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import streamlit as st
from rag import RAGProcessor
import os
from dotenv import load_dotenv
import tempfile
# Load environment variables
load_dotenv()
# Check for API key
if not os.getenv('GOOGLE_API_KEY'):
st.error("Please set the GOOGLE_API_KEY in your .env file.")
st.stop()
def initialize_session_state():
"""Initialize session state variables."""
if "rag_processor" not in st.session_state:
st.session_state.rag_processor = RAGProcessor()
if "vector_store" not in st.session_state:
st.session_state.vector_store = None
def save_uploaded_files(uploaded_files):
"""Save uploaded files to a temporary directory and return file paths."""
try:
temp_dir = tempfile.mkdtemp()
file_paths = []
for uploaded_file in uploaded_files:
file_path = os.path.join(temp_dir, uploaded_file.name)
with open(file_path, "wb") as f:
f.write(uploaded_file.getbuffer())
file_paths.append(file_path)
return file_paths
except Exception as e:
st.error(f"Error saving uploaded files: {e}")
return []
def main():
st.set_page_config(
page_title="Finance Buddy",
page_icon="💰",
layout="wide"
)
initialize_session_state()
# Main header with emoji
st.markdown("<div class='main-header'>", unsafe_allow_html=True)
st.markdown(
"<h1 style='text-align: center;'>💰 Finance Buddy</h1>",
unsafe_allow_html=True
)
st.markdown("</div>", unsafe_allow_html=True)
# Sidebar
with st.sidebar:
st.image("PL_image-removebg-preview.png", use_column_width=True)
st.title("📄 Document Analysis")
uploaded_files = st.file_uploader(
"Upload P&L Documents (PDF)",
accept_multiple_files=True,
type=['pdf']
)
if uploaded_files and st.button("Process Documents", key="process_docs"):
with st.spinner("Processing documents..."):
try:
# Save uploaded files and process them
file_paths = save_uploaded_files(uploaded_files)
if file_paths:
st.session_state.vector_store = st.session_state.rag_processor.process_documents(file_paths)
st.success("✅ Documents processed successfully!")
except Exception as e:
st.error(f"Error processing documents: {e}")
# Main content
st.markdown("""
💡 **Ask questions about your P&L statements and financial data.**
""")
# Query input
query = st.text_input("🔍 Ask your question:", key="query")
if query:
if not st.session_state.vector_store:
st.warning("Please upload and process documents first!")
else:
with st.spinner("Analyzing..."):
try:
response = st.session_state.rag_processor.generate_response(
query,
st.session_state.vector_store
)
st.markdown("### 📋 Response:")
st.markdown(f">{response}")
except Exception as e:
st.error(f"Error generating response: {e}")
# Footer
st.markdown("---")
st.markdown(
"<p style='text-align: center;'>💼 Built with Streamlit & Google Generative AI</p>",
unsafe_allow_html=True
)
if __name__ == "__main__":
main()
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