t

app.py

@@ -1,45 +1,13 @@
-"""Python file to serve as the frontend"""
-import streamlit as st
-from streamlit_chat import message
-
-from langchain.chains import ConversationChain
-from langchain.llms import OpenAI
-import os
-
-def load_chain():
-    """Logic for loading the chain you want to use should go here."""
-    llm = OpenAI(temperature=0)
-    chain = ConversationChain(llm=llm)
-    return chain
-
-chain = load_chain()
-
-# From here down is all the StreamLit UI.
-st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
-st.header("LangChain Demo")
-
-if "generated" not in st.session_state:
-    st.session_state["generated"] = []
-
-if "past" not in st.session_state:
-    st.session_state["past"] = []
+"""
+# My first app
+Here's our first attempt at using data to create a table:
+"""
 
+import streamlit as st
+import pandas as pd
+df = pd.DataFrame({
+  'first column': [1, 2, 3, 4],
+  'second column': [10, 20, 30, 40]
+})
 
-def get_text():
-    input_text = st.text_input("You: ", "Hello, Nice to meet you", key="input")
-    return input_text
-
-
-user_input = get_text()
-
-if user_input:
-    output = chain.run(input=user_input)
-
-    st.session_state.past.append(user_input)
-    st.session_state.generated.append(output)
-
-if st.session_state["generated"]:
-    for i in range(len(st.session_state["generated"]) - 1, -1, -1):
-        message(st.session_state["past"][i], is_user=True, key=str(i) + "_user")
-        message(st.session_state["generated"][i], key=str(i))
-
+df