Abstract: The methods, systems, and computer networking apparatuses described herein enable language models to receive input (e.g., a query or a request) from a user or application, and without any additional training data or instructions, determine to generate a function call based on the received input from the user and generate the function call based on the determination. In some embodiments, a language model may further access an external tool or application to request an output as a response to the generated function call. The disclosed methods, systems, and networking apparatuses improve the technical field by incorporating language model capabilities within the function calling process, and allowing for function-related information to be provided to a language model via input received in any number of formats or types, including structured or unstructured input, language or non-language input, or any combination thereof.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for executing generative models for private conversations within protected inference environments. In particular, in some embodiments, the disclosed systems receive an encrypted chat message marked with a private status. In addition, in some embodiments, the disclosed systems generate a decrypted chat message by decrypting the encrypted chat message using a shared session key based on a hardware-backed attestation indicating server-side processing by a trusted execution environment. Moreover, in some embodiments, the disclosed systems generate a re-encrypted chat message by re-encrypting the decrypted chat message with an additional session key established for a private engine instance.

Abstract: The present technology pertains to a file search tool for use with a generative response engine. For example, the present technology pertains to a service that can create a database and index of files and make them searchable by the generative response engine, which can provide responses based on the documents in the index.

Abstract: A device may receive, from a user of a computing device and via an application, a user query. A device may generate a data package comprising the user query and user identity information. A device may transmit, via a company application programming interface (API) between the application and a generative response engine, the data package to the generative response engine. The generative response engine provides resources to process the user query based on entitlements associated with a user account. User anonymity and user entitlements can be fulfilled for the user experience when the user interacts with the generative response engine through the company API, even when the user is not logged into the generative response engine.

Abstract: Disclosed herein are methods, systems, and computer-readable media for integrating an application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a registration of an external API via a user interface connected to a natural language model, the natural language model being configured to integrate a plurality of external APIs, accessing a manifest file hosted at a first online location by a publisher of the external API, the manifest file comprising parameters for interfacing with the external API and a second online location of a specification associated with the external API, the parameters and second online location being defined by the publisher of the external API, accessing the specification at the second online location, and integrating the external API with the natural language model based on data from at least one of the manifest file or the specification.

Abstract: The methods, systems, and computer networking apparatuses described herein enable language models to receive input (e.g., a query or a request) from a user or application, and without any additional training data or instructions, determine to generate a function call based on the received input from the user and generate the function call based on the determination. In some embodiments, a language model may further access an external tool or application to request an output as a response to the generated function call. The disclosed methods, systems, and networking apparatuses improve the technical field by incorporating language model capabilities within the function calling process, and allowing for function-related information to be provided to a language model via input received in any number of formats or types, including structured or unstructured input, language or non-language input, or any combination thereof.

Abstract: The present technology pertains to providing, configuring and operating of a virtual assistant that can be accessible via an application programming interface. The virtual assistant can be configured with a customized system message, and can have access to a conversation thread of undefined length, whereby the virtual assistant can both be specialized for a given task and can have an ability to recall past interactions, thus mimicking the skill and memory of a human assistant. The present technology provides for a first entity to configure the virtual assistant and to call the virtual assistant by referencing its assistant ID.

Abstract: Disclosed herein are methods, systems, and computer-readable media for integrating an application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a registration of an external API via a user interface connected to a natural language model, the natural language model being configured to integrate a plurality of external APIs, accessing a manifest file hosted at a first online location by a publisher of the external API, the manifest file comprising parameters for interfacing with the external API and a second online location of a specification associated with the external API, the parameters and second online location being defined by the publisher of the external API, accessing the specification at the second online location, and integrating the external API with the natural language model based on data from at least one of the manifest file or the specification.

Abstract: The present technology pertains to providing, configuring and operating of a virtual assistant that can be accessible via an application programming interface. The virtual assistant can be configured with a customized system message, and can have access to a conversation thread of undefined length, whereby the virtual assistant can both be specialized for a given task and can have an ability to recall past interactions, thus mimicking the skill and memory of a human assistant. The present technology provides for a first entity to configure the virtual assistant and to call the virtual assistant by referencing its assistant ID.

Abstract: The methods, systems, and computer networking apparatuses described herein enable language models to receive input (e.g., a query or a request) from a user or application, and without any additional training data or instructions, determine to generate a function call based on the received input from the user and generate the function call based on the determination. In some embodiments, a language model may further access an external tool or application to request an output as a response to the generated function call. The disclosed methods, systems, and networking apparatuses improve the technical field by incorporating language model capabilities within the function calling process, and allowing for function-related information to be provided to a language model via input received in any number of formats or types, including structured or unstructured input, language or non-language input, or any combination thereof.

Abstract: Disclosed herein are methods, systems, and computer-readable media for integrating an application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a registration of an external API via a user interface connected to a natural language model, the natural language model being configured to integrate a plurality of external APIs, accessing a manifest file hosted at a first online location by a publisher of the external API, the manifest file comprising parameters for interfacing with the external API and a second online location of a specification associated with the external API, the parameters and second online location being defined by the publisher of the external API, accessing the specification at the second online location, and integrating the external API with the natural language model based on data from at least one of the manifest file or the specification.

Abstract: Disclosed herein are methods, systems, and computer-readable media for integrating a particular external application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a first input at the natural language model user interface, determining the first input includes a request to integrate the particular external application programming interface (API) with the natural language model user interface, identifying the particular external API based on the received input, integrating the particular external API with the natural language model user interface, accessing the particular external API based on the first input or a second input at the natural language model user interface, and transmitting, based on the accessing, a response message to the natural language model user interface, the response message including a result of the accessing.

Abstract: Disclosed herein are methods, systems, and computer-readable media for integrating a particular external application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a first input at the natural language model user interface, determining the first input includes a request to integrate the particular external application programming interface (API) with the natural language model user interface, identifying the particular external API based on the received input, integrating the particular external API with the natural language model user interface, accessing the particular external API based on the first input or a second input at the natural language model user interface, and transmitting, based on the accessing, a response message to the natural language model user interface, the response message including a result of the accessing.

Abstract: Disclosed herein are methods, systems, and computer-readable media for integrating a particular external application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a first input at the natural language model user interface, determining the first input includes a request to integrate the particular external application programming interface (API) with the natural language model user interface, identifying the particular external API based on the received input, integrating the particular external API with the natural language model user interface, accessing the particular external API based on the first input or a second input at the natural language model user interface, and transmitting, based on the accessing, a response message to the natural language model user interface, the response message including a result of the accessing.

Abstract: Disclosed herein are methods, systems, and computer-readable media for integrating a particular external application programming interface (API) with a natural language model user interface. In one embodiment, a method includes receiving a first input at the natural language model user interface, determining the first input includes a request to integrate the particular external application programming interface (API) with the natural language model user interface, identifying the particular external API based on the received input, integrating the particular external API with the natural language model user interface, accessing the particular external API based on the first input or a second input at the natural language model user interface, and transmitting, based on the accessing, a response message to the natural language model user interface, the response message including a result of the accessing.