Update app.py

app.py

@@ -17,7 +17,7 @@ PAYLOAD = {
 }
 
 def fetch_data():
-    """Fetch stock card report data from API, return cleaned DataFrame"""
+    """Fetch stock card report data from API and return cleaned DataFrame"""
     response = requests.post(API_URL, data=PAYLOAD)
     if response.status_code == 200:
         try:
@@ -86,7 +86,6 @@ if not GOOGLE_API_KEY:
 def generateResponse(prompt, df):
     """Generate response using PandasAI with SmartDataframe"""
     llm = GoogleGemini(api_key=GOOGLE_API_KEY)
-    # Use SmartDataframe for a single DataFrame
     pandas_agent = SmartDataframe(df, config={
         "llm": llm, 
         "response_parser": StreamLitResponse
@@ -113,7 +112,6 @@ def render_chat_message(message):
                 st.write("Unsupported plot format")
         except Exception as e:
             st.error(f"Error rendering plot: {e}")
-    
     if "content" in message:
         st.markdown(message["content"])
 
@@ -162,39 +160,63 @@ def handle_userinput(question, df):
 def main():
     st.set_page_config(page_title="AI Chat with Your Data", page_icon="📊")
 
-    # Initialize session state variables
+    # Initialize session state variables if not present
     if "chat_history" not in st.session_state:
         st.session_state.chat_history = []
     if "dfs" not in st.session_state:
         st.session_state.dfs = fetch_data()  # Load DataFrame at startup
 
-    # Create two tabs: one for Chat and one for Reports
+    # Create two tabs: Chat and Reports
     tab_chat, tab_reports = st.tabs(["Chat", "Reports"])
 
+    # --- Chat Tab ---
     with tab_chat:
         st.title("AI Chat with Your Data 📊")
-        # Create a placeholder container for chat messages so that they update smoothly
+        # Container for chat messages so they update smoothly
         chat_container = st.container()
         with chat_container:
             for message in st.session_state.chat_history:
                 with st.chat_message(message["role"]):
                     render_chat_message(message)
-
+        # Chat input
         user_question = st.chat_input("Ask a question about your data:")
         if user_question:
             handle_userinput(user_question, st.session_state.dfs)
-            # Refresh the chat container to show new messages immediately
+            # Update chat container immediately after processing the input
             chat_container.empty()
             with chat_container:
                 for message in st.session_state.chat_history:
                     with st.chat_message(message["role"]):
                         render_chat_message(message)
 
+    # --- Reports Tab ---
     with tab_reports:
         st.title("Reports")
-        st.write("This tab is under construction.")
+        st.write("Filter by product to generate a report")
+        # Reload the data (or use the existing one) for reports
+        df_report = fetch_data()
+        if df_report is not None and not df_report.empty:
+            product_names = df_report["product"].unique().tolist() if "product" in df_report.columns else []
+            selected_products = st.multiselect("Select Product(s)", product_names, default=product_names)
+            if st.button("Apply Filters and Generate Report"):
+                filtered_df = df_report.copy()
+                if selected_products:
+                    filtered_df = filtered_df[filtered_df["product"].isin(selected_products)]
+                st.write("Filtered DataFrame Preview:")
+                with st.expander("Preview"):
+                    st.dataframe(filtered_df.head())
+                with st.spinner("Generating Report, Please Wait...."):
+                    prompt = (
+                        "You are an expert business analyst. Analyze the following data and generate a comprehensive and insightful business report "
+                        "including key performance indicators and recommendations.\n\nData:\n" + str(filtered_df.to_json(orient='records'))
+                    )
+                    response = generateResponse(prompt, filtered_df)
+                    # Display the report text; adjust according to your response format.
+                    st.markdown(response.get("value", "No report generated."))
+        else:
+            st.error("No data available for reports.")
 
-    # Sidebar with options
+    # --- Sidebar Options ---
     with st.sidebar:
         st.subheader("Options")
         if st.button("Reload Data"):