\chapter{Implementation}
\label{chap:implementation}

\section{Introduction}
\label{sec:chap4:intro}

In this chapter, we transition from theoretical framework to a functional software solution. Our focus is on developing the backend Django Python server and the frontend Figma plugin, aiming to seamlessly integrate AI technologies for UI generation within the Figma environment. This chapter provides a comprehensive overview of the development process, detailing environment setup, frontend and backend implementation, testing, deployment, and other related tasks.

\section{Setting Up the Development Environment}
\label{sec:chap4:setdevenvironment}

We will cover in this section the essential steps in creating the development environment both for frontend and backend development. Once established, it guarantees a seamless blending of resources and tools that are indispensable for efficient software development, during collaboration.

\subsection{Version Control with Git}
\label{subsec:chap4:git}

Version control is essential in modern software development for tracking changes, managing code efficiently, and maintaining project integrity. For this thesis project, I utilize Git as the version control system. Git provides a robust and flexible framework for preserving project histories, enabling a seamless development workflow.

\subsection{GitHub Repository}
\label{subsec:chap4:github}

To leverage additional features and centralize my project codebase, I hosted my Git repository on GitHub. GitHub serves as a central hub for organizing project milestones, tracking issues, and storing project files. Utilizing GitHub's features such as branches, commits, and pull requests enhances project management and organization, fostering accountability and transparency in the development process.

\subsection{Integrated Development Environment (IDE)}
\label{subsec:chap4:ide}

I use Visual Studio Code (VS Code) as my primary Integrated Development Environment (IDE) for coding and development tasks. VS Code offers a wide range of features including code editing, debugging, version control integration, and extensibility through plugins and extensions. Its extensive ecosystem and user-friendly interface provide the necessary tools to write, test, and debug code efficiently, contributing to the overall success of this thesis project.

\subsection{Frontend Development Setup}
\label{subsec:chap4:frontenddev}

Setting up the frontend development environment for creating the Figma plugin requires several steps to ensure seamless integration with the Figma desktop application. Here is a detailed explanation:

\begin{itemize}
   \item \textbf{Login and Access Plugin Development Section:} After installing the Figma desktop application, I signed into my Figma account and accessed the "Development" submenu within the "Plugins" section, typically found in the left sidebar menu.

   \item \textbf{Create a New Plugin:} I initiated the creation of a new plugin by clicking the "New Plugin" button within the "Development" submenu. I was prompted to name the plugin and select a project type. Selecting the "Figma" project type aligned with my goal to develop a Figma plugin.

   \item \textbf{Choose Figma Design:} Upon selecting the "Figma" project type, I chose a design template for the plugin. Figma offers various design templates tailored for different functionalities. I selected the "Figma Design" template, ideal for UI-focused plugins.

   \item \textbf{Generate Plugin Folder:} Upon completion of the plugin creation process, Figma automatically generated a folder on my local machine. This folder contained boilerplate code and template files essential for plugin development. I opened this folder in Visual Studio Code, my preferred code editor, to begin development.

   \item \textbf{Add TypeScript and React:} To enhance type safety and development efficiency, I utilized TypeScript as the foundation for the Figma plugin template. Additionally, I incorporated React, a popular JavaScript library for building user interfaces. Integrating React into the Figma plugin enabled dynamic and interactive UI components, benefiting from its extensive range of components and state management features.
\end{itemize}

This setup, tailored to my work style and project requirements, establishes a solid foundation for effective frontend development, allowing me to create innovative and user-friendly plugins for the Figma platform.

\subsection{Backend Development Setup}
\label{subsec:chap4:backenddev}

Setting up the backend development environment for my Django Python server involved several steps to ensure seamless integration and efficient implementation. Below is a detailed explanation of the setup process:

\begin{itemize}
    \item \textbf{Python Installation:} The first step was to install Python on my local machine, as Django development is done in Python. I downloaded and installed the latest version of Python from the official Python website to ensure compatibility with Django and other dependencies.

    \item \textbf{Virtual Environment Setup:} To keep my Python project isolated and manage dependencies effectively, I set up a virtual environment using the 'venv' module. This allowed me to install packages specific to my project without affecting the global Python environment.

    \item \textbf{Django Installation:} With the virtual environment activated, I installed Django using pip, the Python package manager. This command installed the latest version of Django and its dependencies within the virtual environment, ensuring a clean and isolated development setup.

    \item \textbf{Project Initialization:} Using Django's command-line interface (CLI), I initialized a new Django project by running the django-admin startproject command followed by the project name. This command generated the necessary project files and directory structure to set up the initial scaffolding for the Django application.

    \item \textbf{App Creation:} Within the Django project, I created one or more Django apps to encapsulate specific functionalities or features. Each app is a modular component of the larger project, containing models, views, templates, and other resources relevant to its domain.

    \item \textbf{Configuration Settings:} I configured various settings in the Django project, including middleware, URL routing, static file handling, and database settings. These configurations were specified in the settings.py file within the project directory, allowing customization and flexibility as needed.

    \item \textbf{URL Routing:} Using Django's URL routing mechanism, I defined URL patterns and linked them to views or viewsets responsible for handling incoming HTTP requests. This facilitated the mapping of URLs to specific endpoints within the Django application, enabling the creation of RESTful API endpoints.
    
    \item \textbf{Integration with External Services:} As part of the backend setup, I integrated external services such as ChatGPT with the Django application to enable seamless communication and collaboration between the frontend and backend components. This involved setting up data serialization and deserialization processes, authentication methods, and API endpoints to facilitate data exchange between the Django server and the Figma plugin.
\end{itemize}

Following these steps and adhering to Django best practices, I established a solid foundation for building and implementing the Django Python server. This setup enabled effective backend development for my thesis project, facilitating smooth integration with external services and reliable communication with frontend components.

\section{Frontend Implementation: Figma Plugin}
\label{sec:chap4:frontendimp}

In this section, I provide a detailed account of how I implemented the frontend for my Figma plugin using React. The frontend consists of two main routes: the homepage route ("/") and the process route ("/process"). The following code snippet demonstrates how I configured these routes using React Router:

\begin{verbatim}
import React from 'react';
import {
  MemoryRouter,
  Routes,
  Route,
} from "react-router-dom";
import '../styles/ui.css';
import Homepage from './Homepage';
import Process from './Process';
import Layout from './Layout';

function App() {
  return (
    <MemoryRouter>
      <Routes>
        <Route path='/' Component={Layout} >
          <Route path="/" Component={Homepage} />
          <Route path="/process" Component={Process} />
          <Route path="/prject-description" Component={ProjectDescription} />
        </Route>
      </Routes>
    </MemoryRouter>
  );
}

export default App;
\end{verbatim}

The above code sets up three routes using React Router: one for the homepage ("/"), one for the process page ("/process") and another for the project description page ("/prject-description"). Each route is associated with a different component: \texttt{HomePage}, \texttt{Process} and \texttt{ProjectDescription}, respectively.

\subsection{Homepage Route}
\label{subsec:chap4:homepageroute}

The homepage route ("/") serves as the landing page for the Figma plugin. It provides users with an overview of the plugin's features and capabilities. As shown in Figure \ref{fig:screen1}, the homepage acts as an introductory page, guiding users through the initial steps required to use the plugin effectively. Key features include:
\begin{itemize}
    \item \textbf{OpenAI API Key:} A critical step for using ChatGPT is obtaining an OpenAI API key. Users are prompted to enter this key to enable the plugin's functionality.
    \item \textbf{Billing Setup:} Users must ensure that billing is enabled in their OpenAI account to cover the costs associated with API calls.
    \item \textbf{Navigation Buttons:}  The "Let's Start" button redirects users to the Process route, while the "Give Feedback" button links to a Google Form for collecting user feedback.
\end{itemize} 

\begin{figure}[h]
    \centering
    \begin{minipage}[t]{.49\linewidth}
    \begin{figure}[H]
	\centering
	\includegraphics[width=\linewidth]{images/screen1.png}
	\caption{HomePage screen when the plugin has been launched}
	\label{fig:screen1}
    \end{figure}
    \end{minipage}
    \hfill
    \begin{minipage}[t]{.49\linewidth}
    \begin{figure}[H]
	\centering
	% svg inclusion, requires inkscape
	\includegraphics[width=\linewidth]{images/screen2.png}
	\caption{Process screen for generating appropriate user interface}
	\label{fig:screen2}
    \end{figure}
    \end{minipage}
\end{figure}


\subsection{Process Route}
\label{subsec:chap4:processroute}

Users are guided through the process of creating user interfaces with AI technology by the process route ("/process"). Users can input their OpenAI API key and project description using an organized, step-by-step interface, as demonstrated in the image \ref{fig:screen2}. Furthermore, the route is built to handle common issues that could occur during communication between the Django server and the OpenAI API, giving users helpful feedback to aid in troubleshooting. 

\subsection{Project Description Route}
\label{subsec:chap4:pdroute}

The application includes a dedicated page to assist users in writing a clear and comprehensive project description as demonstrated in the image \ref{fig:screen3}. This page, accessible via a link labeled "How to write a good Project Description?" below the project description text box, in the process page as it shown in the image \ref{fig:screen2}. It provides essential guidelines to ensure users can maximize the benefits of the plugin. The page titled "Crafting an Effective Project Description" outlines three key areas which is described in the chapter \ref{sec:chap4:howtoprojdesc}. The page concludes with a call-to-action button, encouraging users to start generating their UI components based on the crafted description.

\begin{figure}[h]
\centering
\includegraphics[width=\linewidth]{images/screen3.png}
\caption{Crafting an Effective Project Description Page}
\label{fig:screen3}
\end{figure}



\subsection{Managing Plugin Logic with 'controller.ts'}
\label{subsec:chap4:controllerts}

The 'controller.ts' file functions as the Figma plugin's main logic handler, coordinating user input, server connectivity, and plugin functionality. It functions mostly through event handling, which is an essential component of Figma plugin development.

\subsubsection{Event-Driven Architecture}
\label{subsubsec:chap4:eventdrivenarch}

The use of event-driven architecture in the 'controller.ts' file is essential to its functionality. The 'figma.ui.onmessage' event handler, which listens for incoming messages from the plugin UI or other sources, is essential to this design. These messages typically contain instructions or data payloads that trigger specific actions within the plugin.

\begin{verbatim}
figma.ui.onmessage = async (msg) => {
  // Handle incoming messages based on their type
  switch (msg.type) {
    case 'start-process':
      // Perform actions based on the message type
      // ...
      break;
    default:
      // Handle other message types
      // ...
      break;
  }
};
\end{verbatim}


\subsubsection{Message Handling}
\label{subsubsec:chap4:messagehandling}

The message is processed by the 'controller.ts' file based on its kind upon receipt. This may entail a variety of duties, including starting a process, resolving issues, or changing the user interface. For example, the controller starts the process by sending the OpenAI API key and project description to the server for analysis in response to a "start-process" message.

\begin{verbatim}
case 'start-process':
  let projectDescription = msg.description;
  let openAIKey = msg.openAIKey;
  
  // Start the process by sending the project description
  // and OpenAI API key to the server
  await startProcess(projectDescription, openAIKey);
  // ...
  break;


async function startProcess(projectDescription, openAIKey) {
  try {
    // Send a POST request to the server's process API endpoint
    const response = await fetch(api_url_prefix + 'api/process/', {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
      },
      body: JSON.stringify({
        projectDescription: projectDescription,
        openAIKey: openAIKey
      }),
    });

    // Check if the response status is OK (HTTP status code 200)
    if (response.ok) {
      return response.json();
    } else {
      // If the response status is not OK
      await response.json().then((data) => {
        figma.ui.postMessage({
          type: 'process-failed',
          message: data.error,
        });
      });
    }
  } catch (error) {
    // If an error occurs during the request 
    figma.ui.postMessage({
      type: 'process-failed',
      message: 'Process failed. Server error.',
    });
  }
}
\end{verbatim}

\subsubsection{Manipulating Figma Documents for UI Generation}
\label{subsubsec:chap4:manipulatingfigmadocuments}

The ability of the 'controller.ts' file to manipulate Figma documents programmatically by utilizing the Figma API is one of its key features. With this feature, the Figma plugin may create user interfaces (UIs) inside the Figma environment that are dynamically generated and customized to meet the unique needs of every project.

The plugin may create UI elements dynamically within the Figma document, including text layers, shapes, photos, and more, by having access to the Figma API. For example, the plugin might generate buttons for navigation, input fields for user input, text layers to show project details, and other UI elements necessary for the project's interface.

Moreover, UI elements can be extensively customized and adjusted using the Figma API in accordance with project requirements and design preferences. The position, size, color, font, and styling of UI elements are among the many properties that developers can manage to guarantee uniformity and adherence to design guidelines.

The 'controller.ts' file allows designers and developers to iterate on UI designs immediately within the familiar Figma environment by integrating smoothly with the Figma document editing workflow. By doing away with the need for additional design tools or manual modifications, this integration improves productivity, speeds up collaboration, and streamlines the design process.

The supplied createText and createRectangle functions serve as an example of how the plugin may be used to programmatically create text layers and rectangles inside of a Figma document. The foundation of the plugin's ability to create dynamic, adaptable user interfaces (UIs) that meet project needs is formed by these and related functions.

\begin{verbatim}


// Function to create a text node
function createText(parent, x, y, content,
fontSize, type = 'normal') {
  const text = figma.createText();
  text.x = x;
  text.y = y;

  // Check if text length is more than 60 characters
  if (content.length > 60) {
    text.characters = content;
    text.fontSize = fontSize;
    // Allow the text to resize vertically
    text.textAutoResize = "HEIGHT"; 
    // Set a maximum width of 300 pixels
    text.resize(300, text.height); 
  } else {
    text.characters = content;
    text.fontSize = fontSize;
  }

  // Make text bold
  if (type === 'bold') {
    text.fontName = { family: "Inter", style: "Bold" };
  }

  parent.appendChild(text);

  return text;
}


// Function to create a rectangle (representing a navigation 
//bar, content area, and footer)
function createRectangle(parent, x, y, width,
height, color, type) {
  const rect = figma.createRectangle();
  rect.x = x;
  rect.y = y;
  rect.resize(width, height);
  rect.fills = [{ 
  type: 'SOLID',
  color: { r: color[0], g: color[1], b: color[2] }
  }];

  // Set name based on type for identification
  if (type) {
    rect.name = type;
  }

  parent.appendChild(rect);
  return rect;
}
\end{verbatim}

\section{Backend Implementation: Django Python Server}
\label{sec:chap4:backendimp}

The Backend Implementation of the Figma plugin relies on a Django Python Server to manage the application's logic and handle communication with external services such as ChatGPT. This server-side component serves as the backbone of the plugin, coordinating various tasks and facilitating seamless interaction between different components.

\subsection{REST API for Managing the Application}
\label{subsec:chap4:restapi}

The main interface for controlling the functionality of the program is the REST API exposed by the Django Python Server. With the help of this API, clients—like the Figma plugin—can interact with the server and carry out particular tasks, like starting the UI creation process.

\subsection{Process Endpoint for ChatGPT Communication}
\label{subsec:chap4:chatgptcom}

The 'process' endpoint, which is intended to handle requests related to UI generation using ChatGPT, is one of the main features of the REST API. The project description and OpenAI key are extracted by the server from the request payload when it receives a POST request to the 'process' endpoint.



\subsection{Interaction with ChatGPT}
\label{subsec:chap4:chatgptinter}

After the required data has been retrieved, the Django server contacts ChatGPT to provide user interface designs based on the project description that has been supplied. In order to retrieve the necessary UI elements, the communication procedure usually entails sending queries to ChatGPT and processing the results.

\subsection{Template-based UI Generation}
\label{subsec:chap4:templatebasedui}

The server uses a template-based technique to speed up the UI generation process. A pre-made JSON template is created, detailing the UI design's hierarchy down to the page names and related components. The template has different user interface (UI) components in each part, including buttons, lists, forms, navigation bars, and more.


\subsection{Instruction and Rules for ChatGPT}
\label{subsec:chap4:instrucandrule}

Furthermore, the server incorporates particular guidelines and directives into the conversation with ChatGPT. Following predetermined criteria and design concepts, ChatGPT is guided by these instructions while generating UI designs using the template that has been provided.

Sample Workflow:

\begin{enumerate}
    \item The Figma plugin sends a POST request to the Django server's \texttt{process} endpoint, providing the project description and OpenAI key.
    \item The Django server initiates communication with ChatGPT, requesting UI design generation based on the provided project description.
    \item ChatGPT responds with UI design suggestions, which are processed by the Django server.
    \item The Django server constructs a JSON template based on the received suggestions, specifying the structure of the UI design.
    \item The Django server sends additional instructions and rules to ChatGPT, guiding the UI generation process.
    \item ChatGPT generates a JSON-based UI design according to the provided template and instructions, which is then returned to the Django server.
    \item The Django server processes the final JSON-based UI design and sends it to the Figma plugin.
    \item The Figma plugin uses the Figma API to render the designs within the Figma environment based on the received JSON.
\end{enumerate}


\subsection{Interaction with OpenAI API for Design Generation}
\label{subsec:chap4:interactionOpenAIAPI}

In this section, I describe the interaction with the OpenAI API to generate the necessary design elements for a specific project in Figma. This interaction involved crafting specific prompts to describe the required pages and user interface elements, and then generating a JSON structure containing all the information needed for creating these designs in Figma.

\subsubsection{Prompt Crafting and API Interaction}
\label{subsubsec:chap4:promptcrafting}

To effectively communicate with the OpenAI API and obtain the necessary design elements, I used two main prompts. The first prompt was to describe all the pages required for the project along with their user interface elements. The second prompt was to generate a JSON containing all the user interface elements following specific rules.

\subsubsection{First Prompt: Describing Pages and UI Elements}
\label{subsubsec:chap4:firstprompt}

The first prompt was designed to list all the pages required for the project along with their user interface elements. Here is the Python code snippet used to send this prompt to the OpenAI API:

\begin{verbatim}
    response_first_api = client.chat.completions.create(
    model="gpt-3.5-turbo",
    temperature=0,
    messages=[
    {
    "role": "user",
    "content": f"""With the help of the project description below,
    describe all the pages required for this project with the user
    interface elements that the page needs. 
    Output template: list all of the pages with a numerical list
    and for each page list all of
    the user interface elements and the items that they contain.
    Don't put any additional text.
    Project description: {project_description} """,
   },
    {
        "role": "system",
        "content": "I want you to act as a web designer"
    }
    ],
)
\end{verbatim}

\textbf{Description:}

\begin{itemize}
    \item \textbf{Purpose:} The primary goal of this prompt is to obtain a detailed list of pages and their respective user interface elements required for the project. This helps in creating a structured blueprint of the website's design.
    \item \textbf{Structure:} The prompt is structured to include a concise and clear project description, followed by a specific output template. This ensures that the API response is formatted in a way that is easy to parse and use in subsequent steps.
    \item \textbf{Components:} \begin{itemize}
        \item \textbf{Role of User:} The user provides a detailed project description and requests a structured output.
        \item \textbf{Role of System:} The system is instructed to act as a web designer, ensuring the response aligns with design principles.
    \end{itemize}
    \item \textbf{Output:} The expected output is a numerical list of pages, each containing a list of user interface elements. This output serves as the groundwork for generating the JSON structure used in Figma.
\end{itemize}

\textbf{Example Response:}

\begin{verbatim}
1. Home Page
    - Header: Navigation Bar (Home, About, Services, Contact)
    - Main Section: Welcome Text, Image Carousel
    - Footer: Contact Information, Social Media Links

2. About Page
    - Header: Navigation Bar (Home, About, Services, Contact)
    - Main Section: Company History, Team Members
    - Footer: Contact Information, Social Media Links

3. Services Page
    - Header: Navigation Bar (Home, About, Services, Contact)
    - Main Section: Service List, Service Descriptions
    - Footer: Contact Information, Social Media Links

4. Contact Page
    - Header: Navigation Bar (Home, About, Services, Contact)
    - Main Section: Contact Form (Name, Email, Message, Submit Button)
    - Footer: Contact Information, Social Media Links

\end{verbatim}

\subsubsection{Second Prompt: Generating JSON for Figma}
\label{subsubsec:chap4:secondprompt}

The second prompt was designed to generate an RFC8259 compliant JSON structure containing all the user interface elements for each page based on the result gathered from the first prompt. This JSON structure follows a specific template and rules. Here is the Python code snippet used to send this prompt to the OpenAI API:

\begin{verbatim}
     response_second_api = client.chat.completions.create(
                model="gpt-3.5-turbo-1106",
                response_format={"type": 'json_object'},
                temperature=0,
                messages=[
                    {
            "role": "user",
            "content": """Please generate a RFC8259 compliant
            JSON containing all of the user interface
            elements for each page based on the provided text,
            following the template below:
Template:
{
  "pages": [
    {
      "page_name": "Page 1",
      "sections": [
        {
          "label": "Header",
          "elements": [
            {
              "type": "navigation_bar",
              "label": "Navigation Bar",
              "items": []
            }
          ]
        },
        {
          "label": "Column 1",
          "elements": [
            {
              "type": "list",
              "label": "List 1",
              "headers": [
                "Item 1",
                "Item 2"
              ]
            }
          ]
        },
        {
          "label": "Column 2",
          "elements": [
            {
              "type": "form",
              "label": "Add Book Form",
              "inputs": [
                {
                  "type": "text",
                  "label": "Title"
                },
                {
                  "type": "text",
                  "label": "Purchase Date"
                },
                {
                  "type": "text",
                  "label": "Description"
                },
                {
                  "type": "button",
                  "label": "Submit"
                }
              ]
            },
            {
              "type": "form",
              "label": "Update Book Form",
              "inputs": [
                {
                  "type": "text",
                  "label": "Title"
                },
                {
                  "type": "date",
                  "label": "Purchase Date"
                },
                {
                  "type": "text",
                  "label": "Description"
                },
                {
                  "type": "button",
                  "label": "Update"
                }
              ]
            }
          ]
        },
        {
          "label": "Footer",
          "elements": []
        }
      ]
    },
    {
      "page_name": "Page 2",
      "sections": [
        {
          "label": "Header",
          "elements": [
            {
              "type": "navigation_bar",
              "label": "Navigation Bar",
              "items": [
                "Home",
                "About"
              ]
            }
          ]
        },
        {
          "label": "Column 1",
          "elements": [
            {
              "type": "image",
              "label": "Image Label",
            },
            {
              "type": "button",
              "label": "Button 1"
            },
            {
              "type": "button",
              "label": "Button 2"
            }
          ]
        },
        {
          "label": "Column 2",
          "elements": [
            {
              "type": "list",
              "label": "List 1",
              "headers": [
                "Item 1",
                "Item 2"
              ]
            },
            {
              "type": "text",
              "label": "Title",
              "content": "This is a test text."
            }
          ]
        },
        {
          "label": "Footer",
          "elements": []
        }
      ]
    }
  ],
  'connections':[
        {
            'from_page' : 'page_name',
            'from_type' : 'button',
            'from_label' : 'Button 1',
            'to_page' : 'page_name',
        },{
            'from_page' : 'page_name',
            'from_type' : 'navigation_bar',
            'from_label' : 'Navigation Bar',
            'to_page' : 'page_name',  
        }
  ]
}

Instructions:
- Generate a JSON that adheres to the RFC8259 standard.
- Generate only the JSON without any additional information and check that
output is a valid JSON.
- The JSON should contain the user interface elements for each page
mentioned in the provided text.
- Include all the pages mentioned in the text.
- Each page should have a name and a list of sections.
- Each section should have a label and a list of elements. 
label is mandatory for all sections.
- Detect appropriate label for the sections.
- The "Header" section should contain a navigation bar (menu)
as a "navigation_bar" element.
- If a section can be shown as a table, include a "list" element inside
the section and detect the appropriate headers for the table.
- Forms should be represented as "form" elements with their respective
inputs included inside the "inputs" label.
Do not add elements of the form inside another section.
- Buttons related to a form should be added as elements within the form.
- The "Footer" and "Header" section should be available on each page.
- Do not modify the template; strictly follow the template rules.
- Detect a label for each element inside sections.
- If the element is a not a list or a form , it should be a type "text" 
with the appropriate content inside "content"
and an appropriate "label" or it can be an image
with type "image" and an appropriate "label".
- If the element is a filter, it should be added
as type "form" with appropriate inputs.
- If the connection item type is 'navigation_bar', in the 'from_label' put
the label of link item instead of label of Navigation Menu.
- If the navigarion_bar elements are long and more than 5 elements, try to
add only 4 of them as navigation_bar
and add others as buttons inside the pages.
- Try to detect all elements inside the output.
                        """, },
                {
                "role": "system",
                "content": "i want you to act as a web designer"
                },
                {
                "role": "assistant",
                "content": response_first_api.choices[0].message.content
                }
                ],
            )
\end{verbatim}

\begin{itemize}
    \item \textbf{Purpose:} The main objective of this prompt is to generate a structured JSON that adheres to the RFC8259 standard. This JSON contains detailed information about each page and its user interface elements, facilitating the design process in Figma.
    \item \textbf{Structure:} The prompt is structured to provide a comprehensive template and set of rules that the API response must follow. This ensures that the output JSON is consistent, well-organized, and suitable for direct use in Figma.
    \item \textbf{Components:} \begin{itemize}
        \item \textbf{Role of User:} The user provides specific instructions and a detailed template that the output JSON must adhere to.
        \item \textbf{Role of System:} The system is instructed to act as a web designer, ensuring the response aligns with design principles and standards.
        \item \textbf{Content of First API Response:} The response from the first API call is included in the prompt to provide the necessary context and details about the pages and their elements. 
    \end{itemize}
    \item \textbf{Output:} The expected output is an RFC8259 compliant JSON structure that contains all the user interface elements for each page, following the provided template and instructions.
\end{itemize}

\textbf{Example Response:}

\begin{verbatim}
{
   "pages":[
      {
         "page_name":"Home Page",
         "sections":[
            {
               "label":"Header",
               "elements":[
                  {
                     "type":"navigation_bar",
                     "label":"Navigation Bar",
                     "items":[
                        "Home",
                        "About",
                        "Services",
                        "Contact"
                     ]
                  }
               ]
            },
            {
               "label":"Main Section",
               "elements":[
                  {
                     "type":"text",
                     "label":"Welcome Text",
                     "content":"Welcome to our website!"
                  },
                  {
                     "type":"image",
                     "label":"Image Carousel"
                  }
               ]
            },
            {
               "label":"Footer",
               "elements":[
                  {
                     "type":"text",
                     "label":"Contact Information",
                     "content":"123 Main St, Anytown, USA"
                  },
                  {
                     "type":"text",
                     "label":"Social Media Links",
                     "content":"Follow us on social media!"
                  }
               ]
            }
         ]
      },
      {
         "page_name":"About Page",
         "sections":[
            {
               "label":"Header",
               "elements":[
                  {
                     "type":"navigation_bar",
                     "label":"Navigation Bar",
                     "items":[
                        "Home",
                        "About",
                        "Services",
                        "Contact"
                     ]
                  }
               ]
            },
            {
               "label":"Main Section",
               "elements":[
                  {
                     "type":"text",
                     "label":"Company History",
                     "content":"Our company was founded in..."
                  },
                  {
                     "type":"text",
                     "label":"Team Members",
                     "content":"Meet our team..."
                  }
               ]
            },
            {
               "label":"Footer",
               "elements":[
                  {
                     "type":"text",
                     "label":"Contact Information",
                     "content":"123 Main St, Anytown, USA"
                  },
                  {
                     "type":"text",
                     "label":"Social Media Links",
                     "content":"Follow us on social media!"
                  }
               ]
            }
         ]
      },
      {
         "page_name":"Services Page",
         "sections":[
            {
               "label":"Header",
               "elements":[
                  {
                     "type":"navigation_bar",
                     "label":"Navigation Bar",
                     "items":[
                        "Home",
                        "About",
                        "Services",
                        "Contact"
                     ]
                  }
               ]
            },
            {
               "label":"Main Section",
               "elements":[
                  {
                     "type":"list",
                     "label":"Service List",
                     "headers":[
                        "Service Name",
                        "Description"
                     ]
                  },
                  {
                     "type":"text",
                     "label":"Service Descriptions",
                     "content":"We offer the following services..."
                  }
               ]
            },
            {
               "label":"Footer",
               "elements":[
                  {
                     "type":"text",
                     "label":"Contact Information",
                     "content":"123 Main St, Anytown, USA"
                  },
                  {
                     "type":"text",
                     "label":"Social Media Links",
                     "content":"Follow us on social media!"
                  }
               ]
            }
         ]
      },
      {
         "page_name":"Contact Page",
         "sections":[
            {
               "label":"Header",
               "elements":[
                  {
                     "type":"navigation_bar",
                     "label":"Navigation Bar",
                     "items":[
                        "Home",
                        "About",
                        "Services",
                        "Contact"
                     ]
                  }
               ]
            },
            {
               "label":"Main Section",
               "elements":[
                  {
                     "type":"form",
                     "label":"Contact Form",
                     "inputs":[
                        {
                           "type":"text",
                           "label":"Name"
                        },
                        {
                           "type":"text",
                           "label":"Email"
                        },
                        {
                           "type":"text",
                           "label":"Message"
                        },
                        {
                           "type":"button",
                           "label":"Submit"
                        }
                     ]
                  }
               ]
            },
            {
               "label":"Footer",
               "elements":[
                  {
                     "type":"text",
                     "label":"Contact Information",
                     "content":"123 Main St, Anytown, USA"
                  },
                  {
                     "type":"text",
                     "label":"Social Media Links",
                     "content":"Follow us on social media!"
                  }
               ]
            }
         ]
      }
   ],
   "connections":[
      {
         "from_page":"Home Page",
         "from_type":"button",
         "from_label":"Button 1",
         "to_page":"About Page"
      },
      {
         "from_page":"Home Page",
         "from_type":"navigation_bar",
         "from_label":"About",
         "to_page":"About Page"
      }
   ]
}

\end{verbatim}




\subsection{Error Handling for OpenAI API}
\label{subsec:chap4:errorhandlingchatgpt}

Moreover, error handling techniques for known OpenAI API failures are built into the Django server. This includes looking for typical problems like misplaced API keys or not enough funds in the user's OpenAI account. The server makes sure that the UI generation process runs more smoothly and robustly by proactively addressing these problems.

\section{How to Write a Detailed Project Description}
\label{sec:chap4:howtoprojdesc}

Writing a detailed and clear project description is crucial for generating useful UI recommendations with the Figma plugin. Here are some key points to consider when crafting your project description to ensure the best possible results:

\begin{enumerate}
    \item \textbf{Define the Scope:} Outline the scope of your project. Specify the application type (e.g., web, mobile), primary user tasks and specific necessary features in detail.
    \item \textbf{Identify the Target Audience:} Explain the end-users including their demographics, user needs and specifics of the users scenarios that the UI must support.
    \item \textbf{Specify Functional Requirements:} Identify the primary functions that should exist in the application. Outline precisely what every function should achieve.
\end{enumerate}

It is necessary to follow these guidelines so as to ensure that the project description is comprehensive and informative, therefore, allowing the Figma plugin to create UI elements that are perfectly suitable for your project needs and expectations.






