SYSTEMS AND METHODS FOR PROCESSING LANGUAGE MODEL DATA IN DISTRIBUTED COMPUTING ENVIRONMENTS
Systems and methods for processing language model data in distributed computing environments are disclosed. A system can receive, from a client device during a communication session, a prompt identifying a request. The system can determine that the prompt is to be augmented with additional information to satisfy the request. The system can retrieve, from at least one data source and based on the prompt, a set of additional contextual data to satisfy the request. The system can generate an input context using the prompt and the set of additional contextual data. The system can generate, using the language model and the input context, an output message identifying data relating to the request.
1 . A system, comprising:
one or more processors coupled to non-transitory memory, the one or more processors configured to:
maintain a data structure comprising a plurality of wager opportunities corresponding to a plurality of live events;
receive, from a client device, a prompt comprising a request for a wager recommendation;
generate, using a language model and the prompt, output identifying at least one wager opportunity of the plurality of wager opportunities selected to satisfy the request; and
provide the output to the client device in response to the request.
2 . The system of claim 1 , wherein the one or more processors are further configured to:
establish a communication session responsive to a message received from the client device; and
store the prompt and the output in a second data structure corresponding to the communication session.
3 . The system of claim 1 , wherein the one or more processors are further configured to:
provide a graphical user interface comprising an input field and an output region;
receive the prompt via the input field; and
provide the output for presentation at the client device via the output region.
4 . The system of claim 1 , wherein the one or more processors are further configured to:
generate an input context for the language model using the prompt and the data structure; and
provide the input context as input to the language model.
5 . The system of claim 4 , wherein the one or more processors are further configured to:
identify a subset of the plurality of wager opportunities using the prompt; and
generate the input context using data of the subset.
6 . The system of claim 1 , wherein the client device is associated with a player profile, and wherein the one or more processors are further configured to:
receive a second request to place at least one wager from the client device; and
update the player profile according to the second request to place the at least one wager.
7 . The system of claim 1 , wherein the one or more processors are further configured to:
receive an update corresponding to at least one live event of the plurality of live events; and
modify the data structure based on the update to the at least one live event.
8 . The system of claim 1 , wherein the prompt is a first prompt, and wherein the one or more processors are further configured to:
receive, from the client device, a second prompt identify an attribute for the wager recommendation; and
generate the output using the language model, the first prompt, and the second prompt.
9 . The system of claim 1 , wherein the client device is associated with a player profile, and wherein the one or more processors are further configured to:
generate the output further based on a one or more historical wagers identified in the player profile.
10 . The system of claim 1 , wherein the one or more processors are further configured to:
determine an intent metric based on the prompt; and
generate the output further based on the intent metric.
11 . A method, comprising:
maintaining, by one or more processors coupled to non-transitory memory, a data structure comprising a plurality of wager opportunities corresponding to a plurality of live events;
receiving, by the one or more processors, from a client device, a prompt comprising a request for a wager recommendation;
generating, by the one or more processors, using a language model and the prompt, output identifying at least one wager opportunity of the plurality of wager opportunities selected to satisfy the request; and
providing, by the one or more processors, the output to the client device in response to the request.
12 . The method of claim 11 , further comprising:
establishing, by the one or more processors, a communication session responsive to a message received from the client device; and
storing, by the one or more processors, the prompt and the output in a second data structure corresponding to the communication session.
13 . The method of claim 11 , further comprising:
providing, by the one or more processors, a graphical user interface comprising an input field and an output region;
receiving, by the one or more processors, the prompt via the input field; and providing, by the one or more processors, the output for presentation at the client device via the output region.
14 . The method of claim 11 , further comprising:
generating, by the one or more processors, an input context for the language model using the prompt and the data structure; and
providing, by the one or more processors, the input context as input to the language model.
15 . The method of claim 14 , further comprising:
identifying, by the one or more processors, a subset of the plurality of wager opportunities using the prompt; and
generating, by the one or more processors, the input context using data of the subset.
16 . The method of claim 11 , wherein the client device is associated with a player profile, and further comprising:
receiving, by the one or more processors, a second request to place at least one wager from the client device; and
updating, by the one or more processors, the player profile according to the second request to place the at least one wager.
17 . The method of claim 11 , further comprising:
receiving, by the one or more processors, an update corresponding to at least one live event of the plurality of live events; and
modifying, by the one or more processors, the data structure based on the update to the at least one live event.
18 . The method of claim 11 , wherein the prompt is a first prompt, and further comprising:
receiving, by the one or more processors, from the client device, a second prompt identify an attribute for the wager recommendation; and
generating, by the one or more processors, the output using the language model, the first prompt, and the second prompt.
19 . The method of claim 11 , wherein the client device is associated with a player profile, and further comprising:
generating, by the one or more processors, the output further based on a one or more historical wagers identified in the player profile.
20 . The method of claim 11 , further comprising:
determining, by the one or more processors, an intent metric based on the prompt; and generating, by the one or more processors, the output further based on the intent metric.