Importing required libraries: It imports streamlit and Ollama. Streamlit header: The program displays a title with the given emoji. Session state management: A session_state object is created to manage user messages, roles, and chat content during runtime. Messages are stored in this dictionary-like structure. Message handling function (generate_response()): This function uses Ollama's chat method to generate a stream of text responses from the model. It yields partial tokens which are then appended to st.session_state["full_message"]. The generated response is sent back to the user via Streamlit's chat interface, while also updating the session state with new messages and full content for future processing or display. Input handling: Using st.chat_input(), user prompts are captured as input and stored in the session state. Then, Ollama's AI model generates a response based on that input which is sent back to the user using st.session_state["full_message"]. After displaying the assistant's generated message, it updates the session state with new messages for further conversation handling.