Update app.py

app.py

@@ -146,15 +146,32 @@ def fact_check_flow(user_question):
     # Step 5: Use scraped data as context and run generate chain
 
     final_response = generate_chain.invoke({"question": user_question, "context": context})
+
+    # Process output
+    verdict = final_response['system_verdict']
+    explanation = final_response['explanation']
+    
+    if verdict == "Fact":
+        verdict_html = f"<span style='color:green; font-size: 24px;'><strong>{verdict}</strong></span>"
+    else:
+        verdict_html = f"<span style='color:red; font-size: 24px;'><strong>{verdict}</strong></span>"
     
-    return final_response
+    explanation_html = f"<p style='font-size: 14px;'>{explanation}</p>"
+    
+    return verdict_html + explanation_html
 
 # Example Use
 # user_question = "biden is not joining election in 2024"
 # result = fact_check_flow(user_question)
 # print(result)
 
-demo = gr.Interface(fn=fact_check_flow, inputs="textbox", outputs="textbox")
+demo = gr.Interface(
+    fn=fact_check_flow,
+    inputs="textbox",
+    outputs="html", 
+    title="Fact or Fiction: LLama-powered Fact-Checker AI Agent",
+    description="This is a fact checker engine that uses web crawling and LLM for verifying user information. This prototype is being used by the author to submit a proposal for Meta's competition."
+)
 
 if __name__ == "__main__":
     demo.launch()