Code Editor for app.py

import streamlit as st
import pandas as pd
import openai
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()

# Configure OpenAI
openai.api_key = os.getenv("OPENAI_API_KEY")

def generate_commentary(attribution_data):
    """Generate commentary using OpenAI API based on attribution data"""
    prompt = f"""
    Based on the following portfolio attribution data:
    {attribution_data}
    
    Generate a detailed investment commentary that:
    1. Explains the main drivers of performance
    2. Highlights notable sector/stock contributions
    3. Provides context for the attribution results
    4. Uses professional investment language
    
    Format the commentary in clear paragraphs.
    """
    
    try:
        response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "system", "content": "You are an expert investment portfolio manager skilled at writing attribution commentary."},
                {"role": "user", "content": prompt}
            ]
        )
        return response.choices[0].message.content
    except Exception as e:
        return f"Error generating commentary: {str(e)}"

# App title
st.title("Portfolio Attribution Commentary Generator")

# API Key input
api_key = st.text_input("Enter your OpenAI API Key", type="password")
if api_key:
    openai.api_key = api_key

# File upload
uploaded_file = st.file_uploader("Upload attribution data (CSV)", type="csv")

if uploaded_file is not None:
    try:
        # Read the CSV file
        df = pd.read_csv(uploaded_file)
        
        # Display the attribution data
        st.subheader("Attribution Data")
        st.dataframe(df)
        
        # Generate commentary button
        if st.button("Generate Commentary"):
            if not openai.api_key:
                st.error("Please enter your OpenAI API key")
            else:
                with st.spinner("Generating commentary..."):
                    # Convert DataFrame to string for the prompt
                    attribution_text = df.to_string()
                    commentary = generate_commentary(attribution_text)
                    
                    # Display generated commentary in an editable text area
                    st.subheader("Generated Commentary")
                    edited_commentary = st.text_area(
                        "Edit the commentary as needed:",
                        value=commentary,
                        height=400
                    )
                    
                    # Add download button for the commentary
                    if st.button("Download Commentary"):
                        st.download_button(
                            label="Download Commentary as Text",
                            data=edited_commentary,
                            file_name="attribution_commentary.txt",
                            mime="text/plain"
                        )
                        
    except Exception as e:
        st.error(f"Error processing file: {str(e)}")

# Instructions
with st.expander("How to use"):
    st.markdown("""
    1. Enter your OpenAI API key
    2. Upload a CSV file containing portfolio attribution data
    3. Click 'Generate Commentary' to create an AI-generated investment commentary
    4. Edit the generated commentary as needed
    5. Download the final commentary using the download button
    
    Expected CSV format:
    - The file should contain attribution data with columns like Security, Sector, Weight, Return, Contribution, etc.
    - Make sure the data is clean and properly formatted
    """)

# Add footer with disclaimer
st.markdown("---")
st.caption("Disclaimer: This tool uses AI to generate commentary. Please review and edit all generated content before use.")