Create app.py

app.py

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+from transformers import pipeline, AutoTokenizer, AutoModelForQuestionAnswering
+import gradio as gr
+import time
+
+# Author information
+author = "Chris Choodai"
+
+tokenizer = AutoTokenizer.from_pretrained("distilbert-base-cased-distilled-squad")
+model = AutoModelForQuestionAnswering.from_pretrained("distilbert-base-cased-distilled-squad")
+qa_pipe = pipeline("question-answering", model=model, tokenizer=tokenizer)
+
+def response(context, question):
+    result = qa_pipe(context=context, question=question)
+    return result['answer']
+
+input_context = gr.Textbox(lines=10, label='Input Context', placeholder='Enter context here...')
+input_question = gr.Textbox(label='Input Question', placeholder='Ask your question here...')
+output_text = gr.Textbox(label="Response", placeholder='Response will display here..')
+
+interface = gr.Interface(response, inputs=[input_context, input_question], outputs=output_text,
+                        title="<div style='color: #336699; font-size: 24px; font-weight: bold; border: 2px solid #336699; padding: 10px; border-radius: 10px;'>Bert Context Based Question Answering</div>",
+                        description=f"""<div style='color: #666666; font-family: Arial, sans-serif;'>
+                                        <p style='margin-top: 10px;'>Enter context and question to get the response.</p>
+                                        <p>Developed by <span style='color: #336699; font-weight: bold;'>{author}</span>.</p>
+                                        </div>""",
+                        theme="default" # Change theme to default
+                        )
+
+# Define example contexts, questions, and expected responses
+examples = [
+    ["The capital of France is Paris.", "What is the capital of France?", "Paris"],
+    ["Water boils at 100 degrees Celsius or 212 degrees Fahrenheit.", "At what temperature does water boil?", "100 degrees Celsius"],
+    ["The Mona Lisa was painted by Leonardo da Vinci.", "Who painted the Mona Lisa?", "Leonardo da Vinci"],
+]
+
+def simulate_interaction():
+    for example in examples:
+        context, question, expected_response = example
+        input_context.value = context
+        input_question.value = question
+        time.sleep(2)  # Simulating user typing delay
+        response_text = response(context, question)
+        output_text.value = response_text
+        time.sleep(2)  # Simulating response delay
+
+# Simulate user interaction
+simulate_interaction()
+# Deploy the interface
+interface.launch(share=True, debug=True)