting-up-jac-cloud.md

@@ -1,4 +1,4 @@
-# Setting Up Your Jac Cloud Application
+# Setting Up Your Jac Cloud Application (Part 1/3)
 Jac Cloud is a jaclang plugin that bootstraps your jac application into a running web server. It allows you to serve your jac code as a REST API and interact with it from any client that can make HTTP requests. To set up Jac Cloud, you need to install the `jaclang` and `jac-cloud` python package using pip:
 
 ```bash

jac/support/jac-lang.org/docs/learn/tutorial/2_building-a-rag-chatbot.md

@@ -1,4 +1,4 @@
-# Building a RAG Chatbot with Jac Cloud and Streamlit
+# Building a RAG Chatbot with Jac Cloud and Streamlit (Part 2/3)
 Now that we have a jac application served up, let's build a simple chatbot using Retrieval Augmented Generation (RAG) with Jac Cloud and Streamlit as our frontend interface.
 
 ### Preparation / Installation

jac/support/jac-lang.org/docs/learn/tutorial/3_rag-dialogue-routing-chatbot.md

@@ -1,4 +1,4 @@
-# RAG + Dialogue Routing Chatbot
+# RAG + Dialogue Routing Chatbot (Part 3/3)
 Now that you have built a RAG chatbot, you can enhance it by adding dialogue routing capabilities. Dialogue routing is the process of directing the conversation to the appropriate dialogue model based on the user's input.
 
 In some cases, the user query that comes in may not be suitable for the RAG model, and it may be better to route the conversation to a different model or a different dialogue system altogether. In this part of the tutorial, you will learn how to build a RAG chatbot with dialogue routing capabilities using Jac Cloud and Streamlit.