Update app.py

app.py

@@ -44,31 +44,31 @@ def store_message(name: str, message: str, outputfileName: str):
     basedir = os.path.dirname(__file__)
     savePath = outputfileName
     
-    # if file doesnt exist, create it with labels
+    # if file doesn't exist, create it with labels and a few default rows
     from os.path import exists
     file_exists = exists(savePath)
     
-    if (file_exists==False):
-        with open(savePath, "w") as f: #write
-            f.write(str("time, message, text\n")) # one time only to get column headers for CSV file
-            if name and message:
-                writer = csv.DictWriter(f, fieldnames=["time", "message", "name"])
-                writer.writerow(
-                    {"time": str(datetime.now()), "message": message.strip(), "name": name.strip()  }
-                )
-        df = pd.read_csv(savePath)
-        df = df.sort_values(df.columns[0],ascending=False)
-    else:
-        if name and message:
-            with open(savePath, "a") as csvfile:
-                writer = csv.DictWriter(csvfile, fieldnames=[ "time", "message", "name", ])
-                writer.writerow(
-                    {"time": str(datetime.now()), "message": message.strip(), "name": name.strip()  }
-                )
-        df = pd.read_csv(savePath)
-        df = df.sort_values(df.columns[0],ascending=False)
+    if not file_exists:
+        with open(savePath, "w") as f:  # Create and write column headers and default content
+            f.write("time, message, name\n")  # Column headers
+            # Write a few default rows (if needed)
+            f.write(f"{str(datetime.now())}, Welcome to Chatback!, System\n")
+            f.write(f"{str(datetime.now())}, How can I assist you today?, System\n")
+            
+    # Proceed to add the actual message if name and message are provided
+    if name and message:
+        with open(savePath, "a") as csvfile:
+            writer = csv.DictWriter(csvfile, fieldnames=["time", "message", "name"])
+            writer.writerow(
+                {"time": str(datetime.now()), "message": message.strip(), "name": name.strip()}
+            )
+    
+    # Load and sort the dataframe
+    df = pd.read_csv(savePath)
+    df = df.sort_values(df.columns[0], ascending=False)
     return df
 
+
 mname = "facebook/blenderbot-400M-distill"
 model = BlenderbotForConditionalGeneration.from_pretrained(mname)
 tokenizer = BlenderbotTokenizer.from_pretrained(mname)