18 results about "Tooltip" patented technology

The invention discloses an intelligent tool calling method based on knowledge base matching, and the method comprises the following steps: S1, carrying out the blocking processing of prompt words of an MCP tool set, marking a feature tag for each tool, and forming a tool prompt word knowledge base; s2, obtaining a question text input by a user, carrying out semantic matching on the question text of the user and the feature tag of the tool cue word knowledge base, calculating the similarity and obtaining a corresponding matching result; s3, according to the matching result, entering the tool cue word knowledge base to recognize and automatically output a matched tool name; s4, if the user confirms that the tool name is accurate, tool execution is started; if the user neglects the tool name, displaying a tool list arranged according to a similarity descending order to the user for manual selection; s5, calling a tool confirmed or selected by the user and obtaining an execution result; and S6, summarizing the execution result through a large language model, and returning the summarized execution result to the user. The problem that a user cannot accurately call the optimal MCP tool is solved.

Techniques for large language model (LLM)-based correction based on a multi-tool prompt are described. In an example, a computer system receives, via a user interface, user input including user-provided information and indicating a request for a task to be performed on the user-provided information. The computer system generates, by using an LLM associated with a prompt, a first input to a first tool based on the user input. The prompt indicating a sequence of steps to perform for the task and tools available to the LLM. The first tool corresponds to a first step of the sequence of steps. The computer system determines, by using the LLM, a first output of the first tool in response to the first input and an update to the user-provided information based on the first output and a completion of the task. The computer system causes the user interface to present the update.

Mechanisms are provided to compress a tool prompt. An original tool prompt is segmented into text chunks. At least one semantic vector representation of the text chunks is generated and a first semantic distribution of the original tool prompt is generated based on the at least one semantic vector representation. A perturbed semantic vector representation is generated by eliminating at least one text chunk from the text chunks, and a second semantic distribution is generated based on the perturbed semantic vector representation. A comparison of the first and second semantic distributions is performed to generate at least one similarity metric. A compressed tool prompt is generated based on the at least one similarity metric by eliminating one or more text chunks that have a similarity metric that is above a threshold similarity value.

A header and a timestamp element for the header may be generated based on a request to process data for a page of a user interface. A tooltip with descriptive information for the timestamp element may be generated and displayed based on proximity of an interactive element to the timestamp element, and a page representation window may be displayed based on an interaction with the timestamp element. The page representation window includes a representation of the data field and its content that is indicative of how the data field and its content existed at a time of the request to process data. Moreover, an indicator of correspondence between the timestamp element and the page representation window may be displayed. Based on interaction with a settings indicator element, a header settings window for modifying settings for the header may be displayed with view options (e.g., all, custom, etc.) for data submissions.

The images represented in the image diagrams are interactive graphical user interfaces (GUIs) that visually convey information to a user related to systems for (i) creating and / or modifying and / or analyzing unit operations and data generated therefrom in manufacturing processes, such as cell and gene therapy manufacturing processes, (ii) combining live data from databases with textual information, and (iii) interactive analysis of data (e.g., patient data visualization systems) and analysis of data related to manufacturing processes. (A. Graph-Based Visualization and Interactive Data Views for Pharmaceutical Manufacturing Process Data Reconciliation) For example, in certain embodiments, the images represented in the image diagrams are associated with graph-based visualization tools that enable a user to analyze data related to one or more experiments and / or manufacturing processes used to produce pharmaceutical products and / or variations thereof. In particular, the images for graph-based visualization and data analysis GUI tools represented in the image diagrams can be used in association with GUIs that enable a user to automatically and / or semi-automatically (e.g., in conjunction with user review and / or input) generate visualizations that facilitate the examination of experiments and / or manufacturing processes and reconcile data generated across multiple processes and / or process runs. For example, among other things, the interactive graph-based visualization tools and their images may be provided (e.g., rendered) individually or together via one or more GUIs or windows, sub-windows, panels, etc. (Process Graph) For example, the image diagram illustrates a GUI that provides a visualization of a process graph. In one embodiment, the graph-based visualization tool represented in the image diagram includes generating and / or rendering a process graph that displays an experimental and / or manufacturing process for the production of pharmaceutical products, including biologics such as cell-based therapeutics and biologic drugs. The process graph includes multiple nodes, each representing a data point corresponding to a unit operation in a particular experimental and / or manufacturing process where information is collected and / or an action is performed.The image diagrams further illustrate various approaches for capturing and / or displaying these data points and how users interact with them. (Comparing and Reconciling Multiple Processes) In certain embodiments, the images depicted in the image diagrams are used as GUIs to provide graph-based visualization tools that provide comparison and / or reconciliation of data from multiple experiments and / or manufacturing processes, e.g., in an automated and / or semi-automated manner (e.g., coupled with user interactions such as review and selection actions). Among other things, the images depicted in the image diagrams include designs that overlay multiple graph processes, structurally compare them, and reconcile them based on data points. For example, the images depicted in the image diagrams may provide rendering data created by process comparison and reconciliation tools that (e.g., automatically) identify and address discrepancies, missing data, or anomalies, which can be used to generate a harmonized data set for further analysis, such as mathematical modeling. Thus, among other things, the graph-based visualization tools provided in the images depicted in the image diagrams address the challenges presented by unreconciled data across multiple experiments and / or manufacturing processes and / or within a single process that may be performed under varying conditions. Achieving automated reconciliation of such data is a significant challenge that, if not addressed, hinders effective and accurate analysis, which, in turn, can dramatically impact a user's and / or organization's ability to optimize and / or maintain manufacturing process quality and / or develop new processes. In particular, the images presented in the graph-based visualizations and the graphical representations that present them aid in adjusting sampling points to maximize overlay for effective comparisons and / or, in certain embodiments, identify overlapping points in existing data for effective real-time analysis. For example, the graphical representations show examples of multiple levels of data views and clickable / expandable pop-ups. In particular, in certain embodiments, the graphical representations are associated with GUIs that integrate the ability to collect and link actual data with process diagrams.For example, multiple levels of data can be viewed in an interactive and dynamic manner. For example, images presented in pictorial diagrams provide a high-level view, and while not all data may be directly visible, they provide clickable / expandable, customized, dynamic nodes for each node type, allowing users to simultaneously inspect and analyze collected and / or input data. In this manner, images presented in pictorial diagrams facilitate the identification and analysis of differences between processes. In some embodiments, structural differences between different processes indicate variations in conditions (e.g., temperature, duration, chemical concentrations), as well as the sequence and / or presence of certain steps. While unit operations (basic steps or stages in a process) may be generally similar to other processes, unique conditions and / or sequences can significantly affect the outcome, or the nature of the product or result. Thus, images presented in pictorial diagrams that provide visual display tools can be extremely useful in process optimization, troubleshooting, and ensuring that a process meets desired specifications. For example, changing the device that performs a unit operation and / or certain parameter values ​​within the unit operation (e.g., rotation speed, total volume, duration, etc.) can have a significant impact on the quality, recovery, efficacy, etc. of the output of that unit operation, which in turn can affect characteristics such as the biological / potency of the product, and additionally or alternatively, factors such as the cost of production, the number of doses produced per manufacturing run, and the like. Thus, among other things, images depicted in pictorial diagrams can be associated with and provided with GUIs that present generated data, such as automatically generated data (e.g., using ontologies), which helps to identify commonalities and / or differences between studies and facilitates performing analyses to determine, for example, whether device or parameter changes have significant impacts.In particular, as described herein, a graph-based visualization tool represented in a pictorial diagram provides a user with a visual representation of one or more manufacturing processes via a graph-based approach that easily communicates and highlights differences in conditions and unit operations, as well as their nature. For example, an image represented in a pictorial diagram may include visual features that highlight unreconciled data points. This approach facilitates the identification and correction of data reconciliation issues, thereby streamlining data analysis for research and process development conducted in the creation and production of pharmaceuticals, such as cell-based therapeutics and biologic drugs. (i. Process Graph with Interactive Nodes) The pictorial diagram illustrates an example of a graph-based visualization of a manufacturing process. As shown in the pictorial diagram, a manufacturing process can be represented and displayed via a process graph. Each node in the process graph displays a data point corresponding to a unit operation in the particular manufacturing process that it (e.g., the process graph) represents. The node may include information about the current data state and content (e.g., in real time) of the data point it represents. Within a graph-based visualization, nodes can be dynamic, such that, for example, a user interaction with a particular node (e.g., a mouse hover, click, touchscreen tap or long press, etc.) triggers the display of a tooltip indicating the current data state for the displayed data point, including data collected at various stages of the manufacturing process. Process graphs can be rendered and used for experiment design and process execution to outline complex manufacturing experiments over multiple days of manufacturing procedures and to visualize and track different stages of a real-time experiment.Experimental Overview: In some embodiments, a graph is displayed as an experimental overview, providing a high-level overview of an experiment, including the process steps and (e.g., approximate) order in which they were performed, the dates particular process steps were performed, how the process steps relate to one another (e.g., the top half of FIG. 1A ), and an overview of the various states / arms evaluated during the experiment and how those states relate to one another (e.g., the bottom half of FIG. 1A ). Timeline: In some embodiments, a process graph may include a timeline, displaying multiple timepoints, such as the days, during which a particular experiment or manufacturing process represented by the graph was performed. As shown in the image depicted in the pictorial diagram, the timeline may be displayed along the horizontal axis, with labeled circular icons used to visually represent individual timepoints (e.g., days of execution from day 1 through day 21). Other ways of visually displaying the timeline may be used, for example, along the vertical axis and / or using other shaped icons, other units (e.g., hours, weeks, etc.). Process Unit Operations: In some embodiments, a process graph may visually identify individual process unit operations performed during a manufacturing process. Individual process unit operations may be displayed, for example, through a combination of text labels and icons or markings that convey the particular unit operations performed and, optionally, the time at which they are carried out and / or their (e.g., temporal) relationship with respect to other unit operations. For example, the graph-based visualization shown in the image depicted in the pictorial diagram includes a series of text labels along the top row (of nodes) identifying various unit operations such as "Material Preparation," "Start-Up," "Transduction," and "Compounding." In one embodiment, as shown in the image depicted in the pictorial diagram, for example, the text labels also include a numerical component and identify the particular day on which each unit operation is performed, and the text labels are arranged sequentially from left to right along the horizontal axis to mark the order in which the operations are performed over time.The vertical dotted lines extending downward from each text label provide a visual guide for the expected schedule for each unit operation and / or a temporal mapping of the manufacturing process. (Data Points (Nodes)) As shown in the images depicted in the pictorial diagrams, data points in the manufacturing process associated with a particular unit operation and from which pertinent information (measurements and / or recorded observations) is collected are represented via nodes. Nodes may be rendered as icons such as filled circles as shown in the images depicted in the pictorial diagrams. In the images depicted in the pictorial diagrams, each circle is a node and is positioned so as to be visually aligned with a particular unit operation. That is, in the images depicted in the pictorial diagrams, it is located on a vertical dotted line extending downward from a text label identifying a particular unit operation, thereby identifying the data point related to that particular unit operation. (Connectivity) In some embodiments, the process graph may display the dependency or sequence of material and / or data flow from one unit operation to another via rendered connections between the various nodes. For example, as shown in the image depicted in the pictorial diagram, node connectivity may be rendered as lines connecting nodes across a timeline. (Data Connection Points) Specific points along the process where data is collected are marked, such as important checkpoints for quality control or measurements required for process evaluation. (Arms) In some embodiments, a process graph may include and / or display one or more (e.g., separate) arms, each representing a different experimental condition and / or baseline process variation. For example, in the image depicted in the pictorial diagram, the arms are rendered as various smaller graphs positioned below the timeline. Each line in the arms section indicates a different arm / condition as defined by the operator.Labels are provided to help clarify the focus of these steps and / or to distinguish and identify nodes as belonging to one condition, so that corresponding data collected from the laboratory are placed in the correct node and we do not mix data across conditions. In this case, the base process may be the step following a standard or control process, while other processes are steps that make experimental changes to that process or supplement the base process (e.g., making media, preparing materials, etc.). (Baseline Process and Base Process Graph) A baseline process may be a control and / or standard procedure and may be rendered as a base process graph. Text labels, color schemes, icon styles, positioning, and the like may be used to visually identify the baseline process, such as in graph-based visualizations. For example, in images presented in pictorial diagrams, the baseline process is identified and displayed as a node line directly below the timeline. In process graphs of images presented in pictorial diagrams, the baseline process may be the standard process against which other variations are compared. Variations and Outputs / Endpoints In some embodiments, a graph-based visualization can include one or more auxiliary subgraphs, each corresponding to and representing variations to experimental conditions and / or baseline versions of a manufacturing process. For example, the image depicted in the image diagram shows auxiliary subgraphs displaying variations labeled as "Ver1.1," "Ver1.2," "Ver2.1," "Ver2.3," etc., and "Condition 1," "Condition 2," "Condition 3," etc., representing different experimental arms or conditions. In this manner, the graph-based visualization tool can be used to communicate variations in materials used, process conditions, or specific unit operations performed. Additionally or alternatively, endpoints and / or outputs of different processes can also be displayed (e.g., via endpoint graphs).For example, as shown in the image depicted in the pictorial diagram, a series of nodes labeled "Out.1" and "Out.2" represent different endpoints and / or outputs of a process, such as different ways of processing or storing a final product. For example, in the exemplary subgraph shown in the image depicted in the pictorial diagram, lines refer to experimental conditions or interrelated subsets of a process, such as preparing materials (e.g., media) to feed a cell-containing process. Arm / condition sections help orient operators to the specific task being performed, and by identifying various arms in a descriptive manner, data collected in the lab are entered into corresponding nodes, and numbers / quantities, etc., are not mixed between conditions. Process graphs therefore facilitate the visualization and management of complex manufacturing processes. Among other things, they allow researchers to track the progress of experiments, compare different conditions or variations side by side, and ensure that data is systematically collected at designated points throughout the process. The ability to visualize the entire process in this way helps identify bottlenecks, ensure consistency, and facilitate data-driven decision-making.

1. Name of the product in this design: Graphical User Interface for Modeling, Simulation and Analysis of Electronic Equipment. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: It is used for the digital management of the entire process of modeling, simulation and analysis. Various parameters can be edited in the input boxes of the interface. The X in the design interface represents text and / or numbers and / or letters and / or symbols. 6. Human-Computer Interaction Method of Graphical User Interface: The main view is the main interface of the newly created "Project2", in which the "Flow" tab is selected by default; clicking the "Optimize" tab in the main view displays the change state diagram 1; editing the corresponding parameters in the input box on the right side of the change state diagram 1 displays the change state diagram 2; clicking the "Testkey" tab of the design change state diagram 2 displays the change state diagram 3; clicking the "Import" button of the change state diagram 3 displays the change state diagram 4; clicking the "Choose" button of the change state diagram 4 displays the change state diagram 5; clicking the "Run" button of the change state diagram 5 displays the change state diagram 6, in which a hover text tooltip informs the user of the object to be run; clicking the "Run" button of the change state diagram 6 displays the change state diagrams 7 and 8 in sequence; clicking "Create Prediction" in the left area of ​​the change state diagram 8 displays the change state diagram 9, in which the Create Prediction pop-up window is shown; clicking the Create button in the change state diagram 9... The "OK" button in the Prediction pop-up window displays the change status diagram 10, in which the "Flow" tab is selected by default; clicking the "Edit" button to the right of "Project2 / Prediction_P1 / Flow" above the table in the change status diagram 10 displays the change status diagram 11; clicking the "Prediction_P1" node in the change status diagram 11 and selecting "Optimize" displays the change status diagram 12; clicking the "Run" button in the change status diagram 12 displays the change status diagram 13.

A system and a method for generating contextually relevant prompts for Gen AI tools are disclosed. A user input corresponding to a data object is received for determining object characteristics. A plurality of pre-determined categories is determined from a pre-defined prompt library database based on the determined object characteristics, which is rendered for selection by a user. A plurality of pre-determined sub-categories is determined from the pre-defined prompt library database based on a selected pre-determined category from amongst the plurality of pre-determined categories and the plurality of pre-determined sub-categories is rendered for selection by the user. A selected pre-determined sub-category is transformed by inserting contextual data received from the user and the prompts are generated based on the transformed pre-determined sub-category.

Techniques for managing tasks and resources using a map-based GUI are disclosed. A system determines locations and available actions associated with the tasks. The system generates a map representing a geographic region and markers indicating the locations of the tasks within the region. In response to the selection of a marker corresponding to a particular task, the system presents an interactive tooltip corresponding to the available action. Responsive to the selection of the graphic element, the system calls an API that performs the action while concurrently presenting the map.

The application discloses a form verification error information prompting method, device and equipment, and creates an observer instance observe to listen to a form verification error information prompting element; when it is listened that the form verification error information prompting element is changed and mounted, the text content of the form verification error information prompting element is acquired, and a pre-configured tooltip prompt box is opened to display the text content, form verification error information is prompted through the prompt box, the problem that the traditional form verification error prompt scheme is not beautiful in prompt effect is effectively solved, the original complex form verification rule logic is reserved, the expansibility and adaptability are strong, and the mainstream UI component library form component can be quickly matched.

1. Name of the product in this design: Graphical User Interface for Hardware Management of Testing Machine for Electronic Equipment. 2. Intended use of this design: for use in electronic devices. 3. The key design features of this product are the graphical user interface content displayed on the electronic device. 4. The image or photograph that best illustrates the design points: Change state diagram 6. 5. As is customary, rear view, left view, right view, top view, and bottom view are omitted. 6. Purpose of the graphical user interface: for online upgrades, online loading, and editing of test machine hardware information. 7. Human-Computer Interaction Method of Graphical User Interface: The main view is the main interface. Clicking the "Account" menu item in the main menu will bring up a submenu, leading to the transition state shown in Figure 1. Clicking the "LogIn" menu item in the submenu will bring up a login dialog box, leading to the transition state shown in Figure 2. Entering login information in the login dialog box and clicking the "Log In" button will close the dialog box. The login account name will be displayed to the right of the "Account" text in the upper right corner of the main interface, leading to the transition state shown in Figure 3. Moving the mouse to the "Power On" button in the toolbar will display the button function tooltip in the lower right corner, leading to the transition state shown in Figure 4. Clicking the "Power On" button will power on the test machine, leading to the transition state shown in Figure 5. After power-on, the interface will automatically transition to the transition state shown in Figure 6. The test terminal information will be displayed in the table control in the middle of the interface, and the power-on process and completion information log will be displayed in the log output column at the bottom of the interface.

The images represented in the image diagrams are interactive graphical user interfaces (GUIs) that visually convey information to a user related to systems for (i) creating and / or modifying and / or analyzing unit operations and data generated therefrom in manufacturing processes, such as cell and gene therapy manufacturing processes, (ii) combining live data from databases with textual information, and (iii) interactive analysis of data (e.g., patient data visualization systems) and analysis of data related to manufacturing processes. (A. Graph-Based Visualization and Interactive Data Views for Pharmaceutical Manufacturing Process Data Reconciliation) For example, in certain embodiments, the images represented in the image diagrams are associated with graph-based visualization tools that enable a user to analyze data related to one or more experiments and / or manufacturing processes used to produce pharmaceutical products and / or variations thereof. In particular, the images for graph-based visualization and data analysis GUI tools represented in the image diagrams can be used in association with GUIs that enable a user to automatically and / or semi-automatically (e.g., in conjunction with user review and / or input) generate visualizations that facilitate the examination of experiments and / or manufacturing processes and reconcile data generated across multiple processes and / or process runs. For example, among other things, the interactive graph-based visualization tools and their images may be provided (e.g., rendered) individually or together via one or more GUIs or windows, sub-windows, panels, etc. Comparing and Reconciling Multiple Processes In certain embodiments, the images represented in the pictorial diagrams are used as GUIs that provide graph-based visualization tools that provide comparison and / or reconciliation of data from multiple experiments and / or manufacturing processes, e.g., in an automated and / or semi-automated manner (e.g., in conjunction with user interactions such as review and selection actions). Among other things, the images represented in the pictorial diagrams include designs that overlay multiple graph processes, structurally compare them, and reconcile them based on data points.For example, images presented in pictorial diagrams may provide rendering data, missing data, or anomalies created by process comparison and reconciliation tools that (e.g., automatically) identify and address discrepancies and can be used to generate harmonized data sets for further analysis, such as mathematical modeling. Thus, among other things, the graph-based visualization tools provided in images presented in pictorial diagrams address the challenges presented by unreconciled data across multiple experiments and / or manufacturing processes and / or within a single process that may be run under varying conditions. Achieving automated reconciliation of such data is a significant challenge that, if not addressed, hinders effective and accurate analysis, which, in turn, can dramatically impact a user's and / or organization's ability to optimize and / or maintain manufacturing process quality and / or develop new processes. Among other things, graph-based visualizations and the images presented in pictorial diagrams may aid in adjusting sampling points to maximize overlay for effective comparison and / or, in certain embodiments, identify overlapping points in existing data for effective real-time analysis. In some embodiments, structural differences between different processes indicate variations in conditions (e.g., temperature, duration, chemical concentrations), as well as the sequence and / or presence of certain steps. While unit operations (basic steps or stages in a process) may be generally similar to other processes, unique conditions and / or sequences can greatly affect the outcome, or the nature of the product or result. Thus, images presented in pictorial diagrams that provide visual display tools can be extremely valuable in process optimization, troubleshooting, and ensuring that a process meets desired specifications.For example, changing the device performing a unit operation and / or certain parameter values ​​within the unit operation (e.g., rotation speed, total volume, duration, etc.) can have a significant impact on the quality, recovery, efficacy, etc. of the output of that unit operation, which in turn can affect characteristics such as the biological / potency of the product, and additionally or alternatively, factors such as the cost of production, the number of doses produced per manufacturing run, and the like. Thus, among other things, images represented in pictorial diagrams can be associated with and provided as GUIs that present generated data, such as automatically generated data (e.g., using ontologies), to help identify commonalities and / or differences between studies and facilitate analysis to determine, for example, whether device or parameter changes have significant impacts. Among other things, graph-based visualization tools represented in pictorial diagrams, as described herein, provide users with visual representations of one or more manufacturing processes via a graph-based approach that easily communicates and highlights differences in conditions and unit operation, as well as their nature. For example, images represented in pictorial diagrams can include visual features that highlight unadjusted data points. This approach facilitates the identification and correction of data reconciliation issues, thereby streamlining data analysis for research and process development conducted in the creation and production of pharmaceuticals, such as cell-based therapeutics and biologic drugs. (i. Process Graph with Interactive Nodes) The image diagram shows an example of a graph-based visualization of a manufacturing process. As shown in the image diagram, a manufacturing process can be represented and displayed via a process graph. Each node in the process graph represents a data point corresponding to a unit operation in the particular manufacturing process that it (e.g., the process graph) represents. The node may include information about the current data state and content (e.g., in real time) of the data point that it represents.Within a graph-based visualization, nodes can be dynamic, such that, for example, user interaction with a particular node (e.g., mouse hover, click, touchscreen tap, or long press) triggers the display of a tooltip indicating the current data state of the displayed data point, including data collected at various stages of the manufacturing process. Process graphs can be rendered and used for experimental design and process execution to visualize and track different stages of a real-time experiment, outlining complex manufacturing experiments spanning multiple days of manufacturing procedures. Experimental Overview: In one embodiment, a graph is displayed as an experiment overview, providing a high-level overview of the experiment, including the process steps and (e.g., approximate) order in which they were performed, the dates specific process steps were performed, how the process steps relate to each other (e.g., the top half of FIG. 1A ), and an overview of the various states / arms evaluated during the experiment and how those states relate to each other (e.g., the bottom half of FIG. 1A ). Timeline: In one embodiment, a process graph can include a timeline, displaying multiple time points, such as the days in which a specific experiment or manufacturing process represented by the graph was performed. A timeline may be displayed along the horizontal axis, with labeled circular icons used to visually represent individual time points (running days 1 through 21). Other ways of visually representing the timeline may be used, such as along the vertical axis and / or using icons of other shapes, other units (e.g., hours, weeks, etc.). Process Unit Operations In some embodiments, a process graph may visually identify individual process unit operations performed during the manufacturing process. Individual process unit operations may be displayed, for example, via a combination of text labels and icons, or markings that convey the particular unit operations performed and, optionally, the times at which they are performed, and / or their (e.g., temporal) relationship with respect to other unit operations.For example, a graph-based visualization may include a series of text labels along the top row (of nodes) identifying various unit operations such as "Material Preparation," "Start-Up," "Transduction," and "Compounding." In some embodiments, for example, the text labels also include a numerical component, identifying the specific day on which each unit operation is performed, and the text labels are arranged sequentially from left to right along the horizontal axis to mark the order of operations over time. Vertical dotted lines extending downward from each text label provide a visual guide for the planned schedule for each unit operation and / or a temporal mapping of the manufacturing process. (Data Points (Nodes)) Data points in the manufacturing process associated with a particular unit operation and from which relevant information (measurements and / or recorded observations) is collected are displayed via nodes. Nodes may be rendered as icons, such as filled circles. Each circle is a node and is positioned to visually align with a particular unit operation; that is, it is located on a vertical dotted line extending downward from a text label identifying a particular unit operation, thereby identifying a data point related to that particular unit operation. (Connectivity) In some embodiments, a process graph may display the dependency or sequence of material and / or data flow from one unit operation to another through rendered connections between various nodes. For example, node connectivity may be rendered as lines connecting nodes across a timeline. (Data Connection Points) Distinct points along the process where data is collected are marked, such as important checkpoints for quality control or measurements required for process evaluation. (Arms) In some embodiments, a process graph may include and / or display one or more (e.g., separate) arms, each representing different experimental conditions and / or baseline process variations. For example, arms are rendered as various smaller graphs positioned below the timeline. Each line in the arms section indicates a different arm / condition as defined by the operator.Labels are provided to help clarify the focus of these steps and / or to distinguish and identify nodes as belonging to one condition, so that corresponding data collected from the laboratory are placed in the correct node and we do not mix data across conditions. In this case, the base process may be the step that follows a standard or control process, while other processes are steps that make experimental changes to that process or supplement the base process (e.g., making media, preparing materials, etc.). (Baseline Process and Base Process Graph) A baseline process may be a control and / or standard procedure and may be rendered as a base process graph. Text labels, color schemes, icon styles, positioning, and the like may be used to visually identify the baseline process, such as in a graph-based visualization. For example, the baseline process is identified and displayed as a node line directly below the timeline. In a process graph, the baseline process may be the standard process against which other variations are compared. Variations and Outputs / Endpoints: In certain embodiments, a graph-based visualization may include one or more auxiliary subgraphs, each corresponding to and representing variations to experimental conditions and / or baseline versions of a manufacturing process. Additionally or alternatively, different process endpoints and / or outputs may also be displayed (e.g., via endpoint graphs). Process graphs thus facilitate visualizing and managing complex manufacturing processes. Among other things, they enable researchers to track experimental progress, compare different conditions or variations side-by-side, and ensure that data is systematically collected at specified points throughout the process. The ability to visualize the entire process in this manner helps identify bottlenecks, ensure consistency, and facilitate data-driven decision-making. iii. Comparing and Tuning Multiple Processes: In certain embodiments, a graph-based visualization tool provides a GUI that offers techniques for the automated comparison and tuning of multiple manufacturing processes.Among other things, they visually communicate and compare multiple manufacturing processes in a manner that facilitates understanding the interactions between different manufacturing processes or the same process under different conditions. The pictorial illustration shows an example of comparing multiple manufacturing processes. The pictorial illustration shows multiple (three) overlaid and coordinated process graphs, each displaying a similar sequence of unit operations across a daily timeline. These multiple process graphs may display different experimental runs and / or batches in the manufacturing process. In the image depicted in the pictorial illustration, each graph may display the sequence of unit operations across a daily timeline. These graphs may display different experimental runs or batches in the manufacturing process, allowing for easy comparison and analysis of these separate activities over the same period of time. Comparing multiple graphs in this manner allows a user to, among other things: (i) identify patterns and trends. In some embodiments, overlaying graphs allows a user to easily discern general trends or patterns across different data sets or time periods. (ii) assess consistency and variability. In some embodiments, comparing graphs assesses the consistency of a process or experiment and helps identify any variability or anomalies. (iii) benchmark performance. In some embodiments, graphs can be used to display different batches or experimental runs, allowing a user to compare them and determine which performs better for a certain metric. (iv) Understanding Relationships. In some embodiments, seeing how different variables interact over time can help understand the relationships between them. (v) Making Informed Decisions. In some embodiments, the clear comparisons facilitated through the tool make it easier to make decisions based on empirical data, such as improving a process or replicating a successful experiment. In particular, images depicted in pictorial diagrams provide users with a visual display that facilitates process comparison by overlaying multiple graphs and providing visual cues based on and displaying comparative analysis of their structures and data points.For example, overlaying multiple graphs allows for direct visual comparison of different experimental runs or process batches. In certain embodiments, differences or similarities between one or more processes may be identified (e.g., automatically) and visually highlighted, e.g., as shown in a pictorial diagram. For example, if one process deviates in a unit operation, the process comparison and adjustment tools described herein may detect and flag this variation, e.g., via variations in the type, size, color, etc. of icons used to display nodes. For example, in the image depicted in the pictorial diagram, the process variation is flagged as an enlarged, color-coded (orange) circle.

The invention provides a tool calling method and device, electronic equipment and a storage medium. The method comprises the steps of determining a target available tool matched with input information in a plurality of available tool classes registered in advance based on tool prompt information and the input information input to a large model; wherein the available tool classes comprise available tools and tool attribute information corresponding to the available tools, and the tool prompt information is obtained based on the tool attribute information in the multiple available tool classes; and based on the called target available tool and the input information, generating large model output information corresponding to the input information.

A method, computer program product, and computer system are provided for generating instructions for user interface changes based on version updates. First data corresponding to a first input by a user on a first version of a user interface is received. An interface element on a second version of the user interface corresponding to the first input is identified. The second version of the user interface corresponds to an older version of the user interface than the first version. The second version of the user interface and the interface element are displayed to the user. Second data corresponding to a second input by the user on the displayed second version of the user interface is received. The first version of the user interface and a toast or tooltip corresponding to a new location of the interface element within the first version of the user interface are displayed to the user.

The invention relates to the technical field of static language AI collaboration, in particular to a static language code library and AI collaboration method, which comprises the following steps of: defining program method description and generating interface metadata; the conversion program method is described as an AI tool cue word, user transmission content, the AI tool cue word and an AI return structure cue word are merged into a final cue word to be transmitted to the AI, and a result is returned after final AI recognition; judging whether to call a local method or not according to a result returned by the AI, if so, reflecting to call the local method and returning a result; the AI iteratively calls a local method until a final result is returned; according to the method, the dynamic interaction capability between the static language and the AI can be improved, and the interaction accuracy is improved.

According to some embodiments, systems and methods are provided including a memory storing program code to: execute a functional automation tool for an application under test in at least two languages, wherein execution of the functional automation tool includes a rendering of a plurality of user interfaces in each of the at least two languages; identify at least one of a label and a tooltip in each of the plurality of user interfaces; capture a screenshot for each of the plurality of user interfaces, wherein the captured screenshots include a first screenshot and at least one subsequent screenshot; identify the subsequent screenshot as unique or redundant; and render a language acceptance testing output for each unique screenshot, displaying each identified label and tooltip in the at least two languages. Numerous other aspects are provided.

Solutions are disclosed that provide entity driven templates for customized user prompts. Examples surface suggested prompts to a user to guide a chat with a generative artificial intelligence (AI) model, so that the user is able to receive more accurate and more relevant responses than might be expected from a freeform query or a set of generic prompts that do not account for the user's particular organization or role within that organization. A user interface (UI) tooltip enables users to select available data fields associated with entities in a query prompt to receive more relevant, focused results. The entities are culled from data that is specific to the user's own organization, and in some examples prioritized and focused based on the user's particular role in the organization and / or permission to access various elements within the data.

The invention discloses an element display regulation and control method and device, a storage medium and an electronic device, and relates to the technical field of smart home, the method comprises the following steps: creating a tool prompt container through text attribute information detected in real time from a document object model element to obtain a loading container, carrying out mounting association on the loading container and the document object model element; creating a tool prompt container according to the text attribute information to obtain a loading container, and carrying out mounting association on the loading container and the document object model element; and under the condition that mounting association is completed, decomposing a target text corresponding to the document object model element into a first text and a second text, and regulating and controlling a visual display result of the document object model element according to the first text and the second text. The problems that the processing process of the overflow text is complex and the processing cost is high in the prior art are solved.

The images represented in the image diagrams are interactive graphical user interfaces (GUIs) that visually convey information to a user related to systems for (i) creating and / or modifying and / or analyzing unit operations and data generated therefrom in manufacturing processes, such as cell and gene therapy manufacturing processes, (ii) combining live data from databases with textual information, and (iii) interactive analysis of data (e.g., patient data visualization systems) and analysis of data related to manufacturing processes. (A. Graph-Based Visualization and Interactive Data Views for Pharmaceutical Manufacturing Process Data Reconciliation) For example, in certain embodiments, the images represented in the image diagrams are associated with graph-based visualization tools that enable a user to analyze data related to one or more experiments and / or manufacturing processes used to produce pharmaceutical products and / or variations thereof. In particular, the images for graph-based visualization and data analysis GUI tools represented in the image diagrams can be used in association with GUIs that enable a user to automatically and / or semi-automatically (e.g., in conjunction with user review and / or input) generate visualizations that facilitate the examination of experiments and / or manufacturing processes and reconcile data generated across multiple processes and / or process runs. For example, among other things, the interactive graph-based visualization tools and their images may be provided (e.g., rendered) individually or together via one or more GUIs or windows, sub-windows, panels, etc. Comparing and Reconciling Multiple Processes In certain embodiments, the images represented in the pictorial diagrams are used as GUIs that provide graph-based visualization tools that provide comparison and / or reconciliation of data from multiple experiments and / or manufacturing processes, e.g., in an automated and / or semi-automated manner (e.g., in conjunction with user interactions such as review and selection actions). Among other things, the images represented in the pictorial diagrams include designs that overlay multiple graph processes, structurally compare them, and reconcile them based on data points.For example, images presented in the pictorial diagrams may provide rendering data, missing data, or anomalies created by process comparison and reconciliation tools that (e.g., automatically) identify and address discrepancies and can be used to generate harmonized data sets for further analysis, such as mathematical modeling. Thus, among other things, the graph-based visualization tools provided in the images presented in the pictorial diagrams address the challenges presented by unreconciled data across multiple experiments and / or manufacturing processes and / or within a single process that may be performed under varying conditions. Achieving automated reconciliation of such data is a significant challenge that, if not addressed, hinders effective and accurate analysis, which, in turn, can dramatically impact a user's and / or organization's ability to optimize and / or maintain the quality of their manufacturing processes and / or develop new processes. Among other things, graph-based visualizations and the images presented in the pictorial diagrams may aid in adjusting sampling points to maximize overlay for effective comparisons and / or, in certain embodiments, identify overlapping points in existing data for effective real-time analysis. For example, the pictorial diagrams show examples of multiple levels of data views and clickable / expandable pop-ups. In particular, in some embodiments, the pictorial diagram is associated with a GUI that integrates the ability to collect and link actual data with the process diagram. For example, multiple levels of data can be viewed in an interactive and dynamic manner. For example, the image represented in the pictorial diagram provides a high-level view, and while not all data may be directly visible, it provides clickable / expandable and customized dynamic nodes for each node type, thereby allowing the user to simultaneously inspect and analyze collected and / or input data. In this manner, the image represented in the pictorial diagram facilitates the identification and analysis of differences between processes. In some embodiments, structural differences between different processes indicate variations in conditions (e.g., temperature, duration, chemical concentrations), as well as the order and / or existence of certain steps.While unit operations (basic steps or stages in a process) may be generally similar to other processes, specific conditions and / or sequences can significantly affect the outcome, or the nature of the product or result. Thus, images represented in pictorial diagrams that provide visual display tools can be extremely valuable in process optimization, troubleshooting, and ensuring that a process meets desired specifications. For example, changing the device performing the unit operation and / or specific parameter values ​​within the unit operation (e.g., rotation speed, total volume, duration, etc.) can have a significant impact on the quality, recovery, efficacy, etc. of the output of that unit operation, which in turn can affect characteristics such as product biological / potency, and additionally or alternatively, factors such as cost of production, number of doses produced per manufacturing run, and the like. Thus, among other things, images represented in pictorial diagrams can be associated with and provide GUIs that present generated data, such as automatically generated data (e.g., using ontologies), which can help identify commonalities and / or differences between studies and facilitate analysis to determine, for example, whether device or parameter changes have significant impacts. In particular, as described herein, a graph-based visualization tool represented in a pictorial diagram provides a user with a visual representation of one or more manufacturing processes via a graph-based approach that easily communicates and highlights differences in conditions and unit operations, as well as their nature. For example, the image represented in the pictorial diagram may include visual features that highlight unreconciled data points. This approach facilitates the identification and correction of data reconciliation issues, thereby streamlining data analysis for research and process development conducted in the creation and production of pharmaceuticals, such as cell-based therapeutics and biologic drugs. (i. Process Graph with Interactive Nodes) The pictorial diagram illustrates an example of a graph-based visualization of a manufacturing process. As shown in the pictorial diagram, a manufacturing process can be represented and displayed via a process graph.Each node in a process graph displays a data point corresponding to a unit operation in the particular manufacturing process it (e.g., the process graph) represents. A node may include information about the current data state and content (e.g., in real time) of the data point it represents. Within a graph-based visualization, nodes may be dynamic, such that, for example, user interaction with a particular node (e.g., mouse hover, click, touchscreen tap, or long press) triggers the display of a tooltip indicating the current data state of the displayed data point, including data collected at various stages of the manufacturing process. Process graphs may be rendered and used for experimental design and process execution to visualize and track different stages of a real-time experiment, outlining complex manufacturing experiments over multiple days of a manufacturing procedure. Experimental Summary: In one embodiment, a graph is displayed as an experiment summary, providing a high-level overview of the experiment, including the process steps and (e.g., approximate) order in which they were performed, the days that specific process steps were performed, how the process steps relate to each other, and an overview of the various states / arms evaluated during the experiment and how those states relate to each other. Timeline: In some embodiments, a process graph may include a timeline, displaying multiple time points, such as days, during which a particular experiment or manufacturing process represented by the graph is performed. As shown in the image depicted in the pictorial diagram, the timeline may be displayed along the horizontal axis, with labeled circular icons used to visually represent individual time points (running days 1 through 21). Other ways of visually displaying the timeline may be used, such as using icons of other shapes along the vertical axis and / or other units (e.g., hours, weeks, etc.). Process Unit Operations: In some embodiments, a process graph may visually identify individual process unit operations performed during the manufacturing process.Individual process unit operations may be displayed, for example, via a combination of text labels and icons or markings that convey the specific unit operations performed and, optionally, the time they are performed and / or their (e.g., temporal) relationship with respect to other unit operations. In some embodiments, as shown, for example, in the images depicted in the pictorial diagrams, the text labels also include a numerical component to identify the specific day on which each unit operation is performed, and the text labels are arranged sequentially from left to right along the horizontal axis to mark the order of operations performed over time. Vertical dotted lines extending down from each text label provide a visual guide for the planned schedule for each unit operation and / or a temporal mapping of the manufacturing process. (Data Points (Nodes)) As shown in the images depicted in the pictorial diagrams, data points in the manufacturing process associated with specific unit operations and from which relevant information (measurements and / or recorded observations) is collected are displayed via nodes. Nodes may be rendered as icons, such as filled circles, as shown in the images depicted in the pictorial diagrams. In the image depicted in the pictorial diagram, each circle is a node and is positioned to visually align with a particular unit operation. That is, in the image depicted in the pictorial diagram, it is placed on a vertical dotted line extending downward from a text label identifying a particular unit operation, thereby identifying a data point related to that particular unit operation. (Connectivity) In some embodiments, the process graph may display the dependency or sequence of material and / or data flow from one unit operation to another through rendered connections between various nodes. For example, as shown in the image depicted in the pictorial diagram, node connectivity may be rendered as lines connecting nodes across a timeline. (Data Connection Points) Specific points where data are collected are marked along the process, such as checkpoints important for quality control or measurements required for process evaluation.(Arms) In some embodiments, a process graph may include and / or display one or more (e.g., separate) arms, each representing a different experimental condition and / or variation in a baseline process. For example, in the image shown in the pictorial diagram, the arms are rendered as various smaller graphs positioned below the timeline. Each line in the arms section indicates a different arm / condition as defined by the operator. Labels are provided to help clarify the focus of these steps and / or to distinguish and identify nodes as belonging to a condition so that corresponding data collected from the laboratory is placed in the correct node and we do not confuse data across conditions. In this case, a base process may be a step that follows a standard or control process, while other processes are steps that make experimental changes to that process or supplement the base process (e.g., making media, preparing materials, etc.). (Baseline Process and Base Process Graph) A baseline process may be a control and / or standard procedure and may be rendered as a base process graph. Text labels, color schemes, icon styles, positioning, and the like can be used to visually identify a baseline process, such as in a graph-based visualization. For example, in an image depicted in a pictorial diagram, the baseline process is identified and displayed as a nodal line directly below the timeline. In a process graph depicted in a pictorial diagram, the baseline process may be a standard process against which other variations are compared. (Variations and Outputs / Endpoints) In certain embodiments, a graph-based visualization can include one or more auxiliary subgraphs, each corresponding to and representing variations to experimental conditions and / or baseline versions of a manufacturing process. For example, the image depicted in the pictorial diagram shows auxiliary subgraphs displaying variations labeled as "Ver1.1," "Ver1.2," "Ver2.1," "Ver2.3," etc., and "Condition 1," "Condition 2," "Condition 3," etc., representing different experimental arms or conditions.In this manner, graph-based visualization tools can be used to communicate variations in materials used, process conditions, or specific unit operations being performed. Additionally or alternatively, different process endpoints and / or outputs can also be displayed (e.g., via endpoint graphs). For example, as shown in the image depicted in the pictorial diagram, a series of nodes labeled "Out.1" and "Out.2" represent different endpoints and / or outputs of a process, such as different ways of processing or storing a final product. For example, in the exemplary subgraph shown in the image depicted in the pictorial diagram, lines refer to experimental conditions or interrelated subsets of a process, such as preparing materials (e.g., media) to feed a cell-containing process. Arm / condition sections help orient operators to the specific tasks being performed, and by using descriptive methods to identify various arms, data collected in the laboratory is entered into the corresponding nodes, and numbers / quantities, etc., are not confused between conditions. Thus, process graphs facilitate the visualization and management of complex manufacturing processes. Among other things, they allow researchers to track the progress of experiments, compare different conditions or variations side by side, and ensure that data is systematically collected at designated points throughout the process. The ability to visualize the entire process in this way helps identify bottlenecks, ensure consistency, and facilitate data-driven decision-making.