1

app.py

@@ -1,13 +1,45 @@
-"""
-# My first app
-Here's our first attempt at using data to create a table:
-"""
-
+"""Python file to serve as the frontend"""
 import streamlit as st
-import pandas as pd
-df = pd.DataFrame({
-  'first column': [1, 2, 3, 4],
-  'second column': [10, 20, 30, 40]
-})
+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"] = []
+
+
+def get_text():
+    input_text = st.text_input("You: ", "Hello, Nice to meet you", key="input")
+    return input_text
+
+
+
+
+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))
+
+user_input = get_text()
+if user_input:
+    output = chain.run(input=user_input)
 
-df
+    st.session_state.past.append(user_input)
+    st.session_state.generated.append(output)