asd

app.py

@@ -570,6 +570,9 @@ def classify_text(text):
     main_score = probabilities[0][predicted_class].item()
     return main_label, main_score
 
+def clean_text(text):
+    return text.replace("paraphrasedoutput: ", "")
+
 @spaces.GPU
 def generate_paraphrases(text, setting, output_format):
     sentences = splitter.split(text)
@@ -689,20 +692,21 @@ def generate_paraphrases(text, setting, output_format):
     else:
         return json.dumps(json_output, indent=2), "\n\n".join([v[0] for v in human_versions])
 
+def clean_paraphrased_output(text):
+    cleaned_text = clean_text(text)
+    return cleaned_text
+
 # Define the Gradio interface
 iface = gr.Interface(
-    fn=generate_paraphrases,
+    fn=clean_paraphrased_output,
     inputs=[
-        gr.Textbox(lines=5, label="Input Text"),
-        gr.Slider(minimum=1, maximum=5, step=1, label="Readability to Human-like Setting"),
-        gr.Radio(["text", "json"], label="Output Format")
+        gr.Textbox(lines=5, label="Input Text")
     ],
     outputs=[
-        gr.Textbox(lines=20, label="Detailed Paraphrases and Classifications"),
-        gr.Textbox(lines=10, label="Human-like or Less Confident Machine-generated Paraphrases")
+        gr.Textbox(lines=20, label="Cleaned Text")
     ],
-    title="Advanced Diverse Paraphraser with Human-like Filter",
-    description="Enter a text, select a setting from readable to human-like, and choose the output format to generate diverse paraphrased versions. Combined versions are classified, and those detected as human-produced or less confidently machine-generated are presented in the final output."
+    title="Clean Paraphrased Output",
+    description="Enter a text with 'paraphrasedoutput:' prefix and get the cleaned text."
 )
 
 # Launch the interface