Update app.py

app.py

@@ -1,56 +1,57 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import T5Tokenizer, T5ForConditionalGeneration
 from sentence_transformers import SentenceTransformer, util
-import random
+import torch
 
 # Load models
-from transformers import T5Tokenizer, T5ForConditionalGeneration
-
 tokenizer = T5Tokenizer.from_pretrained("Vamsi/T5_Paraphrase_Paws", use_fast=False)
 model = T5ForConditionalGeneration.from_pretrained("Vamsi/T5_Paraphrase_Paws")
-
-def generate_paraphrase(text):
-    input_ids = tokenizer.encode("paraphrase: " + text, return_tensors="pt", max_length=256, truncation=True)
-    output_ids = model.generate(input_ids, max_length=80, num_return_sequences=1, do_sample=True, top_k=120, top_p=0.98)
-    return tokenizer.decode(output_ids[0], skip_special_tokens=True)
-
 similarity_model = SentenceTransformer('all-MiniLM-L6-v2')
 
-# Tone modifier prompts
+# Tone prompt variations
 tone_prompts = {
-    "Academic": "Rewrite this in a scholarly and formal way:",
-    "Casual": "Rewrite this casually like a real student would talk:",
-    "Friendly": "Make this sound friendly and human-like:",
-    "Stealth (AI Detection Bypass)": "Paraphrase to avoid sounding like AI-generated content:"
+    "Academic": "Rewrite this in a formal and academic way:",
+    "Casual": "Rewrite this in a casual and relaxed way:",
+    "Friendly": "Make this sound like a friendly human wrote it:",
+    "Stealth (AI Detection Bypass)": "Reword this to avoid AI detection and sound natural:"
 }
 
+def generate_paraphrase(text, tone):
+    prompt = tone_prompts.get(tone, "Paraphrase:")
+    input_text = f"{prompt} {text.strip()}"
+    input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=256, truncation=True)
+    output_ids = model.generate(
+        input_ids,
+        max_length=80,
+        num_return_sequences=1,
+        do_sample=True,
+        top_k=120,
+        top_p=0.95
+    )
+    return tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
 def humanize_text(input_text, tone):
     if not input_text.strip():
         return "Please enter some text.", "", ""
 
-    style_prompt = tone_prompts.get(tone, "Paraphrase:")
-    result = paraphraser(f"{style_prompt} {input_text}", max_length=80, num_return_sequences=1)
-    output_text = generate_paraphrase(input_text)
-
+    # Generate output
+    output_text = generate_paraphrase(input_text, tone)
 
-    # Semantic similarity score
+    # Compute semantic similarity
     emb1 = similarity_model.encode(input_text, convert_to_tensor=True)
     emb2 = similarity_model.encode(output_text, convert_to_tensor=True)
     similarity_score = util.pytorch_cos_sim(emb1, emb2).item()
-
-    score_description = "✔️ Humanized (Safe)" if similarity_score < 0.92 else "⚠️ Still Close to AI Tone"
+    score_description = "✅ Very Human-Like" if similarity_score < 0.9 else "⚠️ May Still Sound AI-Generated"
 
     return output_text, f"{similarity_score:.2f}", score_description
 
-# Gradio Interface
-with gr.Blocks(theme=gr.themes.Base(primary_hue="blue", secondary_hue="blue")) as demo:
-    gr.Markdown("""
-    <h1 style='text-align: center; color: #0f172a;'>🧠 Taha's AI Humanizer Tool</h1>
-    <p style='text-align: center; color: #334155;'>Rewriting AI-generated text to sound real, authentic, and undetectable — made by Taha.</p>
-    """)
+# UI
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🧠 Taha's AI Humanizer Tool")
+    gr.Markdown("*Rewriting AI-generated text to sound real, authentic, and undetectable — made by Taha.*")
 
     with gr.Row():
-        input_text = gr.Textbox(lines=6, label="🔤 Enter Your AI-Sounding Text")
+        input_text = gr.Textbox(lines=6, label="📝 Enter Your AI-Sounding Text")
         output_text = gr.Textbox(lines=6, label="✅ Humanized Output")
 
     tone = gr.Radio(["Academic", "Casual", "Friendly", "Stealth (AI Detection Bypass)"], label="🎯 Select Tone", value="Stealth (AI Detection Bypass)")
@@ -59,13 +60,6 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue="blue", secondary_hue="blue")) a
         similarity = gr.Textbox(label="🔍 Semantic Similarity Score")
         score_label = gr.Textbox(label="🧠 Humanization Check")
 
-    btn = gr.Button("🚀 Humanize It")
-
-    btn.click(fn=humanize_text, inputs=[input_text, tone], outputs=[output_text, similarity, score_label])
-
-    gr.Markdown("""
-    <hr>
-    <p style='text-align: center; font-size: 14px; color: #64748b;'>✨ Created with love by <strong>Taha</strong> — helping students stay original.</p>
-    """)
+    gr.Button("🚀 Humanize It").click(fn=humanize_text, inputs=[input_text, tone], outputs=[output_text, similarity, score_label])
 
-demo.launch()
+demo.launch()