langchain-ollama with streamlit

langchain-ollama.py

import streamlit as st
from langchain.llms.ollama import Ollama 

llm = Ollama(model='deepseek-r1:1.5b')

if "messages" not in st.session_state:
    st.session_state.messages = []

st.title('Deepseek with Streamlit')
st.write('Using LangChain, Ollama and streamlit. The ollama model is already installed locally on my machine')


for message in st.session_state.messages:
    with st.chat_message(message['role']):
        st.write(message['content'])

user_input = st.chat_input("Write something...")


if user_input and user_input.strip():
    st.session_state.messages.append({'role': 'user', 'content': user_input})
    with st.chat_message("user"):
        st.markdown(user_input)

    result = llm.predict(user_input)
    st.session_state.messages.append({'role': 'deepseek','content':result})

    with st.chat_message("deepseek"):
        st.markdown(result)