Update app.py

app.py

@@ -143,6 +143,16 @@ def predict(user_input,company):
     return prediction
 
 
+examples = [
+    ["What are the company's policies and frameworks regarding AI ethics, governance, and responsible AI use as detailed in their 10-K reports?", "AWS"],
+    ["What are the primary business segments of the company, and how does each segment contribute to the overall revenue and profitability?", "AWS"],
+    ["What are the key risk factors identified in the 10-K report that could potentially impact the company's business operations and financial performance?", "AWS"],
+    ["Has the company made any significant acquisitions in the AI space, and how are these acquisitions being integrated into the company's strategy?", "Microsoft"],
+    ["How much capital has been allocated towards AI research and development?","Google"],
+    ["What initiatives has the company implemented to address ethical concerns surrounding AI, such as fairness, accountability, and privacy?","IBM"],
+    ["How does the company plan to differentiate itself in the AI space relative to competitors?","Meta"]
+]
+
 def get_predict(question, company):
     # Implement your prediction logic here
     if company == "AWS":
@@ -163,6 +173,11 @@ def get_predict(question, company):
     else:
         return "Invalid company selected"
 
+    # Implement your prediction logic here
+    for example_question, example_company in examples:
+        if question == example_question and selectedCompany == example_company:
+            return f"This is the output for the example question: {example_question}"
+
     output = predict(question, selectedCompany)
     return output
 
@@ -189,5 +204,7 @@ with gr.Blocks(theme="gradio/seafoam@>=0.0.1,<0.1.0") as demo:
         outputs=output
     )
 
+    examples_component = gr.Examples(examples=examples, inputs=[question, company])
+
 demo.queue()
 demo.launch(auth=("demouser", os.getenv('PASSWD')))