| """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() |
|
|
| |
| 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) |
|
|
| st.session_state.past.append(user_input) |
| st.session_state.generated.append(output) |
|
|
