Challenge

Training the Language Model to comprehend customized user requirements more effectively and deliver answers with greater accuracy involved an iterative process. Grasping the input flow to input into the model, enabling it to comprehend information in a formatted structure, proved complex and necessitated various batch processes.

Approach

when a user poses a question through the UI, it is relayed to OpenAI for processing. OpenAI comprehends the question and generates SQL queries based on the input we've previously provided to the assistant. These generated queries are then employed to retrieve data from Snowflake. Finally, the fetched data is presented back to the user in the UI. This streamlined process ensures efficient interaction between the user interface, OpenAI, Snowflake, and the user, facilitating seamless information retrieval.

Outcome

enabled business users to access information from Snowflake without the need to manually input queries. Through the streamlined process, the user can effortlessly retrieve the desired data through the UI by just a simple question, enhancing efficiency and usability.