Update app.py

app.py

@@ -3,13 +3,16 @@ import pandas as pd
 import matplotlib.pyplot as plt
 from google import genai
 
-# 🔑 ADD YOUR GEMINI API KEY HERE
+# 🔑 ADD YOUR GEMINI API KEY
 client = genai.Client(api_key="AIzaSyCvvewIh6BVyULlEmw1QE75vWsEmu8QNH0")
 
 
 # ---------- READ FILE ----------
 def read_file(file):
     try:
+        if file is None:
+            return pd.DataFrame()
+
         if file.name.endswith(".xlsx"):
             return pd.read_excel(file.name)
         else:
@@ -26,10 +29,13 @@ def preview(file):
     return df.head(20)
 
 
-# ---------- SIMPLE CONVERSION (WEBINAR → COURSE) ----------
+# ---------- SIMPLE CONVERSION ----------
 def convert(file):
     df = read_file(file)
 
+    if df.empty:
+        return pd.DataFrame({"Message": ["No data"]})
+
     if "Time in Session (minutes)" not in df.columns:
         return pd.DataFrame({"Message": ["No recognizable webinar structure"]})
 
@@ -64,7 +70,6 @@ def convert(file):
         "Satisfaction (1-5)": [satisfaction]
     })
 
-    # add health score
     result["Health Score"] = (
         (result["NPS Score"] * 0.4) +
         (result["Completion Rate (%)"] * 0.3) +
@@ -76,21 +81,24 @@ def convert(file):
 
 # ---------- CHART ----------
 def make_chart(df):
-    if "Course Name" not in df.columns:
+    if df is None or df.empty or "Course Name" not in df.columns:
         return None
 
     fig, ax = plt.subplots()
     ax.bar(df["Course Name"], df["Health Score"])
     plt.xticks(rotation=45)
     plt.title("Course Health Score")
+
     return fig
 
 
 # ---------- AI CHAT ----------
 def chat_with_data(file, message, history):
+    if history is None:
+        history = []
+
     try:
         df = read_file(file)
-
         preview_text = df.head(20).to_string()
 
         prompt = f"""
@@ -102,10 +110,10 @@ def chat_with_data(file, message, history):
         User question:
         {message}
 
-        Help them understand:
+        Explain:
         - what this dataset is
-        - what is wrong with structure
-        - how to convert it into course metrics (NPS, completion, satisfaction)
+        - what issues exist
+        - how to structure it into course metrics
         """
 
         response = client.models.generate_content(
@@ -118,11 +126,14 @@ def chat_with_data(file, message, history):
     except Exception as e:
         reply = str(e)
 
-    history.append((message, reply))
+    # ✅ NEW CHAT FORMAT (FIXED)
+    history.append({"role": "user", "content": message})
+    history.append({"role": "assistant", "content": reply})
+
     return history, history
 
 
-# ---------- MAIN UI ----------
+# ---------- UI ----------
 with gr.Blocks() as app:
     gr.Markdown("# 📊 Course Quality Tracker + AI Assistant")
 
@@ -136,7 +147,7 @@ with gr.Blocks() as app:
     chart = gr.Plot()
 
     gr.Markdown("## 🤖 Ask AI about your data")
-    chatbot = gr.Chatbot()
+    chatbot = gr.Chatbot(type="messages")
     msg = gr.Textbox(label="Ask anything about your dataset")
 
     # actions