Analytics Dashboard Builder
Run ID: 69cd04373e7fb09ff16a728a2026-04-01Analytics
PantheraHive BOS
BOS Dashboard

Analytics Dashboard Builder: Design Requirements & Specifications

This document outlines the comprehensive design requirements and specifications for your upcoming Analytics Dashboard. Our goal is to create a highly functional, intuitive, and visually appealing dashboard that empowers users with actionable insights.


1. Executive Summary

This phase, "Research & Design Requirements," lays the groundwork for the Analytics Dashboard. We've focused on defining the core functionalities, user experience principles, visual aesthetics, and technical considerations to ensure the final product is robust, scalable, and directly addresses your business needs. The proposed design emphasizes clarity, actionability, and user-centric customization.


2. Core Design Principles & Objectives

Our design approach is guided by the following principles:

  • Clarity & Simplicity: Data must be easy to understand at a glance, minimizing cognitive load.
  • Actionability: Insights should directly inform decisions and lead to tangible actions.
  • Customizability: Users should be able to tailor their views, metrics, and report layouts.
  • Performance: The dashboard must load quickly and respond efficiently to user interactions.
  • Scalability: Designed to accommodate future data sources, metrics, and user growth.
  • Accessibility: Adherence to WCAG guidelines to ensure usability for all users.
  • Consistency: Uniformity in design elements, interactions, and terminology across all sections.

3. Target Audience

The dashboard is designed for a diverse set of stakeholders, each requiring different levels of detail and types of insights:

  • Executives/Leadership: High-level KPIs, strategic overview, trend analysis.
  • Marketing Managers: Campaign performance, website traffic, lead generation, ROI.
  • Sales Directors: Revenue trends, sales pipeline, conversion rates, regional performance.
  • Product Managers: User engagement, feature adoption, churn rates, customer satisfaction.
  • Data Analysts: Granular data exploration, custom report building, export capabilities.

4. Detailed Design Specifications: Key Metrics & Data Points

The dashboard will be organized into thematic sections, each presenting relevant KPIs and visualizations.

4.1. Global Filters & Controls

  • Date Range Selector: Pre-defined options (e.g., "Today," "Last 7 Days," "This Month," "Last Quarter," "This Year") and a custom date range picker.
  • Granularity Selector: Ability to switch between Daily, Weekly, Monthly, Quarterly, Yearly views for time-series data.
  • Global Filters: Depending on data sources, common filters might include:

* Region/Geography

* Product/Service Category

* Marketing Channel

* Customer Segment

4.2. Overview Dashboard

  • Purpose: Provide a high-level summary of critical business performance indicators.
  • Key Metrics (KPI Cards - prominent display with comparison to previous period):

* Total Revenue / Sales

* Total Website Traffic (Unique Visitors)

* Total Leads Generated

* Overall Conversion Rate (e.g., Lead-to-Customer)

* Active Users (e.g., Monthly Active Users)

  • Visualizations:

* Revenue Trend: Line chart displaying revenue over the selected period (e.g., daily, weekly).

* Traffic Sources Breakdown: Donut or pie chart showing percentage contribution of different traffic sources (Organic, Paid, Direct, Referral, Social).

* Top 5 Products/Services by Revenue: Horizontal bar chart.

* Geographic Performance Map: Heatmap or choropleth map showing key metric (e.g., sales) by region/country.

4.3. Sales & Revenue Analytics

  • Purpose: Deep dive into sales performance, revenue generation, and customer value.
  • Key Metrics:

* Average Order Value (AOV)

* Customer Lifetime Value (CLTV)

* New vs. Returning Customer Revenue

* Sales Cycle Length

* Subscription Churn Rate (if applicable)

  • Visualizations:

* Sales Funnel: Visual representation of conversion stages (e.g., Lead -> MQL -> SQL -> Opportunity -> Won).

* Revenue by Product/Service: Stacked bar chart or table.

* Revenue by Sales Channel: Bar chart.

* Customer Acquisition Cost (CAC) vs. CLTV: Comparison chart.

* Sales Team Performance: Table with individual or team metrics (e.g., deals closed, revenue generated).

4.4. Marketing & Website Analytics

  • Purpose: Monitor marketing campaign effectiveness, website engagement, and lead generation.
  • Key Metrics:

* Bounce Rate

* Average Session Duration

* Pages Per Session

* Cost Per Acquisition (CPA)

* Return on Ad Spend (ROAS)

* Lead Source Performance

* Email Open Rate, Click-Through Rate (CTR)

  • Visualizations:

* Website Traffic Trends: Line chart (Total, Unique Visitors).

* Top Landing Pages: Table showing page views, bounce rate, conversion rate per page.

* Marketing Campaign Performance: Table comparing different campaigns by cost, leads, conversions, ROAS.

* Lead Generation by Source: Bar chart.

* User Flow/Path Analysis: (Advanced feature) Visualizing common user journeys.

4.5. Product & User Engagement Analytics

  • Purpose: Understand how users interact with products/services and identify areas for improvement.
  • Key Metrics:

* Daily/Weekly/Monthly Active Users (DAU/WAU/MAU)

* User Retention Rate

* Feature Adoption Rate

* Customer Satisfaction Score (CSAT), Net Promoter Score (NPS)

* Time Spent in Key Features

  • Visualizations:

* User Retention Cohort Analysis: Heatmap or line chart.

* Feature Usage Breakdown: Bar chart or treemap.

* NPS/CSAT Trend: Line chart.

* Top User Segments: Table or bar chart.

4.6. Interactivity & Drill-Down

  • Clickable Charts: Clicking on a segment of a chart (e.g., a bar in a bar chart, a slice in a pie chart) should filter other related charts or drill down to more granular data.
  • Hover Tooltips: Display detailed data points on hover over charts and tables.
  • Sortable Tables: All data tables should be sortable by column headers.
  • Search Functionality: For large data tables or lists.
  • Export Options: Allow users to export individual charts or entire dashboard views as CSV, PDF, or image files.

5. Wireframe Descriptions: Layout & Structure

The dashboard will follow a modern, responsive grid-based layout, primarily optimized for desktop viewing but adaptable to larger tablets.

5.1. Global Elements

  • Top Navigation Bar (Header):

* Left: Company Logo, Dashboard Title (Analytics Dashboard).

* Center: Global Date Range Selector, Global Filters.

* Right: User Profile/Settings (Avatar, Logout), Help/Support Link, Notification Bell.

  • Left Sidebar Navigation:

* Expandable/Collapsible.

* Top: Search bar for dashboards/reports.

* Main Links: Overview, Sales & Revenue, Marketing, Product & Usage, Custom Reports (if applicable).

* Bottom: Settings, Feedback.

5.2. Dashboard Page Layout (Example: Overview)

  • Grid System: Flexible grid (e.g., 12-column) to arrange widgets.
  • Top Row: KPI Cards:

* 4-5 prominent KPI cards, each occupying 2-3 columns.

* Each card will display: Metric Name, Current Value, Percentage Change (vs. previous period), Small sparkline chart for trend.

  • Second Row: Primary Trend Charts:

* Two large charts (e.g., Revenue Trend, Website Traffic Trend), each occupying 6 columns.

* Interactive: Hover for details, ability to toggle time granularity.

  • Third Row: Breakdown & Summary:

* Two medium-sized widgets, each occupying 6 columns.

* Example: Traffic Sources Breakdown (Donut Chart), Top Products by Revenue (Bar Chart).

  • Fourth Row: Detailed Tables/Maps:

* One full-width (12-column) widget or two 6-column widgets.

* Example: Geographic Sales Performance (Map), or a detailed Top Customers Table.

5.3. Widget Design

  • Consistent Card Design: Each visualization or table will reside within a distinct card with a title, optional subtitle, and clear borders.
  • Header Actions: Each widget header may include:

* "..." (More Options) menu for specific widget filters, export, or expand.

* Info icon (i) for metric definitions.

  • Loading States: Clear loading indicators (spinners, skeleton screens) for data fetching.
  • Empty States: User-friendly messages when no data is available for a specific widget.

6. Visual Design Elements

6.1. Color Palette

The chosen palette aims for professionalism, readability, and accessibility, while maintaining a modern aesthetic.

  • Primary Accent: #007BFF (Strong Blue) - Used for primary buttons, active states, key data highlights.
  • Secondary Accent: `#28A74
gemini Output

Analytics Dashboard Builder: Detailed Design Specifications

This document outlines the comprehensive design specifications for the "Analytics Dashboard Builder." It details the user experience, visual design, and core functionalities, ensuring a professional, intuitive, and powerful tool for data analysis. This deliverable serves as the blueprint for the development phase, providing a clear vision for the final product.


1. Project Overview & Goals

The Analytics Dashboard Builder aims to empower users to easily connect to various data sources, visualize their data through interactive charts and reports, and build custom dashboards without requiring extensive technical knowledge.

Key Goals:

  • Empowerment: Provide users with self-service analytics capabilities.
  • Usability: Ensure an intuitive and user-friendly interface for all skill levels.
  • Flexibility: Support diverse data sources and offer extensive customization options for reports and dashboards.
  • Actionability: Present data in a clear, concise, and actionable manner to drive informed decision-making.

Target Audience: Business Analysts, Marketing Managers, Sales Directors, Product Managers, Executives, and other data-driven professionals.


2. Core Features & Functionality

The platform will include the following key features:

  • Interactive Data Visualizations: A rich library of chart types (bar, line, pie, scatter, gauge, maps, tables, KPIs) with drill-down and hover capabilities.
  • Drag-and-Drop Report Builder: An intuitive interface for users to select data fields, choose visualization types, and configure report parameters.
  • Multiple Data Source Integration: Connectors for popular platforms (e.g., CRM, ERP, Marketing Automation, Web Analytics, Databases) and generic CSV/Excel upload.
  • Filtering & Segmentation: Advanced filtering options (date ranges, categorical, numerical) applicable at dashboard and report levels.
  • Customizable Dashboards: Users can create, save, and personalize multiple dashboards by arranging, resizing, and configuring widgets.
  • Scheduled Reporting & Alerts: Ability to schedule report delivery via email and set up alerts for specific data thresholds.
  • User & Role-Based Access Control: Granular
gemini Output

Analytics Dashboard Builder: Finalized Design Assets & Specifications

Project: Analytics Dashboard Builder

Step: 3 of 3 - Finalize Design Assets

Date: October 26, 2023

We are pleased to present the finalized design assets and comprehensive specifications for your Analytics Dashboard. This document outlines the detailed design, user experience (UX) recommendations, and technical considerations to ensure the dashboard is not only aesthetically pleasing but also highly functional, intuitive, and actionable.

Our design philosophy centers on Clarity, Actionability, and User-Centricity, aiming to transform complex data into easily digestible and impactful insights for your stakeholders.


1. Dashboard Overview & Core Principles

The Analytics Dashboard is designed as a centralized hub for critical business metrics, offering a holistic view of performance across various domains (e.g., Sales, Marketing, Operations, Finance).

Core Principles:

  • Actionable Insights: Every visualization and metric aims to guide users towards understanding what is happening and why, facilitating informed decision-making.
  • User-Centric Design: Prioritizing ease of use, intuitive navigation, and quick access to information for diverse user roles.
  • Performance & Scalability: Designed to handle large datasets efficiently while maintaining responsiveness and speed.
  • Visual Clarity: Employing best practices in data visualization to prevent cognitive overload and highlight key trends and anomalies.
  • Responsiveness: Ensuring a consistent and optimized experience across various devices and screen sizes.

2. Detailed Design Specifications

2.1. Layout Structure

The dashboard will utilize a flexible, grid-based layout for optimal organization and responsiveness.

  • Header (Fixed Top Bar):

* Left: Company Logo (branding)

* Center: Dashboard Title (e.g., "Overall Business Performance Dashboard")

* Right: Global Date Range Selector, User Profile/Settings Icon, Notifications Icon.

  • Global Filter Panel (Below Header, Collapsible/Expandable):

* Houses primary filters affecting all dashboard widgets (e.g., Department, Region, Product Category, Campaign).

* Designed for quick application and clear indication of active filters.

  • Main Content Area (Flexible Grid):

* Composed of modular "cards" or "widgets," each presenting a specific metric or visualization.

* Widgets will be organized into logical sections (e.g., Key Performance Indicators, Trend Analysis, Distribution, Detailed Data).

* Supports drag-and-drop reordering and resizing (if personalization is enabled in a future phase).

  • Footer (Optional - for advanced dashboards):

* Typically not present in standard dashboards to maximize screen real estate for data. Could include copyright or version info if critical.

2.2. Key Components & Widgets

Each component is designed for maximum clarity and utility:

  • Key Performance Indicator (KPI) Cards:

* Structure: Large primary number (current value), secondary number (percentage change from previous period/target), small sparkline chart depicting recent trend, clear label.

* Interactivity: Hover for detailed tooltip, click for drill-down to supporting data/report.

* Example: "Total Revenue: $1.2M (+5% vs. last month)"

  • Line Charts:

* Purpose: Visualize trends over time (e.g., Revenue Growth, Website Traffic, Customer Acquisition).

* Features: Multiple data series support, tooltips on hover for specific data points, zoom/pan functionality for detailed analysis of timeframes.

* Design: Clean lines, minimal grid, prominent data points.

  • Bar Charts (Vertical & Horizontal):

* Purpose: Compare discrete categories (e.g., Sales by Product Category, Performance by Region, Top 10 Customers).

* Features: Sorting options, drill-down on bar click, stacked bar options for segment comparison.

* Design: Clear axis labels, consistent color coding, value labels where appropriate.

  • Pie/Donut Charts:

* Purpose: Show proportions of a whole (e.g., Market Share, Customer Acquisition Channels, Expense Breakdown).

* Features: Percentage labels, legend, interactive slices that highlight on hover.

* Design: Limit to 5-7 segments for readability; group smaller segments into "Other."

  • Data Tables/Grids:

* Purpose: Present detailed, tabular data with drill-down capabilities (e.g., Top Selling Products, Customer List, Transaction Details).

* Features: Sortable columns, search functionality, pagination, export options (CSV, Excel), inline editing (if applicable).

* Design: Alternating row colors for readability, sticky headers for scrolling.

  • Geographical Maps:

* Purpose: Visualize location-based data (e.g., Sales by State/Country, Customer Density).

* Features: Color-coded regions based on metric value, hover for region-specific data, zoom/pan.

* Design: Clean map base, clear legends.

  • Filter & Control Elements:

* Date Range Selector: Pre-defined ranges (Today, Last 7 Days, This Month, YTD) and custom range picker.

* Dropdowns/Multi-Select: For categories, departments, products.

* Search Bars: For quick filtering of tables or specific data points.

* Apply/Clear Buttons: For group filters, to prevent instant updates on every selection.

2.3. Interactivity & Responsiveness

  • Hover States: Visual feedback on all interactive elements (buttons, links, chart segments, KPI cards) to indicate clickability.
  • Click-through/Drill-down: Clicking on a KPI card, chart segment, or table row will typically open a more detailed view (modal, new page, or updated dashboard state) providing granular data.
  • Filter Application: Filters will update dashboard content dynamically or upon an "Apply" button click, with clear loading indicators.
  • Export Options: Users can export individual widgets or the entire dashboard view to common formats (CSV, PDF, PNG).
  • Personalization (Future Consideration): Ability for users to save custom dashboard layouts, rearrange widgets, or hide irrelevant ones.
  • Responsive Design:

* Desktop: Full-width, multi-column layout.

* Tablet: Adapts to 1 or 2 columns, potentially collapsing some less critical elements.

* Mobile: Single-column stacked layout, optimized for touch interaction. Filters may move to a dedicated modal or slide-out panel.


3. Wireframe Descriptions

The following describes the intended structure and content placement for a typical dashboard view.

3.1. Main Dashboard View (Desktop)

  • Top Bar (Fixed):

* [Company Logo] [Dashboard Title: "Overall Business Performance"] [Date Range Selector] [User Profile Icon]

  • Global Filter Panel (Collapsible, below Top Bar):

* [Dropdown: Department] [Dropdown: Region] [Multi-Select: Product Category] [Search Bar] [Button: Apply Filters] [Button: Clear Filters]

  • Section 1: Key Performance Indicators (KPIs) - Full Width Row

* [KPI Card: Total Revenue] [KPI Card: New Customers] [KPI Card: Conversion Rate] [KPI Card: Average Order Value] [KPI Card: Customer Lifetime Value]

  • Section 2: Trend Analysis - Two-Column Layout

* Column 1 (Left, Larger):

* [Card Title: Revenue Trend Over Time]

* [Line Chart: Monthly Revenue over 12 months, showing actual and target lines]

* Column 2 (Right, Smaller):

* [Card Title: Sales by Product Category]

* [Vertical Bar Chart: Top 5 Product Categories by Sales, with "Other" category]

  • Section 3: Distribution & Detailed Data - Two-Column Layout

* Column 1 (Left):

* [Card Title: Customer Acquisition Channels]

* [Donut Chart: Percentage breakdown of acquisition channels (e.g., Organic, Paid Search, Social, Referral)]

* Column 2 (Right):

* [Card Title: Top 10 Products by Revenue]

* [Data Table: Product Name | Revenue | Units Sold | Profit Margin (Sortable Columns)]

  • Section 4: Regional Performance (Optional) - Full Width

* [Card Title: Revenue Performance by Region]

* [Geographical Map: World/Country map with regions color-coded by revenue performance]

3.2. Drill-down Example (Clicking "Total Revenue" KPI)

  • Modal Window / New Dashboard View:

* Header: [Dashboard Title: "Revenue Details"] [Breadcrumb: Overall Business Performance > Total Revenue]

* Filters: [Date Range Selector] [Dropdown: Sales Representative] [Dropdown: Customer Segment]

* Content:

* [Line Chart: Daily Revenue Breakdown]

* [Bar Chart: Revenue by Sales Rep]

* [Data Table: All Transactions (Transaction ID, Date, Customer, Product, Amount, Status)]

* [Button: Export to CSV]


4. Color Palettes & Typography

4.1. Color Palette

The chosen palette is designed for modern aesthetics, excellent readability, and effective data differentiation.

  • Primary Brand Color (Accent): #007BFF (Vibrant Blue)

Usage:* Key interactive elements (buttons, primary links), active states, main chart series, primary headers.

  • Secondary Brand Color: #6C757D (Muted Grey)

Usage:* Secondary buttons, inactive states, borders, subtle UI elements.

  • Neutral Colors (Backgrounds & Text):

* Background: #F8F9FA (Light Grey/Off-White) - Main dashboard background.

* Card Background: #FFFFFF (Pure White) - For individual widget cards.

* Text Primary: #212529 (Dark Grey) - Main body text, labels.

* Text Secondary: #6C757D (Muted Grey) - Helper text, less prominent labels.

* Borders/Dividers: #E2E6EA (Light Grey)

  • Data Visualization Colors (Chart Series):

* A carefully selected palette of 5-7 distinct colors for charts to ensure clear differentiation without visual clutter.

* #007BFF (Blue), #28A745 (Green), #FFC107 (Yellow/Amber), #DC3545 (Red), #6F42C1 (Purple), #20C997 (Teal), #FD7E14 (Orange).

Usage:* To represent different data series or categories in charts.

  • Status Colors:

* Success: #28A745 (Green) - For positive trends, successful operations.

* Warning: #FFC107 (Yellow/Amber) - For cautionary alerts, moderate deviations.

* Error: #DC3545 (Red) - For critical issues, negative trends, errors.

* Info: #17A2B8 (Cyan) - For informational messages.

4.2. Typography

  • Primary Font Family: Inter (or similar modern sans-serif like Roboto, Open Sans)

Usage:* Headings, KPI numbers, primary labels.

* Weights: Regular (400), Medium (500), Semi-Bold (600), Bold (700)

  • Secondary Font Family: Inter (or similar, maintaining consistency)

Usage:* Body text, chart labels, filter options, detailed table data.

  • Font Sizes (Examples):

* Dashboard Title: 24px (Semi-Bold)

* KPI Numbers: 36px (Bold)

* Card Titles: 18px (Semi

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Built with PantheraHive BOS

"); zip.file(folder+"src/app/app.component.css",".app-header{display:flex;flex-direction:column;align-items:center;justify-content:center;min-height:60vh;gap:16px}h1{font-size:2.5rem;font-weight:700;color:#6366f1} "); } zip.file(folder+"src/app/app.config.ts","import { ApplicationConfig, provideZoneChangeDetection } from '@angular/core'; import { provideRouter } from '@angular/router'; import { routes } from './app.routes'; export const appConfig: ApplicationConfig = { providers: [ provideZoneChangeDetection({ eventCoalescing: true }), provideRouter(routes) ] }; "); zip.file(folder+"src/app/app.routes.ts","import { Routes } from '@angular/router'; export const routes: Routes = []; "); Object.keys(extracted).forEach(function(p){ var fp=p.startsWith("src/")?p:"src/"+p; zip.file(folder+fp,extracted[p]); }); zip.file(folder+"README.md","# "+slugTitle(pn)+" Generated by PantheraHive BOS. ## Setup ```bash npm install ng serve # or: npm start ``` ## Build ```bash ng build ``` Open in VS Code with Angular Language Service extension. "); zip.file(folder+".gitignore","node_modules/ dist/ .env .DS_Store *.local .angular/ "); } /* --- Python --- */ function buildPython(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^```[w]* ?/m,"").replace(/ ?```$/m,"").trim(); var reqMap={"numpy":"numpy","pandas":"pandas","sklearn":"scikit-learn","tensorflow":"tensorflow","torch":"torch","flask":"flask","fastapi":"fastapi","uvicorn":"uvicorn","requests":"requests","sqlalchemy":"sqlalchemy","pydantic":"pydantic","dotenv":"python-dotenv","PIL":"Pillow","cv2":"opencv-python","matplotlib":"matplotlib","seaborn":"seaborn","scipy":"scipy"}; var reqs=[]; Object.keys(reqMap).forEach(function(k){if(src.indexOf("import "+k)>=0||src.indexOf("from "+k)>=0)reqs.push(reqMap[k]);}); var reqsTxt=reqs.length?reqs.join(" "):"# add dependencies here "; zip.file(folder+"main.py",src||"# "+title+" # Generated by PantheraHive BOS print(title+" loaded") "); zip.file(folder+"requirements.txt",reqsTxt); zip.file(folder+".env.example","# Environment variables "); zip.file(folder+"README.md","# "+title+" Generated by PantheraHive BOS. ## Setup ```bash python3 -m venv .venv source .venv/bin/activate pip install -r requirements.txt ``` ## Run ```bash python main.py ``` "); zip.file(folder+".gitignore",".venv/ __pycache__/ *.pyc .env .DS_Store "); } /* --- Node.js --- */ function buildNode(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^```[w]* ?/m,"").replace(/ ?```$/m,"").trim(); var depMap={"mongoose":"^8.0.0","dotenv":"^16.4.5","axios":"^1.7.9","cors":"^2.8.5","bcryptjs":"^2.4.3","jsonwebtoken":"^9.0.2","socket.io":"^4.7.4","uuid":"^9.0.1","zod":"^3.22.4","express":"^4.18.2"}; var deps={}; Object.keys(depMap).forEach(function(k){if(src.indexOf(k)>=0)deps[k]=depMap[k];}); if(!deps["express"])deps["express"]="^4.18.2"; var pkgJson=JSON.stringify({"name":pn,"version":"1.0.0","main":"src/index.js","scripts":{"start":"node src/index.js","dev":"nodemon src/index.js"},"dependencies":deps,"devDependencies":{"nodemon":"^3.0.3"}},null,2)+" "; zip.file(folder+"package.json",pkgJson); var fallback="const express=require("express"); const app=express(); app.use(express.json()); app.get("/",(req,res)=>{ res.json({message:""+title+" API"}); }); const PORT=process.env.PORT||3000; app.listen(PORT,()=>console.log("Server on port "+PORT)); "; zip.file(folder+"src/index.js",src||fallback); zip.file(folder+".env.example","PORT=3000 "); zip.file(folder+".gitignore","node_modules/ .env .DS_Store "); zip.file(folder+"README.md","# "+title+" Generated by PantheraHive BOS. ## Setup ```bash npm install ``` ## Run ```bash npm run dev ``` "); } /* --- Vanilla HTML --- */ function buildVanillaHtml(zip,folder,app,code){ var title=slugTitle(app); var isFullDoc=code.trim().toLowerCase().indexOf("=0||code.trim().toLowerCase().indexOf("=0; var indexHtml=isFullDoc?code:" "+title+" "+code+" "; zip.file(folder+"index.html",indexHtml); zip.file(folder+"style.css","/* "+title+" — styles */ *{margin:0;padding:0;box-sizing:border-box} body{font-family:system-ui,-apple-system,sans-serif;background:#fff;color:#1a1a2e} "); zip.file(folder+"script.js","/* "+title+" — scripts */ "); zip.file(folder+"assets/.gitkeep",""); zip.file(folder+"README.md","# "+title+" Generated by PantheraHive BOS. ## Open Double-click `index.html` in your browser. Or serve locally: ```bash npx serve . # or python3 -m http.server 3000 ``` "); zip.file(folder+".gitignore",".DS_Store node_modules/ .env "); } /* ===== MAIN ===== */ var sc=document.createElement("script"); sc.src="https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.1/jszip.min.js"; sc.onerror=function(){ if(lbl)lbl.textContent="Download ZIP"; alert("JSZip load failed — check connection."); }; sc.onload=function(){ var zip=new JSZip(); var base=(_phFname||"output").replace(/.[^.]+$/,""); var app=base.toLowerCase().replace(/[^a-z0-9]+/g,"_").replace(/^_+|_+$/g,"")||"my_app"; var folder=app+"/"; var vc=document.getElementById("panel-content"); var panelTxt=vc?(vc.innerText||vc.textContent||""):""; var lang=detectLang(_phCode,panelTxt); if(_phIsHtml){ buildVanillaHtml(zip,folder,app,_phCode); } else if(lang==="flutter"){ buildFlutter(zip,folder,app,_phCode,panelTxt); } else if(lang==="react-native"){ buildReactNative(zip,folder,app,_phCode,panelTxt); } else if(lang==="swift"){ buildSwift(zip,folder,app,_phCode,panelTxt); } else if(lang==="kotlin"){ buildKotlin(zip,folder,app,_phCode,panelTxt); } else if(lang==="react"){ buildReact(zip,folder,app,_phCode,panelTxt); } else if(lang==="vue"){ buildVue(zip,folder,app,_phCode,panelTxt); } else if(lang==="angular"){ buildAngular(zip,folder,app,_phCode,panelTxt); } else if(lang==="python"){ buildPython(zip,folder,app,_phCode); } else if(lang==="node"){ buildNode(zip,folder,app,_phCode); } else { /* Document/content workflow */ var title=app.replace(/_/g," "); var md=_phAll||_phCode||panelTxt||"No content"; zip.file(folder+app+".md",md); var h=""+title+""; h+="

"+title+"

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Generated by PantheraHive BOS
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