✨ Updated grammar logic with prompt instruction

app.py

@@ -11,25 +11,33 @@ model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
 def correct_grammar(text):
     if not text.strip():
         return "Please enter some text to correct."
-    
-    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
-    with torch.no_grad():
-        outputs = model.generate(
-            **inputs,
-            max_length=512,
-            num_beams=5,
-            early_stopping=True,
-            do_sample=False
-        )
-    return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
+    # Add instruction to prompt
+    prompt = f"Fix grammar: {text}"
+
+    try:
+        inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
+        with torch.no_grad():
+            outputs = model.generate(
+                **inputs,
+                max_length=128,
+                num_beams=5,
+                early_stopping=True,
+                temperature=0.7,
+                do_sample=False
+            )
+        return tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
+    except Exception as e:
+        return f"⚠️ Error: {str(e)}"
+
+# Gradio UI
 iface = gr.Interface(
     fn=correct_grammar,
     inputs=gr.Textbox(label="Enter text to correct", placeholder="Type here...", lines=3),
     outputs=gr.Textbox(label="Corrected text", lines=3),
     title="Grammar Correction",
-    description="Fixes grammar using a fine-tuned T5 model.",
-    examples=["She go to market.", "He don't like it.", "We was playing."]
+    description="Fix grammar errors using a fine-tuned T5 model. Example: 'He don't like it' → 'He doesn't like it'.",
+    examples=["She go to market.", "I is a boy", "He don't like apples", "We was playing outside"]
 )
 
 if __name__ == "__main__":