Update app.py

app.py

@@ -58,9 +58,8 @@ def detect_ai_generated(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512).to(device)
     with torch.no_grad():
         outputs = model(**inputs)
-    probabilities = torch.softmax(outputs.logits, dim=1)
-    ai_probability = probabilities[0][1].item()  # Probability of being AI-generated
-    return ai_probability
+        probabilities = torch.softmax(outputs.logits, dim=1)
+    return probabilities[0][1].item()  # Probability of being AI-generated
 
 # Humanize the AI-detected text using the SRDdev Paraphrase model
 def humanize_text(AI_text):
@@ -69,14 +68,15 @@ def humanize_text(AI_text):
     for paragraph in paragraphs:
         if paragraph.strip():
             inputs = paraphrase_tokenizer(paragraph, return_tensors="pt", max_length=512, truncation=True).to(device)
-            paraphrased_ids = paraphrase_model.generate(
-                inputs['input_ids'],
-                max_length=inputs['input_ids'].shape[-1] + 20,  # Slightly more than the original input length
-                num_beams=4,
-                early_stopping=True,
-                length_penalty=1.0,
-                no_repeat_ngram_size=3,
-            )
+            with torch.no_grad():  # Avoid gradient calculations for faster inference
+                paraphrased_ids = paraphrase_model.generate(
+                    inputs['input_ids'],
+                    max_length=inputs['input_ids'].shape[-1] + 20,  # Slightly more than the original input length
+                    num_beams=4,
+                    early_stopping=True,
+                    length_penalty=1.0,
+                    no_repeat_ngram_size=3,
+                )
             paraphrased_text = paraphrase_tokenizer.decode(paraphrased_ids[0], skip_special_tokens=True)
             paraphrased_paragraphs.append(paraphrased_text)
     return "\n\n".join(paraphrased_paragraphs)
@@ -104,4 +104,4 @@ interface = gr.Interface(
 )
 
 # Launch the Gradio app
-interface.launch(debug=True)
+interface.launch(debug=False)  # Turn off debug mode for production