Update app.py

app.py

@@ -1,41 +1,79 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load grammar correction model
-grammar_corrector = pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
+# Load models
+grammar_model = pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
+meaning_model = pipeline("text2text-generation", model="facebook/bart-large-cnn")
 
-# Load text generation model for meaning & phrase suggestion
-meaning_generator = pipeline("text2text-generation", model="facebook/bart-large-cnn")
-
-def analyze_text(user_input):
+def dictionary_grammar_bot(user_input):
     try:
-        # Grammar correction
-        corrected = grammar_corrector(user_input, max_length=128, clean_up_tokenization_spaces=True)[0]['generated_text']
+        # --- Grammar Correction ---
+        grammar_output = grammar_model(
+            user_input,
+            max_new_tokens=128,
+            clean_up_tokenization_spaces=True
+        )[0]['generated_text']
+
+        # --- Meaning / Definition ---
+        meaning_prompt = f"Explain the meaning and definition of the word or phrase: {user_input}"
+        meaning_output = meaning_model(
+            meaning_prompt,
+            max_new_tokens=200,
+            clean_up_tokenization_spaces=True
+        )[0]['generated_text']
+
+        # --- Phrase Suggestions ---
+        phrase_prompt = f"Suggest grammatically correct alternative phrases or rephrasings for: {user_input}"
+        phrase_output = meaning_model(
+            phrase_prompt,
+            max_new_tokens=120,
+            clean_up_tokenization_spaces=True
+        )[0]['generated_text']
+
+        # --- Example Sentence ---
+        sentence_prompt = f"Write an example sentence using the phrase: {user_input}"
+        sentence_output = meaning_model(
+            sentence_prompt,
+            max_new_tokens=120,
+            clean_up_tokenization_spaces=True
+        )[0]['generated_text']
+
+        # Format structured output
+        response = f"""
+### 🧩 Grammar Correction
+{grammar_output}
+
+---
+
+### 📘 Meaning / Definition
+{meaning_output}
+
+---
+
+### 💬 Phrase Suggestions
+{phrase_output}
 
-        # Meaning / Usage generation
-        meaning_prompt = f"Explain the meaning and usage of the phrase: {user_input}"
-        meaning = meaning_generator(meaning_prompt, max_length=150, clean_up_tokenization_spaces=True)[0]['generated_text']
+---
 
-        # Phrase suggestion
-        phrase_prompt = f"Suggest a few grammatically correct alternative phrases for: {user_input}"
-        phrases = meaning_generator(phrase_prompt, max_length=100, clean_up_tokenization_spaces=True)[0]['generated_text']
+### ✏️ Example Sentence
+{sentence_output}
+"""
 
-        return (
-            f"🧠 **Grammar Corrected:** {corrected}\n\n"
-            f"📘 **Meaning & Usage:** {meaning}\n\n"
-            f"💬 **Phrase Suggestions:** {phrases}"
-        )
+        return response
 
     except Exception as e:
         return f"⚠️ Error: {str(e)}"
 
-# Gradio UI
+# --- Gradio UI ---
 iface = gr.Interface(
-    fn=analyze_text,
-    inputs=gr.Textbox(label="Enter a word, phrase, or sentence", placeholder="Type here..."),
+    fn=dictionary_grammar_bot,
+    inputs=gr.Textbox(
+        label="Enter a word, phrase, or sentence",
+        placeholder="Example: resistance movement failed"
+    ),
     outputs=gr.Markdown(label="AI Response"),
     title="Dictionary & Grammar Chatbot",
-    description="AI-powered chatbot that provides meanings, grammar corrections, and phrase suggestions.",
+    description="AI-powered chatbot that provides meanings, grammar corrections, phrase suggestions, and example sentences.",
     theme="gradio/soft"
 )