Update app.py

app.py

@@ -1,33 +1,31 @@
 import gradio as gr
 from transformers import pipeline
+import difflib
 
-# Load the faster model
-model_name = "pszemraj/flan-t5-base-grammar-synthesis"  # ✅ Use flan-t5-base (faster)
-pipe = pipeline("text2text-generation", model=model_name, max_new_tokens=200)
+# Use a solid grammar correction + improvement model
+pipe = pipeline("text2text-generation", model="pszemraj/flan-t5-base-grammar-synthesis")
 
-# Word limit (adjust as needed)
-MAX_WORDS = 500
+def respond(prompt):
+    # Generate revised essay
+    revised = pipe(prompt, max_new_tokens=1024)[0]['generated_text']
 
-def check_essay(essay):
-    # Word limit enforcement
-    words = essay.strip().split()
-    if len(words) > MAX_WORDS:
-        return f"❗ Your essay is too long. Please limit it to {MAX_WORDS} words or less."
+    # Generate a word-level diff
+    diff = difflib.ndiff(prompt.split(), revised.split())
+    changes = [line for line in diff if line.startswith("- ") or line.startswith("+ ")]
 
-    # Run model
-    result = pipe(essay, max_new_tokens=200, temperature=0.5)
-    corrected_text = result[0]['generated_text']
-    return corrected_text
+    # Format explanation
+    if changes:
+        explanation = "\n".join(changes)
+    else:
+        explanation = "No significant changes were made. Minor improvements only."
 
-# Gradio interface
-iface = gr.Interface(
-    fn=check_essay,
-    inputs=gr.Textbox(lines=20, placeholder="Paste your essay here..."),
-    outputs=gr.Textbox(label="Revised Essay"),
-    title="Essay Checker (Fast & Free)",
-    description=f"Check and improve your essay instantly. Max {MAX_WORDS} words for speed."
-)
-
-if __name__ == "__main__":
-    iface.launch()
+    return f"📝 Revised Essay:\n\n{revised}\n\n🛠️ Explanation of Changes:\n\n{explanation}"
 
+# Set up Gradio interface
+gr.Interface(
+    fn=respond,
+    inputs="text",
+    outputs="text",
+    title="Free AI Essay Bot",
+    description="Paste an essay below. The AI will revise it and explain the changes."
+).launch()