update landing page

.streamlit/config.toml

@@ -0,0 +1,6 @@
+[theme]
+primaryColor="#523EFD"
+backgroundColor="#FFFFFF"
+secondaryBackgroundColor="#D4CEFF"
+textColor="#262730"
+font="sans serif"

chat.py

@@ -40,27 +40,26 @@ def login():
     if "user_name" in st.session_state or ("jump_query_ask" in st.session_state and st.session_state.jump_query_ask):
         return True
     st.subheader("🤗 Welcom to [MyScale](https://myscale.com)'s [ChatData](https://github.com/myscale/ChatData)! 🤗 ")
-    st.write("You can now chat with ArXiv and Wikipedia! You can also try to build your RAG system with those knowledge base via [our public read-only credentials!](https://github.com/myscale/ChatData#data-schema) 🌟\n")
-    st.write("Built purely with streamlit 👑 , LangChain 🦜🔗 and love for AI!")
+    st.write("You can now chat with ArXiv and Wikipedia! 🌟\n")
+    st.write("Built purely with streamlit 👑 , LangChain 🦜🔗 and love ❤️ for AI!")
     st.write("Follow us on [Twitter](https://x.com/myscaledb) and [Discord](https://discord.gg/D2qpkqc4Jq)!")
+    st.write("For more details, please refer to [our repository on GitHub](https://github.com/myscale/ChatData)!")
     st.divider()
     col1, col2 = st.columns(2, gap='large')
     with col1.container():
         st.write("Try out MyScale's Self-query and Vector SQL retrievers!")
         st.write("In this demo, you will be able to see how those retrievers "
                  "**digest** -> **translate** -> **retrieve** -> **answer** to your question!")
-        st.write("It is a step-by-step tour to understand RAG pipeline.")
         st.session_state["jump_query_ask"] = st.button("Query / Ask")
     with col2.container():
-        st.warning("To use chat, please jump to [https://myscale-chatdata.hf.space](https://myscale-chatdata.hf.space)")
-        st.info("We used [Auth0](https://auth0.com) as our identity provider. "
-                "We will **NOT** collect any of your conversation in any form for any purpose.")
+        # st.warning("To use chat, please jump to [https://myscale-chatdata.hf.space](https://myscale-chatdata.hf.space)")
         st.write("Now with the power of LangChain's Conversantional Agents, we are able to build "
-                 "conversational chatbot with RAG! The agent will decide when and what to retrieve "
-                 "based on your question!")
-        st.write("All those conversation history management and retrievers are provided within one MyScale instance!")
+                 "an RAG-enabled chatbot within one MyScale instance! ")
         st.write("Log in to Chat with RAG!")
         login_button(AUTH0_CLIENT_ID, AUTH0_DOMAIN, "auth0")
+    st.divider()
+    st.write("- [Privacy Policy](https://myscale.com/privacy/)\n"
+             "- [Terms of Sevice](https://myscale.com/terms/)")
     if st.session_state.auth0 is not None:
         st.session_state.user_info = dict(st.session_state.auth0) 
         if 'email' in st.session_state.user_info: