Intelligent query decomposition, specialized model routing, and hierarchical aggregation with conflict resolution

A method comprising:

• receiving, from a user, a query comprising a request relating to a particular domain;
• determining, based on the query, a set of sub-queries using a decomposition model trained to determine sub-queries;
• inputting the set of sub-queries into a routing model to determine a set of specialized models for the set of sub-queries, wherein the routing model is trained to assign sub-queries for input into a set of specialized models according to one or more routing strategies;
• for each particular sub-query in the set of sub-queries:
• routing the particular sub-query to a respective specialized model in the set of specialized models;
• inputting the particular sub-query into the respective specialized model to generate an output;
• assigning, to each respective output, a confidence score;
• and
• classifying one or more intents associated with the query by using a trained intent classification model to detect both a primary intent and at least one secondary intent within the query, wherein the trained intent classification model assigns a confidence score to each detected intent, and
• generating an aggregated output by combining the set of outputs according to (i) a weighted aggregation algorithm that prioritizes outputs with higher confidence scores and (ii) a plurality of conflict resolution rules, wherein the aggregated output is based at least in part on the one or more intents;
• and
• causing display of the aggregated output in response to the query.

A system comprising:

• a storage device;
• and
• one or more processors communicatively coupled to the storage device storing instructions thereon, that cause the one or more processors to:
• receive, from a user, a query comprising a request relating to a particular domain;
• determine, based on the query, a set of sub-queries using a decomposition model trained to determine sub-queries;
• utilize a load balancer, the load balancer being configured to distribute the set of sub-queries across multiple instances of the set of specialized models and manage allocation of system resources to the multiple instances of the set of specialized models,
• wherein the load balancer is further configured to prevent resource bottlenecks by directing each sub-query of the set of sub-queries to a selected instance of the set of specialized models based at least in part on a real-time system load and an availability of computational resources;
• input the set of sub-queries into a routing model to determine a set of specialized models for the set of sub-queries, wherein the routing model is trained to assign sub-queries for input into a set of specialized models according to one or more routing strategies;
• for each particular sub-query in the set of sub-queries:
• route the particular sub-query to a respective specialized model in the set of specialized models;
• input the particular sub-query into the respective specialized model to generate an output;
• and
• assign, to each respective output, a confidence score;
• generate an aggregated output by combining the set of outputs according to (i) a weighted aggregation algorithm that prioritizes outputs with higher confidence scores and (ii) a plurality of conflict resolution rules;
• and
• cause display of the aggregated output in response to the query.