Update app.py

app.py

@@ -3,7 +3,7 @@ import gradio as gr
 import PyPDF2
 import random
 import pandas as pd
-from io import StringIO
+from io import BytesIO
 import csv
 import os
 
@@ -29,7 +29,9 @@ def generate(file, temperature, max_new_tokens, top_p, repetition_penalty):
 
     # CSV dosyası için başlık
     if not os.path.exists("synthetic_data.csv"):
-        save_to_csv("Original Sentence", "Synthetic Data")
+        with open("synthetic_data.csv", mode='w', newline='', encoding='utf-8') as file:
+            writer = csv.writer(file)
+            writer.writerow(["Original Sentence", "Synthetic Data"])
 
     for sentence in sentences:
         sentence = sentence.strip()
@@ -55,7 +57,9 @@ def generate(file, temperature, max_new_tokens, top_p, repetition_penalty):
             print(f"Error generating data for sentence '{sentence}': {e}")
             save_to_csv(sentence, f"Error: {e}")
 
-    return gr.File(value="synthetic_data.csv", file_name="synthetic_data.csv")
+    # CSV dosyasını okuyup byte olarak döndür
+    with open("synthetic_data.csv", "rb") as file:
+        return file.read(), "synthetic_data.csv"
 
 gr.Interface(
     fn=generate,
@@ -66,7 +70,7 @@ gr.Interface(
         gr.Slider(label="Top-p (nucleus sampling)", value=0.95, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens"),
         gr.Slider(label="Repetition penalty", value=1.0, minimum=1.0, maximum=2.0, step=0.1, interactive=True, info="Penalize repeated tokens"),
     ],
-    outputs="file",
+    outputs=gr.File(label="Download Synthetic Data CSV"),
     title="Synthetic Data Generation",
     description="This tool generates synthetic data from the sentences in your PDF and saves it to a CSV file.",
     allow_flagging="never",