answer:Чтобы добавить `DeltaTime` в эти функции, предполагая, что вы хотите создать какой-то вид интерполяции или плавного движения, вы должны убедиться, что изменения происходят с учетом времени, прошедшего с последнего обновления. `DeltaTime` обычно представляет собой время в секундах, прошедшее с момента последнего кадра (или тика), и это значение используется для обеспечения независимого от кадров частоты обновления логики. Формулы с `DeltaTime` будут выглядеть следующим образом: ``` (CamX - OldX) / 10 * DeltaTime (CamY - OldY) / 10 * DeltaTime ``` Здесь `(CamX - OldX) / 10` и `(CamY - OldY) / 10` вычисляют некую базовую величину изменения координат, и затем результат умножается на `DeltaTime` для учета времени. Однако обратите внимание, что если ваша цель - интерполировать позицию камеры от `OldX` к `CamX` и от `OldY` к `CamY` за определенный период времени, разделение на '10' может оказаться неуместным. Вместо этого вам, возможно, потребуется использовать более сложные методы интерполяции, такие как линейная интерполяция (Lerp) или сглаживающая интерполяция (Slerp), которые могут включать использование параметра t, представляющего прогресс между начальным и конечным значениями, который мог бы изменяться со временем, например: ``` Lerp(OldX, CamX, t) Lerp(OldY, CamY, t) ``` Где 't' может изменяться от 0 до 1 в зависимости от `DeltaTime` и желаемой продолжительности интерполяции. Например, если вы хотите, чтобы интерполяция заняла 2 секунды, `t` будет увеличиваться на `(DeltaTime / 2.0)` каждый кадр.

answer:It appears you're providing the names and versions of two different Python libraries: 1. `gradio` - A Python library that allows you to quickly create easy-to-use, customizable UI components for your machine learning models or any Python script. - **Name:** gradio - **Version:** 4.8.0 2. `matplotlib` - A widely-used Python library that provides tools for creating static, interactive, and animated visualizations in Python. - **Name:** matplotlib - **Version:** 3.8.2 Both libraries are commonly used in data science and machine learning projects. `gradio` for creating interfaces to interact with models, and `matplotlib` for data visualization. Please note that the version numbers mentioned above are for clarification purposes and may not correspond to actual releases, as these are constantly updated. Always check the official package repositories or documentation for the most current version information.

answer:The code snippet you've shared is relatively complex and appears to set up a Gradio app with two functionalities: 1. **Fetching PR details:** It includes a form where users can enter a Purchase Request (PR) number and select a status. Upon clicking the "Fetch PR Details" button, it executes the `fetch_data` function, which queries a MySQL database for PR details and returns the results formatted in HTML. 2. **Displaying a pie chart:** It includes a pie chart that displays the count of PRs by status, using data from the same MySQL database. This chart is generated using the `matplotlib` library and is displayed on the Gradio app. Here is a breakdown of the functionality implemented in this Gradio app: - **clear_form:** Clears the input fields. - **fetch_data:** Queries the database for records based on the input PR number and status, and formats the results in HTML. - **plot_pie_chart:** Generates a pie chart showing the distribution of PR statuses. The Gradio app is configured using the `gr.Blocks` context manager, setting up a tabbed interface. For the database connection, it's important to note that you should never hardcode sensitive credentials like passwords in your code. Instead, use environmental variables or other secure methods to store and access these credentials. The Gradio interface consists of: - A textbox for entering the PR number. - A radio button group for selecting the status. - A button to fetch the PR details and another to clear the form. - A `gr.Plot` component that shows the pie chart, which is loaded initially with all statuses. Lastly, the app is launched with the `launch` method, setting `share=True`, which means that when the Gradio app is running, it will create a publicly shareable link that you can use to access the app from different devices. Please ensure you have the necessary MySQL database and table (`PR_Details`) with appropriate columns and data to support this application. Additionally, make sure to handle the security aspect of the database credentials properly. If you were to run this code, make sure that: - You have Gradio installed and imported correctly (`gradio` as `gr`). - The MySQL database is running and accessible with the credentials provided. - The MySQL connector for Python is installed. - `matplotlib` is installed for generating pie charts.

answer:It looks like you're trying to use the `gr.Plot` component incorrectly in Gradio. The `gr.Plot` component does not accept a 'plot' keyword argument for directly setting a function to generate the plot when creating the component. Instead, you should use the `gr.Plot` component to display a plot, and then use an interaction function (like the one you have for "Fetch PR Details") to update that plot when a certain input changes or a button is pressed. Here's how you could structure it: 1. Define the `gr.Plot` component with no plot initially: ```python pie_chart_output = gr.Plot(label="Status Pie Chart") ``` 2. Create a function that updates the content of the plot output component: ```python def update_pie_chart(): pie_chart = plot_pie_chart() return pie_chart ``` 3. Set up an interaction where selecting a status or clicking a button will update the plot: ```python # This could be a status selection interaction or a button press, depending on your needs some_input_component.change( update_pie_chart, inputs=[], outputs=[pie_chart_output] ) ``` For example, if you just want to show the pie chart once when the app loads without any interaction needed from the user, then you might call `update_pie_chart` outside of any interaction setup, store the pie chart figure, and then pass it when initializing the `pie_chart_output` component, like this: ```python initial_pie_chart = plot_pie_chart() with gr.Blocks() as app: # ... (your other components and interactions) pie_chart_output = gr.Plot(label="Status Pie Chart", figure=initial_pie_chart) # ... (rest of your code) app.launch(share=True) ``` You'll need to ensure that the `plot_pie_chart` function is returning a plot in a format that the `gr.Plot` component can render, such as a `matplotlib` figure. Make sure all the inputs and outputs are connected correctly in the Gradio app interactions, and lastly, note that this is a general guideline; you might need to adjust the code to fit exactly into your Gradio app structure.