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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})
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