Abstract: Methods, systems and computer program products for analyzing historical user interactions across multiple users within a content management system. This approach employs machine learning to identify patterns and similarities in user behavior, enabling more accurate AI agent assignment and customization. By considering the collective behavior of user groups, the invention can provide AI agents that are better tailored to specific tasks and user needs, ultimately improving their effectiveness and user satisfaction.

Abstract: Methods, systems and computer program products for analyzing historical user interactions across multiple users within a content management system. This approach employs machine learning to identify patterns and similarities in user behavior, enabling more accurate AI agent assignment and customization. By considering the collective behavior of user groups, the invention can provide AI agents that are better tailored to specific tasks and user needs, ultimately improving their effectiveness and user satisfaction.

Abstract: Methods, systems, and computer program products for managing interactions between a content management system (CMS) and a large language model (LLM) system. The semantics of user questions can be considered before prompting an LLM, or alternatively, before querying datasets that are local to the CMS. Given a user question to be answered, the embedding of the user question can be matched against preconfigured sample question embeddings to determine a best match. A prompt corresponding to the determined best match is then configured based on identification of the class or classes that correspond to the matched question. Prompts for provision to LLMs can be synthesized based on a particular user's identity and/or based on the particular user's historical collaboration activities over objects of the CMS. The LLM can be hosted by a third-party provider. Alternatively all or portions of a large language model system can be hosted within the CMS.

Abstract: Methods, systems, and computer program products for collaboration systems. A method for identifying selected portions of a set of content objects for use in generating a large language model (LLM) prompt comprises: identifying a content management system (CMS) wherein collaboration activities occur over time and over content objects maintained in the CMS, and wherein the CMS maintains a historical record of occurrences of the collaborator activities over the content objects. Upon receiving a natural language query from a CMS collaborator, reducing a larger corpus of content objects to a smaller corpus of context passages that are used in an LLM prompt. The smaller corpus of passages is formed using a two-phase reduction scheme whereby firstly, selected constituents from the larger corpus of content objects are identified based on CMS metadata; and then, rather than considering the larger corpus, instead considering only the selected constituents when generating the LLM prompt.

Abstract: Methods, systems, and computer program products for managing interactions between a content management system (CMS) and a large language model (LLM) system. The semantics of user questions can be considered before prompting an LLM, or alternatively, before querying datasets that are local to the CMS. Given a user question to be answered, the embedding of the user question can be matched against preconfigured sample question embeddings to determine a best match. A prompt corresponding to the determined best match is then configured based on identification of the class or classes that correspond to the matched question. Prompts for provision to LLMs can be synthesized based on a particular user's identity and/or based on the particular user's historical collaboration activities over objects of the CMS. The LLM can be hosted by a third-party provider. Alternatively all or portions of a large language model system can be hosted within the CMS.

Abstract: A method for processing content management system workflows. Systems and subsystems are established for configuring a content management system to implement workflow processes wherein the content management system (CMS) exposes instances of stored content objects to a plurality of user devices through an electronic interface. Further systems and subsystem are established for identifying metadata maintained by the CMS for the stored content objects, and for identifying a generative AI entity (GAIE) to interact with the CMS. On an ongoing basis, the foregoing systems and subsystems carry out steps for (1) forming a GAIE prompt, wherein the GAIE prompt comprises at least a portion of the metadata identified from the CMS for the stored content objects, (2) receiving a response from the GAIE, wherein the response corresponds to the GAIE prompt; and (3) using, by the CMS, the response from the GAIE to implement processing of a content management system workflow.

Abstract: Methods, systems, and computer program products for managing interactions between a content management system (CMS) and a large language model (LLM) system. The semantics of user questions can be considered before prompting an LLM, or alternatively, before querying datasets that are local to the CMS. Given a user question to be answered, the embedding of the user question can be matched against preconfigured sample question embeddings to determine a best match. A prompt corresponding to the determined best match is then configured based on identification of the class or classes that correspond to the matched question. Prompts for provision to LLMs can be synthesized based on a particular user's identity and/or based on the particular user's historical collaboration activities over objects of the CMS. The LLM can be hosted by a third-party provider. Alternatively all or portions of a large language model system can be hosted within the CMS.

Abstract: Methods, systems, and computer program products for managing interactions between a content management system (CMS) and a large language model (LLM) system. The semantics of user questions can be considered before prompting an LLM, or alternatively, before querying datasets that are local to the CMS. Given a user question to be answered, the embedding of the user question can be matched against preconfigured sample question embeddings to determine a best match. A prompt corresponding to the determined best match is then configured based on identification of the class or classes that correspond to the matched question. Prompts for provision to LLMs can be synthesized based on a particular user's identity and/or based on the particular user's historical collaboration activities over objects of the CMS. The LLM can be hosted by a third-party provider. Alternatively all or portions of a large language model system can be hosted within the CMS.

Abstract: Systems and methods for managing file operations over shared content in the presence of two or more heterogeneous file systems. A virtual file system provides data consistency pertaining to asynchronous interactions between the heterogeneous storage systems. Operations of the virtual file system include receiving a file system call from a first storage environment for performing one or more data operations at a second storage environment. After receiving the file system call, the virtual file system issues file system calls to the second storage environment and records a first set of metadata. To determine if and when the one or more data operations at the second storage environment have completed, the virtual file system accesses a second set of metadata from the second storage environment. The two sets of metadata are compared. If there are differences, then the virtual file system performs time delays until the two sets of metadata agree.

Abstract: A system and method for facilitating cache alignment in a cross-enterprise file collaboration system. The example method includes maintaining a plurality of messages in a cache, each message associated with a message offset; determining a message batch size; receiving a first request for a message characterized by a first offset; responding to the first request at least in part by sending an amount of data equal to the batch size starting at the first offset; receiving a second request for a second message of characterized by a second offset; and if the second offset plus the data batch size spans across a boundary determined by the first offset plus the data batch size, then responding to the second request by sending an amount of data equal to the first offset plus the data batch size minus the second offset. In a more specific embodiment, the first and second requests are received from different committers.

Abstract: A system and method for facilitating implementing a computing task (such as selectively transforming and/or writing data retrieved from a message stream of a message broker) via concurrent computing in a networked computing environment. The example method includes using a distributed software framework to encapsulate overhead functionality for facilitating extracting data from a data stream output from the message broker and writing associated data to one or more targets in a networked computing environment; and accommodating custom code as a plugin to one or more modules of the software framework. In a more specific embodiment, the one or more modules include one or more committers. The overhead functionality includes functionality for facilitating selective redistribution of work when a process becomes unreliable; tracking of offsets for message batches in the data stream; automatically assigning work to nodes in the networked computing environment.

Abstract: Systems and methods for managing file operations over shared content in the presence of two or more heterogeneous file systems. A virtual file system provides data consistency pertaining to asynchronous interactions between the heterogeneous storage systems. Operations of the virtual file system include receiving a file system call from a first storage environment for performing one or more data operations at a second storage environment. After receiving the file system call, the virtual file system issues file system calls to the second storage environment and records a first set of metadata. To determine if and when the one or more data operations at the second storage environment have completed, the virtual file system accesses a second set of metadata from the second storage environment. The two sets of metadata are compared. If there are differences, then the virtual file system performs time delays until the two sets of metadata agree.

Abstract: A system and method for facilitating cache alignment in a cross-enterprise file collaboration system. The example method includes maintaining a plurality of messages in a cache, each message associated with a message offset; determining a message batch size; receiving a first request for a message characterized by a first offset; responding to the first request at least in part by sending an amount of data equal to the batch size starting at the first offset; receiving a second request for a second message of characterized by a second offset; and if the second offset plus the data batch size spans across a boundary determined by the first offset plus the data batch size, then responding to the second request by sending an amount of data equal to the first offset plus the data batch size minus the second offset. In a more specific embodiment, the first and second requests are received from different committers.

Abstract: A system and method for facilitating implementing a computing task (such as selectively transforming and/or writing data retrieved from a message stream of a message broker) via concurrent computing in a networked computing environment. The example method includes using a distributed software framework to encapsulate overhead functionality for facilitating extracting data from a data stream output from the message broker and writing associated data to one or more targets in a networked computing environment; and accommodating custom code as a plugin to one or more modules of the software framework. In a more specific embodiment, the one or more modules include one or more committers. The overhead functionality includes functionality for facilitating selective redistribution of work when a process becomes unreliable; tracking of offsets for message batches in the data stream; automatically assigning work to nodes in the networked computing environment.