Chatbot Development and Integration Flashcards

What is the purpose of a 'context object' passed between chatbot dialogue turns?

Answer: Carrying conversation state such as confirmed entities and prior intents across multiple messages

The context object is the bot's working memory during a session, enabling coherent multi-step conversations.

Which integration method allows a chatbot to look up real-time data like inventory or account balances?

Answer: Live API calls to backend systems during the conversation

Real-time API integrations let chatbots fetch up-to-date information from backend systems to give accurate, live responses.

What is 'human handoff' integration in enterprise chatbots?

Answer: Seamlessly transferring a conversation to a live human agent when the bot cannot adequately help

Human handoff passes the conversation, including full context history, to a live agent so the user doesn't have to repeat themselves.

What role does a 'message broker' play in high-scale chatbot architectures?

Answer: Decoupling message intake from processing to ensure reliability under high traffic loads

Message brokers like Kafka or RabbitMQ queue incoming messages, preventing overload and ensuring every message is processed.

Why is 'idempotency' important when chatbots process webhook events?

Answer: To ensure that duplicate event deliveries don't cause the same action to be performed multiple times

Idempotent handlers check for duplicate event IDs so retried webhook deliveries don't trigger repeated actions like duplicate charges.

What is the benefit of using a 'bot framework' like Microsoft Bot Framework or Rasa?

Answer: They provide reusable components for NLU, dialogue management, and channel connectors, accelerating development

Bot frameworks abstract common chatbot infrastructure, letting developers focus on business logic rather than rebuilding core components.