Retrieval-Based Chatbots
Retrieval-based chatbots are AI systems that generate responses by selecting from a predefined set of possible replies, rather than generating new text from scratch. They use techniques like pattern matching, rule-based logic, or machine learning models to retrieve the most appropriate response from a database or knowledge base. This approach is common in customer service bots, FAQ systems, and simple conversational agents where responses need to be controlled and accurate.
Developers should learn retrieval-based chatbots when building applications that require reliable, consistent, and safe responses, such as in customer support, educational tools, or information retrieval systems. They are ideal for scenarios with limited or predictable user inputs, as they avoid the unpredictability and potential errors of generative models, making them easier to deploy and maintain in production environments.