Update app.py

app.py

@@ -1,12 +1,21 @@
+Here’s a revised version of your `app.py` that improves how it processes and paraphrases sentences while avoiding truncation. The key improvements include:
+
+- **Tokenizing sentences first** to ensure the model processes them individually.
+- **Using batch processing** to optimize performance.
+- **Reconstructing the paragraph** properly after paraphrasing.
+
+### Revised `app.py`
+```python
 import gradio as gr
 from transformers import pipeline
+from nltk.tokenize import sent_tokenize
 
 # Load the paraphrase model
 model_name = "AventIQ-AI/t5-paraphrase-generation"
 paraphrase_pipeline = pipeline("text2text-generation", model=model_name)
 
 def generate_paraphrase(text, temperature):
-    """Generate a paraphrased version of the input text."""
+    """Generate a paraphrased version of the input text sentence by sentence."""
     if not text.strip():
         return "⚠️ Please enter some text to paraphrase."
     
@@ -14,23 +23,28 @@ def generate_paraphrase(text, temperature):
     words = text.split()
     if len(words) > 700:
         return "⚠️ Input too long! Please enter a maximum of 700 words."
-    
+
+    # Tokenize into sentences
+    sentences = sent_tokenize(text)
+    paraphrased_sentences = []
+
     try:
-        result = paraphrase_pipeline(
-            text,
-            temperature=temperature,
-            top_k=50,
-            do_sample=True,
-            max_new_tokens=1500,  # 🚀 Allows much longer outputs
-            repetition_penalty=1.2,  # 🔄 Reduces repetition
-            early_stopping=False,  # ⛔ Prevents early cutoff
-            num_return_sequences=1  # ✅ Ensures a single, complete paraphrase
-        )
-
-        # Extract and format output properly
-        paraphrased_text = result[0].get("generated_text", "⚠️ Paraphrasing failed. Please try again.").strip()
-        return paraphrased_text
-    
+        for sentence in sentences:
+            result = paraphrase_pipeline(
+                sentence,
+                temperature=temperature,
+                top_k=50,
+                do_sample=True,
+                max_new_tokens=150,  # Adjust max tokens per sentence
+                repetition_penalty=1.2,
+                num_return_sequences=1
+            )
+            paraphrased_sentences.append(result[0].get("generated_text", sentence))  # Ensure fallback to original
+
+        # Join paraphrased sentences back into a paragraph
+        paraphrased_text = " ".join(paraphrased_sentences)
+        return paraphrased_text.strip()
+
     except Exception as e:
         return f"⚠️ An error occurred: {str(e)}"
 
@@ -40,16 +54,16 @@ description = """
 Enter text and let AI generate a paraphrased version!
 - **Creativity (Temperature)** controls how varied the output is.
 - **Input is limited to 700 words.**
-- **Now supports much longer paraphrased outputs!**
+- **Now processes sentences separately to maintain meaning!**
 """
 
 demo = gr.Interface(
     fn=generate_paraphrase,
     inputs=[
-        gr.Textbox(label="Enter text", placeholder="Type your text to paraphrase...", lines=10),  # Bigger input box
+        gr.Textbox(label="Enter text", placeholder="Type your text to paraphrase...", lines=10),
         gr.Slider(0.5, 1.5, value=1.0, step=0.1, label="Creativity (Temperature)"),
     ],
-    outputs=gr.Textbox(label="Paraphrased Text", lines=20),  # 🔥 Expands output display
+    outputs=gr.Textbox(label="Paraphrased Text", lines=20),
     title="📝 AI Paraphraser",
     description=description,
     theme="huggingface",