Update app.py

app.py

@@ -177,17 +177,22 @@ if selected_class != "New Class":
         st.table(schema_df[["name", "dataType"]])  # Display only the name and dataType columns
 
 # Before ingesting data into Weaviate, check if CSV columns match the class schema
-if csv_file is not None and class_schema:  # Ensure class_schema is not None
+if csv_file is not None:
     data = csv_file.read().decode("utf-8")
     dataframe = pd.read_csv(StringIO(data))
     
+    # Display the uploaded CSV data
+    st.write("Uploaded CSV Data:")
+    st.write(dataframe)
+
     # Check if columns match
-    schema_columns = [prop["name"] for prop in class_schema["properties"]]
-    if set(dataframe.columns) != set(schema_columns):
-        st.error("The columns in the uploaded CSV do not match the schema of the selected class. Please check and upload the correct CSV.")
-    else:
-        # Ingest data into Weaviate
-        ingest_data_to_weaviate(dataframe, class_name, class_description)
+    if class_schema:  # Ensure class_schema is not None
+        schema_columns = [prop["name"] for prop in class_schema["properties"]]
+        if set(dataframe.columns) != set(schema_columns):
+            st.error("The columns in the uploaded CSV do not match the schema of the selected class. Please check and upload the correct CSV or create a new class.")
+        else:
+            # Ingest data into Weaviate
+            ingest_data_to_weaviate(dataframe, class_name, class_description)
 
     # Input for questions
     questions = st.text_area("Enter your questions (one per line)")