input: Write a function to generate responses using a trained model and DialogFlow.
  assert generate_response("Hello, how can I help you?") == "response_text_based_on_model"
  assert generate_response("What is the weather like today?") == "response_text_based_on_model"
  assert generate_response("Tell me a joke") == "response_text_based_on_model"
output: def generate_response(user_input):
      import dialogflow_v2 as dialogflow
      from google.api_core.exceptions import InvalidArgument
  
      DIALOGFLOW_PROJECT_ID = 'your-project-id'
      DIALOGFLOW_LANGUAGE_CODE = 'en'
      SESSION_ID = 'current-user-id'
  
      session_client = dialogflow.SessionsClient()
      session = session_client.session_path(DIALOGFLOW_PROJECT_ID, SESSION_ID)
      
      text_input = dialogflow.types.TextInput(text=user_input, language_code=DIALOGFLOW_LANGUAGE_CODE)
      query_input = dialogflow.types.QueryInput(text=text_input)
  
      try:
          response = session_client.detect_intent(session=session, query_input=query_input)
      except InvalidArgument:
          raise
  
      return response.query_result.fulfillment_text