Update app.py

app.py

@@ -4,15 +4,15 @@ import torch, gradio as gr, re
 # ------------------------
 # Load Models
 # ------------------------
-# Stage 1: Paraphraser
+# Stage 1: Paraphraser (Parrot)
 paraphrase_model_name = "prithivida/parrot_paraphraser_on_T5"
 paraphrase_tokenizer = AutoTokenizer.from_pretrained(paraphrase_model_name)
 paraphrase_model = AutoModelForSeq2SeqLM.from_pretrained(paraphrase_model_name)
 
-# Stage 2: Expander (Flan-T5-Large)
+# Stage 2: Lightweight Expander (flan-t5-small)
 expander = pipeline(
     "text2text-generation",
-    model="google/flan-t5-large",
+    model="google/flan-t5-small",
     device=0 if torch.cuda.is_available() else -1
 )
 
@@ -46,13 +46,13 @@ def paraphrase_fn(text, num_return_sequences=1, temperature=1.2, top_p=0.92):
 
         outputs = paraphrase_model.generate(
             **inputs,
-            max_new_tokens=128,
+            max_new_tokens=64,
             num_return_sequences=int(num_return_sequences),
             do_sample=True,
             top_p=float(top_p),
             temperature=float(temperature),
-            min_length=20,
-            length_penalty=1.2
+            min_length=10,
+            length_penalty=1.0
         )
         decoded = paraphrase_tokenizer.batch_decode(outputs, skip_special_tokens=True)
 
@@ -69,16 +69,16 @@ def paraphrase_fn(text, num_return_sequences=1, temperature=1.2, top_p=0.92):
     return " ".join(all_outputs).strip()
 
 # ------------------------
-# Stage 2: Expansion
+# Stage 2: Light Expansion
 # ------------------------
-def expand_text(text, temperature=0.9, top_p=0.95):
+def expand_text(text, temperature=0.7, top_p=0.9):
     expanded = expander(
-        f"Expand and make this text more detailed, natural, and human-like:\n{text}",
-        max_new_tokens=250,
+        f"Lightly enhance this text by adding small natural words, transitions, or adjectives (like 'actually', 'quite', 'additionally', 'really'). Do NOT rewrite completely:\n{text}",
+        max_new_tokens=80,
         temperature=float(temperature),
         top_p=float(top_p)
     )[0]['generated_text']
-    return expanded
+    return expanded.strip()
 
 # ------------------------
 # Final Pipeline
@@ -90,7 +90,7 @@ def humanize_pipeline(text, variants=1, temperature=1.2, top_p=0.92):
     # Stage 1: Paraphrase
     base = paraphrase_fn(text, num_return_sequences=variants, temperature=temperature, top_p=top_p)
 
-    # Stage 2: Expand & Smooth
+    # Stage 2: Light Expansion
     expanded = expand_text(base, temperature=temperature, top_p=top_p)
 
     return expanded
@@ -107,8 +107,8 @@ iface = gr.Interface(
         gr.Slider(0.6, 1.0, step=0.01, value=0.92, label="Top-p"),
     ],
     outputs=gr.Textbox(label="Final Humanized Text"),
-    title="📝 Writenix Humanizer v2",
-    description="Two-stage pipeline: Paraphrase + Expand. Produces longer, more natural, human-like rewrites that are harder to detect."
+    title="📝 Writenix Humanizer v3 (Light Mode)",
+    description="Two-stage pipeline: Paraphrase + Subtle Expansion. Adds natural filler words, transitions, and adjectives instead of rewriting everything."
 )
 
 iface.launch()