replaced with text gen task

app.py

@@ -10,10 +10,8 @@ translator_en_id = pipeline("translation_en_to_id", model="Helsinki-NLP/opus-mt-
 translator_id_en = pipeline("translation_id_to_en", model="Helsinki-NLP/opus-mt-id-en")
 ner = pipeline("ner", grouped_entities=True)
 
-# New: Load dictionary/thesaurus model
-#dictionary_model = pipeline("text2text-generation", model="google/flan-t5-large")
-dictionary_model = pipeline("text2text-generation", model="google/flan-t5-small")
-
+# New: Text Generation pipeline
+text_generator = pipeline("text-generation", model="gpt2")
 
 # Functions for each feature
 def summarize_text(text):
@@ -57,12 +55,11 @@ def extract_entities(text):
     formatted = "\n".join([f"{e['entity_group']}: {e['word']}" for e in entities])
     return formatted
 
-# New: Dictionary + Thesaurus function
-def define_and_list_synonyms(word):
-    if not word.strip():
-        return "Please enter a word."
-    prompt = f"Define the word '{word}' and give 5 related words or synonyms."
-    result = dictionary_model(prompt, max_new_tokens=60)
+# New: Text Generation function
+def generate_text(prompt):
+    if not prompt.strip():
+        return "Please enter a starting phrase."
+    result = text_generator(prompt, max_length=100, num_return_sequences=1)
     return result[0]["generated_text"]
 
 # Build Gradio interface
@@ -70,7 +67,7 @@ with gr.Blocks() as demo:
     gr.Markdown("# Multi-Function AI Assistant")
     gr.Markdown(
         "This app provides **Text Summarization**, **Question Answering**, **Sentiment Analysis**, "
-        "**Translation**, **Named Entity Recognition**, and a **Dictionary-Thesaurus**. "
+        "**Translation**, **Named Entity Recognition**, and **Text Generation**. "
         "All models run efficiently on CPU, suitable for free tier deployment."
     )
 
@@ -99,24 +96,24 @@ with gr.Blocks() as demo:
         ner_button = gr.Button("Extract Entities")
         ner_button.click(extract_entities, inputs=ner_input, outputs=ner_output)
 
-    with gr.Tab("Translation (EN → BM)"):
+    with gr.Tab("Translation (EN → ID)"):
         trans_input = gr.Textbox(label="Enter English text", lines=4, placeholder="Type English text here...")
-        trans_output = gr.Textbox(label="Malay Translation", lines=3)
+        trans_output = gr.Textbox(label="Indonesian Translation", lines=3)
         trans_button = gr.Button("Translate")
         trans_button.click(translate_en_to_id, inputs=trans_input, outputs=trans_output)
 
-    with gr.Tab("Translation (BM → EN)"):
-        trans_input = gr.Textbox(label="Enter Malay text", lines=4, placeholder="Type Malay text here...")
+    with gr.Tab("Translation (ID → EN)"):
+        trans_input = gr.Textbox(label="Enter Indonesian text", lines=4, placeholder="Type Indonesian text here...")
         trans_output = gr.Textbox(label="English Translation", lines=3)
         trans_button = gr.Button("Translate")
         trans_button.click(translate_id_to_en, inputs=trans_input, outputs=trans_output)
 
-    # New: Dictionary + Thesaurus Tab
-    with gr.Tab("Dictionary + Thesaurus"):
-        dict_input = gr.Textbox(label="Enter a word", placeholder="e.g., resilient")
-        dict_output = gr.Textbox(label="Definition and Related Words", lines=4)
-        dict_button = gr.Button("Get Meaning and Synonyms")
-        dict_button.click(define_and_list_synonyms, inputs=dict_input, outputs=dict_output)
+    # New: Text Generation Tab
+    with gr.Tab("Text Generation"):
+        gen_input = gr.Textbox(label="Enter a starting phrase", lines=3, placeholder="e.g., Once upon a time")
+        gen_output = gr.Textbox(label="Generated Text", lines=6)
+        gen_button = gr.Button("Generate")
+        gen_button.click(generate_text, inputs=gen_input, outputs=gen_output)
 
     gr.Markdown(
         "### Notes:\n"