Abstract: A device detects a trigger to toggle from a local mode to a query mode, the trigger detected based on input into a notebook interface relating to a dataframe. The device receives input of a query into a cell within the notebook interface, the query relating to the dataframe, and determines, based on having entered the query mode, to combine the query with a prior query from a prior cell within the notebook interface, resulting in generation of an combined query. The device executes the combined query with respect to a data warehouse, receives a command to perform a function with respect to the combined query, and determines, based on characteristics of the command, to execute the command using memory of the notebook interface. The device outputs, using the notebook interface, a graphical representation of results of the command, the results informed by the combined query.

Abstract: An application receives a natural language query from a user into a cell of a notebook environment and responsively determines a set of precedent cells and a profile of the user. The application determines a portion of the data warehouse graph that corresponds to the natural language query. The application primes the large language model with priming context that is based on the portion of the data warehouse graph that corresponds to the natural language query, the precedent cells from which the code cell depends, and the profile of the user, the priming resulting in a primed large language model. The application inputs the natural language query into the primed large language model and receives, as output from the large language model, a response to the natural language query. The application provides the response to the natural language query to the user.

Abstract: An application receives, in a code cell connected to a plurality of cells in a graph structure, a natural language command to generate code. The application determines, using directed edges of the graph structure, a set of precedent cells from which the code cell depends. The application inputs into a machine learning model the natural language command and values from the set of precedent cells pertaining to the code, and receives, as output from the machine learning model, generated code. The application updates the code cell to include the generated code.

Abstract: A device detects a trigger to toggle from a local mode to a query mode, the trigger detected based on input into a notebook interface relating to a dataframe. The device receives input of a query into a cell within the notebook interface, the query relating to the dataframe, and determines, based on having entered the query mode, to combine the query with a prior query from a prior cell within the notebook interface, resulting in generation of an combined query. The device executes the combined query with respect to a data warehouse, receives a command to perform a function with respect to the combined query, and determines, based on characteristics of the command, to execute the command using memory of the notebook interface. The device outputs, using the notebook interface, a graphical representation of results of the command, the results informed by the combined query.