Update app.R

app.R

@@ -1,743 +1,89 @@
-# app.R — OrgEmbed: Generate Organizational Name Embeddings with LinkOrgs
-# ------------------------------------------------------------------------------
-# Features
-# - CSV upload or text paste, with column auto-detect + explicit selector
-# - Validations & friendly notifications
-# - One-click embedding generation (ML backend, v4 by default)
-# - Real-time progress milestones (+ large-input confirmation)
-# - Summary card + DT preview
-# - Clean CSV export of embeddings
-# - Basic embedding statistics (incl. PCA variance explained)
-# - Modern, accessible UI (bslib theme), tooltips, and help modal
-#
-# Assumptions
-# - Internet required on first ML backend setup/download.
-# - LinkOrgs installed & accessible; otherwise the app guides you to install.
-#
-# Best Practices
-# - Reactive parsing and caching
-# - Robust tryCatch blocks with console logging
-# - Clear separation of concerns with small helpers
-# ------------------------------------------------------------------------------
-
-options(shiny.maxRequestSize = 50 * 1024^2)  # accept CSVs up to ~X MB
-options(error = NULL)
-
-suppressPackageStartupMessages({
-  library(shiny)
-  library(bslib)
-  library(DT)
-  library(shinyWidgets)
-})
-
-# conda configuration for cross-platform Docker environments
-configure_python <- function() {
-  cat("[conda config] Starting Python configuration...\n")
-  
-  # Define potential conda locations for different platforms/Docker images
-  conda_paths <- c(
-    Sys.getenv("CONDA_EXE"),                    # User-defined
-    Sys.which("conda"),                         # System PATH
-    "/opt/conda/bin/conda",                     # Common Docker location
-    "/usr/local/bin/conda",                     # Alternative location
-    "/home/user/miniconda3/bin/conda",          # User miniconda
-    "/root/miniconda3/bin/conda",               # Root miniconda
-    "/usr/bin/conda",                           # System conda
-    file.path(Sys.getenv("HOME"), "miniconda3", "bin", "conda"),  # Home miniconda
-    file.path(Sys.getenv("HOME"), "anaconda3", "bin", "conda")    # Home anaconda
-  )
-  
-  # Remove empty strings and find first existing conda
-  conda_paths <- conda_paths[nzchar(conda_paths)]
-  conda_bin <- Find(file.exists, conda_paths)
-  
-  python_configured <- FALSE
-  config_method <- "none"
-  
-  # Method 1: Try conda environment
-  if (!is.null(conda_bin) && file.exists(conda_bin)) {
-    cat("[conda config] Found conda at:", conda_bin, "\n")
-    tryCatch({
-      reticulate::use_condaenv("LinkOrgs_env", conda = conda_bin, required = TRUE)
-      python_configured <- TRUE
-      config_method <- "conda_env"
-      cat("[reticulate] Successfully configured conda environment 'LinkOrgs_env'\n")
-    }, error = function(e) {
-      cat("[conda config] Failed to use conda env 'LinkOrgs_env':", conditionMessage(e), "\n")
-    })
-  } else {
-    cat("[conda config] No conda binary found in expected locations\n")
-  }
-  
-  # Method 2: Try RETICULATE_PYTHON environment variable
-  if (!python_configured && nzchar(Sys.getenv("RETICULATE_PYTHON"))) {
-    python_path <- Sys.getenv("RETICULATE_PYTHON")
-    cat("[conda config] Trying RETICULATE_PYTHON:", python_path, "\n")
-    tryCatch({
-      reticulate::use_python(python_path, required = TRUE)
-      python_configured <- TRUE
-      config_method <- "env_var"
-      cat("[conda config] Successfully configured Python from RETICULATE_PYTHON\n")
-    }, error = function(e) {
-      cat("[conda config] Failed to use RETICULATE_PYTHON:", conditionMessage(e), "\n")
-    })
-  }
-  
-  # Method 3: Try default conda base environment as fallback
-  if (!python_configured && !is.null(conda_bin)) {
-    cat("[conda config] Trying default conda base environment...\n")
-    tryCatch({
-      reticulate::use_condaenv("base", conda = conda_bin, required = FALSE)
-      python_configured <- TRUE
-      config_method <- "conda_base"
-      cat("[conda config] Successfully configured conda base environment\n")
-    }, error = function(e) {
-      cat("[conda config] Failed to use conda base environment:", conditionMessage(e), "\n")
-    })
-  }
-  
-  # Method 4: Let reticulate auto-discover
-  if (!python_configured) {
-    cat("[conda config] Falling back to reticulate auto-discovery...\n")
-    tryCatch({
-      # Force reticulate to initialize
-      reticulate::py_config()
-      python_configured <- TRUE
-      config_method <- "auto_discovery"
-      cat("[conda config] Successfully auto-discovered Python\n")
-    }, error = function(e) {
-      cat("[conda config] Auto-discovery failed:", conditionMessage(e), "\n")
-    })
-  }
-  
-  # Always attempt to log final configuration (this runs no matter what)
-  tryCatch({
-    config <- reticulate::py_config()
-    cat("[conda config] FINAL CONFIG:\n")
-    cat("[conda config]   Method:", config_method, "\n")
-    cat("[conda config]   Python:", config$python, "\n")
-    cat("[conda config]   Version:", config$version, "\n")
-    cat("[conda config]   NumPy:", config$numpy, "\n")
-    if (!is.null(conda_bin)) {
-      cat("[reticulate]   Conda:", conda_bin, "\n")
-    }
-  }, error = function(e) {
-    cat("[conda config] ERROR: Could not retrieve Python configuration:", conditionMessage(e), "\n")
-    cat("[conda config] Configuration method attempted:", config_method, "\n")
-  })
-  
-  return(python_configured)
-}
-
-# Execute the configuration
-configure_python()
-
-# Optional tooltips (if bsplus is available)
-has_bsplus <- requireNamespace("bsplus", quietly = TRUE)
-if (has_bsplus) {
-  bs_tooltip <- function(id, title) bsplus::shinyInput_label_embed(id) %>%
-    bsplus::bs_embed_tooltip(title, placement = "right")
-} else {
-  bs_tooltip <- function(id, title) NULL
-}
-
-#--- Helpers -------------------------------------------------------------------
-
-# Nicely guess the name column from a data.frame
-guess_name_col <- function(df) {
-  nms <- tolower(names(df))
-  patterns <- c("^names?$", "^orgnames?$", "organization", "^org$", "company", "entity", "name")
-  cand <- unique(unlist(lapply(patterns, function(p) which(grepl(p, nms)))))
-  if (length(cand) >= 1) names(df)[cand[1]] else names(df)[1]
-}
-
-# Parse pasted text into a data.frame with one "names" column
-parse_pasted_names <- function(txt) {
-  lines <- unlist(strsplit(txt, "\n", fixed = TRUE))
-  lines <- trimws(lines)
-  lines <- lines[nzchar(lines)]
-  if (length(lines) == 0) return(data.frame(names = character(0)))
-  data.frame(names = lines, stringsAsFactors = FALSE)
-}
-
-# Rename embedding columns to emb_001, emb_002, ...
-rename_embed_cols <- function(df, name_col) {
-  embed_cols <- setdiff(names(df), name_col)
-  if (length(embed_cols) == 0) return(df)
-  new_names <- sprintf("emb_%03d", seq_along(embed_cols))
-  names(df)[match(embed_cols, names(df))] <- new_names
-  df
-}
-
-# Extract only the numeric embedding matrix from a final result
-only_embedding_matrix <- function(final_df) {
-  is_num <- vapply(final_df, is.numeric, logical(1))
-  final_df[, is_num, drop = FALSE]
-}
-
-# Safe notification wrapper
-notify <- function(txt, type = "message", duration = 5) {
-  shiny::showNotification(txt, type = type, duration = duration)
-}
-
-#--- UI ------------------------------------------------------------------------
-
-theme <- bs_theme(bootswatch = "flatly")
-
-ui <- page_sidebar(
-  title = div(
-    tags$a(
-      "OrgEmbed:",
-      href   = "https://huggingface.co/spaces/cjerzak/LinkOrgs_Online",
-      target = "_blank",
-      rel    = "noopener noreferrer",
-      style  = "font-weight:700; text-decoration:none; color:inherit;",
-      id     = "orgembed_link",
-      title  = "Open the LinkOrgs Space in a new tab"
-    ),
-    span(" Generate Organizational Name Embeddings Using ",
-         tags$a("LinkOrgs",
-                href = "https://github.com/cjerzak/LinkOrgs-software",
-                target = "_blank",
-                style = "color: inherit; text-decoration: underline;"),
-         style = "color: #D3D3D3;")
-  ),
-  theme = theme,
-  
-  sidebar = sidebar(
-    width = 360,
-    tags$style(HTML("
-      .sidebar .shiny-input-container { margin-bottom: 12px; }
-      .small-note { font-size: 0.9rem; color: #666; }
-      .tight { margin-top: -6px; }
-    ")),
-    
-    # Input mode
-    radioButtons(
-      "input_mode", "Input method",
-      choices = c("CSV upload" = "csv", "Text paste" = "text"),
-      selected = "csv", inline = TRUE
-    ),
-    #bs_tooltip("input_mode", "Choose how you want to provide names"),
-    
-    # CSV upload controls
-    conditionalPanel(
-      "input.input_mode == 'csv'",
-      fileInput("file_csv", "Upload CSV", accept = ".csv", multiple = FALSE),
-      uiOutput("col_select_ui"),
-      div(class = "small-note tight",
-          "Tip: We guess the organization name column but let you override it.")
-    ),
-    
-    # Text paste controls
-    conditionalPanel(
-      "input.input_mode == 'text'",
-      textAreaInput(
-        "text_names", "Paste one name per line", rows = 6, placeholder = "Apple Inc.\nAlphabet\nMicrosoft"
-      ),
-      actionLink("load_examples", "Load examples"),
-      #bs_tooltip("text_names", "One organization per line. Empty lines are ignored.")
-    ),
-    
-    hr(),
-    
-    # Advanced options
-    numericInput("max_rows", "Max rows to process", value = 5000, min = 100, step = 100),
-    checkboxInput("include_names", "Include original names/columns in output", value = TRUE),
-    selectInput("ml_version", "ML model version", choices = c("v1", "v2", "v3", "v4"), selected = "v4"),
-    
-    hr(),
-    
-    # Main action
-    actionButton("process", "Process Names", class = "btn-primary", icon = icon("play")),
-    helpText("Large inputs (> 1000 rows) will prompt for confirmation."),
-    
-    hr(),
-    
-    # Visible warning for users
-    div(class = "alert alert-warning", style = "margin-top:8px; padding:8px;",
-        strong("Warning: "), "Do not navigate away from page while computing embeddings! May take 10 mins to compile neural nets."
-    ),
-    
-    # External help link (opens in new tab)
-    # External help link (opens in new tab)
-    tags$a(
-      id = "open_help_link",
-      href = "https://connorjerzak.com/linkorgs-summary/",
-      target = "_blank",
-      rel = "noopener",
-      icon("circle-question"),
-      " Technical details."
-    ),
-    tags$span(
-      "Citation: Libgober, B., & Jerzak, C. T. (2024). Linking datasets on organizations using half a billion open-collaborated records. ",
-      tags$i("Political Science Research and Methods. "),
-      tags$a(
-        href = "https://doi.org/10.1017/psrm.2024.55",
-        target = "_blank",
-        rel = "noopener",
-        "https://doi.org/10.1017/psrm.2024.55"
-      ),
-      #". ",
-    tags$a(
-      href = "https://connorjerzak.com/wp-content/uploads/2024/07/LinkOrgsBib.txt",
-      target = "_blank",
-      rel = "noopener",
-      " [.bib]"
-    )
-    ),
-  ),
-  # Main body
-  layout_columns(
-    col_widths = c(12),
-    # Input Preview Card
-    card(
-      header = "1) Preview input",
-      card_body(
-        div(class = "small-note", "Shows up to the first 10 rows by default."),
-        fluidRow(
-          column(
-            width = 4,
-            prettySwitch("show_all_preview", "Show full table", value = FALSE)
-          ),
-          column(
-            width = 4,
-            actionButton("refresh_preview", "Refresh preview", icon = icon("arrows-rotate"))
-          )
-        ),
-        DTOutput("input_preview")
-      )
-    ),
-    
-    # Embedding Generation & Summary Card
-    card(
-      header = "2) Generate embeddings",
-      card_body(
-        # Summary (appears after success)
-        uiOutput("summary_card"),
-        br(),
-        conditionalPanel(
-          "output.has_embeddings == true",
-          strong("Embeddings preview"),
-          div(class = "small-note tight", "First 5 rows; download the full CSV below."),
-          DTOutput("emb_preview"),
-          br(),
-          downloadButton("download_embeddings", "Download Embeddings CSV", class = "btn-success")
-        )
-      )
-    ),
-    
-    # Analysis Card
-    conditionalPanel(
-      "output.has_embeddings == true",
-      card(
-        header = "3) Embedding Summary",
-        card_body(
-          div(class = "small-note",
-              "Some statistics and PCA variance explained."),
-          uiOutput("stats_display")
-        )
-      )
-    )
-  )
-)
-
-#--- Server --------------------------------------------------------------------
-
-server <- function(input, output, session) {
-  
-  # State ----------------------------------------------------------------------
-  backend_ready <- reactiveVal(FALSE)
-  embeddings_df <- reactiveVal(NULL)   # final data.frame (original + embeddings)
-  pca_2d <- reactiveVal(NULL)          # data.frame with 2D PCA
-  pca_10d <- reactiveVal(NULL)         # data.frame with 10D PCA
-  pending_df <- reactiveVal(NULL)      # for large dataset confirmation
-  large_threshold <- 1000
-  
-  # Help modal -----------------------------------------------------------------
-  observeEvent(input$open_help_link, ignoreInit = TRUE, {
-    showModal(modalDialog(
-      title = "How to use OrgEmbed",
-      easyClose = TRUE, size = "l",
-      tagList(
-        tags$ol(
-          tags$li("Choose an input method: upload a CSV or paste names."),
-          tags$li("For CSV, confirm/select the column that contains organization names."),
-          tags$li("Click ", tags$strong("Process Names"), " to generate embeddings."),
-          tags$li("After completion, inspect the preview and click ",
-                  tags$strong("Download Embeddings CSV"), " to export."),
-          tags$li("Optionally, use PCA to reduce to 2 or 10 dimensions and download.")
-        ),
-        tags$hr(),
-        tags$p(class = "small-note",
-               "First-time ML backend setup needs internet to download model files.")
-      )
-    ))
-  })
-  
-  # Fill examples for text paste -----------------------------------------------
-  observeEvent(input$load_examples, {
-    updateTextAreaInput(session, "text_names", value = "Google\nAlphabet Inc.\nMicrosoft\nMeta Platforms\nOpenAI")
-  })
-  
-  # Reactive: parse CSV or text input ------------------------------------------
-  raw_input <- reactive({
-    mode <- input$input_mode
-    if (identical(mode, "csv")) {
-      req(input$file_csv)
-      df <- tryCatch(
-        read.csv(input$file_csv$datapath, stringsAsFactors = FALSE, check.names = FALSE),
-        error = function(e) {
-          cat("[CSV read error] ", conditionMessage(e), "\n")
-          notify("Could not read CSV. Ensure it's a valid .csv file.", "error", 7)
-          NULL
-        }
-      )
-      validate(need(!is.null(df) && nrow(df) > 0, "Uploaded CSV appears empty."))
-      df
-    } else {
-      validate(need(nzchar(input$text_names), "Please paste at least one name."))
-      parse_pasted_names(input$text_names)
-    }
-  })
-  
-  # Update/select name column after CSV upload
-  observeEvent(raw_input(), {
-    if (identical(input$input_mode, "csv")) {
-      df <- raw_input()
-      guessed <- guess_name_col(df)
-      updateSelectInput(session, "col_select", choices = names(df), selected = guessed)
-    }
-  })
-  
-  # UI for selecting names column (CSV)
-  output$col_select_ui <- renderUI({
-    req(input$input_mode == "csv", raw_input())
-    selectInput("col_select", "Names column", choices = names(raw_input()))
-  })
-  
-  # Input preview (first 10 rows or full) --------------------------------------
-  preview_data <- reactive({
-    df <- raw_input()
-    if (identical(input$input_mode, "csv")) {
-      # show selected column + keep other cols for context
-      # Nothing to subset here; selection is shown but preview shows all cols
-    } else {
-      # text mode ensures column named "names"
-    }
-    df
-  })
-  
-  observeEvent(input$refresh_preview, {
-    # No-op: triggers re-run of preview_data by invalidating reactives
-    invisible(TRUE)
-  })
-  
-  output$input_preview <- renderDT({
-    df <- preview_data()
-    req(df)
-    to_show <- if (isTRUE(input$show_all_preview)) df else head(df, 10)
-    datatable(
-      to_show,
-      options = list(pageLength = 10, scrollX = TRUE, dom = 'tip'),
-      rownames = FALSE
-    )
-  })
-  
-  # Large dataset confirmation flow --------------------------------------------
-  proceed_with_large <- function(df) {
-    pending_df(df)
-    showModal(modalDialog(
-      title = "Large dataset detected",
-      "You are about to process ", tags$b(nrow(df)), " rows.",
-      tags$p("This may take 1–5 minutes depending on your hardware and network. Proceed?"),
-      footer = tagList(
-        actionButton("confirm_large", "Proceed", class = "btn-primary"),
-        modalButton("Cancel")
-      ),
-      easyClose = TRUE
-    ))
-  }
-  
-  observeEvent(input$confirm_large, {
-    df <- pending_df()
-    removeModal()
-    if (!is.null(df)) isolate(run_embeddings(df))
-    pending_df(NULL)
-  })
-  
-  # Core: run embeddings --------------------------------------------------------
-  run_embeddings <- function(df) {
-    req(nrow(df) > 0)
-    
-    # Determine the names column
-    by_col <- if (identical(input$input_mode, "csv")) {
-      req(input$col_select %in% names(df))
-      input$col_select
-    } else {
-      # text mode
-      "names"
-    }
-    
-    # Validate names column non-empty
-    validate(need(any(nzchar(trimws(df[[by_col]]))), "Please provide at least one valid name."))
-    # Enforce max rows
-    if (nrow(df) > input$max_rows) {
-      notify(sprintf("Input truncated to max_rows = %d.", input$max_rows), "warning", 6)
-      df <- df[seq_len(input$max_rows), , drop = FALSE]
-    }
-    
-    withProgress(message = "Generating embeddings...", value = 0, {
-      incProgress(0.10, detail = "Parsing input...")
-      # Defensive copy and clean names
-      df[[by_col]] <- trimws(df[[by_col]])
-      df <- df[nzchar(df[[by_col]]), , drop = FALSE]
-      validate(need(nrow(df) > 0, "Please provide at least one valid name."))
-      
-      incProgress(0.20, detail = "Initializing model...")
-      
-      incProgress(0.50, detail = "Calling LinkOrgs (ML embeddings)...")
-      if (!requireNamespace("LinkOrgs", quietly = TRUE)) {
-        notify("Package 'LinkOrgs' not installed. See README to install.", "error", 10)
-        return(invisible(NULL))
-      }
-      
-      # Main call: ExportEmbeddingsOnly = TRUE
-      rep_x <- NULL
-      err <- NULL
-      pdf(NULL)  # Open null device to discard plots
-      tryCatch({
-        rep_x <- LinkOrgs::LinkOrgs(
-          x = df, y = NULL,
-          by.x = by_col,
-          algorithm = "ml",
-          ml_version = input$ml_version,
-          ExportEmbeddingsOnly = TRUE
-        )
-      }, error = function(e) {
-        err <<- e
-      })
-      dev.off()  # Clean up the null device
-      
-      if (!is.null(err)) {
-        cat("[LinkOrgs error] ", conditionMessage(err), "\n")
-        notify("Embedding generation failed. Backend setup may be incomplete. Check internet/conda and retry.", "error", 10)
-        return(invisible(NULL))
-      }
-      
-      incProgress(0.80, detail = "Post-processing embeddings...")
-      
-      # rep_x$embedx is a data.frame with first column = by_col and remaining = embeddings
-      embed_df <- rep_x$embedx
-      # standardize embedding column names
-      embed_df <- rename_embed_cols(embed_df, name_col = by_col)
-      
-      # Compose final output
-      final <- if (isTRUE(input$include_names)) {
-        # Bind to original df, avoiding duplicated name col
-        cols_to_add <- setdiff(names(embed_df), by_col)
-        cbind(df, embed_df[, cols_to_add, drop = FALSE])
-      } else {
-        # Return only embeddings (keep name column for context)
-        embed_df
-      }
-      
-      embeddings_df(final)
-      
-      incProgress(1.00, detail = "Complete!")
-      notify(sprintf("Embeddings generated for %d names.", nrow(final)), "message", 5)
-    })
-  }
-  
-  # Process button: orchestrate large confirmation + run -----------------------
-  observeEvent(input$process, {
-    df <- raw_input()
-    req(df)
-    
-    # Validate CSV names column selection exists
-    if (identical(input$input_mode, "csv")) {
-      if (!isTRUE(input$col_select %in% names(df))) {
-        notify("Invalid names column—please select again.", "error", 7)
-        return(invisible(NULL))
-      }
-    } else {
-      # Text mode already enforced with req(text != "")
-    }
-    
-    # Large dataset prompt
-    if (nrow(df) > large_threshold) {
-      proceed_with_large(df)
-      return(invisible(NULL))
-    }
-    
-    # Otherwise proceed immediately
-    run_embeddings(df)
-  })
-  
-  # Summary card ---------------------------------------------------------------
-  output$summary_card <- renderUI({
-    final <- embeddings_df()
-    if (is.null(final)) {
-      tagList(
-        div(class = "small-note",
-            "Click ", tags$strong("Process Names"),
-            " to start. You'll see progress updates here.")
-      )
-    } else {
-      emb_mat <- only_embedding_matrix(final)
-      dims <- ncol(emb_mat)
-      n <- nrow(final)
-      bslib::card(
-        bslib::card_body(
-          HTML(sprintf(
-            "<h4 style='margin-top:0;'>Embeddings ready</h4>
-             <p class='small-note' style='margin-bottom:6px;'>
-               Generated embeddings for <b>%d</b> names.
-             </p>
-             <p class='small-note tight'>
-               Dimensions: <b>%d</b> (columns starting with <code>emb_</code>).
-             </p>", n, dims
-          ))
-        )
-      )
-    }
-  })
-  
-  # Flag for conditionalPanel
-  output$has_embeddings <- reactive({
-    !is.null(embeddings_df())
-  })
-  outputOptions(output, "has_embeddings", suspendWhenHidden = FALSE)
-  
-  # Embedding preview (first 5 rows) -------------------------------------------
-  output$emb_preview <- renderDT({
-    final <- embeddings_df(); req(final)
-    to_show <- head(final, 5)
-    datatable(
-      to_show,
-      options = list(pageLength = 5, scrollX = TRUE, dom = 'tip'),
-      rownames = FALSE
-    )
-  })
-  
-  # Download full embeddings ----------------------------------------------------
-  output$download_embeddings <- downloadHandler(
-    filename = function() "org_embeddings.csv",
-    content = function(file) {
-      final <- embeddings_df(); req(final)
-      write.csv(final, file, row.names = FALSE)
-    }
-  )
-  
-  # - helpful statistics 
-  embedding_stats <- reactive({
-    final <- embeddings_df(); req(final)
-    emb <- only_embedding_matrix(final); req(ncol(emb) >= 1)
-    
-    # extra safety: coerce to a numeric matrix in case anything came in as characters
-    emb <- as.matrix(emb)
-    mode(emb) <- "numeric"
-    
-    pc <- prcomp(emb, center = TRUE, scale. = TRUE)
-    var_exp <- pc$sdev^2 / sum(pc$sdev^2) * 100
-    cum_var <- cumsum(var_exp)
-    
-    list(
-      n    = nrow(emb),
-      dims = ncol(emb),
-      p1   = round(var_exp[1], 1),
-      p2   = round(cum_var[min(2,  length(cum_var))],  1),
-      p10  = round(cum_var[min(10, length(cum_var))],  1),
-      p100 = round(cum_var[min(100,length(cum_var))],  1)
-    )
-  })
-  
-
-  # add to output 
-  output$stats_display <- renderUI({
-    stats <- embedding_stats()
-    
-    # Compose terminal text
-    txt <- paste0(
-      "orgembed@localhost:~$ stats\n",
-      "-------------------------------------\n",
-      sprintf("rows (n)     : %s\n", format(stats$n, big.mark = ",")),
-      sprintf("dims (d)     : %s\n", format(stats$dims, big.mark = ",")),
-      "PCA variance explained:\n",
-      sprintf("  PC1        : %.1f%%\n", stats$p1),
-      sprintf("  PC1+2      : %.1f%%\n", stats$p2),
-      sprintf("  PC1–10     : %.1f%%\n", stats$p10),
-      sprintf("  PC1–100    : %.1f%%\n", stats$p100)
-    )
-    
-    # Safely escape for JS
-    txt_js <- gsub("\\\\", "\\\\\\\\", txt)
-    txt_js <- gsub("'", "\\\\'", txt_js)
-    txt_js <- gsub("\n", "\\\\n", txt_js)
-    
-    tagList(
-      # Inline CSS for terminal aesthetics
-      tags$style(HTML("
-      .terminal-box {
-        background: #0b0f12;
-        color: #b6ffb3;
-        font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, 'Liberation Mono', 'Courier New', monospace;
-        font-size: 0.95rem;
-        padding: 16px 18px;
-        border-radius: 8px;
-        border: 1px solid rgba(0,255,100,0.25);
-        box-shadow: inset 0 0 0 1px rgba(0,255,100,0.05), 0 10px 24px rgba(0,0,0,0.25);
-        position: relative;
-        overflow: hidden;
-      }
-      .terminal-pre { white-space: pre-wrap; margin: 0; line-height: 1.35; }
-      .terminal-title { opacity: 0.95; margin-bottom: 8px; }
-      .terminal-cursor {
-        display: inline-block; width: 0.6ch; height: 1em; margin-left: 4px;
-        background: #b6ffb3; animation: blink 1s steps(1) infinite;
-        vertical-align: -0.2em;
-      }
-      @keyframes blink { 50% { opacity: 0; } }
-      .terminal-scanlines:before {
-        content: ''; position: absolute; inset: 0; pointer-events: none;
-        background: linear-gradient(rgba(255,255,255,0.03) 50%, transparent 0);
-        background-size: 100% 3px; mix-blend-mode: overlay;
-      }
-    ")),
-      
-      # Terminal container
-      div(class = "terminal-box terminal-scanlines",
-          tags$div(
-            class = "terminal-title",
-            HTML("orgembed<span style='color:#66ff66'>@</span>localhost:~$ <span style='opacity:.8'>stats</span>")
-          ),
-          tags$pre(id = "term_stats", class = "terminal-pre"),
-          tags$span(class = "terminal-cursor")
-      ),
-      
-      # Type-out effect
-      tags$script(HTML(sprintf("
-      (function(){
-        var el = document.getElementById('term_stats');
-        if (!el) return;
-        var text = '%s';
-        el.textContent = '';
-        var i = 0;
-        var speed = 8; // ms per character
-        (function type(){
-          if (i < text.length) {
-            el.textContent += text.charAt(i++);
-            setTimeout(type, speed);
-          }
-        })();
-      })();
-    ", txt_js)))
-    )
-  })
-
-  
-}
-
-# Run --------------------------------------------------------------------------
-shinyApp(ui, server)
-
+output$stats_display <- renderUI({
+  stats <- embedding_stats()
+  
+  # Terminal-style HTML with monospace font and terminal aesthetics
+  terminal_output <- HTML(paste0(
+    '<div style="
+      background-color: #0c0c0c;
+      color: #00ff00;
+      font-family: \'Courier New\', monospace;
+      padding: 20px;
+      border-radius: 5px;
+      border: 2px solid #333;
+      box-shadow: 0 0 10px rgba(0, 255, 0, 0.1);
+      font-size: 14px;
+      line-height: 1.6;
+    ">',
+    '<div style="color: #888; margin-bottom: 10px;">$ linkorg_stats --summary</div>',
+    '<div style="border-bottom: 1px solid #333; margin-bottom: 15px; padding-bottom: 10px;">',
+    '<span style="color: #00ff00;">═══════════════════════════════════════════════════════</span><br/>',
+    '<span style="color: #00ff00;"> EMBEDDING SUMMARY STATISTICS</span><br/>',
+    '<span style="color: #00ff00;">═══════════════════════════════════════════════════════</span>',
+    '</div>',
+    
+    '<div style="margin-bottom: 8px;">',
+    '<span style="color: #888;">[INFO]</span> ',
+    '<span style="color: #fff;">Processing complete at:</span> ',
+    '<span style="color: #0099ff;">', format(Sys.time(), "%Y-%m-%d %H:%M:%S %Z"), '</span>',
+    '</div>',
+    
+    '<div style="margin-bottom: 8px;">',
+    '<span style="color: #888;">[DATA]</span> ',
+    '<span style="color: #fff;">Total embeddings generated:</span> ',
+    '<span style="color: #ffff00; font-weight: bold;">', stats$n, '</span>',
+    '</div>',
+    
+    '<div style="margin-bottom: 8px;">',
+    '<span style="color: #888;">[DATA]</span> ',
+    '<span style="color: #fff;">Embedding dimensions:</span> ',
+    '<span style="color: #ffff00; font-weight: bold;">', stats$dims, '</span>',
+    '</div>',
+    
+    '<div style="margin-top: 15px; border-top: 1px solid #333; padding-top: 15px;">',
+    '<div style="color: #00ff00; margin-bottom: 10px;">▶ Principal Component Analysis Results:</div>',
+    '</div>',
+    
+    '<div style="margin-left: 20px; margin-bottom: 8px;">',
+    '<span style="color: #888;">├─</span> ',
+    '<span style="color: #fff;">PC1 variance explained:</span> ',
+    '<span style="color: #00ff00;">', sprintf("%.1f%%", stats$p1), '</span>',
+    '</div>',
+    
+    '<div style="margin-left: 20px; margin-bottom: 8px;">',
+    '<span style="color: #888;">├─</span> ',
+    '<span style="color: #fff;">PC1-2 cumulative variance:</span> ',
+    '<span style="color: #00ff00;">', sprintf("%.1f%%", stats$p2), '</span>',
+    '</div>',
+    
+    '<div style="margin-left: 20px; margin-bottom: 8px;">',
+    '<span style="color: #888;">├─</span> ',
+    '<span style="color: #fff;">PC1-10 cumulative variance:</span> ',
+    '<span style="color: #00ff00;">', sprintf("%.1f%%", stats$p10), '</span>',
+    '</div>',
+    
+    '<div style="margin-left: 20px; margin-bottom: 8px;">',
+    '<span style="color: #888;">└─</span> ',
+    '<span style="color: #fff;">PC1-100 cumulative variance:</span> ',
+    '<span style="color: #00ff00;">', sprintf("%.1f%%", stats$p100), '</span>',
+    '</div>',
+    
+    '<div style="margin-top: 15px; padding-top: 10px; border-top: 1px solid #333;">',
+    '<span style="color: #888;">[STATUS]</span> ',
+    '<span style="color: #00ff00;">✓ Analysis complete</span>',
+    '</div>',
+    
+    '<div style="margin-top: 8px;">',
+    '<span style="color: #888;">$ <span style="animation: blink 1s infinite;">_</span></span>',
+    '</div>',
+    
+    '<style>',
+    '@keyframes blink {',
+    '  0%, 50% { opacity: 1; }',
+    '  51%, 100% { opacity: 0; }',
+    '}',
+    '</style>',
+    '</div>'
+  ))
+  
+  terminal_output
+})