SYSTEMS AND METHODS FOR GENERATING LANGUAGE MODEL CONTEXT ACCORDING TO LOCATION-BASE NETWORK MESSAGES

1 . A system, comprising:

one or more processors coupled to non-transitory memory, the one or more processors configured to:

receive, from a client device during a communication session, a prompt identifying a request for a wager recommendation;

determine that the prompt is to be augmented with at least one of location information, information corresponding to one or more sports teams, information corresponding to one or more wager types, or odds information to satisfy the request for the wager recommendation;

responsive to determining that the prompt is to be augmented, retrieve, from at least one data source and based on the prompt, a set of additional contextual data to satisfy the request for the wager recommendation;

generate an input context using the prompt and the set of additional contextual data; and

generate, using a language model and the input context, an output message identifying the wager recommendation.

2 . The system of claim 1 , wherein the one or more processors are further configured to:

determine that the prompt is to be augmented with the location information; and

retrieve one or more candidate wagers corresponding to the location information for inclusion in the set of additional contextual data.

3 . The system of claim 1 , wherein the at least one data source comprises one or more of the client device, a player profile associated with the client device, or a database storing information relating to one or more live events.

4 . 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:

determine that the prompt is to be augmented with profile information; and

retrieve at least a subset of data stored in the player profile for inclusion in the set of additional contextual data.

5 . The system of claim 1 , wherein the one or more processors are further configured to:

determine that the prompt is to be augmented with the information corresponding to one or more sports teams; and

retrieve at least a subset of data from a database storing sports information for inclusion in the set of additional contextual data.

6 . The system of claim 1 , wherein the one or more processors are further configured to:

determine that the prompt is to be augmented with the information corresponding to one or more wager types; and

retrieve at least a subset of data from a database storing wager information of a plurality of candidate wagers for inclusion in the set of additional contextual data.

7 . The system of claim 1 , wherein the one or more processors are further configured to:

determine that the prompt is to be augmented with the odds information for at least one wager; and

retrieve at least a subset of data from a database storing odds information of a plurality of wagers for inclusion in the set of additional contextual data.

8 . The system of claim 1 , wherein the one or more processors are further configured to:

generate a classification of intent for the prompt; and

determine that the prompt is to be augmented with additional information based on the classification of the intent.

9 . The system of claim 8 , wherein the one or more processors are further configured to:

generate the classification of the intent for the prompt by providing at least a portion of the prompt as input to a machine-learning model.

10 . The system of claim 1 , wherein the one or more processors are further configured to:

receive a second prompt in response to the output message;

generate a second input context using the second prompt and a second set of additional contextual information retrieved according to the second prompt; and

execute the language model using the second input context to generate a second output message in response to the second prompt.

11 . A method, comprising:

receiving, by one or more processors coupled to non-transitory memory, from a client device during a communication session, a prompt identifying a request for a wager recommendation;

determining, by the one or more processors, that the prompt is to be augmented with at least one of location information, information corresponding to one or more sports teams, information corresponding to one or more wager types, or odds information to satisfy the request for the wager recommendation;

responsive to determining that the prompt is to be augmented, retrieving, by the one or more processors, from at least one data source and based on the prompt, a set of additional contextual data to satisfy the request for the wager recommendation;

generating, by the one or more processors, an input context using the prompt and the set of additional contextual data; and

generating, by the one or more processors, using a language model and the input context, an output message identifying the wager recommendation.

12 . The method of claim 11 , further comprising:

determining, by the one or more processors, that the prompt is to be augmented with the location information; and

retrieving, by the one or more processors, one or more candidate wagers corresponding to the location information for inclusion in the set of additional contextual data.

13 . The method of claim 11 , wherein the at least one data source comprises one or more of the client device, a player profile associated with the client device, or a database storing information relating to one or more live events.

14 . The method of claim 11 , wherein the client device is associated with a player profile, and further comprising:

determining, by the one or more processors, that the prompt is to be augmented with profile information; and

retrieving, by the one or more processors, at least a subset of data stored in the player profile for inclusion in the set of additional contextual data.

15 . The method of claim 11 , further comprising:

determining, by the one or more processors, that the prompt is to be augmented with the information corresponding to one or more sports teams; and

retrieving, by the one or more processors, at least a subset of data from a database storing sports information for inclusion in the set of additional contextual data.

16 . The method of claim 11 , further comprising:

determining, by the one or more processors, that the prompt is to be augmented with the information corresponding to one or more wager types; and

retrieving, by the one or more processors, at least a subset of data from a database storing wager information of a plurality of candidate wagers for inclusion in the set of additional contextual data.

17 . The method of claim 11 , further comprising:

determining, by the one or more processors, that the prompt is to be augmented with the odds information for at least one wager; and

retrieving, by the one or more processors, at least a subset of data from a database storing odds information of a plurality of wagers for inclusion in the set of additional contextual data.

18 . The method of claim 11 , further comprising:

generating, by the one or more processors, a classification of intent for the prompt; and

determining, by the one or more processors, that the prompt is to be augmented with additional information based on the classification of the intent.

19 . The method of claim 18 , further comprising:

generating, by the one or more processors, the classification of the intent for the prompt by providing at least a portion of the prompt as input to a machine-learning model.

20 . The method of claim 11 , further comprising:

receiving, by the one or more processors, a second prompt in response to the output message;

generating, by the one or more processors, a second input context using the second prompt and a second set of additional contextual information retrieved according to the second prompt; and

executing, by the one or more processors, the language model using the second input context to generate a second output message in response to the second prompt.