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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("📊 BizIntel AI Ultra – Business Intelligence Agent")
# ──────────────────────────────────────────────────────────────
# ❶ DATA SOURCE SELECTION (CSV or 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 ✅")
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 ✅")
# ──────────────────────────────────────────────────────────────
# ❷ OPTIONAL IMAGE UPLOAD + PREVIEW
# ──────────────────────────────────────────────────────────────
st.markdown("---")
st.subheader("📷 Optional: Upload an Image for Preview / Future Analysis")
uploaded_image = st.file_uploader(
"Upload an image (PNG or 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)
# 👉 If you later want to pass the image to an agent, you can add code here
# e.g. result = image_analysis_agent.run(input=image_path)
# ──────────────────────────────────────────────────────────────
# ❸ RUN BUSINESS ANALYTICS PIPELINE
# ──────────────────────────────────────────────────────────────
if file_path:
st.markdown("---")
st.info("Running analytics pipeline… ⏳")
result = analytics_coordinator.run(input=file_path)
st.subheader("📝 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)
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