AUTOMATED CONTENT CREATION AND CONTENT SERVICES FOR COLLABORATION PLATFORMS

1 . A computer-implemented method for providing technical assistance using a messaging service, the method comprising:

receive a request message generated at a first client device by a first user, the request message including a natural language user input provided to a chat interface of a messaging platform;

in response to the request message being directed to an automated chat service, generate a first prompt comprising:

first predetermined query prompt text; and

at least a portion of the natural language user input;

communicate the first prompt to a generative output engine;

receive a first response from the generative output engine, the response comprising an answer overview responsive to the request message;

cause the answer overview to be transmitted to the first client device via the messaging platform; and

cause the answer overview to be transmitted to a content model as a model input;

receive from the content model, a model output comprising a set of content items obtained from a set of content sources;

generate a content summary for each content item of the set of content items; and

provide a respective content link and a respective content summary for transmission to the first client device via the messaging platform.

2 . The method of claim 1 , wherein:

the set of content sources include: a knowledge base platform, collaboration community postings, engineering documentation, and public webpages;

the generative output engine is a predictive model trained using data extracted from the knowledge base platform and collaboration community postings; and

the content model is a transformer model trained using a set of historical question-answer pairs, the set of question answer pairs including content obtained from the set of content sources.

3 . The method of claim 1 , wherein:

the request message includes a designated character; and

in response to receiving the designated character, the request message is directed to the automated chat service.

4 . The method of claim 1 , further comprising:

analyze the natural language user input to determine an intent metric;

in response to the intent metric satisfying a criteria, direct the request message to a first recipient; and

in response to the intent metric failing to satisfy the criteria, direct the request message to a second recipient operating the automated chat service.

5 . The method of claim 4 , wherein:

the automated chat service is a first automated chat service;

the first recipient operates a second automated chat service, wherein the second automated chat service is configured to:

analyze the natural language user input to determine a request type; and

select a predefined chat sequence in accordance with the determined request type, the predefined chat sequence defining a series of response entries; and

in response to a selection of the deterministic chat sequence, cause a first response entry of the series of response entries to be transmitted to the first client device via the messaging platform.

6 . The method of claim 4 , wherein the intent metric indicates a conformity of the natural language user input with respect to one or more request types of the second automated chat service.

7 . The method of claim 1 , wherein:

in response to a user input, extract content from the content summary; and submit a new issue request to an issue tracking platform using an application programming interface, the issue request including the content extracted from the content summary.

8 . The method of claim 1 , wherein the method further comprises providing each respective content link and each respective content summary for the set of content items for transmission to the first client device via the messaging platform.

9 . The method of claim 1 , wherein the set of content sources include, a knowledge base platform, engineering documentation, and public webpages.

10 . A system for providing content for a chat session with the user, the system comprising:

a backend of a collaboration platform configured to provide technical assistance, the backend of the collaboration platform executing on a server having a processing unit and computer readable memory storing instructions for:

in response to receiving a request message generated by a first client device of a first user operating a messaging platform, providing the request message to a recipient operating an automated chat service, wherein the automated chat service is configured to:

generate a first prompt comprising:

first predetermined query prompt text; and

at least a portion of a natural language user input extracted from the request message;

communicate the first prompt to a first generative output engine;

receive a first response from the first generative output engine the first response comprising a natural language response to the request message;

cause the natural language response to be transmitted to a content model as a model input;

receive from the content model, a model output comprising a set of content items;

generate a second prompt comprising content extracted from a content item of the set of content items;

communicate the second prompt to a second generative output engine;

receive a second response from the second generative output engine the second response comprising a content summary of the content item; and

provide a respective content summary for transmission to the first client device via the messaging platform.

11 . The system of claim 10 , wherein the instructions further comprise instructions for:

analyzing the natural language user input to determine an intent metric;

in response to the intent metric satisfying a criteria, directing the request message to a first recipient; and

in response to the intent metric failing to satisfy the criteria, directing the request message to a second recipient operating the automated chat service.

12 . The system of claim 10 , wherein:

the automated chat service is a first automated chat service;

the first recipient operates a second automated chat service, wherein the second automated chat service is configured to:

analyze the natural language user input to determine a request type; and

select a predefined chat sequence in accordance with the determined request type, the predefined chat sequence defining a series of response entries; and

in response to a selection of the deterministic chat sequence, cause a first response entry of the series of response entries to be transmitted to the first client device via the messaging platform.

13 . The system of claim 10 , wherein:

in response to a user input, extract content from the content summary; and

submit a new issue request to an issue tracking platform using an application programming interface, the issue request including the content extracted from the content summary.

14 . The system of claim 10 , wherein:

the content model is configured to obtain the set of results from a set of content sources; and

the set of content sources include: a knowledge base platform, engineering documentation, and public webpages.

15 . A computer-implemented method of providing technical assistance using a messaging platform, the method comprising:

receive a user input extracted from a request message generated at a first client device by a first user using the messaging platform;

provide the user input to an automated chat service, wherein the automated chat service is configured to:

generate a first prompt comprising at least a portion of the user input;

communicate the first prompt to a generative output engine;

receive a first response from the generative output engine the first response comprising a natural language response to the request message;

cause the natural language response to be transmitted to the first client device via the messaging platform; and

cause the natural language response to be transmitted to a content model as a model input;

receive from the content model, a model output comprising a set of content items obtained from a set of content sources;

generate a second prompt comprising content extracted from a content item of the set of content items;

communicate the second prompt to the generative output engine;

receive a second response from the generative output engine the second response comprising a content summary of the content item; and

provide a respective content summary for transmission to the first client device via the messaging platform.

16 . The computer-implemented method of claim 15 , wherein:

the request message includes a designated character; and

in response to receiving the designated character, the request message is directed to the automated chat service.

17 . The computer-implemented method of claim 15 , wherein:

the set of content sources include a knowledge base platform and engineering documentation;

the generative output engine is a predictive model trained using data extracted from the content sources; and

the content model is a transformer model trained using a set of historical question-answer pairs, the set of question answer pairs including content obtained from the set of content sources.

18 . The computer-implemented method of claim 15 , wherein:

the first prompt is communicated to the generative output engine using an API call transmitted to the generative output engine; and

the second prompt is communicated to the generative output engine using the API call.

19 . The computer-implemented method of claim 15 , wherein a response message is transmitted to an operator before being relayed to the first client device via the messaging platform.

20 . The computer-implemented method of claim 15 , wherein subsequent to providing the respective content summary for transmission to the first client device, the method further comprises providing a set of links to the set of content items to the first client device via the messaging platform.