A real time Chat Application using Confluent
iLink is proud to be a part of the Build with Confluent initiative. By verifying our streaming-based use cases with Confluent, you can have confidence that our Confluent-based service offering is not only built on the leading data streaming platform but also verified by the experts at Confluent.
Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations.
Our data augmentation architecture relies on two primary sources: the “Flight Itinerary System” and the “Flight Policy System.” The Flight Policy System securely stores policy-related information in Azure Blob Storage, while the Flight Itinerary System contains flight customer data, flight itineraries, and flight gate details such as flight numbers, departure/arrival times, and routes.
To ensure continuous updates and availability of the most recent information, data from these sources is streamed into Confluent topics named “Flight Itinerary” and “Flight Policy” using Confluent connectors. Within Confluent Cloud, Flink SQL enriches the “Flight Customer Data,” “Flight Itineraries Data,” and “Flight Gate Data,” creating an enriched topic called “Flight Data.”
Our architecture integrates seamlessly with Azure App Service, which consumes data from Confluent topics and collaborates with the Language Model (LLM) “Chat GPT” to further enrich the data. The enriched data is stored in the Confluent topic “Flight Data Embeddings,” which natively integrates with Vector DB for additional analysis or storage.
In our real-time chat application, user queries are stored in the “Questions” topic. The Azure App Service backend analyzes these questions using Chat GPT, retrieves relevant answers from Vector DB, and stores them in the “Answers” topic within the Confluent environment. The Real-time Chat Application Front End Integration offers a user-friendly interface for seamless interaction with the chatbot, ensuring accurate and timely responses to inquiries.
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