Update app.py

app.py

@@ -140,6 +140,25 @@ def classify_interface(text):
 def generate_interface(prompt, length=50, temp=0.7):
     return generate_text(prompt, textgen_model, textgen_tokenizer, max_length=int(length), temperature=float(temp))
 
+# Define example inputs for the classifier
+classifier_examples = [
+    ["The process of photosynthesis converts light energy into chemical energy, producing oxygen as a byproduct."],
+    ["The Pythagorean theorem states that in a right-angled triangle, the square of the length of the hypotenuse equals the sum of squares of the other two sides."],
+    ["The Industrial Revolution began in Great Britain in the late 18th century and spread to other parts of Europe and North America."],
+    ["Atoms consist of a nucleus containing protons and neutrons, surrounded by electrons that orbit in energy levels."],
+    ["Differential equations are mathematical equations that relate a function with its derivatives, representing rates of change."],
+    ["The Treaty of Versailles was signed in 1919, officially ending World War I and imposing harsh penalties on Germany."]
+]
+
+# Define example inputs for the text generator
+generator_examples = [
+    ["The structure of DNA consists of", 50, 0.7],
+    ["Newton's laws of motion explain", 75, 0.8],
+    ["Climate change affects ecosystems by", 100, 0.7],
+    ["Quantum mechanics revolutionized physics when", 60, 0.9],
+    ["Chemical reactions occur when", 50, 0.6]
+]
+
 # Create Gradio interface
 with gr.Blocks(title="Science Text Analyzer") as demo:
     gr.Markdown("# Science Text Analyzer")
@@ -156,6 +175,16 @@ with gr.Blocks(title="Science Text Analyzer") as demo:
                 classify_button = gr.Button("Classify")
             with gr.Column():
                 output = gr.Textbox(label="Classification Result", placeholder="The predicted subject and confidence will appear here.")
+        
+        # Add examples for the classifier
+        gr.Examples(
+            examples=classifier_examples,
+            inputs=text_input,
+            outputs=output,
+            fn=classify_interface,
+            cache_examples=True
+        )
+        
         classify_button.click(fn=classify_interface, inputs=text_input, outputs=output)
     
     with gr.Tab("Generate Text"):
@@ -172,6 +201,16 @@ with gr.Blocks(title="Science Text Analyzer") as demo:
                 generate_button = gr.Button("Generate")
             with gr.Column():
                 generated_output = gr.Textbox(label="Generated Text", lines=8, placeholder="The generated text will appear here.")
+        
+        # Add examples for the text generator
+        gr.Examples(
+            examples=generator_examples,
+            inputs=[prompt_input, length_slider, temp_slider],
+            outputs=generated_output,
+            fn=generate_interface,
+            cache_examples=True
+        )
+        
         generate_button.click(fn=generate_interface, inputs=[prompt_input, length_slider, temp_slider], outputs=generated_output)
 
     gr.Markdown("### About This App")
@@ -182,6 +221,5 @@ with gr.Blocks(title="Science Text Analyzer") as demo:
     "for **educational research**, **content creation**, and **curriculum support**."
 )
 
-
 # Launch the app
-demo.launch()
+demo.launch()