Machine learning based on graphical element generator for communication platform
Techniques for generating graphical elements via a communication platform are discussed herein. For example, one or more machine-learning models associated with a communication platform may be configured to receive, as input and from a user of the communication platform, a sentiment and/or a graphical element. The machine-learning model may be trained, using prior natural language statements and prior confidence levels associated with previous graphical elements, to output one or more graphical elements associated with the input. The one or more graphical elements may be shared via the communication platform and used to accurately and effectively convey thoughts, emotions, reactions, and ideas, for example.
1. A method, implemented at least in part by one or more computing devices associated with a group-based communication platform, comprising:
receiving, from a user associated with the group-based communication platform, an indication of an interaction between the user and the group-based communication platform;
receiving, from the user, a request to generate one or more graphical elements for the group-based communication platform, wherein the request includes at least one natural language statement associated with the one or more graphical elements;
inputting the request to generate the one or more graphical elements for the group-based communication platform into a machine-learning model, wherein the machine-learning model is trained based at least in part on (i) first data including information regarding prior natural language statements associated with prior graphical elements, and (ii) second data including prior confidence levels associated with prior requests to generate prior graphical elements, to learn one or more relationships between the first data and the second data, such that the machine-learning model is configured to use the learned relationships to generate the one or more graphical elements and one or more respective confidence levels associated with the one or more graphical elements upon the inputting of the request;
receiving, from the machine-learning model and based at least in part on inputting the request, the one or more graphical elements, wherein the one or more graphical elements are generated by the machine-learning model;
causing presentation, to the user and via the one or more computing devices, of the one or more graphical elements;
receiving, from the user, an indication of a selection of one of the one or more graphical elements to share to the group-based communication platform; and
sending, based at least in part on the indication, the selected one of the one or more graphical elements to the group-based communication platform.
2. The method of claim 1 , wherein the interaction between the user and the group-based communication platform includes at least one of:
a message;
a reply;
a reaction;
an image;
an audio file; or
a document.
3. The method of claim 1 , wherein the request to add the graphical element to the group-based communication platform includes at least one of:
a sentiment; or
a description of a graphical element.
4. The method of claim 3 , further comprising:
determining that at least one of the sentiment or the description of the graphical element contains offensive language; and
refraining from generating the graphical element.
5. The method of claim 1 , further comprising:
receiving, from the user, an indication of a selection of graphical element to share to the group-based communication platform; and
sending, based at least in part on receiving the indication of the selection of the graphical element by the user, the graphical element to the group-based communication platform.
6. The method of claim 5 , wherein the user is a first user and wherein sharing the graphical element to the group-based communication platform includes sharing the graphical element to a first channel, the method further comprising:
receiving, from a second user associated with the first channel, and indication to share the graphical element to a second channel associated with the group-based communication platform, wherein the second channel is different than the first channel;
determining the first channel is a private channel; and
refraining from sending, based at least in part on determining the first channel is a public channel, the graphical element to the second channel.
7. The method of claim 5 , wherein the user is a first user and wherein sharing the graphical element to the group-based communication platform includes sharing the graphical element to a first channel, the method further comprising:
receiving, from a second user associated with the first channel, and indication to share the graphical element to a second channel associated with the group-based communication platform, wherein the second channel is different than the first channel;
determining the first channel is a public channel; and
sending, based at least in part on determining the first channel is a public channel, the graphical element to the second channel.
8. The method of claim 5 , wherein the graphical element is a first graphical element, the method further comprising:
determining a visual aspect associated with the graphical element;
storing the visual aspect associated with the graphical element as a preferred visual aspect;
receiving, from the user, a request to add a second graphical element to the group-based communication platform; and
generating a second graphical element, wherein the second graphical element includes the preferred visual aspect.
9. A system comprising:
one or more processors; and
one or more non-transitory computer-readable media comprising instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
receiving, from a user associated with a group-based communication platform, an indication of an interaction between the user and the group-based communication platform;
receiving, from the user, a request to add a graphical element to the group-based communication platform;
inputting the request to add a graphical element to the group-based communication platform into a machine-learning model;
receiving, from the machine-learning model and based at least in part on inputting the request, the graphical element, wherein the graphical element was generated by the machine-learning model; and
causing presentation, to the user and via one or more computing devices associated with the user, of the graphical element.
10. The system of claim 9 , wherein the interaction between the user and the group-based communication platform includes at least one of:
a message;
a reply;
a reaction;
an image;
an audio file; or
a document.
11. The system of claim 9 , wherein the request to add the graphical element to the group-based communication platform includes at least one of:
a sentiment; or
a description of a graphical element.
12. The system of claim 11 , the operations further comprising:
determining that at least one of the sentiment or the description of the graphical element contains offensive language; and
refraining from generating the graphical element.
13. The system of claim 9 , the operations further comprising:
receiving, from the user, an indication of a selection of graphical element to share to the group-based communication platform; and
sending, based at least in part on receiving the indication of the selection of the graphical element by the user, the graphical element to the group-based communication platform.
14. The system of claim 13 , wherein the user is a first user and wherein sharing the graphical element to the group-based communication platform includes sharing the graphical element to a first channel, the operations further comprising:
receiving, from a second user associated with the first channel, and indication to share the graphical element to a second channel associated with the group-based communication platform, wherein the second channel is different than the first channel;
determining the first channel is a private channel; and
refraining from sending, based at least in part on determining the first channel is a public channel, the graphical element to the second channel.
15. The system of claim 13 , wherein the user is a first user and wherein sharing the graphical element to the group-based communication platform includes sharing the graphical element to a first channel, the operations further comprising:
receiving, from a second user associated with the first channel, and indication to share the graphical element to a second channel associated with the group-based communication platform, wherein the second channel is different than the first channel;
determining the first channel is a public channel; and
sending, based at least in part on determining the first channel is a public channel, the graphical element to the second channel.
16. The system of claim 13 , wherein the graphical element is a first graphical element, the operations further comprising:
determining a visual aspect associated with the graphical element;
storing the visual aspect associated with the graphical element as a preferred visual aspect;
receiving, from the user, a request to add a second graphical element to the group-based communication platform; and
generating a second graphical element, wherein the second graphical element includes the preferred visual aspect.
17. One or more computer-readable media comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
receive, from a user associated with a group-based communication platform, an indication of an interaction between the user and the group-based communication platform;
receive, from the user, a request to add a graphical element to the group-based communication platform;
input the request to add a graphical element to the group-based communication platform into a machine-learning model;
receive, from the machine-learning model and based at least in part on inputting the request, the graphical element, wherein the graphical element was generated by the machine-learning model; and
cause presentation, to the user and via one or more computing devices associated with the user, of the graphical element.
18. The one or more computer-readable media of claim 17 , wherein the request to add the graphical element to the group-based communication platform includes at least one of:
a sentiment; or
a description of a graphical element.
19. The one or more computer-readable media of claim 18 , the operations further comprising:
receiving, from the user, an indication of a selection of graphical element to share to the group-based communication platform; and
sending, based at least in part on receiving the indication of the selection of the graphical element by the user, the graphical element to the group-based communication platform.
20. The one or more computer-readable media of claim 18 , the operations further comprising:
determining an accessibility level associated with the indication of a selection to share the graphical element to the group-based communication platform; and
associating the accessibility level with graphical element;
wherein sending the graphical element to the group-based communication platform is based at least in part on the accessibility level associated with the graphical element.