Update app.py

app.py

@@ -36,16 +36,23 @@ def generate_insights(df):
 
     return insights
 
-    if df.empty:
-        st.error("The uploaded dataset is empty. Please upload a valid dataset.")
-        st.stop()
-
 # RAG setup using Hugging Face summarization
 def generate_query_summary(df, query):
     summarizer = pipeline("summarization")
     combined_text = " ".join(df.astype(str).apply(lambda x: " ".join(x), axis=1))
-    result = summarizer(query + " " + combined_text, max_length=100, min_length=30, do_sample=False)
-    return result[0]['summary_text']
+
+    # Truncate text to avoid token limit issues
+    max_input_length = 1024
+    if len(combined_text) > max_input_length:
+        combined_text = combined_text[:max_input_length]
+
+    try:
+        result = summarizer(query + " " + combined_text, max_length=100, min_length=30, do_sample=False)
+        return result[0]['summary_text']
+    except IndexError:
+        return "Error: Unable to generate a summary. Ensure the query and data are valid."
+    except Exception as e:
+        return f"Error during summarization: {e}"
 
 # Streamlit app
 st.title("Employee Performance Dashboard")
@@ -77,4 +84,4 @@ if uploaded_file is not None:
             st.markdown("#### Summary")
             st.write(summary)
 else:
-    st.info("Please upload a CSV file.")
+    st.info("Please upload a CSV file.")