app.py

from openai import OpenAI
import streamlit as st
from langchain_openai import ChatOpenAI
from tools import sentiment_analysis_util
import numpy as np
from dotenv import load_dotenv
import os

st.set_page_config(page_title="LangChain Agent", layout="wide")
load_dotenv()
OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]

llm = ChatOpenAI(model="gpt-3.5-turbo")

from langchain_core.runnables import RunnableConfig

st.title("💬 ExpressMood")

@st.cache_resource
def initialize_session_state():
    if "chat_history" not in st.session_state:
        st.session_state["messages"] = [{"role":"system", "content":"""
You are a sentiment analysis expert. Answer all questions related to cryptocurrency investment reccommendations. Say I don't know if you don't know.
"""}]

initialize_session_state()

client = OpenAI(api_key=OPENAI_API_KEY)

if "openai_model" not in st.session_state:
    st.session_state["openai_model"] = "gpt-3.5-turbo"

if prompt := st.chat_input("Any other questions? "):
    # Add user message to chat history
    st.session_state.messages.append({"role": "user", "content": prompt})
    # Display user message in chat message container
    with st.chat_message("user"):
        st.markdown(prompt)
    # Display assistant response in chat message container
    with st.chat_message("assistant"):
        stream = client.chat.completions.create(
            model=st.session_state["openai_model"],
            messages=[
                {"role": m["role"], "content": m["content"]}
                for m in st.session_state.messages
            ],
            stream=True,
        )
        response = st.write_stream(stream)
    st.session_state.messages.append({"role": "assistant", "content": response})