Update app.py

app.py

@@ -8,6 +8,13 @@ model = GLiNER.from_pretrained("numind/NuNER_Zero")
 
 classifier = pipeline("zero-shot-classification", model="MoritzLaurer/deberta-v3-base-zeroshot-v1")
 
+css = """
+h1 {
+    text-align: center;
+    display:block;
+}
+"""
+
 #define a function to process your input and output
 def zero_shot(doc, candidates):
     given_labels = candidates.split(", ")
@@ -16,12 +23,26 @@ def zero_shot(doc, candidates):
     scores = dictionary['scores']
     return dict(zip(labels, scores))
 
-examples = [
+examples_text = [
+    [
+    "I am very happy today",
+    "positive, negative"
+    ],
+    [
+    "This is a news about Soccer",
+    "world, politics, technology, sport"
+    ]
+]
+examples_ner = [
     [
         "The Moon is Earth's only natural satellite. It orbits at an average distance of 384,400 km (238,900 mi), about 30 times the diameter of Earth. Over time Earth's gravity has caused tidal locking, causing the same side of the Moon to always face Earth. Because of this, the lunar day and the lunar month are the same length, at 29.5 Earth days. The Moon's gravitational pull – and to a lesser extent, the Sun's – are the main drivers of Earth's tides.",
         "celestial body,quantity,physical concept",
-        0.3,
-        False
+        0.3
+    ],
+    [
+        "test aja",
+        "celestial body,quantity,physical concept",
+        0.3
     ],
 ]
 
@@ -62,37 +83,57 @@ def ner(
     r["entities"] =  merge_entities(r["entities"])
     return r
 
-with gr.Blocks(title="Zero-Shot Demo") as demo: #, theme=gr.themes.Soft()
+
+with gr.Blocks(title="Zero-Shot Demo", css=css) as demo: #, theme=gr.themes.Soft()
+
+    gr.Markdown(
+            """
+            # Zero-Shot Model Demo
+            """
+        )
 
     #create input and output objects
     with gr.Tab("Zero-Shot Text Classification"):
-        #input object1
-        input1 = gr.Textbox(label="Text")
-        #input object 2
-        input2 = gr.Textbox(label="Labels")
-        #output object
+
+        gr.Markdown(
+            """
+            ## Zero-Shot Text Classification
+            """
+        )
+
+        input1 = gr.Textbox(label="Text", value=examples_text[0][0])
+        input2 = gr.Textbox(label="Labels",value=examples_text[0][1])
         output = gr.Label(label="Output")
-        #create interface
+
         gui = gr.Interface(
-            title="Zero-Shot Text Classification",
+            # title="Zero-Shot Text Classification",
             fn=zero_shot,
             inputs=[input1, input2],
             outputs=[output]
         )
 
+        examples = gr.Examples(
+            examples_text,
+            fn=zero_shot,
+            inputs=[input1, input2],
+            outputs=output,
+            cache_examples=True,
+        )
+
+
     with gr.Tab("Zero-Shot NER"):
         gr.Markdown(
             """
-            # Zero-Shot Named Entity Recognition (NER)
+            ## Zero-Shot Named Entity Recognition (NER)
             """
         )
 
         input_text = gr.Textbox(
-            value=examples[0][0], label="Text input", placeholder="Enter your text here", lines=3
+            value=examples_ner[0][0], label="Text input", placeholder="Enter your text here", lines=3
         )
         with gr.Row() as row:
             labels = gr.Textbox(
-                value=examples[0][1],
+                value=examples_ner[0][1],
                 label="Labels",
                 placeholder="Enter your labels here (comma separated)",
                 scale=2,
@@ -100,7 +141,7 @@ with gr.Blocks(title="Zero-Shot Demo") as demo: #, theme=gr.themes.Soft()
             threshold = gr.Slider(
                 0,
                 1,
-                value=0.3,
+                value=examples_ner[0][2],
                 step=0.01,
                 label="Threshold",
                 info="Lower the threshold to increase how many entities get predicted.",
@@ -111,16 +152,14 @@ with gr.Blocks(title="Zero-Shot Demo") as demo: #, theme=gr.themes.Soft()
 
         submit_btn = gr.Button("Submit")
 
-        # Submitting
-        # input_text.submit(
-        #     fn=ner, inputs=[input_text, labels, threshold], outputs=output
-        # )
-        # labels.submit(
-        #     fn=ner, inputs=[input_text, labels, threshold], outputs=output
-        # )
-        # threshold.release(
-        #     fn=ner, inputs=[input_text, labels, threshold], outputs=output
-        # )
+        examples = gr.Examples(
+            examples_ner,
+            fn=ner,
+            inputs=[input_text, labels, threshold],
+            outputs=output,
+            cache_examples=True,
+        )
+
         submit_btn.click(
             fn=ner, inputs=[input_text, labels, threshold], outputs=output
         )