Update app.py

app.py

@@ -178,14 +178,14 @@ agent_executor = AgentExecutor(agent=agent, tools=tools, memory= memory, verbose
 max_iterations = 5
 iterations = 0
 
-def answer_question(user_question, city="United Arab Emirates"):
+def answer_question(user_question):
     """
     This function takes a user question as input and generates a response using an agent executor.
     It iterates until a valid response is generated or the maximum number of iterations is reached.
 
     Parameters:
     - user_question (str): The question asked by the user.
-    - city (str): The city to use for the agent executor. Default is "United Arab Emirates".
+    
 
     Returns:
     - str: The generated response or an error message if no valid response is generated within the iteration limit.
@@ -215,8 +215,7 @@ def answer_question(user_question, city="United Arab Emirates"):
     response_text = response_text.replace('\n', ' ').replace('  ', ' ').strip()
 
     return response_text
-#css_code='body{background-image:url("https://picsum.photos/seed/picsum/200/300");}'
-css_code = ".gradio-container {background: url(https://picsum.photos/seed/picsum/200/300);}"
+
 # Create the Gradio interface
 iface = gr.Interface(
     fn=answer_question,
@@ -224,7 +223,7 @@ iface = gr.Interface(
     outputs="text",
     title="Chat with your data",
     description="Ask a question about the database or API or a document and get a response in natural language.",
-    #css=css_code
+    
 )
 
 # Launch the Gradio interface