import streamlit as st from agents.analytics_pipeline import analytics_coordinator import os from db_connector import fetch_data_from_db, list_tables, SUPPORTED_ENGINES st.set_page_config(page_title="BizIntel AI Ultra", layout="wide") st.title("πŸ“Š BizIntel AI Ultra – Business Intelligence Agent") # ────────────────────────────────────────────────────────────── # ❢ DATA SOURCE SELECTION (CSVΒ orΒ Database) # ────────────────────────────────────────────────────────────── input_source = st.radio("Select data source", ["Upload CSV", "Connect to SQL Database"]) file_path = None if input_source == "Upload CSV": uploaded_file = st.file_uploader("Upload CSV", type="csv") if uploaded_file: file_path = os.path.join("data", uploaded_file.name) with open(file_path, "wb") as f: f.write(uploaded_file.read()) st.success("CSV file uploaded βœ…") elif input_source == "Connect to SQL Database": engine = st.selectbox("Database engine", SUPPORTED_ENGINES) conn_str = st.text_input("SQLAlchemy connection string") if conn_str: tables = list_tables(conn_str) if tables: table_name = st.selectbox("Choose a table", tables) if table_name: file_path = fetch_data_from_db(conn_str, table_name) st.success(f"Fetched **{table_name}** as CSV βœ…") # ────────────────────────────────────────────────────────────── # ❷ OPTIONALΒ IMAGEΒ UPLOADΒ +Β PREVIEW # ────────────────────────────────────────────────────────────── st.markdown("---") st.subheader("πŸ“· Optional: Upload an Image for Preview / Future Analysis") uploaded_image = st.file_uploader( "Upload an image (PNG orΒ JPG)", type=["png", "jpg", "jpeg"], key="img" ) if uploaded_image is not None: image_path = os.path.join("data", uploaded_image.name) with open(image_path, "wb") as f: f.write(uploaded_image.read()) st.image(image_path, caption="Uploaded Image", use_column_width=True) # πŸ‘‰Β If you later want to pass the image to an agent, you can add code here # e.g.Β result = image_analysis_agent.run(input=image_path) # ────────────────────────────────────────────────────────────── # ❸ RUNΒ BUSINESSΒ ANALYTICSΒ PIPELINE # ────────────────────────────────────────────────────────────── if file_path: st.markdown("---") st.info("Running analytics pipeline… ⏳") result = analytics_coordinator.run(input=file_path) st.subheader("πŸ“ Analysis & Strategy Report") st.text(result) # Display generated charts if they exist if os.path.exists("sales_plot.png"): st.image("sales_plot.png", caption="Sales Trend", use_column_width=True) if os.path.exists("forecast_plot.png"): st.image("forecast_plot.png", caption="Forecast Chart", use_column_width=True)