added description and example

app.py

@@ -12,6 +12,18 @@ import tempfile
 from inference.model_inference import Inference
 from configs import *
 
+DESC_MD = """
+
+### This space is a demo for [Major Entity Identification (MEI)](https://arxiv.org/abs/2406.14654). MEI takes entities as additional input and aims to detect the mentions that refer only to these entities.
+
+### Place the text in the text box with a single phrase of a selected entity in double curly braces(example: a single instance of {{Ron}} if you want to track Ron). Note that you can select one phrase for each entity and multiple entities can be selected. Check out the example below for clarity.
+
+### The demo provides a json file with clusters and an HTML file with visualizations. The visualizations are color-coded based on the clusters.
+
+### Static: Uses an instance of: MEIRa-S model
+### Hybrid: Uses an instance of: MEIRa-H model
+"""
+
 
 def get_MEIRa_clusters(doc_name, text, model_type):
     model_str = MODELS[model_type]
@@ -117,7 +129,7 @@ with gr.Blocks() as demo:
         fn=coref_visualizer,
         inputs=[
             gr.Textbox(lines=1, placeholder="Enter document name:"),
-            gr.Textbox(lines=100, placeholder="Enter text for coreference resolution:"),
+            gr.Textbox(lines=10, placeholder="Enter text for coreference resolution:"),
             gr.Radio(choices=options, label="Select an Option"),
         ],
         outputs=[
@@ -126,7 +138,15 @@ with gr.Blocks() as demo:
             html_button,
             json_button,
         ],
-        title="Coreference Resolution Visualizer",
+        title="MEI Visualizer",
+        description=DESC_MD,
+        examples=[
+            [
+                "example",
+                "{{Harry}} went to Hogwarts to meet Hemoine and {{Ron}} . He also met Ron's mother at the railway station.",
+                "static",
+            ]
+        ],
     )
 
 demo.launch(debug=True)