Electronic device, method, and non-transitory computer-readable storage medium for generating input data on basis of output data

Abstract

According to one embodiment, a method performed by an electronic device may comprise the operations of: identifying, on the basis of a language-based user input, first input data including a first intent related to a first domain and second input data including a second intent related to a second domain; acquiring first response data related to the first intent on the basis of inputting the first input data into an application; generating third input data on the basis of the first response data and the second input data; acquiring second response data related to the second intent on the basis of inputting the third input data into the application; and providing, on the basis of the second response data, a service in the second domain associated with a service in the first domain.

Description

Electronic device, method, and non-transitory computer-readable storage medium for generating input data based on output data The present disclosure relates to an electronic device, a method, and a non-transitory computer-readable storage medium for generating input data based on output data. Electronic devices can provide services that perform functions at the user's request using interactive applications. The electronic devices can identify the user's voice input and perform functions based on the voice input. Using an artificial intelligence model, the electronic devices can identify the function requested by the user based on the voice input. The electronic devices can then perform the function requested by the user. The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above is applicable as prior art related to the present disclosure. Aspects of the present disclosure address at least the problems and / or disadvantages mentioned above and provide at least the advantages described below. Accordingly, aspects of the present disclosure provide an electronic device, a method, and a non-transitory computer-readable storage medium for generating input data based on output data. Additional aspects will be set forth in part in the description which follows, and in part will be apparent from the description or may be learned by practicing the embodiments provided. According to one embodiment, an electronic device may include at least one processor including instructions, a memory including one or more storage media, and a processing circuit. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify, based on a language-based user input, first input data comprising a first intent associated with a first domain and second input data comprising a second intent associated with a second domain, input the first input data into an application using one or more trained models, obtain first response data associated with the first intent based on inputting the first input data into the application, generate third input data based on the first response data and the second input data, input the third input data into the application, obtain second response data associated with the second intent based on inputting the third input data into the application, and provide, based on the second response data, a service on the second domain associated with a service on the first domain. According to one embodiment, a method performed by an electronic device may include: identifying, based on a language-based user input, first input data including a first intent related to a first domain and second input data including a second intent related to a second domain; inputting the first input data into an application; obtaining, based on the inputting of the first input data into the application, first response data related to the first intent; generating, based on the first response data and the second input data, third input data; inputting the third input data into the application; obtaining, based on the inputting of the third input data into the application, second response data related to the second intent; and providing, based on the second response data, a service on the second domain linked to a service on the first domain. According to one embodiment, a non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed by at least one processor of an electronic device, cause the electronic device to identify, based on a language-based user input, first input data including a first intent associated with a first domain and second input data including a second intent associated with a second domain, input the first input data into the application, obtain first response data associated with the first intent based on the inputting of the first input data into the application, generate third input data based on the first response data and the second input data, input the third input data into the application, obtain second response data associated with the second intent based on the inputting of the third input data into the application, and provide, based on the second response data, a service on the second domain associated with a service on the first domain. Other aspects, advantages and important features of the present disclosure will become apparent to those skilled in the art from the following detailed description of various embodiments of the present disclosure taken in conjunction with the accompanying drawings. The above and other aspects, features and advantages of specific embodiments of the present disclosure will become more apparent from the following description taken in conjunction with the drawings, in which: FIG. 1 is a block diagram of an electronic device within a network environment according to one embodiment; FIG. 2A illustrates an example of the operation of an interactive application, according to one embodiment; FIG. 2b illustrates an example of a simplified block diagram of an electronic device, according to one embodiment; FIG. 3 illustrates a flowchart of the operation of an electronic device according to one embodiment; FIGS. 4A and 4B illustrate examples of an electronic device and a server for providing a service based on user input based on multi-turn and / or multi-intent, according to one embodiment; FIG. 5 illustrates an example of the operation of an electronic device for configuring input data of a third artificial intelligence model according to one embodiment; FIG. 6 illustrates an example of the operation of an electronic device for configuring output data for user input, according to one embodiment; FIGS. 7A and 7B illustrate examples of operation of an electronic device according to one embodiment; FIGS. 8A and 8B illustrate examples of operation of an electronic device according to one embodiment; FIGS. 9A and 9B illustrate examples of operation of an electronic device according to one embodiment; FIGS. 10A, 10B, and 10C illustrate examples of operation of an electronic device according to one embodiment; FIGS. 11A and 11B illustrate examples of operation of an electronic device according to one embodiment; FIG. 12 illustrates an example of operation of an electronic device according to one embodiment; FIG. 13 illustrates an example of operation of an electronic device according to one embodiment; FIG. 14 illustrates an example of operation of an electronic device according to one embodiment; FIG. 15 illustrates an example of operation of an electronic device according to one embodiment; FIGS. 16A and 16B illustrate examples of operation of an electronic device according to one embodiment; FIG. 17 illustrates an example of operation of an electronic device according to one embodiment; FIG. 18 is a block diagram illustrating an integrated intelligence system according to one embodiment; FIG. 19 is a diagram showing a form in which relationship information between concepts and actions is stored in a database according to various embodiments; FIG. 20 is a diagram showing a screen in which a user terminal processes voice input received through an intelligent app according to various embodiments; Figure 21 is a schematic diagram of an exemplary AI (artificial intelligence) system. The same reference numbers are used throughout the drawing to indicate the same elements. The following description, with reference to the accompanying drawings, is provided to facilitate a comprehensive understanding of various embodiments of the present disclosure, as defined by the claims and their equivalents. While it includes numerous specific details to facilitate this understanding, it should be considered merely illustrative. Accordingly, those skilled in the art will recognize that various changes and modifications to the various embodiments described herein can be made without departing from the scope of the present disclosure. Furthermore, descriptions of well-known functions and configurations may be omitted for clarity and brevity. The terms and words used in the following description and claims are not limited to their bibliographic meanings, but are merely used by the inventors to facilitate a clear and consistent understanding of the present disclosure. Therefore, those skilled in the art will appreciate that the following description of various embodiments of the present disclosure is provided for illustrative purposes only and is not intended to limit the present disclosure as defined by the appended claims and their equivalents.

[0003] It should be understood that the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a component surface" includes reference to one or more of those surfaces. It should be understood that each block of the flowchart and the combination of flowcharts can be performed by one or more computer programs containing instructions. The entirety of one or more computer programs may be stored in a single memory device, or the one or more computer programs may be divided into different parts stored in different memory devices. The functions or operations described in the present disclosure may be processed by a single processor or a combination of processors. A single processor or a combination of processors is a circuit that performs processing and includes an application processor (AP, e.g., a central processing unit (CPU)), a communication processor (CP, e.g., a modem), a graphics processing unit (GPU), a neural processing unit (NPU) (e.g., an artificial intelligence (AI) chip), a Wi-Fi chip, a Bluetooth chip, a global positioning system (GPS) chip, a near-field communication (NFC) chip, a connection chip, a sensor controller, a touch controller, a fingerprint sensor controller, a display driver integrated circuit (IC), an audio codec chip, a universal serial bus (USB) controller, a camera controller, an image processing IC, a microprocessor unit (MPU), a system on a chip (SoC), an IC, or a similar circuit. FIG. 1 is a block diagram of an electronic device within a network environment according to one embodiment. Referring to FIG. 1, in a network environment (100), an electronic device (101) may communicate with an electronic device (102) via a first network (198) (e.g., a short-range wireless communication network), or may communicate with at least one of an electronic device (104) or a server (108) via a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) via the server (108). According to one embodiment, the electronic device (101) may include a processor (120), a memory (130), an input module (150), an audio output module (155), a display module (160), an audio module (170), a sensor module (176), an interface (177), a connection terminal (178), a haptic module (179), a camera module (180), a power management module (188), a battery (189), a communication module (190), a subscriber identification module (196), or an antenna module (197). In some embodiments, the electronic device (101) may omit at least one of these components (e.g., the connection terminal (178)), or may have one or more other components added. In some embodiments, some of these components (e.g., the sensor module (176), the camera module (180), or the antenna module (197)) may be integrated into one component (e.g., the display module (160)). The processor (120) may control at least one other component (e.g., a hardware or software component) of the electronic device (101) connected to the processor (120) by executing, for example, software (e.g., a program (140)), and may perform various data processing or calculations. According to one embodiment, as at least a part of the data processing or calculation, the processor (120) may store a command or data received from another component (e.g., a sensor module (176) or a communication module (190)) in a volatile memory (132), process the command or data stored in the volatile memory (132), and store the resulting data in a non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., a central processing unit or an application processor) or a secondary processor (123) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor) that can operate independently or together therewith. For example, if the electronic device (101) includes a main processor (121) and a secondary processor (123), the secondary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a specified function. The secondary processor (123) may be implemented separately from the main processor (121) or as a part thereof. The auxiliary processor (123) may control at least a part of functions or states associated with at least one component (e.g., a display module (160), a sensor module (176), or a communication module (190)) of the electronic device (101), for example, on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. In one embodiment, the auxiliary processor (123) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (180) or a communication module (190)). In one embodiment, the auxiliary processor (123) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (108)). The learning algorithm can include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model can include multiple artificial neural network layers.The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure. The memory (130) can store various data used by at least one component (e.g., processor (120) or sensor module (176)) of the electronic device (101). The data can include, for example, software (e.g., program (140)) and input data or output data for commands related thereto. The memory (130) can include volatile memory (132) or non-volatile memory (134). The program (140) may be stored as software in the memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146). The input module (150) can receive commands or data to be used in a component of the electronic device (101) (e.g., a processor (120)) from an external source (e.g., a user) of the electronic device (101). The input module (150) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen). The audio output module (155) can output audio signals to the outside of the electronic device (101). The audio output module (155) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. According to one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker. The display module (160) can visually provide information to an external party (e.g., a user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling the device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of a force generated by the touch. The audio module (170) can convert sound into an electrical signal, or vice versa, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150), output sound through the sound output module (155), or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (101). The sensor module (176) can detect the operating status (e.g., power or temperature) of the electronic device (101) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (176) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor. The interface (177) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (101) with an external electronic device (e.g., the electronic device (102)). In one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface. The connection terminal (178) may include a connector through which the electronic device (101) may be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector). A haptic module (179) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. According to one embodiment, the haptic module (179) can include, for example, a motor, a piezoelectric element, or an electrical stimulation device. The camera module (180) can capture still images and videos. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes. The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented as, for example, at least a part of a power management integrated circuit (PMIC). A battery (189) may power at least one component of the electronic device (101). In one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell. The communication module (190) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may operate independently from the processor (120) (e.g., application processor) and may include one or more communication processors that support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (194) (e.g., a local area network (LAN) communication module, or a power line communication module). Among these communication modules, the corresponding communication module can communicate with an external electronic device (104) via a first network (198) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (199) (e.g., a long-range communication network such as a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules can be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can verify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) by using subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (196). The wireless communication module (192) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). The NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (192) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (192) can support various technologies for securing performance in a high-frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), an external electronic device (e.g., the electronic device (104)), or a network system (e.g., the second network (199)). According to one embodiment, the wireless communication module (192) may support a peak data rate (e.g., 20 Gbps or more) for eMBB realization, a loss coverage (e.g., 164 dB or less) for mMTC realization, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 1 ms or less for round trip) for URLLC realization. The antenna module (197) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). According to one embodiment, the antenna module (197) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as the first network (198) or the second network (199), may be selected from the plurality of antennas, for example, by the communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (197). According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high-frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high-frequency band. At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)). According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) via a server (108) connected to a second network (199). Each of the external electronic devices (102 or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations executed in the electronic device (101) may be executed in one or more of the external electronic devices (102, 104, or 108). For example, when the electronic device (101) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (101) may, instead of or in addition to executing the function or service by itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (101) may provide an ultra-low latency service by using distributed computing or mobile edge computing, for example. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server utilizing machine learning and / or a neural network. According to one embodiment, the external electronic device (104) or the server (108) may be included in the second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology. According to one embodiment, an electronic device (e.g., electronic device (101)) may provide a conversational artificial intelligence service using a conversational application. The electronic device may receive language-based user input. For example, the language-based user input may include at least one of text input and / or voice input. An electronic device may input input data based on language-based user input into a third artificial intelligence model (e.g., a conversational artificial intelligence model). The electronic device may obtain output data based on the output of the third artificial intelligence model. The electronic device may display a language-based response message based on the output data through the user interface of the conversational application, or perform a function based on the output data. According to one embodiment, language-based user input can be configured in various ways. The language-based user input can be configured based on multi-turns and / or multi-intents. A function may be required to provide a proper response to the language-based user input configured based on multi-turns and / or multi-intents. In the following specification, a specific example of an electronic device (or server) for providing a proper response to the language-based user input configured based on multi-turns and / or multi-intents will be described. The electronic device (or user terminal) described below may correspond to the electronic device (101) of FIG. 1. FIG. 2a illustrates an example of the operation of an interactive application according to one embodiment. Referring to FIG. 2A, the electronic device (200) may include the electronic device (101) of FIG. 1. The electronic device (200) may be a terminal owned by a user. The terminal may include, for example, a personal computer (PC) such as a laptop or desktop, a smartphone, a smartpad, or a tablet PC. The terminal may include a smart accessory such as a smartwatch and / or a head-mounted device (HMD). According to one embodiment, the electronic device (200) can execute an interactive application. For example, the electronic device (200) can execute an interactive application based on a defined utterance. The electronic device (200) can identify an utterance based on a user's voice signal. The electronic device (200) can execute an interactive application based on determining whether the identified utterance corresponds to the defined utterance. For example, the interactive application may be referred to as an artificial intelligence assistant application. According to one embodiment, a conversational application may be used to provide various functions according to a third artificial intelligence model (e.g., an artificial intelligence model). For example, the electronic device (200) may obtain language-based user input using the conversational application. The electronic device (200) may identify input data including an intent based on the language-based user input. For example, the intent may indicate an action to be performed by the electronic device (200). For example, when the electronic device (200) receives a language-based user input such as “Find me a flight ticket to New York,” the electronic device (200) may identify the action according to “Find me a flight ticket,” which is an action to be performed by the electronic device (200), as the intent. The electronic device (200) may identify “New York,” which is an entity representing additional information of the intent. For example, the electronic device (200) may obtain input data including an entity (e.g., "New York") and an intent (e.g., an action according to "Find me a plane ticket") based on a language-based user input (e.g., "Find me a plane ticket to New York"). According to one embodiment, an entity may mean a word or phrase representing a specific object or data. For example, the electronic device (200) may recognize entities in text through an entity recognition model and extract necessary information. For example, in the case of a user's language-based input such as "Find me a plane ticket to New York," "New York, plane ticket" may be classified as an entity, and "Find me a plane ticket" may be classified as an intent. In one embodiment, an intent can represent a concept used in natural language processing in artificial intelligence to understand a user's intention or purpose. For example, for natural language processing in artificial intelligence, a user's intention (or intent) can be classified based on input text through an intent classification model. For example, an interactive application may have the authority to execute other applications and perform functions of other applications. For example, based on the execution of another application, an interactive application may display the user interface of another application within the interactive application. The electronic device (200) may provide functions of the other application using the user interface of the other application displayed within the interactive application. For example, an intent may be associated with a domain. A domain may include an application or service. A domain may indicate an application or service for performing an action according to the intent. For example, if the electronic device (200) identifies an action according to "Find me a flight ticket" as an intent, the electronic device (200) may identify an airline ticket search application as the domain. As a non-limiting example, a domain may be associated with a function related to at least one of software or hardware. As a non-limiting example, a domain may be associated with a unit for performing a task. As a non-limiting example, a domain may be associated with a region of an action performed according to an intent. As a non-limiting example, a domain may be described as a location where processing related to an intent is performed. For example, a first intent may be associated with a first domain, and a second intent may be associated with a second domain. For example, processing of the electronic device (200) for a first intent may be performed on a first domain (e.g., including hardware components of the electronic device (200) and / or software components of the electronic device (200), and processing of the electronic device (200) for a second intent may be performed on a second domain (e.g., including hardware components of the electronic device (200) and / or software components of the electronic device (200). As a non-limiting example, the second intent may be related to the first intent, and processing of the second intent may be performed using a result of processing of the first intent. For example, the second domain may be used for processing that applies a result of the first intent processed on the first domain to the second intent. According to one embodiment, the electronic device (200) may display a user interface (210) of an interactive application through a display (202). For example, the electronic device (200) may display an object (211) representing a language-based user input on a first portion (e.g., a right portion) of the user interface (210). An object (212) representing a language-based response message according to the language-based user input may be displayed on a second portion (e.g., a left portion) of the user interface (210). For example, the electronic device (200) can identify input data including an intent based on a language-based user input. The electronic device (200) can input the input data into a third artificial intelligence model. The electronic device (200) can obtain output data using the third artificial intelligence model into which the input data has been input. The electronic device (200) can identify a language-based response message based on the output data. The electronic device (200) can display an object (212) representing the language-based response message. In one embodiment, language-based user input may be structured based on multi-turns and / or multi-intents. For example, a language-based user input configured based on multi-turns may include consecutive requests for the same and / or similar topics (or conversation content). For example, a first input from a user may be received as "How's the weather today?". The electronic device (200) may provide information about today's weather based on the location of the electronic device (200) in response to the first input. After the information about today's weather is provided, a second input from the user may be received as "What about tomorrow?". The electronic device (200) may provide information about tomorrow's weather based on the location of the electronic device (200) in response to the second input. After the information about tomorrow's weather is provided, a third input from the user may be received as "What about Seoul?". The electronic device (200) may provide information about tomorrow's weather in Seoul in response to the third input. As described above, the electronic device (200) may respond to "What about Seoul?" A third input, such as "What's the weather in Seoul tomorrow?", can be transformed into an input that can be processed (or understood) by a third AI model (e.g., an AI model). Therefore, continuous input on the same and / or similar topic (or conversation content) can be supported without modifying the third input. In one embodiment, a generative model (or a generative AI model) can transform the input so that the user's intention can be clearly understood. Therefore, continuous input can be supported while maintaining the context without separate modification or effort by the user. For example, a language-based user input configured based on multiple intents may include multiple intents. The electronic device (200) may generate (or identify) first input data including a first intent and second input data including a second intent based on the language-based user input. For example, a language-based user input such as "Change my schedule for tonight to 7 o'clock and send it to Mike" may be received. The electronic device (200) may generate (or identify) first input data including a first intent, such as "Change my schedule for tonight to 7 o'clock," and second input data including a second intent, such as "Send a text message to Mike that my schedule for tonight has been changed to 7 o'clock." For example, as an object (211), a language-based user input such as "Tell me how long it takes to get to Seoul and set an alarm for the time I arrive there" may be received. The electronic device (200) may generate (or identify) first input data including a first intent, such as "Tell me how long it takes to get to Seoul from my current location," and second input data including a second intent, such as "Set an alarm for the time I arrive in Seoul." For example, language-based user input may be structured based on both multi-turn and multi-intent. For example, a first user input may be received as "Find me a flight to New York in June." The electronic device (200) may, in response to the first input, provide information indicating flight tickets to New York in June. A second user input may be received as "What about July?". The electronic device (200) may convert the second input, such as "What about July?", into an input that can be processed (or understood) by a third artificial intelligence model (e.g., an artificial intelligence model), such as "Find me a flight to New York in July." A third user input may be received as "Find me a flight under $100 and tell me the weather then." The electronic device (200) can generate (or identify) first input data including a first intent, such as "Find me a plane ticket to New York for less than $100 in July", and second input data including a second intent, such as "Tell me the weather in New York in July", based on the third input. Components of the electronic device (200) according to the above-described embodiments will be described later in FIG. 2b. FIG. 2b illustrates an example of a simplified block diagram of an electronic device, according to one embodiment. Referring to FIG. 2b, the electronic device (200) may include at least some or all of the components of the electronic device (101) of FIG. 1. For example, the electronic device (200) may correspond to the electronic device (101) of FIG. 1. According to one embodiment, the electronic device (200) may include at least one of a processor (201), a display (202), a memory (203), and / or a communication circuit (204). For example, at least some of the processor (201), the display (202), the memory (203), and / or the communication circuit (204) may be omitted depending on the embodiment. According to one embodiment, the processor (201) may include at least a portion of the processor (120) of FIG. 1 or may correspond to at least a portion of the processor (120). For example, the processor (201) may include one or more processors, including an application processor (AP) and / or a communication processor (CP). For example, the processor (201) may be implemented as a single chip, such as a system on chip (SoC), or may be implemented as multiple chips. For example, the processor (201) may be implemented as a single integrated circuit or may be implemented as multiple integrated circuits. For example, the processor (201) may be distributedly arranged within the electronic device (200). The processor (201) may be operatively or operably coupled with or connected with the display (202), the memory (203), and the communication circuitry (204). For example, operatively coupling the processor (201) with another component may mean that the processor (201) can control the other component. The processor (201) may control the display (202), the memory (203), and / or the communication circuitry (204). According to one embodiment, the display (202) of the electronic device (200) can output visualized information (e.g., a screen) to the user. For example, the display (202) can be controlled by a controller, such as a graphic processing unit (GPU), to output visualized information to the user. The display (202) can include a liquid crystal display (LCD), a plasma display panel (PDP), and / or one or more light emitting diodes (LEDs). The LEDs can include organic LEDs (OLEDs). The display (202) can include a flat panel display (FPD) and / or electronic paper. The embodiment is not limited thereto, and the display (202) can have an at least partially curved shape or a deformable shape. A display (202) having a deformable shape can be referred to as a flexible display. According to one embodiment, the memory (203) of the electronic device (200) may include a circuit and / or a storage medium for storing data and / or instructions input and / or output to the processor (201). The memory (203) may include, for example, volatile memory such as random-access memory (RAM) and / or non-volatile memory such as read-only memory (ROM). The non-volatile memory may be referred to as storage. The volatile memory may include, for example, at least one of dynamic RAM (DRAM), static RAM (SRAM), cache RAM, and pseudo SRAM (PSRAM). The non-volatile memory may include, for example, at least one of programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, hard disk, compact disc, solid state drive (SSD), and embedded multi media card (eMMC). According to one embodiment, the memory (203) may include at least a portion of the memory (130) of FIG. 1 or may correspond to at least a portion of the memory (130) of FIG. 1. For example, the memory (203) may be implemented as a single chip or as multiple chips. For example, the memory (203) may be implemented as a single integrated circuit or as multiple integrated circuits. For example, the memory (203) may be distributedly arranged within the electronic device (200). According to one embodiment, the processor (201) of the electronic device (200) may execute instructions of the memory (203) within the electronic device (200) to perform functions and / or operations indicated by the instructions. For example, when the electronic device (200) includes at least one processor, the at least one processor may be configured to collectively or individually execute the instructions. For example, the memory (203) may include at least one model (or at least one artificial intelligence model). The memory (203) may store instructions relating to the at least one model. The memory (203) may include (or store) at least one of a first artificial intelligence model, a second artificial intelligence model, and / or a third artificial intelligence model, which will be described below. According to an embodiment, at least one of the first artificial intelligence model and / or the second artificial intelligence model may be a language-based artificial intelligence model. According to an embodiment, at least one of the first artificial intelligence model, the second artificial intelligence model, and / or the third artificial intelligence model may be included in a chip (e.g., an NPU) distinct from the memory (203). For example, at least one of the first artificial intelligence model, the second artificial intelligence model, and / or the third artificial intelligence model may be implemented as an artificial intelligence model included in hardware (e.g., an artificial intelligence chip) included within a separate device (on-device artificial intelligence) or included in an external server (e.g., an artificial intelligence model). For example, the first AI model, the second AI model, and / or the third AI model may be configured based on at least one AI model. In some embodiments, the third AI model may be configured based on at least one of a rule model and / or a deep model. The first AI model and the second AI model may be configured based on a generative model (or generative AI model). However, this is not limited thereto. In one embodiment, the generative model may include a generative model including a plurality of parameters associated with a neural network having a structure based on an encoder and a decoder, such as a transformer. In one embodiment, the generative model may include a bidirectional model based on learning about an encoder (e.g., bidirectional encoder representations from transformers (BERT)) or an auto-encoding model (e.g., a diffusion model). In one embodiment, the generative model may include an auto-regressor model based on learning about a decoder (e.g., a generative pre-trained transformer (GPT)). In one embodiment, the generative model may include a sequence-to-sequence model based on learning about an encoder and a decoder (e.g., stable diffusion, DALL-E 2). In one embodiment, the generative model may include, but is not limited to, a large language model (LLM) for processing natural language based on a massive number of parameters. The generative model may include parameters for driving a neural network such as a convolutional neural network (CNN), a recurrent neural network (RNN), a feedforward neural network (FNN), and / or a long short-term memory (LSTM). According to one embodiment, the communication circuit (204) can be used for various radio access technologies (RATs). For example, the communication circuit (204) can be used to perform Bluetooth communication, wireless local area network (WLAN) communication, or ultra wideband (UWB) communication. For example, the communication circuit (204) can be used to perform cellular communication. For example, the processor (201) can establish a connection with an external electronic device (e.g., a server) through the communication circuit (204). Figure 3 illustrates a flowchart of the operation of an electronic device according to one embodiment. In the following embodiments, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel. Referring to FIG. 3, in operation 310, the electronic device (200) (or the processor (201) of the electronic device (200)) may generate (or identify) first input data including a first intent related to a first domain and second input data including a second intent related to a second domain, based on a user input. According to one embodiment, the electronic device (200) may display a user interface of an interactive application through a display (202) based on the execution of the interactive application. While the user interface of the interactive application is displayed, the electronic device (200) may obtain user input. For example, the user input may include at least one of a text input and / or a voice input. According to one embodiment, the user input may be composed based on language-based text, language-based voice, images, emoticons, numbers, and / or gestures. According to one embodiment, the electronic device (200) may input a user input into a first AI model. Based on the input of the user input into the first AI model, the electronic device (200) may generate (or identify, obtain) first input data including a first intent and / or second input data including a second intent. For example, the first AI model may be used to identify (or distinguish) an intent from the user input. For example, the first AI model may be configured to regenerate natural sentences that an AI model (e.g., a third AI model) can process. For example, the electronic device (200) may identify (or generate) a prompt by using the user input and / or history information (e.g., information about previous user input). Based on the identified prompt, the electronic device (200) may generate the first input data and / or the second input data through the first AI model. In operation 320, the electronic device (200) may input first input data into an application that utilizes one or more trained models. Based on inputting the first input data into the application that utilizes one or more trained models, the electronic device (200) may obtain first response data related to the first intent. For example, the application that utilizes one or more trained models may be referred to as at least one of an assistant application (or voice assistant application), an assistant function (or voice assistant function), an assistant program (or voice assistant program), or an assistant operation (application) (or voice assistant operation). For example, the application may include one or more trained models. The application may be configured to obtain response data according to input data. The application may be configured to obtain the response data using at least one of the one or more trained models according to the intent of the input data. For example, each of the one or more trained models may be associated with an intent. For example, a first model of the one or more trained models may be associated with a first intent. A second model of the one or more trained models may be associated with a second intent. For example, an application utilizing one or more trained models may operate in conjunction with a conversational application. For example, an application utilizing one or more trained models may be configured to obtain response data for input data acquired through the conversational application. For example, an application utilizing one or more trained models may be configured to perform an assistive function in response to a user's voice input. For example, an application utilizing one or more trained models may be configured to obtain output data based on voice data acquired through the conversational application. According to one embodiment, the electronic device (200) may obtain first response data related to the first intent based on inputting first input data into a trained model (e.g., a third artificial intelligence model, a generative artificial intelligence model). For example, the electronic device (200) may input the first input data into the trained model. For example, the trained model may correspond to the first model related to the first intent. The electronic device (200) may input the first input data into a trained model to obtain first response data for the first input data including the first intent. The electronic device (200) may identify a first domain related to the first intent. The electronic device (200) may identify a first domain (e.g., an application or a service) for performing the first intent. The electronic device (200) may use the first input data as an input value of a third artificial intelligence model and obtain first response data as an output value of the third artificial intelligence model. For example, the first response data may be used to provide a service on the first domain. The electronic device (200) may provide a service on the first domain based on the first response data. According to an embodiment, the electronic device (200) may display a language-based response message according to the first response data within a user interface of an interactive application. For example, a trained model can be used to perform functions related to an interactive application. The trained model can be used to generate (or obtain) output data based on input data. For example, the trained model can be based on a rule model and / or a deep model. However, this is not limited to these. The trained model can also be based on a generative model. In some embodiments, the first response data according to the first input data may be obtained through a third-party application or a chat AI using LLM (e.g., gemini or chat-GPT (generative pre-trained transformer)). In operation 330, the electronic device (200) may generate third input data based on the first response data and / or the second input data. For example, the electronic device (200) may generate the third input data based on inputting at least one of the first response data or the second input data into the first artificial intelligence model. According to an embodiment, the electronic device (200) may generate the third input data based on inputting not only the first response data and / or the second input data, but also history information (e.g., information about previous user input) into the first artificial intelligence model. For example, the electronic device (200) may identify (or generate) a prompt using the first response data, the second input data, and / or history information (e.g., information about previous user input). The electronic device (200) may generate the third input data through the first artificial intelligence model based on the identified prompt. For example, the electronic device (200) may input first response data and second input data, which are results of first input data, into a first artificial intelligence model. The electronic device (200) may generate third input data based on the output of the first artificial intelligence model. For example, the electronic device (200) may change the second input data into third input data by reflecting the first response data into the second input data. The electronic device (200) may change the second input data into third input data that can be processed (or understood) by the trained model. For example, the third input data may include a second intent included in the second input data. When the second input data is changed to the third intent, the second intent of the second input data may be maintained, and the parameters of the second input data may be changed. According to an embodiment, the third input data generated according to operation 330 may include a third intent. Even when the second input data includes a second intent, a third intent distinct from the second input data may be included in the third input data according to the output of the first artificial intelligence model. In operation 340, the electronic device (200) may input third input data into an application that utilizes one or more trained models. Based on inputting the third input data into the application that utilizes one or more trained models, the electronic device (200) may obtain second response data related to the second intent. According to one embodiment, the electronic device (200) may obtain second response data related to the second intent based on inputting third input data into the trained model. For example, the electronic device (200) may input the third input data into the trained model. The electronic device (200) may obtain second response data related to the second intent based on the output of the trained model. For example, the trained model may correspond to the second model related to the second intent. In some embodiments, the second response data according to the third input data may be obtained through a third-party application or a chat AI using LLM (e.g., gemini or chat-GPT (generative pre-trained transformer)). In operation 350, the electronic device (200) may provide a service in a second domain linked to a service in the first domain based on the second response data. For example, the service in the second domain may be performed based on the service in the first domain. To obtain the second response data, third input data obtained based on the first response data may be used. Accordingly, the service in the second domain may be linked to the service in the first domain. In the above-described embodiments, examples for obtaining second response data have been described, but are not limited thereto. For example, N input data and N response data, including fourth input data or fifth input data, may be obtained. Depending on the embodiment, the Nth input data may be obtained based on response data according to the first input data or response data according to the (N-1)th input data. According to one embodiment, the electronic device (200) may provide a service on a first domain based on the first response data. For example, the electronic device (200) may display a first user interface of a first application related to a first domain within a user interface of an interactive application to provide a service on the first domain based on the first response data. The electronic device (200) may display a second user interface of a second application related to the first domain within a user interface of an interactive application to provide a service on the second domain based on the second response data. An example of displaying a first user interface of a first application and a second user interface of a second application within the user interface of an interactive application will be described later with reference to FIG. 10A. For example, the first response data may be used to trigger the execution of a first application and the performance of a function related to the first application. The electronic device (200) may execute the first application and perform a function related to the first application based on the first response data. For example, the second response data may be used to trigger the execution of a second application and the performance of a function related to the second application. The electronic device (200) may execute the second application and perform a function related to the second application based on the second response data. According to one embodiment, the electronic device (200) may stop displaying the user interface of the interactive application based on the first response data and the second response data. The electronic device (200) may display a first user interface of a first application regarding a first domain through the display (202). After displaying the first user interface, the electronic device (200) may display a second user interface of a second application regarding a second domain through the display (202) as an overlay on the first user interface. An example of displaying the second user interface as an overlay on the first user interface will be described later with reference to FIG. 10B. Depending on the embodiment, the first user interface and the second user interface may not be displayed as an overlay. Depending on the embodiment, the first user interface and the second user interface may not be displayed, and an object based on the first response data and the second response data may be displayed within the interactive application. For example, the electronic device (200) may generate (or obtain) output data based on inputting first response data and second response data into a second artificial intelligence model (420) (e.g., the second artificial intelligence model (420) of FIG. 4A or FIG. 4B). The electronic device (200) may display an object based on the output data within an interactive application. According to one embodiment, the processor (201) may display at least one of a first object for executing a first application for a first domain or a second object for executing a second application for a second domain within a user interface of an interactive application. For example, the electronic device (200) may execute a first application based on an input for the first object and display a first user interface of the first application through the display (202). For example, the electronic device (200) may execute a second application based on an input for the second object and display a second user interface of the second application through the display (202). An example of displaying the first object and / or the second object will be described later with reference to FIGS. 9A and 9B. According to one embodiment, the electronic device (200) may generate output data for a user input based on the first response data and the second response data. For example, the electronic device (200) may generate output data for a user input based on the first response data and the second response data to display a response message for the user input. The electronic device (200) may display a language-based response message according to the output data within the user interface of the interactive application. The language-based response message may be displayed as a reply message for the user input. For example, the electronic device (200) may input first response data and second response data into a second artificial intelligence model. Based on inputting the first response data and second response data into the second artificial intelligence model, the electronic device (200) may generate output data for the user input. For example, a second AI model can be used to generate natural responses based on the first and second response data. For example, the second AI model can be referred to as a rewriting natural language generator (NLG). For example, a first artificial intelligence model may be used to process input data. A second artificial intelligence model may be used to process output data. For example, the first artificial intelligence model and / or the second artificial intelligence model may be configured based on a generative model (e.g., a large language model (LLM)). In one embodiment, at least one of the first artificial intelligence model or the second artificial intelligence model may be a language-based model (or a language-based artificial intelligence model). In some embodiments, the first artificial intelligence model and the second artificial intelligence model may be one artificial intelligence model (or a language-based model). For example, the second artificial intelligence model may correspond to the first artificial intelligence model. For example, the first AI model may be used to identify inputs based on user input, including multi-turn and / or multi-intent inputs. The first AI model may provide a function to classify user inputs into inputs that can be processed (or understood) by a trained model (e.g., a third AI model). The first AI model may be used to transform second input data into third input data that reflects the first response data. For example, the first AI model may transform user input into a natural language format supported by the trained model (e.g., a third AI model). For example, the second AI model may be used to combine the first response data and the second response data. The second AI model may be used to generate natural language based on a database specific to the domain of the performed function. The second AI model may generate language-based (or natural language-based) output data in response to the user input based on the history of previously performed functions (or tasks), environmental information, and the user input and / or response data (e.g., the first response data and the second response data). According to one embodiment, the electronic device (200) can identify that the duration for acquiring the second response data exceeds a threshold time. The electronic device (200) can generate first output data according to the first response data and provide the first output data first. After the first output data is provided, the electronic device (200) can generate output data according to the second response data and provide the second output data based on acquiring the second response data. According to one embodiment, the trained model may be configured based on at least one of a rule model and / or a deep model. The trained model may not be able to process user inputs that include intents for various domains. For example, the first artificial intelligence model and the second artificial intelligence model may be configured based on a generative model. Accordingly, the electronic device (200) may use the first artificial intelligence model to distinguish user inputs into first input data and second input data. The first input data and the second input data may be processable by the trained model. The electronic device (200) can obtain third input data based on the first response data and the second input data using the first artificial intelligence model. By obtaining the third input data based on the first response data and the second response data, the electronic device (200) can obtain the third input data from a user input configured based on multi-turns and / or multi-intents. The electronic device (200) can obtain the second response data by inputting the third input data into the trained model. The electronic device (200) can obtain output data by inputting first response data and second response data into a second artificial intelligence model. By obtaining the output data, the electronic device (200) can provide a response message to the user according to a user input configured based on multi-turns and / or multi-intents. Although the first artificial intelligence model, the second artificial intelligence model, and / or the trained model (or the third artificial intelligence model) are described as independent in FIG. 3, this is not limiting. In the present disclosure, the first artificial intelligence model, the second artificial intelligence model, and / or the trained model (or the third artificial intelligence model) may also be configured as a single model. In some embodiments, the output data according to the first response data and the second response data may be obtained through a third-party application or a chat AI using LLM (e.g., gemini or chat-GPT (generative pre-trained transformer)). FIGS. 4A and 4B illustrate examples of an electronic device and a server for providing a service based on user input based on multi-turn and / or multi-intent, according to one embodiment. Referring to FIGS. 4A and 4B , the electronic device (200) may utilize the server (400) to provide a service based on user input based on multi-turns and / or multi-intents. In FIG. 4A , an example in which the third artificial intelligence model (440), which is an example of the above-described trained model, is included in the server (400) will be described. In FIG. 4B , an example in which the third artificial intelligence model (440), which is an example of the above-described trained model, is included in the electronic device (200) will be described. Referring to FIG. 4A, the electronic device (200) may include an application (461), a client (462), and an interactive application (463). The application (461), the client (462), and the interactive application (463) may be included (or stored) in the memory (203) of the electronic device (200). For example, the application (461) may be an application for providing a service according to user input. The application (461) may be related to an intent included in the user input. The application (461) may be related to a domain according to the intent. The application (461) may be related to a domain related to the intent. For example, the client (462) may be used for communication with the server (400). The client (462) may be used for connection to the server (400). For example, the interactive application (463) may be used to receive user input and provide output data according to the user input. For example, the interactive application (463) may be set to have the authority to execute the application (461). The interactive application (463) may be set to have the authority to execute a function within the application (461). According to one embodiment, the server (400) may include a data manager (430), a third artificial intelligence model (440), and a function performer (450). For example, the data manager (430) may be used to manage input data and / or output data of the third artificial intelligence model (440). For example, when the number of intents is n, the data manager (430) may perform a role of storing and managing the history for sequentially processing each of the intents. For example, the data manager (430) may perform a history management of a plurality (e.g., n) of the previous processing results. According to an embodiment, when a generative artificial intelligence model is used, the data manager (430) may also perform a function for modifying or creating at least one prompt for the generative artificial intelligence model. For example, the third artificial intelligence model (440) may be used to obtain output data based on input data. The function performer (450) may be used to perform a function according to the output data. The function performer (450) may be used to perform a function according to the domain (or capsule) of the output data. The function performer (450) may also perform a service provided by an external device distinct from the electronic device (200) or the server (400). According to an embodiment, the third artificial intelligence model may be an example of an application. The application may be configured to utilize one or more trained models. For example, the application may be referred to as at least one of an assistant application (or voice assistant application), an assistant function (or voice assistant function), an assistant program (or voice assistant program), or an assistant operation (application) (or voice assistant operation). For example, the application may include one or more trained models.An application may be configured to obtain response data based on input data. The application may be configured to obtain the response data using at least one of one or more trained models based on the intent of the input data. For example, each of the one or more trained models may be associated with an intent. For example, a first model of the one or more trained models may be associated with a first intent. A second model of the one or more trained models may be associated with a second intent. For example, an application utilizing one or more trained models may operate in conjunction with an interactive application. For example, an application utilizing one or more trained models may be configured to obtain response data in response to input data acquired through the interactive application. For example, the first artificial intelligence model (410) may be used to identify inputs according to multi-turns and / or multi-intents based on user input. The first artificial intelligence model (410) may be used to change the second input data into third input data reflecting the first response data. For example, the second artificial intelligence model (420) may be used to combine the first response data and the second response data. For example, the second artificial intelligence model (420) may be used to generate third input data based on not only the first response data and / or the second response data, but also history information (e.g., conversation history information). Depending on the embodiment, the first artificial intelligence model (410) and the second artificial intelligence model (420) may be configured as a single model (e.g., a language-based model). For example, the second artificial intelligence model (420) may correspond to the first artificial intelligence model (410). According to one embodiment, the first artificial intelligence model (410) and / or the second artificial intelligence model (420) may be included in a different server than the server (400). According to one embodiment, the first artificial intelligence model (410) and / or the second artificial intelligence model (420) may be included in the server (400). For example, the third artificial intelligence model (440) may include an automatic speech recognition (ASR) (441), a natural language understanding (NLU) (442), a dialogue manager (443), an executor (444), and a natural language generation (NLG) (445). For example, the third artificial intelligence model (440) may be configured to obtain response data for a language-based user input. The third artificial intelligence model (440) may be used to identify a function to be performed based on the language-based user input. For example, the first artificial intelligence model (410) and the second artificial intelligence model (420) may be used to reconstruct the language-based user input. For example, the first artificial intelligence model (410) may be configured to distinguish a language-based user input having two intents into first input data regarding the first intent and second input data regarding the second intent. For example, the first artificial intelligence model (410) may be configured to generate third input data based on the first response data and the second response data. For example, the second artificial intelligence model (420) may be configured to generate a response message to be provided to the user based on the first response data and the second response data. An automatic speech recognizer (441) may be used to convert speech data into text at the sentence level. An NLU (442) may be used to infer (or understand) the user's intent from input data. NLU (442) may be used to understand and interpret the meaning of text. A conversation manager (443) may be used to manage conversation flow and / or context. An executor (444) may be used to perform a function based on response data (or output data). Referring to FIG. 4b, the electronic device (200) may include at least some or all of the functional blocks included in the server (400) of FIG. 4a. The server (400) may correspond to the server (400) of FIG. 4a. For example, the electronic device (200) may include at least one of a data manager (430), a third artificial intelligence model (440), a function performer (450), a first artificial intelligence model (410) and / or a second artificial intelligence model (420). When the electronic device (200) includes at least one of the data manager (430), the third artificial intelligence model (440), the function performer (450), the first artificial intelligence model (410) and / or the second artificial intelligence model (420), at least one of the data manager (430), the third artificial intelligence model (440), the function performer (450), the first artificial intelligence model (410) and / or the second artificial intelligence model (420) included in the electronic device (200) may not be included in the server (400). According to one embodiment, the electronic device (200) may include a data manager (430), a third artificial intelligence model (440), a first artificial intelligence model (410), and a second artificial intelligence model (420). For example, the data manager (430), the third artificial intelligence model (440), the first artificial intelligence model (410), and the second artificial intelligence model (420) may be embedded in the electronic device (200). Even when the electronic device (200) includes the data manager (430), the third artificial intelligence model (440), the first artificial intelligence model (410), and the second artificial intelligence model (420), the server (400) may also include the data manager (430), the third artificial intelligence model (440), the first artificial intelligence model (410), and the second artificial intelligence model (420). When the electronic device (200) receives a user input, it may determine a device for processing the user input. For example, if the device for processing user input is determined to be an electronic device (200), the electronic device (200) can obtain response data (or output data) for the user input and provide the response data (or output data) by using the data manager (430), the third artificial intelligence model (440), the first artificial intelligence model (410), and the second artificial intelligence model (420) included in the electronic device (200). For example, if the device for processing user input is determined to be a server (400), the electronic device (200) can transmit the user input to the server (400). The server (400) can obtain response data (or output data) for the user input and provide the response data (or output data) to the electronic device (200). According to one embodiment, the electronic device (200) can perform at least some of the functions according to FIG. 3. The server (400) can perform the remaining some of the functions according to FIG. 3. In the following specification, the operation of an electronic device (200) including a data manager (430), a third artificial intelligence model (440), a first artificial intelligence model (410), and a second artificial intelligence model (420) will be described, as illustrated in FIG. 4B. However, this is for convenience of explanation. According to an embodiment, at least some of the operations of the electronic device (200) may be performed in the server (400). For example, when the operation regarding the third artificial intelligence model (440) is performed in the server (400), the electronic device (200) may obtain first input data and second input data based on a user input, and transmit the first input data and the second input data to the server (400). The server (400) may transmit first response data for the first input data to the electronic device (200). The electronic device (200) may obtain third input data based on the first response data and the second input data. The electronic device (200) can transmit third input data to the server (400). The server (400) can obtain second response data for the third input data and transmit first response data to the electronic device (200). Although the above-described example describes an example in which operations regarding the third artificial intelligence model (440) are performed in the server (400), the present invention is not limited thereto, and similarly to the above-described example, at least some of the operations of the electronic device (200) described below can be performed in the server (400). According to one embodiment, the electronic device (200) may determine a device for processing the input intent or entity as at least one of the server (400) or the electronic device (200) based on the input intent or entity. For example, the electronic device (200) may include at least one of a first artificial intelligence model and a second artificial intelligence model. The electronic device (200) may obtain response data for the input intent or entity using at least one of the first artificial intelligence model and the second artificial intelligence model. The obtained response data may be processed by being merged in the electronic device (200) or the server (400). Although the first artificial intelligence model (410) and the second artificial intelligence model (420) are described as independent in FIGS. 4A and 4B , this is not limiting. In the present disclosure, the first artificial intelligence model (410) and the second artificial intelligence model (420) may also be configured as a single model (e.g., a language-based model). The specific operations of the third artificial intelligence model (440), the first artificial intelligence model (410), and the second artificial intelligence model (420) described above will be described later in FIGS. 5, 6, 7a, and 7b. FIG. 5 illustrates an example of the operation of an electronic device for configuring input data of a third artificial intelligence model according to one embodiment. Referring to FIG. 5, the electronic device (200) can acquire user input. The electronic device (200) can use an automatic speech recognition device (441) to convert voice-based user input into text-based user input. In some embodiments, when text-based user input is received, the automatic speech recognition device (441) may not be used. The electronic device (200) can add text-based user input to a prompt defined for the first artificial intelligence model (410) using the data manager (430). For example, a prompt as shown in the table below can be defined in the electronic device (200). If the content in [FullInfoText] consists of multiple Intents, write each Intent as [Intent1][Intent2], etc., without any additional information using only the content in [FullInfoText], and write each Intent separately so that all the information is in the Intent. The following is an example. [History]"User: Make a schedule to go out with Jimin""B: When should I save the schedule?""User: Tomorrow at 2 PM""B: Should I save the schedule to go out with Jimin tomorrow at 2 PM?""[Current]"User: Umm, make it 3 PM, not 2 PM"[FullInfoText]"Cancel saving the schedule to go out with Jimin tomorrow at 2 PM, and set a schedule to go out with Jimin tomorrow at 3 PM"[Intent1]"Cancel saving the schedule to go out with Jimin tomorrow at 2 PM"[Intent2]"Schedule to go out with Jimin tomorrow at 3 PM" Referring to Table 1, the electronic device (200) can define a prompt configured as in Table 1 for the first artificial intelligence model (410). The electronic device (200) can configure input data of the first artificial intelligence model (410) by adding a user input to the prompt defined for the first artificial intelligence model (410). For example, the prompt can include history information. For example, a conversation history prior to a user input can be configured as history information. The electronic device (200) can configure a conversation history (or other user input) prior to a user input as history information. For example, the electronic device (200) can configure input data of the first artificial intelligence model based on user input using the data manager (430). The electronic device (200) can configure data in a form that can be processed by the first artificial intelligence model using the data manager (430). As described above, based on the prompt and / or few-shot (or one-shot), the first artificial intelligence model (410) can identify one or more intents using history information and user input. The electronic device (200) can identify input data for each of the one or more intents. For example, the electronic device (200) can identify a first intent and a second intent using the first artificial intelligence model (410) based on the user input. The electronic device (200) can identify first input data including the first intent and second input data including the second intent using the first artificial intelligence model (410). For example, when first input data including a first intent and second input data including a second intent are identified using a first artificial intelligence model (410), the electronic device (200) may perform a natural language interpretation operation on the first input data using an NLU (442). Based on the natural language interpretation of the first input data, the electronic device (200) may perform an execution operation linked to an application or service using an executor (444), and obtain first NLG information regarding the result of the execution operation using an NLG (445). For example, the electronic device (200) may identify the first NLG information and the first result information of the execution operation linked to the application or service as first response data. According to one embodiment, the electronic device (200) may input first response data and second input data into the first artificial intelligence model (410). The electronic device (200) may obtain third input data using the first artificial intelligence model (410). The electronic device (200) may obtain second response data based on the third input data using the NLU (442), the executor (444), and the NLG (445). For example, the electronic device (200) may identify second NLG information and second result information of an execution operation linked to an application or service as the second response data. As described above, the electronic device (200) can obtain response data for user inputs of various forms (e.g., multi-turn or multi-intent) by processing user inputs including multiple intents for multiple domains. The electronic device (200) can provide a continuous conversation function according to various forms of user inputs. For example, the electronic device (200) can identify n intents using the first artificial intelligence model (410). The electronic device (200) can rewrite a sentence to be composed of input data using response data of the third artificial intelligence model (440) for each intent. The electronic device (200) can rewrite a sentence to be composed of input data by accumulating response data for the n intents. As an example, the electronic device (200) can rewrite a sentence to be composed of input data by repeatedly performing operations related to the first artificial intelligence model (410), the NLU (442), the executor (444), and / or the NLG (445). For example, the electronic device (200) can identify a user input such as "Turn on Bluetooth and play a song." The electronic device (200) can identify first input data including a first intent, such as "Turn on Bluetooth," and second input data including a second intent, such as "Play a song." The electronic device (200) can obtain first response data for the first input data using the third artificial intelligence model (440). The electronic device (200) can identify that a function can be performed without changing the second input data based on the first response data. The electronic device (200) can obtain second response data for the second input data using the third artificial intelligence model (440). Based on obtaining the first response data and the second response data, the electronic device (200) can perform an action of turning on Bluetooth and an action of playing a song. According to an embodiment, the third artificial intelligence model (440) may be an example of an application that utilizes one or more trained models. The application may be configured to utilize one or more trained models. For example, the application may include one or more trained models. The application may be configured to obtain response data according to input data. The application may be configured to obtain the response data using at least one of the one or more trained models according to the intent of the input data. For example, each of the one or more trained models may be associated with an intent. For example, a first model of the one or more trained models may be associated with a first intent. A second model of the one or more trained models may be associated with a second intent. For example, the electronic device (200) may utilize a first model of the one or more trained models included in the application to obtain first response data for first input data.For example, the electronic device (200) may use a second model among one or more trained models included in the application to obtain second response data for third input data. For example, the electronic device (200) can identify a user input such as "register my schedule for Seoul tomorrow and tell me the weather then." The electronic device (200) can identify first input data including a first intent, such as "register my schedule for Seoul tomorrow," and second input data including a second intent, such as "tell me the weather then." The electronic device (200) can obtain first response data for the first input data using the third artificial intelligence model (440). The electronic device (200) can change the second input data into third input data according to the first response data. The electronic device (200) can obtain third input data such as "tell me the weather for Seoul tomorrow." For example, the third input data can include a second intent for a weather request. However, the present invention is not limited thereto, and the intent included in the third input data can be different from the intent included in the second input data. The electronic device (200) can obtain second response data for third input data using the third artificial intelligence model (440). Based on obtaining the first response data and the second response data, the electronic device (200) can perform an operation of registering tomorrow's Seoul schedule and an operation of providing tomorrow's Seoul weather. FIG. 6 illustrates an example of the operation of an electronic device for configuring output data for user input, according to one embodiment. Referring to FIG. 6, as in FIG. 5, the electronic device (200) may provide the data manager (430) with first response data including first NLG information obtained using the executor (444) and the NLG (445) and first result information of an execution operation linked to an application or service. The electronic device (200) may provide the data manager (430) with second response data including second NLG information obtained using the executor (444) and the NLG (445) and second result information of an execution operation linked to an application or service. The electronic device (200) may use the data manager (430) to add first response data (e.g., first NLG information) and second response data (e.g., second NLG information) to a prompt defined for the second artificial intelligence model (420). For example, a prompt as shown in the table below may be defined in the electronic device (200). [Intent] represents the user's intention contained in [FullInfoText], and [Result] shows the result performed and processed in B through each [Intent]. [Response] should be written based on the information present in [FullInfoText] or [Result]. Please write a [Response] that matches the [Language]. The following is an example. [Language] Korean [FullInfoText] Set the alarm for 7 o'clock and send a message to Kim Min-seong [Intent1] Set the alarm for 7 o'clock [Result1] I set the alarm [Intent2] Send a message to Kim Min-seong [Result2] What should I send to Kim Min-seong? [Response: Simple] I set the alarm. What should I send the message? [Response: Detail] I set the alarm. And what should I send the message to Kim Min-seong? Referring to Table 2, the electronic device (200) can define a prompt configured as in Table 2 for the second artificial intelligence model (420). The electronic device (200) can configure input data of the second artificial intelligence model (420) by adding first response data (e.g., first NLG information) and / or second response data (e.g., second NLG information) to the prompt defined for the second artificial intelligence model (420). For example, the prompt can include history information. For example, a conversation history prior to a user input can be configured as history information. As described above, based on the prompt and / or few-shot (or one-shot) input, the second artificial intelligence model (420) can generate third NLG information. The electronic device (200) can use the first response data and the second response data to construct the third NLG information. Based on the third NLG information, the electronic device (200) can provide the user with natural sentences for various types of utterances. For example, the third NLG information can be referenced as output data for user input. According to one embodiment, the electronic device (200) may store NLG information (e.g., first NLG information, second NLG information, and third NLG information) using the data manager (430). The NLG information may be managed as history information. The electronic device (200) may provide output data for user input using the history information while the current conversation session is maintained. According to one embodiment, the electronic device (200) can identify other language-based user inputs that are not related to history information. For example, the electronic device (200) can identify that other language-based user inputs are not related to previously received language-based user inputs. The electronic device (200) can terminate the session for the previously received language-based user inputs and establish a new session for other language-based user inputs. For example, the other language-based user inputs can include a third intent. The electronic device (200) can configure a fourth intent to establish a new session. The electronic device (200) can terminate the existing session by performing an action according to the fourth intent for establishing a new session. Thereafter, the electronic device (200) can perform an action according to the third intent. For example, the third intent can include an intent for terminating a session, such as "no." According to the above example, the electronic device (200) may identify multiple intents even when it receives a language-based user input having one intent. FIGS. 7A and 7B illustrate examples of operation of an electronic device according to one embodiment. Referring to FIG. 7A, the electronic device (200) can obtain (or identify) a language-based user input (710). Based on inputting the language-based user input (710) into the first artificial intelligence model (410), the electronic device (200) can identify first input data (711) including a first intent and second input data (712) including a second intent. For example, the electronic device (200) can obtain (or identify) a language-based user input (710), such as “Tell me how long it takes to get to Seoul and set an alarm for the time I get there.” The electronic device (200) can identify, based on the language-based user input (710), first input data (711) including a first intent (e.g., tell me the time), such as “Tell me how long it takes to get to Seoul.” The electronic device (200) can identify, based on the language-based user input (710), second input data (712) including a second intent (e.g., set an alarm), such as “Set an alarm for the time I get there.” According to one embodiment, the electronic device (200) may obtain first response data (713) based on inputting first input data (711) to the third artificial intelligence model (440). For example, the electronic device (200) may obtain first response data (713) such as "167 km to Seoul, estimated time of arrival is 1:27 PM." According to an embodiment, the third artificial intelligence model (440) may be an example of an application that utilizes one or more trained models. The application may be configured to utilize one or more trained models. For example, the application may include one or more trained models. Each of the one or more trained models may be associated with an intent. For example, a first model among the one or more trained models may be associated with a first intent. A second model among the one or more trained models may be associated with a second intent. For example, the electronic device (200) may use a first model among one or more trained models included in the application to obtain first response data (713) for first input data (711). According to one embodiment, the electronic device (200) may obtain third input data (713) based on inputting second input data (712) and first response data (713) into the first artificial intelligence model (410). For example, the electronic device (200) may obtain third input data (714), such as “Set an alarm for 1:27 PM today.” The electronic device (200) may obtain second response data (715) based on inputting third input data (714) into the third artificial intelligence model (440). For example, the electronic device (200) may use a second model among one or more trained models included in the application to obtain second response data (715) for the third input data (714). For example, the electronic device (200) may obtain second response data (715), such as "I set an alarm for 1:27 PM today." The electronic device (200) can obtain output data (716) based on inputting the first response data (713) and the second response data (715) into the second artificial intelligence model (420). For example, the electronic device (200) can obtain output data (716) based on not only the first response data (713) and the second response data (715), but also history information (e.g., conversation history information). For example, the electronic device (200) can obtain output data (716) such as "It is 167 km to Seoul, the expected arrival time is 1:27 PM, and I have set an alarm for that time." According to one embodiment, the electronic device (200) may display an object (721) representing user input (710) within a user interface (720) of an interactive application (463). The electronic device (200) may display an object (722) representing output data (716). The object (722) may represent a response to the object (721). Referring to FIG. 7B, the electronic device (200) can obtain (or identify) a language-based user input (760). Based on inputting the language-based user input (760) into the first artificial intelligence model (410), the electronic device (200) can identify first input data (761) including a first intent and second input data (762) including a second intent. For example, the electronic device (200) can obtain (or identify) a language-based user input (760), such as “Text David in Spanish ‘Let’s have lunch together today when you have time.’” The electronic device (200) can identify, based on the language-based user input (760), first input data (761) that includes a first intent (e.g., ‘Translate it’), such as “Translate ‘Let’s have lunch together today when you have time into Spanish.” The electronic device (200) can identify, based on the language-based user input (760), second input data (762) that includes a second intent (e.g., ‘Text it’), such as “Text that to David.” The electronic device (200) can obtain first response data (763) based on inputting the first input data (761) into the third artificial intelligence model (440). For example, the electronic device (200) can obtain first response data (763) such as, "When you have time, let's have lunch together today." The Spanish translation is Si tienes tiempo, almorcemos juntos hoy. The electronic device (200) can obtain third input data (764) based on inputting the second input data (762) and the first response data (763) into the first artificial intelligence model (410). For example, the electronic device (200) can obtain third input data (764), such as “Send a text message to David saying, ‘Si tienes tiempo, almorcemos juntos hoy’.” The electronic device (200) can obtain second response data (765) based on inputting third input data (764) into the third artificial intelligence model (440). For example, the electronic device (200) can obtain second response data (765), such as "Si tienes tiempo, almorcemos juntos hoy, should I text David?" The electronic device (200) can obtain output data (766) based on inputting the first response data (763) and the second response data (765) into the second artificial intelligence model (420). For example, the electronic device (200) can obtain output data (766) such as, "When you have time, let's have lunch together today in Spanish is Si tienes tiempo, almorcemos juntos hoy. Should I text this to David?" According to one embodiment, the electronic device (200) may display an object (771) representing user input (760) within a user interface (720) of an interactive application (463). The electronic device (200) may display an object (722) representing output data (766). The object (772) may represent a response to the object (771). In FIGS. 7A and 7B , a first artificial intelligence model (410) and a second artificial intelligence model (420) are illustrated, respectively. However, the first artificial intelligence model (410) and the second artificial intelligence model (420) may be configured as a single artificial intelligence model. In some embodiments, the first artificial intelligence model (410), the second artificial intelligence model (420), and the third artificial intelligence model (440) may also be configured as a single artificial intelligence model. FIGS. 8A and 8B illustrate examples of operation of an electronic device according to one embodiment. Referring to Fig. 8a, Fig. 8a illustrates an example of a result screen (or user interface) according to the processing results for multiple intents. The result screen according to the processing results for multiple intents may vary depending on the embodiment. The electronic device (200) may display output data according to the conversation context. Referring to FIG. 8A, the electronic device (200) may display a user interface (800) of an interactive application (463). The electronic device (200) may display an object (811) representing a first user input on the user interface (800). The electronic device (200) may obtain output data in response to the first user input. The electronic device (200) may display an object (812) representing the output data. The electronic device (200) can display an object (813) representing a second user input on the user interface (800). The electronic device (200) can identify the first input data and the second input data based on the second user input. The electronic device (200) can identify the first input data, such as "Tell me the route to there." The electronic device (200) can identify the second input data, such as "Register an alarm at that time." The electronic device (200) may display a first user interface (814) of a first application (e.g., a map application) within the user interface (800) to provide a service on a first domain (e.g., a map service) based on first response data according to first input data. According to an embodiment, the first user interface (814) may include at least one of an image, a video, and / or an executable object. The electronic device (200) may display a second user interface (815) of a second application (e.g., a clock application) within the user interface (800) to provide a service on a second domain (e.g., a time service) based on the first response data and the second input data. According to an embodiment, the second user interface (815) may include at least one of an image, a video, and / or an executable object. The electronic device (200) can obtain output data for a user input based on the first response data and the second response data. The electronic device (200) can display an object (816) representing the output data for the user input within the user interface (800). Referring to Fig. 8b, Fig. 8b illustrates an example of a result screen (or user interface) according to the processing result for multi-intent and multi-turn. The electronic device (200) can display a user interface (850) of an interactive application (463). The electronic device (200) can display an object (821) representing a first user input on the user interface (850). The electronic device (200) can identify first input data and second input data based on the first user input. The electronic device (200) can identify first input data, such as "Remind me of my appointment this afternoon or evening." The electronic device (200) can identify second input data, such as "Remind me one hour before that appointment." The electronic device (200) may display a user interface (822) of a first application (e.g., a calendar application) for providing a service on a first domain (e.g., a schedule service) within a user interface (850) based on first response data according to first input data. According to an embodiment, the first user interface (822) may include at least one of an image, a video, and / or an executable object. The electronic device (200) may display a second user interface (823) of a second application (e.g., a notification application) within the user interface (850) to provide a service on a second domain (e.g., a notification service) based on the first response data and the second input data. According to an embodiment, the second user interface (823) may include at least one of an image, a video, and / or an executable object. The electronic device (200) can display an object (824) representing output data for a first user input within a user interface (850). The electronic device (200) may display an object (825) representing a second user input on the user interface (850). The electronic device (200) may obtain response data for the second user input based on the history information and the second user input. For example, the history information may include output data according to the first user input or execution result information for the first application or the second application. The electronic device (200) may display an object (826) within the user interface (850) for asking whether to perform an action based on response data to the second user input. The electronic device (200) may display an object (827) within the user interface (850) according to the input indicating acceptance of performing an action based on response data to the second user input. The electronic device (200) may perform an action based on the response data to the second user input through a third application (e.g., a text application) for providing a service on a third domain (e.g., a text service) based on the response data to the second user input. The electronic device (200) may display an object (828) within the user interface (850) indicating that an action has been performed based on the response data to the second user input. As described above, the electronic device (200) can provide responses according to user inputs configured based on multi-intent and multi-turn. FIGS. 9A and 9B illustrate examples of operation of an electronic device according to one embodiment. Referring to FIGS. 9A and 9B, the electronic device (200) can display a user interface (900) of an interactive application (463) through a display (202). Referring to FIG. 9A, the electronic device (200) can identify a language-based user input including multiple intents. The electronic device (200) can display an object (911) representing the language-based user input on the user interface (900). The electronic device (200) can obtain first input data including a first intent (e.g., tell me the weather) related to a first domain (e.g., weather service) and second input data including a second intent (e.g., play a song) related to a second domain (e.g., music service) based on a language-based user input. The electronic device (200) can obtain first response data based on inputting the first input data to a third artificial intelligence model (440). The electronic device (200) can obtain second response data based on inputting the second input data to the third artificial intelligence model (440). The electronic device (200) can obtain output data based on the first response data and the second response data. The electronic device (200) can display an object (912) based on the output data. For example, the object (912) can include an object (913) for executing an application (e.g., a music application) related to a second domain. The electronic device (200) can execute the application related to the second domain based on an input to the object (913). The electronic device (200) may display a user interface (914) of a first application (e.g., a weather application) for the first domain to provide a service on the first domain based on the first response data. Referring to FIG. 9B, the electronic device (200) can identify a language-based user input including multiple intents. The electronic device (200) can display an object (921) representing the language-based user input on the user interface (900). The electronic device (200) can obtain first input data including a first intent (e.g., tell me the weather) related to a first domain (e.g., weather service) and second input data including a second intent (e.g., play a song) related to a second domain (e.g., music service) based on a language-based user input. The electronic device (200) can obtain first response data based on inputting the first input data to a third artificial intelligence model (440). The electronic device (200) can obtain second response data based on inputting the second input data to the third artificial intelligence model (440). The electronic device (200) can obtain output data based on the first response data and the second response data. The electronic device (200) can display an object (922) based on the output data. The electronic device (200) can display a user interface (923) of a first application (e.g., a weather application) related to the first domain to provide a service on the first domain based on the first response data. For example, object (922) may include object (925) for executing an application related to a second domain (e.g., a music application). Object (925) may include an element indicating time (e.g., an arrow). Object (925) may indicate that the application related to the second domain will be executed after a set amount of time has elapsed. Although not illustrated, object (925) may indicate elapsed time. For example, the electronic device (200) may execute an application for the second domain based on the elapse of a predetermined period of time or on identifying a user input for an object (925). Based on the execution of the application for the second domain, the electronic device (200) may stop displaying the user interface (900) of the interactive application (463) and display the user interface (950) of the application for the second domain. The electronic device (200) may display the user interface (951) of the interactive application (463) as an overlay on the user interface (950). The user interface (951) of the interactive application (463) may indicate a response based on a language-based user input. FIGS. 10A, 10B, and 10C illustrate examples of operation of an electronic device according to one embodiment. Referring to FIGS. 10A, 10B, and 10C, the electronic device (200) can display a user interface (1000) based on the execution of an interactive application (463). The electronic device (200) can identify a language-based user input including a plurality of intents. The electronic device (200) can display an object (1001) representing the language-based user input on the user interface (1000). The electronic device (200) can obtain first input data including a first intent (e.g., "tell me the weather") related to a first domain (e.g., "weather service") and second input data including a second intent (e.g., "play a song") related to a second domain (e.g., "music service") based on a language-based user input. The electronic device (200) can obtain first response data based on inputting the first input data to a third artificial intelligence model (440). The electronic device (200) can obtain third input data based on the first response data and the second input data. The electronic device (200) can obtain second response data based on inputting the third input data to the third artificial intelligence model (440). Referring to FIG. 10A, the electronic device (200) may, within the user interface (1000) of the interactive application (463), display a user interface (1011) of a first application for a first domain to provide a service on the first domain based on the first response data. For example, the first response data may cause the electronic device (200) to display information related to today's weather through a weather application. The first response data may include data that causes the electronic device (200) to provide today's weather through the weather application. For example, if it is determined that the first intent includes a command to inform the weather, the electronic device (200) may determine a weather application related to weather as the first application, and may provide the user with an interface (1011) that displays information related to today's weather output from the first application using some information (e.g., today's weather) among the user inputs. The electronic device (200) may display a user interface (1012) of a second application for the second domain to provide a service on the second domain based on the second response data. For example, the user interface (1011) of the first application and the user interface (1012) of the second application may be displayed within the user interface (1000) of the interactive application (463). Depending on the embodiment, the user interface (1011) of the first application and the user interface (1012) of the second application may be displayed as a single user interface. The electronic device (200) may generate a new user interface using the user interface (1011) including at least one of the functions of the first application and the user interface (1012) including at least one of the functions of the second application. The electronic device (200) may display the new user interface within the user interface (1000) of the interactive application (463). For example, the second response data may cause the electronic device (200) to play music related to today's weather. The first response data may include data that causes the electronic device (200) to play (or provide) music related to today's weather. For example, if the second intent is determined to include a command related to music playback, the electronic device (200) may determine a music playback application related to music playback as the second application and provide the user with an interface (1022) for playing music related to today's weather. Referring to FIG. 10b, the electronic device (200) can stop displaying the user interface (1000) of the interactive application (463). The electronic device (200) can display the user interface (1021) of the first application for the first domain through the display (202). The electronic device (200) can display the user interface (1022) of the second application for the second domain as at least a partial overlay of the user interface (1021) of the first application. Referring to FIG. 10c, the electronic device (200) can stop displaying the user interface (1000) of the interactive application (463). The electronic device (200) can display the user interface (1031) of the second application regarding the second domain through the display (202). The electronic device (200) can display the user interface (1032) of the first application regarding the first domain by overlapping at least a portion of the user interface (1031) of the second application. FIGS. 11A and 11B illustrate examples of operation of an electronic device according to one embodiment. Referring to FIGS. 11A and 11B, the electronic device (200) can provide a response to each of the user inputs based on multi-turn based user inputs. Referring to FIG. 11A, the electronic device (200) can identify a first user input, a second user input, and a third user input. For example, the first user input may be, "Tell me the weather in Seoul." The second user input may be, "How is San Francisco?" The third user input may be, "What is the time difference between the two places?" For example, the electronic device (200) may display an object (1101) representing a first user input within the user interface (1100) of the interactive application (463) (e.g., the interactive application (463) of FIG. 4). The electronic device (200) may display an object (1102-1) and a user interface (1102-2) on the user interface (1100) based on response data to the first user input. The electronic device (200) may input input data according to the first user input into a third artificial intelligence model. The electronic device (200) may obtain response data for the first user input based on inputting the input data according to the first user input into the third artificial intelligence model. The response data for the first user input may include text representing information about the weather in Seoul, and data for executing (or displaying) a weather application representing the weather in Seoul. According to one embodiment, the electronic device (200) may display an object (1103) representing a second user input within the user interface (1100) of the interactive application (463). The electronic device (200) may obtain response data for the second user input based on the history information and the second user input. For example, the history information may include response data for the first user input. For example, the history information may be maintained for the duration of the session. For example, the electronic device (200) may input input data and history information (e.g., response data for the first user input) according to the second user input into the first artificial intelligence model. The electronic device (200) may generate (or obtain) other input data (e.g., “Tell me the weather in San Francisco”) based on inputting the input data and history information according to the user input into the first artificial intelligence model. The electronic device (200) may obtain response data for the second user input based on inputting other input data into the third artificial intelligence model. Depending on the embodiment, the other input data may be configured as a prompt. The response data for the second user input may include text representing information about the weather in San Francisco, and data for executing (or displaying) a weather application representing the weather in San Francisco. According to one embodiment, the electronic device (200) may display an object (1104-1) and a user interface (1104-2) on the user interface (1100) based on response data to the second user input. The electronic device (200) may add the response data to the second user input to the history information. According to one embodiment, the electronic device (200) may display an object (1105) representing a third user input within the user interface (1100) of the interactive application (463). The electronic device (200) may obtain response data for the third user input based on the history information and the third user input. For example, the history information may include response data for the first user input and response data for the second user input. For example, the electronic device (200) may input input data and history information (e.g., response data for the first user input, response data for the second user input) according to a third user input into the first artificial intelligence model. Based on inputting the input data and history information according to the third user input into the first artificial intelligence model, the electronic device (200) may generate (or obtain) other input data (e.g., tell me the time difference between Seoul and San Francisco). Based on inputting other input data into the third artificial intelligence model, the electronic device (200) may obtain response data for the third user input. Depending on the embodiment, the other input data may be configured as a prompt. The response data for the third user input may include text indicating the time difference between Seoul and San Francisco, and data for executing (or displaying) a clock application indicating the respective times of Seoul and San Francisco. The electronic device (200) may display an object (1106-1) and a user interface (1106-2) on the user interface (1100) based on response data for the second user input. The electronic device (200) may add response data for the third user input to the history information. According to one embodiment, the electronic device (200) can identify the end of a session. For example, the electronic device (200) can identify the end of a session based on identifying a change in the conversation topic. For example, the electronic device (200) can identify the end of a session based on identifying that no user input has been received for a period exceeding a threshold time. The electronic device (200) can delete (or discard) history information based on the end of a session. Referring to FIG. 11B, the electronic device (200) can identify a first user input. The electronic device (200) can display an object (1151) representing the first user input within the user interface (1150) of the interactive application (463). The electronic device (200) can display an object (1152) based on response data to the first user input. The electronic device (200) can display an object (1152) in response to the first user input, and then identify the second user input. The electronic device (200) can display an object (1153) representing the second user input within the user interface (1100) of the interactive application (463). The electronic device (200) can obtain response data for the second user input based on the history information and the second user input. For example, the history information can include response data for the first user input. For example, the history information can be maintained while the session is maintained. For example, the data manager (430) of the electronic device (200) can manage the history information while the session is maintained. For example, the data manager (430) can accumulate and store response data for user inputs (e.g., the first user input, the second user input) while the session is maintained. The electronic device (200) may display an object (1154) on the user interface (1150) based on response data to the second user input. The electronic device (200) may add the response data to the second user input to the history information. The electronic device (200) may identify the end of a session. For example, the electronic device (200) may identify the end of a session based on identifying a change in the conversation topic. For example, the electronic device (200) may identify the end of a session based on identifying that no user input is received for a time exceeding a threshold time. The electronic device (200) may delete (or discard) the history information based on the end of the session. FIG. 12 illustrates an example of operation of an electronic device according to one embodiment. Referring to FIG. 12, the electronic device (200) can provide a response according to each of the user inputs based on multi-intent-based user inputs. According to one embodiment, the electronic device (200) may display an object (1201) representing a first user input within a user interface (1200) of an interactive application (463). Based on response data to the first user input, the electronic device (200) may display an object (1202) and a user interface (1203) on the user interface (1200). For example, the first user input may be “Show me tomorrow’s schedule.” Based on the first user input, the electronic device (200) may identify an intent such as “Show me my schedule.” Based on inputting the first user input into a third artificial intelligence model (440) (e.g., the third artificial intelligence model (440) of FIGS. 4A and 4B), the electronic device (200) may obtain text guiding the schedule for tomorrow and data causing the electronic device (200) to execute a schedule application for displaying the schedule for tomorrow. The electronic device (200) can display an object (1204) representing a second user input within the user interface (1200) of the interactive application (463). Based on the second user input, the electronic device (200) can identify first input data including a first intent (e.g., “Remind me to grab my smartwatch 10 minutes before this schedule”) and second input data including a second intent (e.g., “Set an alarm for 7 a.m.”). Based on the first input data and history information including response data to the first user input, the electronic device (200) can obtain third input data (e.g., “Remind me to grab my smartwatch 10 minutes before this schedule and set an alarm for 7 a.m.”) using the first artificial intelligence model (410) (e.g., the first artificial intelligence model (410) of FIG. 4A or 4B). The electronic device (200) can obtain first response data based on third input data. The electronic device (200) can obtain second response data based on second input data. The electronic device (200) may obtain output data using a second artificial intelligence model (420) (e.g., the second artificial intelligence model (420) of FIG. 4A or FIG. 4B) based on the first response data and the second response data. The electronic device (200) may display an object (1205) representing a language-based response message according to the output data within the user interface (1200). According to the above-described embodiment, the electronic device (200) can identify "Remind me to take my smartwatch 10 minutes before this schedule" as the first input data. The electronic device (200) can obtain third input data based on the history information (e.g., information about the 8:00 AM running schedule) and the first input data. The electronic device (200) can obtain third input data, such as "Remind me to take my smartwatch 10 minutes before the 8:00 AM running schedule and set an alarm for 7:00 AM", using the first artificial intelligence model (410). The electronic device (200) can perform a response to each user input based on the multi-intent by obtaining the third input data based on the history information about the conversation history. FIG. 13 illustrates an example of operation of an electronic device according to one embodiment. Referring to FIG. 13, the electronic device (200) can provide responses to user inputs based on multi-intents based on history information. According to one embodiment, the electronic device (200) may display objects (1310) representing a first user input and a response to the first user input within a user interface (1300) of an interactive application (463) (e.g., the interactive application (463) of FIG. 4A or FIG. 4B). The electronic device (200) may display objects (1320) representing a second user input and a response to the second user input within the user interface (1300). The electronic device (200) may store information about the conversation history as history information. According to one embodiment, the electronic device (200) can identify a third user input based on multiple intents. The electronic device (200) can display an object (1331) representing the third user input within the user interface (1300). Based on the third user input, the electronic device (200) can identify the first input data and the second input data. For example, the third user input can be configured based on a multiple intent including a plurality of intents. According to one embodiment, the electronic device (200) can identify a third user input, such as "Save the schedule and send this content to Kim Min-seong as well." The electronic device (200) can identify first input data, such as "Save the schedule." The electronic device (200) can identify second input data, such as "Send this content to Kim Min-seong as well." For example, the electronic device (200) can identify the first input data and the second input data using the first artificial intelligence model (410) (e.g., the first artificial intelligence model (410) of FIG. 4A or 4B). The electronic device (200) can input the third user input and history information into the first artificial intelligence model (410). The electronic device (200) can generate (or identify) first input data and second input data as outputs of the first artificial intelligence model (410) based on inputting third user input and history information into the first artificial intelligence model (410). The electronic device (200) can obtain third input data based on inputting history information and first input data into the first artificial intelligence model (410). The electronic device (200) can obtain third input data, such as "Save the Gwanggyosan Mountain hiking schedule for 7:00 AM next Wednesday." The electronic device (200) can obtain fourth input data based on inputting history information and second input data into the first artificial intelligence model (410). The electronic device (200) can obtain fourth input data, such as, "Send a text message to Kim Min-seong saying, 'It takes 32 minutes to get to the Gwanggyosan access road by 7:00 AM next Wednesday. The expected arrival time is 7:32 AM.'" In one embodiment, the operation on the third input data may be performed on the first domain. The operation on the fourth input data may be performed on the second domain. For example, the electronic device (200) may first obtain first response data for the third input data. Based on the first response data, the electronic device (200) may display an object (1332) and a user interface (1333). The user interface (1333) may include an object (1341) for rejecting an action based on the first response data and an object (1342) for accepting an action based on the first response data. For example, the first response data may include text for asking a user to save a schedule and data for displaying a calendar application for saving the schedule. According to one embodiment, a user of the electronic device (200) may not perform inputs to objects (1341) and (1342). The electronic device (200) may identify acceptance of performing an action according to the first response data by identifying a language-based user input (e.g., “yes”). The electronic device (200) may display an object (1334) representing the language-based user input. The electronic device (200) may display an object (1335) indicating that an action according to the first response data (e.g., data for storing the user’s Gwanggyosan Mountain hiking schedule) has been performed. The electronic device (200) can obtain second response data (e.g., data for sending a text message about the Gwanggyosan Mountain itinerary to Kim Min-seong) for the fourth input data. The electronic device (200) can display an object (1336) and a user interface (1337) based on the second response data. For example, the electronic device (200) can display a user interface (1337) for inquiring whether to perform an action (e.g., adding a Gwanggyosan Mountain hiking itinerary) according to the second response data. For example, the electronic device (200) can display a user interface (1337) for inquiring whether to add the Gwanggyosan Mountain hiking itinerary to a calendar application. For example, the user interface (1337) can include an object (1343) for rejecting the performance of an action according to the second response data and an object (1344) for accepting the performance of an action according to the second response data. A user of the electronic device (200) may perform an input on an object (1344). The electronic device (200) may display an object (1338) indicating that an operation has been performed according to the second response data. The electronic device (200) may display a user interface (1339) indicating a result of performing the operation according to the second response data. For example, the electronic device (200) may display a user interface (1339) indicating that a text message has been sent to Kim Min-seong to indicate a result of performing the operation according to the second response data. According to the above-described embodiment, an example in which the first response data is acquired before the second response data is illustrated, but this is not limited thereto. According to the embodiment, the second response data may be acquired before the first response data. If the second response data is acquired before the first response data, the electronic device (200) may display the object (1336) and the user interface (1337) and then display the object (1332) and the user interface (1333). Although not illustrated, in some embodiments, the electronic device (200) may display one object or user interface based on the first response data and the second response data. FIG. 14 illustrates an example of operation of an electronic device according to one embodiment. Referring to FIG. 14, an electronic device (200) can receive a first user input. The electronic device (200) can display an object (1401) representing the first user input on a user interface (1400) of an interactive application (463) (e.g., the interactive application (463) of FIG. 4A or FIG. 4B). The electronic device (200) can display an object (1402) representing a response to the first user input on the user interface (1400). According to one embodiment, the electronic device (200) can receive a second user input. The electronic device (200) can display an object (1403) representing the second user input on the user interface (1400) of the interactive application (463). The electronic device (200) can change the second user input based on history information. For example, the electronic device (200) can input the history information and the second user input into a first artificial intelligence model (410) (e.g., the first artificial intelligence model (410) of FIG. 4A or 4B ). The electronic device (200) can generate (or acquire, identify) the changed second user input based on inputting the history information and the second user input into the first artificial intelligence model (410). For example, the electronic device (200) can change “Korea is” to “Where is the capital of Korea?” based on history information regarding the conversation history. The electronic device (200) may obtain response data based on the changed second user input. For example, the electronic device (200) may obtain response data based on inputting the changed second user input into the third artificial intelligence model (440) (e.g., the third artificial intelligence model (440) of FIG. 4A or FIG. 4B ). Based on the response data, the electronic device (200) may display an object (1404) representing a response to the second user input on the user interface (1400). For example, the response data may cause the electronic device (200) to display an object (1404) representing the capital of Korea. According to one embodiment, the electronic device (200) can receive a third user input. The electronic device (200) can display an object (1405) representing the third user input on the user interface (1400) of the interactive application (463). The electronic device (200) can change the third user input based on history information. For example, the electronic device (200) can change "Is it raining there this weekend?" to "Is it raining in Seoul this weekend?" based on history information regarding the conversation history. The electronic device (200) can obtain response data based on the changed third user input. Based on the response data, the electronic device (200) can display an object (1406) representing a response to the third user input and a user interface (1407) on the user interface (1400). The electronic device (200) can receive a fourth user input. The electronic device (200) can display an object (1408) representing the fourth user input on the user interface (1400) of the interactive application (463). The electronic device (200) can change the fourth user input based on history information. For example, the electronic device (200) can change "Remind me to take an umbrella that day" to "Remind me to take an umbrella because it is expected to rain in Seoul on Sunday." The electronic device (200) can obtain response data based on the changed fourth user input. Based on the response data, the electronic device (200) can display an object (1409) and a user interface (1410) representing a response to the fourth user input on the user interface (1400). For example, the response data may include text indicating a response to the fourth user input, and data causing the electronic device (200) to register “It’s going to rain in Seoul on Sunday, so take an umbrella” in a calendar application (or a reminder application). Based on the response data, the electronic device (200) may display “I’ll tell you what I found out” through the object (1409). The electronic device (200) may display a user interface (1410) for the calendar application indicating that “It’s going to rain in Seoul on Sunday, so take an umbrella” has been registered in the calendar application. FIG. 15 illustrates an example of operation of an electronic device according to one embodiment. Referring to FIG. 15, the electronic device (200) can display a user interface (1500) of a first application (e.g., a message application) while the first application is running. The electronic device (200) can run an interactive application (463) (e.g., the interactive application (463) of FIG. 4A or FIG. 4B) while the first application (e.g., a message application) is running. The electronic device (200) can display a user interface (1510) of the interactive application (463) by overlapping at least a portion of the user interface (1500) of the first application (e.g., a message application). According to one embodiment, the electronic device (200) can receive user input using an interactive application (463). The electronic device (200) can display an object (1511) representing the user input on a user interface (1510). According to one embodiment, the electronic device (200) can analyze a user input using an artificial intelligence model (e.g., the first artificial intelligence model (410) of FIG. 4A or 4B). The electronic device (200) can change an input value of a second application related to information (e.g., an intent) according to the user input, and execute the second application. For example, the electronic device (200) can identify a user input, such as “Save this schedule.” The electronic device (200) can identify information displayed on the user interface (1500) of the first application that is currently being executed. The electronic device (200) can change the user input based on the identified information (e.g., the user’s appointment information at Hospital A). For example, the electronic device (200) can use the first artificial intelligence model (410) to change “Save this schedule” to “Save the appointment schedule at Hospital A on May 10 at 6 PM.” According to one embodiment, the electronic device (200) may obtain response data based on a changed user input. The electronic device (200) may display an object (1512) indicating that an operation has been performed based on the response data. The electronic device (200) may display a user interface (1513) of a second application (e.g., a calendar application) for providing a service based on the response data. For example, the user interface (1513) may display information regarding the result of performing the operation based on the response data. Figures 16a and 16b illustrate examples of operation of an electronic device according to one embodiment. Referring to FIG. 16A, the electronic device (200) can receive a user input (1601). The user input (1601) can be configured as, "Launch Gallery and tell me the weather." The electronic device (200) can identify first input data and second input data based on the user input (1601). The electronic device (200) can identify first input data such as "Launch Gallery." The electronic device (200) can identify second input data such as "Tell me the weather." According to one embodiment, the electronic device (200) may obtain first response data (e.g., data causing the execution of a gallery application) based on first input data (e.g., "Launch the gallery"). The electronic device (200) may execute the gallery application based on the first response data. The electronic device (200) may display a user interface (1610) of the gallery application. The electronic device (200) may obtain second response data based on second input data (e.g., "Tell me the weather"). The electronic device (200) may execute an interactive application (463) (e.g., the interactive application (463) of FIG. 4A or 4B) based on the second response data (e.g., data causing the execution of a weather application to display the weather). The electronic device (200) may display a user interface (1620) of the interactive application (463). The electronic device (200) may display an object (1621) representing weather information on a user interface (1620). For example, the user interface (1620) may include an object (1622) for receiving additional user input. In FIG. 16a, an example of an interactive application (463) being executed to display weather information is illustrated, but is not limited thereto. Depending on the embodiment, a weather application may also be executed to display weather information. Referring to FIG. 16B, the electronic device (200) can receive a user input (1602). The user input (1601) can be configured as, "Tell me the weather and launch the gallery." The electronic device (200) can identify first input data and second input data based on the user input (1602). The electronic device (200) can identify first input data such as "Tell me the weather." The electronic device (200) can identify second input data such as "Launch the gallery." The electronic device (200) can obtain first response data based on first input data. The electronic device (200) can execute an interactive application (463) based on the first response data. The electronic device (200) can display a user interface (1650) of the interactive application (463). For example, the user interface (1650) can include an object (1651) for displaying weather information. The electronic device (200) can obtain second response data based on the second input data. The electronic device (200) can display an object (1652) for executing the gallery application within the user interface (1650). The electronic device (200) can display a user interface (1660) of the gallery application based on the input to the object (1652). In FIG. 16b, an example of an interactive application (463) being executed to display weather information is illustrated, but is not limited thereto. Depending on the embodiment, a weather application may also be executed to display weather information. FIG. 17 illustrates an example of operation of an electronic device according to one embodiment. Referring to FIG. 17, the electronic device (200) may be a foldable electronic device. The electronic device (200) may identify a user input. For example, the user input may be, "Display a calendar, play music, and also display an album." The electronic device (200) can identify three intents based on a user input. The electronic device (200) can identify a first intent related to a first domain (e.g., a schedule management service), a second intent related to a second domain (e.g., a music playback service), and a third intent related to a third domain (e.g., a gallery launch service) based on the user input. The electronic device (200) can identify first input data including the first intent, second input data including the second intent, and third input data including the third intent based on the user input. According to one embodiment, the electronic device (200) can identify first input data requesting execution of a calendar application (e.g., “Execute (or display) the calendar application”). The electronic device (200) can identify second input data requesting execution of a music playback application (e.g., “Execute (or play music) the music application”). The electronic device (200) can identify third input data requesting execution of a gallery application (e.g., “Execute (or display) the gallery application”). The electronic device (200) can obtain first response data based on first input data. The electronic device (200) can obtain second response data based on second input data. The electronic device (200) can obtain third response data based on third input data. According to one embodiment, the display area (1700) of the electronic device (200) may be divided into a first display area (1701), a second display area (1702), and a third display area (1703). For example, the electronic device (200) may display a first user interface (1710) of a first application (e.g., a calendar application) related to a first domain on the first display area (1701) to provide a service on the first domain. The electronic device (200) may display a second user interface (1720) of a second application related to a second domain on the second display area (1702) to provide a service on the second domain. The electronic device (200) may display a third user interface (1730) of a third application (e.g., a gallery application) related to a third domain on the third display area (1703) to provide a service on the third domain. Figure 18 is a block diagram illustrating an integrated intelligence system according to one embodiment. Referring to FIG. 18, an integrated intelligence system (10) of one embodiment may include a user terminal (1800), an intelligent server (1900), and a service server (2000). A user terminal (1800) of one embodiment (e.g., electronic device (101) of FIG. 1) may be a terminal device (or electronic device) that can connect to the Internet, and may be, for example, a mobile phone, a smart phone, a personal digital assistant (PDA), a laptop computer, a TV, white goods, a wearable device, an HMD, or a smart speaker. According to one embodiment, a user terminal (1800) may include a communication interface (1810), a microphone (1820), a speaker (1830), a display (1840), a memory (1850), and a processor (1860). The components listed above may be operatively or electrically connected to each other. According to one embodiment, the communication interface (1810) may be configured to be connected to an external device to transmit and receive data. According to one embodiment, the microphone (1820) may receive sound (e.g., user speech) and convert it into an electrical signal. According to one embodiment, the speaker (1830) may output the electrical signal as sound (e.g., voice). According to one embodiment, the display (1840) may be configured to display an image or video. According to one embodiment, the display (1840) may display a graphical user interface (GUI) of an app (or application program) being executed. The display (1840) of one embodiment may be configured to display an image or video. The display (1840) of one embodiment may also display a graphical user interface (GUI) of a running app (or application program). The display (1840) of one embodiment may receive touch input via a touch sensor. For example, the display (1840) may receive text input via a touch sensor in an on-screen keyboard area displayed within the display (1840). According to one embodiment, the memory (1850) may store a client module (1851), a software development kit (SDK) (1853), and a plurality of apps (1855). The client module (1851) and the SDK (1853) may configure a framework (or solution program) for performing general functions. In addition, the client module (1851) or the SDK (1853) may configure a framework for processing user input (e.g., voice input, text input, touch input). According to one embodiment, the memory (1850) may be a program for performing a specified function, wherein the plurality of apps (1855) may include a first app (1855_1) and a second app (1855_3). According to one embodiment, each of the plurality of apps (1855) may include a plurality of operations for performing a specified function. For example, the plurality of apps (1855) may include at least one of an alarm app, a message app, and a schedule app. According to one embodiment, the plurality of apps (1855) may be executed by the processor (1860) to sequentially execute at least some of the plurality of operations. According to one embodiment, the processor (1860) can control the overall operation of the user terminal (1800). For example, the processor (1860) can be electrically connected to a communication interface (1810), a microphone (1820), a speaker (1830), a display (1840), and a memory (1850) to perform a designated operation. According to one embodiment, the processor (1860) may also execute a program stored in the memory (1850) to perform a designated function. For example, the processor (1860) may execute at least one of the client module (1851) or the SDK (1853) to perform the following operations for processing user input. The processor (1860) may control the operations of multiple apps (1855), for example, through the SDK (1853). The following operations described as operations of the client module (1851) or the SDK (1853) may be operations executed by the processor (1860). According to one embodiment, the client module (1851) can receive user input. For example, the client module (1851) can generate a voice signal corresponding to a user utterance detected through the microphone (1820). Alternatively, the client module (1851) can receive a touch input detected through the display (1840). Alternatively, the client module (1851) can receive a text input detected through a keyboard or a screen keyboard. In addition, the client module (1851) can receive various forms of user input detected through an input module included in the user terminal (1800) or an input module connected to the user terminal (1800). The client module (1851) can transmit the received user input to the intelligent server (1900). According to one embodiment, the client module (1851) can transmit status information of the user terminal (1800) to the intelligent server (1900) together with the received user input. The above status information may be, for example, the execution status information of the app. According to one embodiment, the client module (1851) may receive a result corresponding to the received user input. For example, the client module (1851) may receive a result corresponding to the user input from the intelligent server (1900). The client module (1851) may display the received result on the display (1840). Additionally, the client module (1851) may output the received result as audio through the speaker (1830). According to one embodiment, the client module (1851) can receive a plan corresponding to the received user input. The client module (1851) can display the results of executing multiple operations of the app according to the plan on the display (1840). For example, the client module (1851) can sequentially display the results of executing multiple operations on the display and output audio through the speaker (1830). As another example, the user terminal (1800) can display only some results of executing multiple operations (e.g., the result of the last operation) on the display and output audio through the speaker (1830). According to one embodiment, the client module (1851) may receive a request from the intelligent server (1900) to obtain information necessary to produce a result corresponding to a user input. The information necessary to produce the result may be, for example, status information of the user terminal (1800). According to one embodiment, the client module (1851) may transmit the necessary information to the intelligent server (1900) in response to the request. According to one embodiment, the client module (1851) can transmit result information of executing multiple operations according to a plan to the intelligent server (1900). The intelligent server (1900) can confirm that the received user input has been correctly processed through the result information. In one embodiment, the client module (1851) may include a voice recognition module. In one embodiment, the client module (1851) may recognize voice inputs to perform limited functions through the voice recognition module. For example, the client module (1851) may execute an intelligent app to process voice inputs to perform organic actions through designated inputs (e.g., "Wake up!"). According to one embodiment, the intelligent server (1900) can receive information related to user voice input from the user terminal (1800) via a communication network. According to one embodiment, the intelligent server (1900) can convert data related to the received voice input into text data. According to one embodiment, the intelligent server (1900) can generate a plan for performing a task corresponding to the user voice input based on the text data. In one embodiment, the plan may be generated by an artificial intelligence (AI) system. The AI ​​system may be a rule-based system, a neural network-based system (e.g., a feedforward neural network (FNN) or a recurrent neural network (RNN)), or a combination of the above or a different AI system. In one embodiment, the plan may be selected from a set of predefined plans or may be generated in real time in response to a user request. For example, the AI ​​system may select at least one plan from a plurality of predefined plans. According to one embodiment, the intelligent server (1900) may transmit the results calculated according to the generated plan to the user terminal (1800), or transmit the generated plan to the user terminal (1800). According to one embodiment, the user terminal (1800) may display the results calculated according to the plan on a display. According to one embodiment, the user terminal (1800) may display the results of executing an operation according to the plan on a display. An intelligent server (1900) of one embodiment may include a front end (1910), a natural language platform (1920), a capsule database (1930), an execution engine (1940), an end user interface (1950), a management platform (1960), a big data platform (1970), and an analytic platform (1980). According to one embodiment, the front end (1910) may receive user input from a user terminal (1800). The front end (1910) may transmit a response corresponding to the user input. According to one embodiment, the natural language platform (1920) may include an automatic speech recognition module (ASR module) (1921), a natural language understanding module (NLU module) (1923), a planner module (1925), a natural language generator module (NLG module) (1927), and a text to speech module (TTS module) (1929). According to one embodiment, the automatic speech recognition module (1921) can convert voice input received from the user terminal (1800) into text data. According to one embodiment, the natural language understanding module (1923) can use the text data of the voice input to determine the user's intention. For example, the natural language understanding module (1923) can perform syntactic analysis or semantic analysis on user input in the form of text data to determine the user's intention. According to one embodiment, the natural language understanding module (1923) can use linguistic features (e.g., grammatical elements) of morphemes or phrases to determine the meaning of words extracted from the user input, and can match the meaning of the determined words to the intent to determine the user's intent. The natural language understanding module (1923) can obtain intent information corresponding to the user's utterance. The intent information can be information indicating the user's intent determined by interpreting text data. Intent information may include information indicating an action or function that a user wishes to perform using the device. According to one embodiment, the planner module (1925) can generate a plan using the intent and parameters determined by the natural language understanding module (1923). According to one embodiment, the planner module (1925) can determine a plurality of domains necessary to perform a task based on the determined intent. The planner module (1925) can determine a plurality of operations included in each of the plurality of domains determined based on the intent. According to one embodiment, the planner module (1925) can determine parameters necessary to execute the determined plurality of operations or result values ​​output by the execution of the plurality of operations. The parameters and the result values ​​can be defined as concepts related to a specified format (or class). Accordingly, the plan can include a plurality of operations and a plurality of concepts determined by the user's intent. The planner module (1925) can determine the relationships between the plurality of operations and the plurality of concepts in a stepwise (or hierarchical) manner. For example, the planner module (1925) can determine the execution order of a plurality of actions based on the user's intention based on a plurality of concepts. In other words, the planner module (1925) can determine the execution order of a plurality of actions based on parameters required for the execution of the plurality of actions and results output by the execution of the plurality of actions. Accordingly, the planner module (1925) can generate a plan including association information (e.g., ontology) between the plurality of actions and the plurality of concepts. The planner module (1925) can generate the plan using information stored in a capsule database (1930) in which a set of relationships between concepts and actions is stored. According to one embodiment, the natural language generation module (1927) can convert specified information into text format. The information converted into text format may be in the form of natural language speech. The text-to-speech module (1929) of one embodiment can convert information in text format into information in speech format. According to one embodiment, the capsule database (1930) can store information about the relationship between a plurality of concepts and actions corresponding to a plurality of domains. For example, the capsule database (1930) can store a plurality of capsules including a plurality of action objects (or action information) and concept objects (or concept information) of a plan. According to one embodiment, the capsule database (1930) can store the plurality of capsules in the form of a concept action network (CAN). According to one embodiment, the plurality of capsules can be stored in a function registry included in the capsule database (1930). According to one embodiment, the capsule database (1930) may include a strategy registry that stores strategy information required when determining a plan corresponding to a voice input. The strategy information may include reference information for determining a single plan when there are multiple plans corresponding to a user input. According to one embodiment, the capsule database (1930) may include a follow-up registry that stores information on follow-up actions for suggesting follow-up actions to a user in a given situation. The follow-up actions may include, for example, follow-up utterances. According to one embodiment, the capsule database (1930) may include a layout registry that stores layout information of information output through the user terminal (1800). According to one embodiment, the capsule database (1930) may include a vocabulary registry that stores vocabulary information included in the capsule information. According to one embodiment, the capsule database (1930) may include a dialog registry in which information about a dialog (or interaction) with a user is stored. According to one embodiment, the capsule database (1930) can update stored objects through a developer tool. The developer tool may include, for example, a function editor for updating action objects or concept objects. The developer tool may include a vocabulary editor for updating vocabulary. The developer tool may include a strategy editor for creating and registering strategies that determine plans. The developer tool may include a dialog editor for creating a dialogue with a user. The developer tool may include a follow-up editor for activating follow-up goals and editing follow-up utterances that provide hints. The follow-up goals may be determined based on currently set goals, user preferences, or environmental conditions. According to one embodiment, the capsule database (1930) may also be implemented within the user terminal (1800). In other words, the user terminal (1800) may include a capsule database (1930) that stores information for determining an action corresponding to a voice input. According to one embodiment, the execution engine (1940) can produce a result using the generated plan. According to one embodiment, the end user interface (1950) can transmit the produced result to the user terminal (1800). Accordingly, the user terminal (1800) can receive the result and provide the received result to the user. According to one embodiment, the management platform (1960) can manage information used in the intelligent server (1900). According to one embodiment, the big data platform (1970) can collect user data. According to one embodiment, the analysis platform (1980) can manage the quality of service (QoS) of the intelligent server (1900). For example, the analysis platform (1980) can manage the components and processing speed (or efficiency) of the intelligent server (1900). According to one embodiment, the service server (2000) may provide a designated service (e.g., food ordering or hotel reservation) to the user terminal (1800). According to one embodiment, the service server (2000) may be a server operated by a third party. For example, the service server (2000) may include a first service server (2001), a second service server (2003), and a third service server (2005) operated by different third parties. According to one embodiment, the service server (2000) may provide information for generating a plan corresponding to the received voice input to the intelligent server (1900). The provided information may be stored, for example, in a capsule database (1930). In addition, the service server (2000) may provide result information according to the plan to the intelligent server (1900). In the integrated intelligence system (10) described above, the user terminal (1800) can provide various intelligent services to the user in response to user input. The user input may include, for example, input via a physical button, touch input, or voice input. According to one embodiment, the user terminal (1800) may provide a voice recognition service through an intelligent app (or voice recognition app) stored internally. In this case, for example, the user terminal (1800) may recognize a user utterance or voice input received through the microphone and provide the user with a service corresponding to the recognized voice input. According to one embodiment, the user terminal (1800) may perform a designated action based on the received voice input, either alone or in conjunction with the intelligent server and / or service server. For example, the user terminal (1800) may execute an app corresponding to the received voice input and perform a designated action through the executed app. According to one embodiment, when a user terminal (1800) provides a service together with an intelligent server (1900) and / or a service server, the user terminal may detect user speech using the microphone (1820) and generate a signal (or voice data) corresponding to the detected user speech. The user terminal may transmit the voice data to the intelligent server (1900) using a communication interface (1810). According to one embodiment, the intelligent server (1900) may generate a plan for performing a task corresponding to the voice input received from the user terminal (1800), or a result of performing an operation according to the plan. The plan may include, for example, a plurality of operations for performing a task corresponding to the user's voice input, and a plurality of concepts related to the plurality of operations. The concept may define parameters input to the execution of the plurality of operations, or result values ​​output by the execution of the plurality of operations. The plan may include association information between the plurality of operations and the plurality of concepts. In one embodiment, the user terminal (1800) can receive the response using the communication interface (1810). The user terminal (1800) can output a voice signal generated within the user terminal (1800) to the outside using the speaker (1830), or can output an image generated within the user terminal (1800) to the outside using the display (1840). FIG. 19 is a diagram showing a form in which relationship information between concepts and actions is stored in a database according to various embodiments. The capsule database (e.g., the capsule database (1930) of FIG. 18) of the intelligent server (e.g., the intelligent server (1900) of FIG. 18) may store multiple capsules in the form of a CAN (concept action network) (2150). The capsule database may store an action for processing a task corresponding to a user's voice input and parameters required for the action in the form of a CAN (concept action network). The CAN may represent an organic relationship between an action and a concept that defines parameters required to perform the action. The capsule database may store a plurality of capsules (e.g., Capsule A (2101), Capsule B (2104)) corresponding to each of a plurality of domains (e.g., applications). According to one embodiment, one capsule (e.g., Capsule A (2101)) may correspond to one domain (e.g., application). In addition, one capsule may correspond to at least one service provider (e.g., CP 1 (2102), CP 2 (2103), CP 3 (2106), or CP 4 (2105)) for performing a function of a domain related to the capsule. According to one embodiment, one capsule may include at least one operation (2115) and at least one concept (2125) for performing a specified function. According to one embodiment, a natural language platform (e.g., the natural language platform (1920) of FIG. 18) can generate a plan for performing a task corresponding to a received speech input using capsules stored in a capsule database. For example, a planner module of the natural language platform (e.g., the planner module (1925) of FIG. 18) can generate a plan using capsules stored in a capsule database. For example, a plan (2107) can be generated using actions (2211, 2213) and concepts (2212, 2214) of Capsule A (2101) and actions (2241) and concepts (2242) of Capsule B (2104). FIG. 20 is a diagram showing a screen for processing voice input received through an intelligent app by a user terminal according to various embodiments. The user terminal (1800) can execute an intelligent app to process user input through an intelligent server (e.g., the intelligent server (1900) of FIG. 13). According to one embodiment, on the 2010 screen, when the user terminal (1800) recognizes a designated voice input (e.g., wake up!) or receives an input via a hardware key (e.g., a dedicated hardware key), the user terminal (1800) may execute an intelligent app for processing the voice input. For example, the user terminal (1800) may execute the intelligent app while the schedule app is running. According to one embodiment, the user terminal (1800) may display an object (e.g., an icon) (2011) corresponding to the intelligent app on a display (e.g., the display (1840) of FIG. 18). According to one embodiment, the user terminal (1800) may receive a voice input by a user's speech. For example, the user terminal (1800) may receive a voice input such as "Tell me my schedule for this week!" According to one embodiment, the user terminal (1800) may display a user interface (UI) (2013) (e.g., an input window) of an intelligent app on which text data of a received voice input is displayed. According to one embodiment, on the 2020 screen, the user terminal (1800) may display a result corresponding to the received voice input. For example, the user terminal (1800) may receive a plan corresponding to the received user input and display "This Week's Schedule" according to the plan. Some of the operations described above may be executed (or performed) by an AI (artificial intelligence) system as described with reference to FIG. 21. Figure 21 is a schematic diagram of an exemplary AI system. Referring to FIG. 21, the AI ​​system (2100) may include an input / output interface (2110), an AI framework (2120), a generative AI model (2130), and / or a knowledge repository (2190). The input / output interface (2110) can receive input. The input can include user input and / or data acquired or generated by the electronic device. The data can include images, videos, and / or sensor data generated by at least one processor of the electronic device (e.g., at least one processor (210) or processor (1720)) (e.g., illuminance data around the electronic device acquired from a sensor or sensor hub (e.g., auxiliary processor (1723), posture data (or orientation data) of the electronic device, temperature inside the electronic device (e.g., temperature of the display (220) or temperature of the at least one processor (210)), size information of a display area of ​​the display (220), and / or images acquired through an image sensor of the electronic device (e.g., included in a camera module (1780)). The user input may include natural language, touch data obtained through touch circuitry included within the display panel (160) (e.g., used to identify input from a finger and / or a stylus), images displayed (and / or to be displayed) on the display panel (160), and / or video. As a non-limiting example, the user input may be received by the input / output interface (2110) together with context information. The context information may be described as additional information obtained in relation to the user input. The context information may relate to a state at the time the user input is received (e.g., including a state of the electronic device and / or a state around the electronic device (e.g., a user state)). For example, the context information may include information about one or more software applications running within the electronic device at the time the user input is received. For example, the context information may include information about a location of the electronic device (or a location of a user of the electronic device) at the time the user input is received.For example, the user input may be integrated with the contextual information. For example, the user input integrated with the contextual information may be received by the input / output interface (2110). The input / output interface (2110) can transmit (or provide) output. The output may include a result (or result information) generated or acquired by the AI ​​system (2100) based at least in part on the input. The format of the output may vary. For example, the output may include natural language. For example, the output may include content (e.g., including media content and / or multimedia content). For example, the output may include an action related to a user of the electronic device. For example, the output may have a format according to a user setting of the electronic device. The input / output interface (2110) can be described as a user query / response interface (2110). The AI ​​framework (2120) can be used to obtain information (or data) about the input from the input / output interface (2110) and control one or more components related to the AI ​​system (2100) using the obtained information. For example, the prompt design component (2121) within the AI ​​framework (2120) can use the acquired information to generate or obtain a prompt for a generative AI model (2130) (e.g., including a large language model (LLM) or a large multimodal model (LMM)). For example, the prompt design component (2121) can be described as an AI component that utilizes a learning algorithm and / or a neural network to provide enhanced prompts over time. For example, the prompt design component (2121) can use the acquired information to access a knowledge component (e.g., a knowledge repository (2190)) that includes user preference data, a prompt library, and / or prompt examples to generate or obtain a prompt. The generated prompt can be provided to the generative AI model (2130) (e.g., including an LLM or LMM). For example, the API / plugin management component (2122) within the AI ​​framework (2120) may be utilized to support communication for additional information requested (or induced) in connection with the prompt provided (or to be provided) to the generative AI model (2130). For example, the API / plugin management component (2122) may be utilized to create or establish channels for communication with various data sources (e.g., knowledge repositories (2190)). For example, the API / plugin management component (2122) may support access to at least some of the data sources. For example, the API / plugin management component (2122) may be utilized to request another component (e.g., an application / service component (2180)) to perform feedback (or response) according to the prompt. As a non-limiting example, information obtained (or generated) through the API / plugin management component (2122) may be provided to the prompt design component (2121) for generating a prompt. As a non-limiting example, information obtained (or generated) through the API / plugin management component (2122) may be provided to the generative AI model (2130). For example, the improvement component (2123) within the AI ​​framework (2120) can at least partially tune (or adjust) (or change) the result (e.g., content) obtained (or output) from the generative AI model (2130). For example, the improvement component (2123) can determine or verify whether the content obtained from the generative AI model (2130) is related to the input. For example, the improvement component (2123) can determine or verify whether the content obtained from the generative AI model (2130) contains biased content. For example, the improvement component (2123) can determine or verify whether the content obtained from the generative AI model (2130) contains harmful content. For example, the improvement component (2123) can support or assist in performing additional processing to improve the content obtained from the generative AI model (2130). For example, the improvement component (2123) may support providing hints to the user to improve the content. A generative AI model (2130) can be described as an artificial intelligence neural network that generates feedback in response to a prompt. For example, the feedback may include additional data and / or information related to the prompt, but relative to the prompt. For example, the feedback may include new content related to the prompt. For example, the generative AI model (2130) may include a model that generates images and / or a model that generates language. For example, the model that generates images may include a generative adversarial network (GAN) and / or a variational autoencoder (VAE). For example, the model that generates images may include a diffusion-based generative model (e.g., a transformer VAE). For example, the model that generates language may include CHAT-GPT 3 and / or CHAT-GPT 4. For example, a generative AI model (2130) may include an LMM that generates the feedback by recognizing text, images, and / or speech. As a non-limiting example, the AI ​​framework (2120) and / or the generative AI model (2130) may be included within an AI module (e.g., including a processing circuit) within the electronic device. For example, the AI ​​module may be operatively coupled with at least one processor of the electronic device. For example, the AI ​​module may be operatively coupled with a display driving circuit of the electronic device. For example, the AI ​​module may be operatively coupled with a sensor hub of the electronic device for one or more sensors within the electronic device. According to one embodiment, an electronic device may include at least one processor including instructions, a memory including one or more storage media, and a processing circuit. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify, based on a language-based user input, first input data comprising a first intent associated with a first domain and second input data comprising a second intent associated with a second domain, input the first input data into an application using one or more trained models, obtain first response data associated with the first intent based on inputting the first input data into the application, generate third input data based on the first response data and the second input data, input the third input data into the application, obtain second response data associated with the second intent based on inputting the third input data into the application, and provide, based on the second response data, a service on the second domain associated with a service on the first domain. In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify the first input data comprising the first intent and the second input data comprising the second intent based on inputting the language-based user input into a language-based first model. According to one embodiment, the first input data including the first intent and the second input data including the second intent can be identified based on inputting the language-based user input into a language-based first model. According to one embodiment, the third input data may be generated based on inputting the first response data and the second input data into the language-based first model. In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate first output data according to the first response data, and to generate second output data according to the second response data after the first output data is generated, based on identifying that a duration for obtaining the second response data exceeds a threshold time. According to one embodiment, the electronic device may include a display. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to display a user interface of a conversational application through the display based on execution of the conversational application, and to obtain a language-based user input while the user interface of the conversational application is displayed. In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to display, through the display, a first user interface of a first application relating to the first domain to provide a service on the first domain based on the first response data within the user interface of the interactive application, and to display, through the display, a second user interface of a second application relating to the second domain to provide the service on the second domain based on the second response data within the user interface of the interactive application. In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to stop displaying the user interface of the interactive application, display a first user interface of the first application relating to the first domain through the display, and display a second user interface of the second application relating to the second domain through the display, overlapping the first user interface. According to one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to display, within the user interface of the interactive application, at least one of a first object for executing a first application relating to the first domain or a second object for executing a second application relating to the second domain. According to one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate output data for the user input based on the first response data and the second response data, and to display a language-based response message according to the output data within the user interface of the interactive application. According to one embodiment, a method performed by an electronic device may include: identifying, based on a language-based user input, first input data including a first intent related to a first domain and second input data including a second intent related to a second domain; inputting the first input data into an application using one or more trained models; obtaining, based on the inputting of the first input data into the application, first response data related to the first intent; generating, based on the first response data and the second input data, third input data; inputting the third input data into the application; obtaining, based on the inputting of the third input data into the application, second response data related to the second intent; and providing, based on the second response data, a service on the second domain that is associated with a service on the first domain. According to one embodiment, the first input data including the first intent and the second input data including the second intent can be identified based on inputting the language-based user input into a language-based first model. According to one embodiment, the third input data may be generated based on inputting the first response data and the second input data into the language-based first model. In one embodiment, the method may include generating output data for the user input based on inputting the first response data and the second response data into a language-based second model. According to one embodiment, the method may include an operation of generating first output data according to the first response data based on identifying that a duration for obtaining the second response data exceeds a threshold time, and an operation of generating second output data according to the second response data after the first output data is generated. According to one embodiment, the method may include, based on execution of a conversational application, displaying a user interface of the conversational application through a display of the electronic device, and obtaining a language-based user input while the user interface of the conversational application is displayed. According to one embodiment, the method may include, within the user interface of the interactive application, displaying a first user interface of a first application relating to the first domain to provide a service on the first domain based on the first response data, and, within the user interface of the interactive application, displaying a second user interface of a second application relating to the second domain to provide the service on the second domain based on the second response data, through the display. According to one embodiment, the method may include, based on the first response data and the second response data, an operation of stopping display of the user interface of the interactive application, and displaying, through the display, a first user interface of the first application relating to the first domain, and an operation of displaying, through the display, a second user interface of the second application relating to the second domain, overlapping the first user interface. In one embodiment, the method may include displaying, within the user interface of the interactive application, at least one of a first object for executing a first application relating to the first domain or a second object for executing a second application relating to the second domain. According to one embodiment, a non-transitory computer-readable storage medium may store one or more programs. The one or more programs may include instructions that, when executed by at least one processor of an electronic device, cause the electronic device to identify, based on a language-based user input, first input data comprising a first intent associated with a first domain and second input data comprising a second intent associated with a second domain, input the first input data into the application, and based on inputting the first input data into the application using one or more trained models, obtain first response data associated with the first intent, based on the first response data and the second input data, generate third input data, input the third input data into the application, and based on inputting the third input data into the application, obtain second response data associated with the second intent, and based on the second response data, provide a service on the second domain associated with a service on the first domain. According to one embodiment, an electronic device may include at least one processor including instructions, a memory including one or more storage media, and a processing circuit. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to identify first input data including a first intent and second input data including a second intent based on inputting a user input to a first artificial intelligence model, input the first input data to a third artificial intelligence model, obtain first response data related to the first intent based on inputting the first input data to the third artificial intelligence model, generate third input data based on inputting the first response data and the second input data to the first artificial intelligence model, input the third input data to the third artificial intelligence model, obtain second response data related to the second intent based on inputting the third input data to the third artificial intelligence model, obtain output data based on inputting the first response data and the second response data to the second artificial intelligence model, and provide the output data to a user of the electronic device. According to the above-described embodiments, AI models based on rule models and deep models may have difficulty processing multi-turn and multi-intent user input. Therefore, by using a model constructed based on a generative model, processing of complex user utterances can be performed on electronic devices. Electronic devices according to embodiments disclosed herein may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to embodiments disclosed herein are not limited to the aforementioned devices. The embodiments of this document and the terminology used herein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. In this document, each of the phrases such as "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" may include any one of the items listed together with the corresponding phrase among the phrases, or all possible combinations thereof. Terms such as "first", "second", or "first" or "second" may be used simply to distinguish the corresponding component from other corresponding components and do not limit the corresponding components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as being "coupled" or "connected" to another component (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component. In one embodiment of this document, the term "module" used may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC). One embodiment of the present document may be implemented as software (e.g., a program (140)) including one or more instructions stored in a storage medium (e.g., an internal memory (136) or an external memory (138)) readable by a machine (e.g., an electronic device (101)). For example, a processor (e.g., a processor (120)) of the machine (e.g., an electronic device (101)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium. According to one embodiment, the method according to one embodiment disclosed in the present document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., by download or upload) through an application store (e.g., the Play Store) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server. According to one embodiment, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and arranged in other components. According to one embodiment, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to one embodiment, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added. While the present disclosure has been shown and described with reference to various embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the present disclosure as defined by the appended claims and their equivalents.

Claims

1. In electronic devices, A memory including instructions and one or more storage media; and At least one processor comprising a processing circuit, The above instructions, when individually or collectively executed by the at least one processor, Based on language-based user input, identify first input data including a first intent related to a first domain and second input data including a second intent related to a second domain, Inputting the above first input data into an application using one or more trained models, Based on inputting the first input data into the application, obtaining first response data related to the first intent, Based on the first response data and the second input data, third input data is generated, Enter the above third input data into the above application, Based on inputting the third input data into the application, obtaining second response data related to the second intent, Causing the electronic device to provide a service on the second domain linked to the service on the first domain based on the second response data. Electronic devices.

2. In the first paragraph, the first input data including the first intent and the second input data including the second intent, Based on inputting the above language-based user input into a language-based model, the identified, Electronic devices.

3. In the second paragraph, the third input data is, Based on inputting the first response data and the second input data into a language-based model, Electronic devices.

4. In the second paragraph, when the instructions are individually or collectively executed by the at least one processor, Causing the electronic device to generate output data for the user input based on inputting the first response data and the second response data into a language-based model. Electronic devices.

5. In the first paragraph, when the instructions are individually or collectively executed by the at least one processor, Generating first output data according to the first response data based on identifying that the duration for obtaining the second response data exceeds a threshold time, After the first output data is generated, causing the electronic device to generate second output data according to the second response data, Electronic devices.

6. In the first paragraph, the electronic device, Includes a display, The above instructions, when individually or collectively executed by the at least one processor, Based on the execution of a conversational application, the user interface of the conversational application is displayed through the display, causing said electronic device to obtain said language-based user input while said user interface of said interactive application is displayed; Electronic devices.

7. In the sixth paragraph, when the instructions are individually or collectively executed by the at least one processor, Within the user interface of the interactive application, a first user interface of a first application for the first domain is displayed to provide a service on the first domain based on the first response data, Causing the electronic device to display, through the display, a second user interface of a second application for the second domain, to provide the service on the second domain based on the second response data, within the user interface of the interactive application. Electronic devices.

8. In the sixth paragraph, when the instructions are individually or collectively executed by the at least one processor, Based on the first response data and the second response data: Stop displaying the user interface of the above interactive application, An operation of displaying a first user interface of a first application for the first domain through the display; and Causing the electronic device to display, through the display, a second user interface of a second application relating to the second domain, overlapping the first user interface; Electronic devices.

9. In the sixth paragraph, when the instructions are individually or collectively executed by the at least one processor, Causing the electronic device to display at least one of a first object for executing a first application for the first domain or a second object for executing a second application for the second domain within the user interface of the interactive application; Electronic devices.

10. In the sixth paragraph, when the instructions are individually or collectively executed by the at least one processor, Based on the first response data and the second response data, generate output data for the user input, Causing the electronic device to display a language-based response message according to the output data within the user interface of the interactive application; Electronic devices.

11. In a method performed by an electronic device, An operation for identifying first input data including a first intent related to a first domain and second input data including a second intent related to a second domain based on language-based user input; An action of inputting the first input data into an application using one or more trained models; An operation of obtaining first response data related to the first intent based on inputting the first input data into the application; An operation of generating third input data based on the first response data and the second input data; An action of inputting the third input data into the application; An operation of obtaining second response data related to the second intent based on inputting the third input data into the application; and Based on the second response data, including an operation of providing a service on the second domain linked to a service on the first domain, method.

12. In the 11th paragraph, the first input data including the first intent and the second input data including the second intent, Based on inputting the above language-based user input into a language-based model, the identified, method.

13. In the 12th paragraph, the third input data is, Based on inputting the first response data and the second input data into a language-based model, method.

14. In the 12th paragraph, the method, An operation of generating output data for the user input based on inputting the first response data and the second response data into a language-based model, method.

15. In a non-transitory computer-readable storage medium storing one or more programs, the one or more programs, when executed by at least one processor of an electronic device, Based on language-based user input, identify first input data including a first intent related to a first domain and second input data including a second intent related to a second domain, Inputting the above first input data into an application using one or more trained models, Based on inputting the first input data into the application, obtaining first response data related to the first intent, Based on the first response data and the second input data, third input data is generated, Based on inputting the third input data into the application, obtaining second response data related to the second intent, Enter the above third input data into the above application, Including instructions for causing the electronic device to provide a service on the second domain linked to a service on the first domain based on the second response data. Non-transitory computer-readable storage medium.

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