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With the fetched data, the system aggregates information from both the flight and hotel searches. An LLM, equipped with a custom prompt, synthesizes this data to generate the travel recommendation, which includes pertinent details such as pricing and additional notes about each option.
4. User Interaction
In the user interface, the travel agent not only presents the suggested itinerary but also allows for further interaction. Users can ask for additional details or inquire about restaurants in their destination using a unique research tab.
5. Backend Infrastructure
The application utilizes a Flask backend that processes API requests and mediates data flows from Bright Data. This ensures secure handling of requests without exposing sensitive information.