Update app.py

app.py

@@ -1,12 +1,14 @@
-
 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")
+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
 
@@ -16,25 +18,50 @@ if input_source == "Upload CSV":
         file_path = os.path.join("data", uploaded_file.name)
         with open(file_path, "wb") as f:
             f.write(uploaded_file.read())
-        st.success("File uploaded.")
+        st.success("CSV file uploaded ✅")
 
 elif input_source == "Connect to SQL Database":
-    engine = st.selectbox("Select database engine", SUPPORTED_ENGINES)
-    conn_str = st.text_input("Connection string (SQLAlchemy format)")
+    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 '{table_name}' as CSV.")
+                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.info("Running analytics pipeline...")
+    st.markdown("---")
+    st.info("Running analytics pipeline… ⏳")
     result = analytics_coordinator.run(input=file_path)
-    st.subheader("Analysis & Strategy Report")
+
+    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"):