Update main.py

main.py

@@ -1,4 +1,4 @@
-# app.py — REVISED: Separated KPI snapshot from memory summary
+# app.py — FIXED: Corrected JSON serialization error in IrisReportEngine
 
 from langchain_google_genai import ChatGoogleGenerativeAI
 import pandas as pd
@@ -278,7 +278,7 @@ def sanitize_answer(ans) -> str:
     return s.strip()
 
 # -----------------------------------------------------------------------------
-# Analyst KPI layer (preserved)
+# Analyst KPI layer (MODIFIED WITH FIXES)
 # -----------------------------------------------------------------------------
 class IrisReportEngine:
     def __init__(self, transactions_data: list, llm_instance):
@@ -326,6 +326,7 @@ class IrisReportEngine:
     def _get_primary_currency(self) -> str:
         try:
             if not self.df.empty and "Currency" in self.df.columns and not self.df["Currency"].mode().empty:
+                # FIX 1: Extract the first item from the mode() Series to prevent serialization issues.
                 return str(self.df["Currency"].mode())
         except Exception:
             pass
@@ -350,8 +351,9 @@ class IrisReportEngine:
             if prev == 0:
                 return "+100%" if cur > 0 else "0.0%"
             return f"{((cur - prev) / prev) * 100:+.1f}%"
-        tx_now = int(current_df.get("Invoice_Number", pd.Series()).nunique()) if "Invoice_Number" in current_df.columns else int(len(current_df))
-        tx_prev = int(previous_df.get("Invoice_Number", pd.Series()).nunique()) if "Invoice_Number" in previous_df.columns else int(len(previous_df))
+        # FIX: Added dtype to pd.Series() to silence the FutureWarning from your traceback.
+        tx_now = int(current_df.get("Invoice_Number", pd.Series(dtype='object')).nunique()) if "Invoice_Number" in current_df.columns else int(len(current_df))
+        tx_prev = int(previous_df.get("Invoice_Number", pd.Series(dtype='object')).nunique()) if "Invoice_Number" in previous_df.columns else int(len(previous_df))
         return {
             "Total Revenue": f"{self.currency} {current_revenue:,.2f} ({pct_change(current_revenue, previous_revenue)})",
             "Gross Profit": f"{self.currency} {current_profit:,.2f} ({pct_change(current_profit, previous_profit)})",
@@ -376,20 +378,22 @@ class IrisReportEngine:
         product_intel = {}
         if len(products_by_profit) > 1:
             product_intel = {
-                "Best in Class (Most Profitable)": products_by_profit.idxmax(),
-                "Workhorse (Most Units Sold)": products_by_units.idxmax() if len(products_by_units) else "N/A",
+                "Best in Class (Most Profitable)": str(products_by_profit.idxmax()),
+                "Workhorse (Most Units Sold)": str(products_by_units.idxmax()) if len(products_by_units) > 0 else "N/A",
                 "Underperformer (Least Profitable > 0)": (
-                    products_by_profit[products_by_profit > 0].idxmin()
+                    str(products_by_profit[products_by_profit > 0].idxmin())
                     if not products_by_profit[products_by_profit > 0].empty else "N/A"
                 ),
             }
         elif not products_by_profit.empty:
-            product_intel = {"Only Product Sold": products_by_profit.index}
+            # FIX 2: Convert the single item from the index to a string to prevent it being a non-serializable Index object.
+            product_intel = {"Only Product Sold": str(products_by_profit.index)}
         staff_intel = {}
         if len(tellers_by_profit) > 1:
-            staff_intel = {"Top Performing Teller (by Profit)": tellers_by_profit.idxmax()}
+            staff_intel = {"Top Performing Teller (by Profit)": str(tellers_by_profit.idxmax())}
         elif not tellers_by_profit.empty:
-            staff_intel = {"Only Teller": tellers_by_profit.index}
+            # FIX 3: Convert the single item from the index to a string.
+            staff_intel = {"Only Teller": str(tellers_by_profit.index)}
         return {
             "Summary Period": summary_period,
             "Performance Snapshot (vs. Prior Period)": headline,
@@ -492,22 +496,54 @@ def bot():
 @cross_origin()
 def busines_report():
     logger.info("=== Starting /report endpoint ===")
-    # ... (code is preserved)
-    return jsonify("Report placeholder")
+    try:
+        request_json = request.get_json()
+        json_data = request_json.get("json_data") if request_json else None
+        prompt = (
+            "You are Quantilytix business analyst. Analyze the following data and generate a "
+            "comprehensive and insightful business report, including appropriate key perfomance "
+            "indicators and recommendations Use markdown formatting and tables where necessary. "
+            "only return the report and nothing else.\ndata:\n" + str(json_data)
+        )
+        response = model.generate_content(prompt)
+        return jsonify(str(response.text))
+    except Exception as e:
+        logger.exception("Error in /report endpoint")
+        return jsonify({"error": "Failed to generate report.", "details": str(e)}), 500
 
 @app.route("/marketing", methods=["POST"])
 @cross_origin()
 def marketing():
     logger.info("=== Starting /marketing endpoint ===")
-    # ... (code is preserved)
-    return jsonify("Marketing placeholder")
+    try:
+        request_json = request.get_json()
+        json_data = request_json.get("json_data") if request_json else None
+        prompt = (
+            "You are an Quantilytix Marketing Specialist. Analyze the following data and generate "
+            "a comprehensive marketing strategy, Only return the marketing strategy. be very creative:\n" + str(json_data)
+        )
+        response = model.generate_content(prompt)
+        return jsonify(str(response.text))
+    except Exception as e:
+        logger.exception("Error in /marketing endpoint")
+        return jsonify({"error": "Failed to generate marketing strategy.", "details": str(e)}), 500
 
 @app.route("/notify", methods=["POST"])
 @cross_origin()
 def notifications():
     logger.info("=== Starting /notify endpoint ===")
-    # ... (code is preserved)
-    return jsonify("Notification placeholder")
+    try:
+        request_json = request.get_json()
+        json_data = request_json.get("json_data") if request_json else None
+        prompt = (
+            "You are Quantilytix business analyst. Write a very brief analysis and marketing tips "
+            "using this business data. your output should be suitable for a notification dashboard so no quips.\n" + str(json_data)
+        )
+        response = model.generate_content(prompt)
+        return jsonify(str(response.text))
+    except Exception as e:
+        logger.exception("Error in /notify endpoint")
+        return jsonify({"error": "Failed to generate notification content.", "details": str(e)}), 500
 
 # -----------------------------------------------------------------------------
 # REVISED: ElevenLabs Voice Briefing Endpoints