Abstract: Examples provide conversational item search refinement using multi-facet filtering of items in a catalog. A multi-facet filter manager extracts facets and actions corresponding to the facets from a user utterance. The facet-actions include an entity-role and one or more filter actions associated with the facets. A facet-action includes filter actions such as exact, exclude, greater than, less than, etc. Multi-facet filters corresponding to the facet-actions are applied to a plurality of items in the catalog. The candidate items remaining after filtering are scored. The scores indicate relevance of each candidate item. One or more of the candidate items with the highest scores are selected. The selected items are added to search results which are returned to the user in response to the conversational search query. The multi-facet filter manager enables faster and more accurate search results using fewer conversational turns for reduced system resource usage and improved user efficiency.

Abstract: Some embodiments provide retail product ordering systems comprising: a user computing device comprising an application executed by a device control circuit to: receive an audible utterance; controls a product identifier application interface to: apply a tokenizer model and obtain a set of individual search words; apply a series of featurizer models to the search words to generate features; and apply a classifier and extractor model based on the features and generate multiple requested product entities each comprising a respective sub-set of the position labeled product terms; wherein the device control circuit is further configured to access a purchase history database, confirm an accuracy of each of requested product entities relative to a purchase history, generate a listing of determined product identifiers corresponding to the confirmed set of the multiple requested product entities, and control a display system of the user computing device to render the listing of determined product identifiers.

Abstract: Examples provide an autonomous application programming interface (API) agent for executing multiple APIs simultaneously in parallel or in sequence. The API agent performs a vector database similarity search using embeddings representing a user query and a plurality of candidate APIs to identify one or more relevant APIs for responding to the user query. The API agent utilizes a large language model (LLM) API orchestrator for performing dynamic slot filling to replace missing API parameters required for calling one or more of the relevant APIs. The API agent executes the query on the relevant APIs to obtain response data from the relevant APIs. The response data is filtered and combined into a single query response which is provided to a user in response to the query.

Abstract: Examples provide conversational item search refinement using multi-facet filtering of items in a catalog. A multi-facet filter manager extracts facets and actions corresponding to the facets from a user utterance. The facet-actions include an entity-role and one or more filter actions associated with the facets. A facet-action includes filter actions such as exact, exclude, greater than, less than, etc. Multi-facet filters corresponding to the facet-actions are applied to a plurality of items in the catalog. The candidate items remaining after filtering are scored. The scores indicate relevance of each candidate item. One or more of the candidate items with the highest scores are selected. The selected items are added to search results which are returned to the user in response to the conversational search query. The multi-facet filter manager enables faster and more accurate search results using fewer conversational turns for reduced system resource usage and improved user efficiency.

Abstract: Some embodiments provide retail product ordering systems comprising: a user computing device comprising an application executed by a device control circuit to: receive an audible utterance; controls a product identifier application interface to: apply a tokenizer model and obtain a set of individual search words; apply a series of featurizer models to the search words to generate features; and apply a classifier and extractor model based on the features and generate multiple requested product entities each comprising a respective sub-set of the position labeled product terms; wherein the device control circuit is further configured to access a purchase history database, confirm an accuracy of each of requested product entities relative to a purchase history, generate a listing of determined product identifiers corresponding to the confirmed set of the multiple requested product entities, and control a display system of the user computing device to render the listing of determined product identifiers.

Abstract: Some embodiments provide retail product ordering systems comprising: a user computing device comprising an application executed by a device control circuit to: receive an audible utterance; controls a product identifier application interface to: apply a tokenizer model and obtain a set of individual search words; apply a series of featurizer models to the search words to generate features; and apply a classifier and extractor model based on the features and generate multiple requested product entities each comprising a respective sub-set of the position labeled product terms; wherein the device control circuit is further configured to access a purchase history database, confirm an accuracy of each of requested product entities relative to a purchase history, generate a listing of determined product identifiers corresponding to the confirmed set of the multiple requested product entities, and control a display system of the user computing device to render the listing of determined product identifiers.

Abstract: Some embodiments provide retail product ordering systems comprising: a user computing device comprising an application executed by a device control circuit to: receive an audible utterance; controls a product identifier application interface to: apply a tokenizer model and obtain a set of individual search words; apply a series of featurizer models to the search words to generate features; and apply a classifier and extractor model based on the features and generate multiple requested product entities each comprising a respective sub-set of the position labeled product terms; wherein the device control circuit is further configured to access a purchase history database, confirm an accuracy of each of requested product entities relative to a purchase history, generate a listing of determined product identifiers corresponding to the confirmed set of the multiple requested product entities, and control a display system of the user computing device to render the listing of determined product identifiers.

Abstract: In some embodiments, methods and systems are provided for processing information requests of workers at a retail facility and retrieving information associated with the retail facility based on the information requests. An electronic device permits a worker at the retail facility to input an information request in association with at least one worker at the retail facility or at least one product at the retail facility. A computing device receives, from the electronic device, electronic data representative of a scope of the information request, analyzes this electronic data to determine the scope of the information request, obtain relevant information from one or more databases, and transmits the obtained information to the electronic device, which in turn outputs the information to the worker.

Abstract: In some embodiments, methods and systems are provided for processing information requests of workers at a retail facility and retrieving information associated with the retail facility based on the information requests. An electronic device permits a worker at the retail facility to input an information request in association with at least one worker at the retail facility or at least one product at the retail facility. A computing device receives, from the electronic device, electronic data representative of a scope of the information request, analyzes this electronic data to determine the scope of the information request, obtain relevant information from one or more databases, and transmits the obtained information to the electronic device, which in turn outputs the information to the worker.