changed website theme and added description

app.py

@@ -206,7 +206,9 @@ def interface():
         # prompt = template_single.format(tab_name, textbox_prompt)
 
         with gr.Tab("Linguistic Entities"):
-            gr.Markdown(" Description Here ")
+            gr.Markdown("<h2>📜 Rules<h2>")
+            gr.Markdown("<h4>- Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5). \n- Enter your OpenAI Api Key and click on 'Submit Key'. \n- Select a Linguistic Entity from the Dropdown. \n- Click 'Submit' to send your inputs to the models. \n- Scroll to the bottom and click 'Clear' to start again.<h4>")
+            gr.Markdown("<h4>🤖 Now the models will output the linguistic entities found in your prompt based on your selections!")
 
             # Inputs
             ling_ents_prompt = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
@@ -243,7 +245,9 @@ def interface():
             #                     outputs=[linguistic_entities, ling_ents_prompt, gpt_ling_ents_chatbot])
 
         with gr.Tab("POS/Chunking"):
-            gr.Markdown(" Description Here ")
+            gr.Markdown("<h2>📜 Rules<h2>")
+            gr.Markdown("<h4>- Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5). \n- Enter your OpenAI Api Key and click on 'Submit Key'. \n- Select a Task from the Dropdown \n- Select a Linguistic Entity from the Dropdown. \n- Click 'Submit' to send your inputs to the models. \n- Scroll to the bottom and click 'Clear' to start again.<h4>")
+            gr.Markdown("<h4>🤖 Now the models will output the POS Tagging or Chunking in your prompt with three Strategies based on your selections!")
 
             # Inputs
             task_prompt = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
@@ -305,7 +309,7 @@ def interface():
             # task_btn.click(gpt_strategies_respond, inputs=[strategy1, task, task_linguistic_entities, gpt_S3_chatbot], 
             #                     outputs=[task, task_prompt, gpt_S3_chatbot])
 
-with gr.Blocks() as demo:
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("# LLM Evaluator With Linguistic Scrutiny")
 
     # load interface