Systems and methods for distributing intent models
Systems, methods, and non-transitory computer-readable media can receive, from a first entity, training data for training an intent model associated with a first intent of a plurality of intents. A first intent model associated with the first intent is generated based on the training data. The first intent model is made available in an intent marketplace for access by a second entity.
1. A computer-implemented method comprising:
receiving, by a computing system, from a first entity, training data for training an intent model associated with a first intent of a plurality of intents, wherein the training data comprises a plurality of natural language statements associated with the first intent;
generating, by the computing system, a first intent model associated with the first intent based on the training data, wherein the first intent model is trained to process natural language requests associated with the first intent;
making, by the computing system, the first intent model available in an intent marketplace for access by other entities to process natural language requests using the first intent model;
receiving, by the computing system, an indication that a second entity has purchased access to the first intent model in order to process natural language requests associated with the first intent and directed to the second entity; and
processing, by the computing system, a natural language request directed to the second entity using the first intent model based on a determination that the second entity has purchased access to the first intent model.
2. The computer-implemented method of claim 1 , wherein the training data comprises a set of private training data and a set of public training data.
3. The computer-implemented method of claim 2 , wherein the first intent model is a public intent model generated based on the set of public training data without utilizing the set of private training data.
4. The computer-implemented method of claim 3 , further comprising generating a second intent model associated with the first intent based at least on the set of private training data.
5. The computer-implemented method of claim 4 , wherein the first intent model is made available in the intent marketplace, and the second intent model is not made available in the intent marketplace.
6. The computer-implemented method of claim 1 , further comprising:
testing the first intent model based on a set of testing data; and
publishing results of the testing the first intent model in the intent marketplace.
7. The computer-implemented method of claim 6 , wherein
the set of testing data comprises a plurality of natural language user requests, and
the testing the first intent model comprises processing the plurality of natural language user requests based on the first intent model.
8. A system comprising:
at least one processor; and
a memory storing instructions that, when executed by the at least one processor, cause the system to perform a method comprising:
receiving, from a first entity, training data for training an intent model associated with a first intent of a plurality of intents, wherein the training data comprises a plurality of natural language statements associated with the first intent;
generating a first intent model associated with the first intent based on the training data wherein the first intent model is trained to process natural language requests associated with the first intent;
making the first intent model available in an intent marketplace for access by other entities to process natural language requests using the first intent model;
receiving an indication that a second entity has purchased access to the first intent model in order to process natural language requests associated with the first intent and directed to the second entity; and
processing a natural language request directed to the second entity using the first intent model based on a determination that the second entity has purchased access to the first intent model.
9. The system of claim 8 , wherein the training data comprises a set of private training data, and a set of public training data.
10. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:
receiving, from a first entity, training data for training an intent model associated with a first intent of a plurality of intents, wherein the training data comprises a plurality of natural language statements associated with the first intent;
generating a first intent model associated with the first intent based on the training data wherein the first intent model is trained to process natural language requests associated with the first intent;
making the first intent model available in an intent marketplace for access by other entities to process natural language requests using the first intent model;
receiving an indication that a second entity has purchased access to the first intent model in order to process natural language requests associated with the first intent and directed to the second entity; and
processing a natural language request directed to the second entity using the first intent model based on a determination that the second entity has purchased access to the first intent model.
11. The non-transitory computer-readable storage medium of claim 10 , wherein the training data comprises a set of private training data, and a set of public training data.