Add agent workflow diagram and enhance agent description in app.py

app.py

@@ -4,16 +4,41 @@ from basic_llama_agent import BasicLammaAgent
 
 agent_instance = BasicLammaAgent()
 
-async def llmResponse(message, *args): 
+
+async def llmResponse(message, *args):
     return await agent_instance(message)
 
-demo = gr.ChatInterface(
+agent_chat = gr.ChatInterface(
     llmResponse,
     title="Personalized News Agent",
-    description="An agent that helps you manage your interests and get personalized news with sentiment, entity analysis, implications, background events, and social media opinion levels.",
+    description=(
+        "A conversational agent that helps you discover and analyze news on topics of your interest. "
+        "You can:\n"
+        "- Get the latest news articles for your query\n"
+        "- Ask for implications of a news article\n"
+        "- Request background events leading up to a news story\n"
+        "- Explore summarized social media reactions (positive/negative) to news events\n\n"
+        "The agent uses tools for news retrieval, implication generation, event chronology, and social sentiment analysis."
+    ),
     type="messages"
 )
 
+info_tab = gr.Blocks()
+with info_tab:
+    gr.Markdown("# Personalized News Agent")
+    gr.Markdown(
+        "A conversational agent that helps you discover and analyze news on topics of your interest. "
+        "You can:\n"
+        "- Get the latest news articles for your query\n"
+        "- Ask for implications of a news article\n"
+        "- Request background events leading up to a news story\n"
+        "- Explore summarized social media reactions (positive/negative) to news events\n\n"
+        "The agent uses tools for news retrieval, implication generation, event chronology, and social sentiment analysis.")
+    gr.Image(value="agent_diagram.png", label="Agent Workflow Diagram")
+
+
+demo = gr.TabbedInterface([info_tab, agent_chat], ["Info", "Agent Chat"])
+
 
 if __name__ == "__main__":
     demo.launch()