#Add loading and display in st.code of the history.  Add and display a dataframe with the input and output pair in an editable grid and code listing:   import streamlit as st
import anthropic
import os
import base64
from streamlit.components.v1 import html

# Set up the Anthropic client
client = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))

# Initialize session state
if "chat_history" not in st.session_state:
    st.session_state.chat_history = []

# Function to get file download link
def get_download_link(file_contents, file_name):
    b64 = base64.b64encode(file_contents.encode()).decode()
    return f'<a href="data:file/txt;base64,{b64}" download="{file_name}">Download {file_name}</a>'

# Streamlit app
def main():
    st.title("Claude 3.5 Sonnet API Demo")

    # User input
    user_input = st.text_input("Enter your message:", key="user_input")

    if user_input:
        # Call Claude API
        response = client.messages.create(
            model="claude-3-sonnet-20240229",
            max_tokens=1000,
            messages=[
                {"role": "user", "content": user_input}
            ]
        )

        # Append to chat history
        st.session_state.chat_history.append({"user": user_input, "claude": response.content[0].text})

        # Clear user input
        st.session_state.user_input = ""

    # Display chat history
    for chat in st.session_state.chat_history:
        st.chat_message(chat["user"], is_user=True)
        st.chat_message(chat["claude"], avatar_style="thumbs", seed="Claude")

    # Save chat history to file
    chat_history_text = "\n".join([f"User: {chat['user']}\nClaude: {chat['claude']}" for chat in st.session_state.chat_history])
    file_download_link = get_download_link(chat_history_text, "chat_history.txt")
    st.markdown(file_download_link, unsafe_allow_html=True)

if __name__ == "__main__":
    main()