Communication platform for a connected environment
Techniques are disclosed to generate relevant responses for requests received in a connected environment. A user communicating with the connected environment may request, in natural language, an operation to be performed. The request may be augmented with the information related to the requesting user to generate an augmented query. The augmented query may be processed by a large language model to generate a response to the augmented query. The response is returned in natural language.
1 . A system to facilitate communication within a connected environment having a plurality of distinct ecosystems comprising:
a processor; and
a memory coupled to the processor, wherein the processor is to:
receive a request to execute an operation in the connected environment, wherein the request is received in natural language;
augment the request with a requestor information to generate an augmented query, wherein the requestor information comprises of:
an identification information of a requestor providing the request, and
a navigation trail of the requestor in the connected environment, wherein the navigation trail is indicative of a sequence of interactions of the requestor within the connected environment;
process the augmented query, using a large language model, to generate a response to the augmented query, wherein the response is a result of the requested operation executed as the augmented query by having the processor:
generate a workflow graph including one or more executable objects required to execute the operation, wherein an executable object is a set of instructions in machine-readable language to execute the augmented query;
determine a flow sequence to execute the one or more executable objects;
assign a sequence number to each of the one or more executable objects in the workflow graph based on the flow sequence; and
execute the one or more executable objects in accordance with the sequence number;
return the response in the natural language.
2 . The system of claim 1 , wherein the request is received at a front-end interface triggerable from a location in the connected environment.
3 . The system of claim 1 , wherein the identification information includes a user identifier and information related to an ecosystem in which the user operates within the connected environment.
4 . The system of claim 3 , wherein the plurality of distinct ecosystems include at least one of a developer ecosystem, an end-user ecosystem, an operations ecosystem, and a customer relationship management (CRM) ecosystem.
5 . The system of claim 1 , wherein the processor is to:
receive a modification to the response;
store a record of the modification in a system of records repository; and
train the large language model using the record of the modification stored in the system of records repository.
6 . A method for facilitating communication within a connected environment having a plurality of ecosystems comprising:
receiving a request to execute an operation in the connected environment, wherein the request is received in natural language;
augmenting the request with requestor information to generate an augmented query, wherein the requestor information comprises of:
an identification information of a user providing the request, and
a navigation trail of the requestor in the connected environment, wherein the navigation trail is indicative of a sequence of interactions of the requestor within the connected environment;
processing the augmented query, using a large language model, to generate a response to the augmented query, wherein the response is a result of the requested operation executed as the augmented query, by:
generating a workflow graph including one or more executable objects required to execute the operation, wherein an executable object is a set of instructions in machine-readable language to execute the augmented query; and
determining a flow sequence to execute the one or more executable objects;
assigning a sequence number to each of the one or more executable objects in the workflow graph based on the flow sequence; and
executing the one or more executable objects in accordance with the sequence number;
return the response in natural language.
7 . The method of claim 6 , wherein the request is received at a front-end interface triggerable from any location in the connected environment.
8 . The method of claim 6 , wherein the identification information includes a user identifier and information related to an ecosystem in which the user operates within the connected environment.
9 . The method of claim 8 , wherein the plurality of distinct ecosystems include at least one of a developer ecosystem, an end-user ecosystem, an operations ecosystem, and a customer relationship management (CRM) ecosystem.
10 . The method of claim 6 , further comprising:
receiving a modification to the response;
storing a record of the modification in a system of records repository; and
training the large language model using the record of the modification stored in the system of records repository.
11 . A non-transitory computer-accessible storage medium storing program comprising instructions for facilitating communication within a connected environment having a plurality of distinct ecosystems, the instructions being executable by a processor to:
receive a request to execute an operation in the connected environment, wherein the request is received in natural language;
augment the request with requestor information to generate an augmented query, wherein the requestor information comprises of:
an identification information of a user providing the request, and
a navigation trail of the requestor in the connected environment, wherein the navigation trail is indicative of a sequence of interactions of the requestor within the connected environment;
process the augmented query, using a large language model, to generate a response to the augmented query, wherein the response is a result of the requested operation executed as the augmented query, wherein the instructions are executable by the processor to:
generate a workflow graph including one or more executable objects required to execute the operation, wherein an executable object is a set of instructions in machine-readable language to execute the augmented query; and
determine a flow sequence to execute the one or more executable objects;
assign a sequence number to each of the one or more executable objects in the workflow graph based on the flow sequence; and
execute the one or more executable objects in accordance with the sequence number;
return the response in natural language.
12 . The non-transitory computer-accessible storage medium of claim 11 , wherein the request is received at a front-end interface triggerable from any location in the connected environment.
13 . The non-transitory computer-accessible storage medium of claim 11 , wherein the identification information includes a user identifier and information related to an ecosystem in which the user operates within the connected environment.
14 . The non-transitory computer-accessible storage medium of claim 13 , wherein the plurality of distinct ecosystems include at least one of a developer ecosystem, an end-user ecosystem, an operations ecosystem, and a customer relationship management (CRM) ecosystem.
15 . The non-transitory computer-accessible storage medium of claim 11 , the instructions being executable by the processor to:
receive a modification to the response;
store a record of the modification in a system of records repository; and
train the large language model using the record of the modification stored in the system of records repository.