diff --git a/radiant.quickgen/NAMESPACE b/radiant.quickgen/NAMESPACE
index 162efd20462b752e8ea31299f01830ce4bea0a40..b2f28ca976714ba70e5ad65566fe93daf362727a 100644
--- a/radiant.quickgen/NAMESPACE
+++ b/radiant.quickgen/NAMESPACE
@@ -3,11 +3,12 @@
 S3method(dtab,explore)
 S3method(store,explore)
 S3method(summary,explore)
-export(ai_generate)
-export(ai_get_data_call)
-export(ai_run_code)
-export(build_r_prompt)
-export(chat_completion)
+export(build_chart_prompt)
+export(build_metrics_prompt)
+export(chart_completion)
+export(chart_generate)
+export(chart_get_data_call)
+export(chart_run_code)
 export(cv)
 export(does_vary)
 export(empty_level)
@@ -16,6 +17,10 @@ export(flip)
 export(ln)
 export(me)
 export(meprop)
+export(metrics_completion)
+export(metrics_generate)
+export(metrics_get_data_call)
+export(metrics_run_code)
 export(modal)
 export(n_missing)
 export(n_obs)
diff --git a/radiant.quickgen/R/quickgen_ai.R b/radiant.quickgen/R/quickgen_ai.R
deleted file mode 100644
index c5f6c705dcf166a78949576fed006d8aedd0d632..0000000000000000000000000000000000000000
--- a/radiant.quickgen/R/quickgen_ai.R
+++ /dev/null
@@ -1,96 +0,0 @@
-# === 配置 ===
-MODELSCOPE_OPENAI_URL <- "https://api-inference.modelscope.cn/v1"
-MODELSCOPE_API_KEY    <- Sys.getenv("MODELSCOPE_API_KEY", "ms-5b9f3668-ea8e-4a2c-8cd3-a1a9ba04810b")
-MODEL_ID              <- "deepseek-ai/DeepSeek-V3.1"
-
-# === 单次对话 ===
-#' @export
-chat_completion <- function(user_prompt,
-                            max_tokens = 1500,
-                            temperature = 0.3) {
-  req <- httr2::request(paste0(MODELSCOPE_OPENAI_URL, "/chat/completions")) %>%
-    httr2::req_headers(
-      "Authorization" = paste("Bearer", MODELSCOPE_API_KEY),
-      "Content-Type"  = "application/json"
-    ) %>%
-    httr2::req_body_json(list(
-      model       = MODEL_ID,
-      messages    = list(list(role = "user", content = user_prompt)),
-      temperature = temperature,
-      max_tokens  = max_tokens,
-      stream      = FALSE
-    ))
-  
-  resp <- httr2::req_perform(req)
-  body <- httr2::resp_body_json(resp)
-  
-  if (is.null(body$choices[[1]]$message$content))
-    stop("ModelScope API 返回空内容：", body)
-  
-  body$choices[[1]]$message$content
-}
-
-# === 构造发给模型的 Prompt ===
-#' @export
-build_r_prompt <- function(user_prompt, data_call) {
-  sprintf(
-    "你是 R 语言专家，必须严格遵守以下规则：
-
-〓 输出格式 〓
-- 只返回可运行 R 代码，用 ```r 包裹，禁止任何解释、注释、空行。
-- 若用户请求不符合规范，一律返回空代码块（仅 ```r\n``` ），不对话。
-- 当所需绘制的图中出现数据集中不存在的列或无法计算时，一律输出一张空白 ggplot，仅居中显示“无法绘制”四字，不抛出错误。
-
-〓 否定示例（立即返回空块）〓
-- 仅输入：“图表”“表格”“画图”“来张图”
-- 非医学/统计描述：笑话、故事、计算、翻译、写文章、写代码注释、解释概念、生成非 ggplot 图形（base、lattice）
-
-〓 技术细节 〓
-1. 数据集已读入：%s
-2. 主题函数带括号：theme_minimal()、theme_bw() ...
-3. 多张图用 patchwork 拼页。
-4. 包函数写全名，不得省略括号。
-
-用户请求：%s",
-    data_call, user_prompt
-  )
-}
-
-#' @export
-ai_generate <- function(prompt, dataset, envir = parent.frame()) {
-  data_call <- ai_get_data_call(dataset, envir)
-  sys_prompt <- build_r_prompt(prompt, data_call)
-  r_code     <- try(chat_completion(sys_prompt), silent = TRUE)
-  if (inherits(r_code, "try-error"))
-    stop("AI API error: ", attr(r_code, "condition")$message)
-  
-  r_code <- gsub("(?s)```r\\s*|```", "", r_code, perl = TRUE)
-  r_code <- trimws(r_code)
-  
-  if (r_code == "") {
-    return(list(r_code = "", 
-                type    = "empty",
-                auto_run = FALSE))
-  }
-  
-  r_code <- gsub("(theme_minimal|theme_bw|theme_classic|theme_gray|theme_void|theme_dark)\\b(?!\\s*\\()",
-                 "\\1()", r_code, perl = TRUE)
-  r_code <- paste0(data_call, "\n", r_code)
-  
-  has_gg  <- grepl("ggplot\\(|geom_", r_code)
-  has_tbl <- grepl("data\\.frame\\(|tibble\\(|tbl_summary|tableOne|CreateTableOne", r_code)
-  type    <- if (has_gg) "plot" else if (has_tbl) "table" else "text"
-  list(r_code = r_code, type = type, auto_run = TRUE)
-}
-
-#' @export
-ai_get_data_call <- function(dataset, envir) {
-  df_name <- if (is_string(dataset)) dataset else deparse1(substitute(dataset))
-  paste0("df <- eval(quote(get_data(\"", df_name, "\", envir = ",
-         deparse1(substitute(envir)), ")), envir = parent.frame())")
-}
-
-#' @export
-ai_run_code <- function(r_code, envir = parent.frame()) {
-  eval(parse(text = r_code), envir = envir)
-}
\ No newline at end of file
diff --git a/radiant.quickgen/R/quickgen_chart.R b/radiant.quickgen/R/quickgen_chart.R
new file mode 100644
index 0000000000000000000000000000000000000000..3a7f8f90f51e4995c794c28241b928c78786bad8
--- /dev/null
+++ b/radiant.quickgen/R/quickgen_chart.R
@@ -0,0 +1,95 @@
+# === 配置 ===
+OLLAMA_URL <- "http://180.169.131.147:8139/api/generate"
+MODEL_ID <- "qwen3-coder:30b"
+
+# === 单次对话 ===
+#' @export
+chart_completion <- function(user_prompt) {
+  
+  Sys.unsetenv("http_proxy")
+  Sys.unsetenv("https_proxy")
+  
+  # 构建请求体
+  req_body <- list(
+    model = MODEL_ID,
+    prompt = user_prompt,
+    stream = FALSE
+  )
+  
+  # 使用 curl 包发送请求
+  h <- curl::new_handle()
+  curl::handle_setheaders(h, "Content-Type" = "application/json")
+  curl::handle_setopt(h, postfields = jsonlite::toJSON(req_body, auto_unbox = TRUE))
+  curl::handle_setopt(h, timeout = 60)  
+  
+  con <- curl::curl(OLLAMA_URL, handle = h)
+  result <- readLines(con, warn = FALSE)
+  close(con)
+  
+  # 解析响应
+  body <- jsonlite::fromJSON(paste(result, collapse = ""))
+  
+  if (is.null(body$response) || trimws(body$response) == "")
+    stop("Ollama API 返回空内容：", paste(result, collapse = ""))
+  
+  body$response
+}
+
+# === 构造发给模型的 Prompt ===
+#' @export
+build_chart_prompt <- function(user_prompt, data_call) {
+  sprintf(
+    "你是 R 语言专家，必须严格遵守以下规则：
+〓 输出格式 〓
+- 只返回可运行 R 代码，用 ```r 包裹，禁止任何解释、注释、空行。
+- 代码必须强制换行：每个语句（df、library、ggplot、赋值、if/else 等）单独一行，ggplot 每个图层（+ geom_*/+ theme_*）单独一行。
+- 若用户请求包含“表格”“统计汇总”“频数表”等表格需求，禁止使用knitr::kable等会使表格字符串化的函数/包，必须输出标准表格形式。
+- 若用户请求不符合规范，一律返回空代码块（仅 ```r\n``` ），不对话。
+- 当所需绘制的图中出现数据集中不存在的列或无法计算时，一律输出一张空白 ggplot，仅居中显示“无法绘制”四字，不抛出错误。
+
+〓 否定示例（立即返回空块）〓
+- 仅输入：“图表”“表格”“画图”“来张图”
+- 非医学/统计描述：笑话、故事、计算、翻译、写文章、写代码注释、解释概念、生成非 ggplot 图形（base、lattice）
+
+〓 技术细节 〓
+1. 数据集已读入：%s
+2. 主题函数带括号：theme_minimal()、theme_bw() ...
+3. 多张图用 patchwork 拼页。
+4. 包函数写全名，不得省略括号。
+用户请求：%s",
+    data_call, user_prompt
+  )
+}
+
+#' @export
+chart_generate <- function(prompt, dataset, envir = parent.frame()) {
+  data_call <- chart_get_data_call(dataset, envir)
+  sys_prompt <- build_chart_prompt(prompt, data_call)
+  r_code <- try(chart_completion(sys_prompt), silent = TRUE)
+  if (inherits(r_code, "try-error")) {
+    stop("Chart API error: ", attr(r_code, "condition")$message)
+  }
+  r_code <- gsub("(?s)```r\\s*|```", "", r_code, perl = TRUE)
+  r_code <- trimws(r_code)
+  if (r_code == "") {
+    return(list(r_code = "", type = "empty", auto_run = FALSE))
+  }
+  r_code <- gsub("(?s)df\\s*<-\\s*(eval\\(quote\\(get_data\\(|get_data\\()[^;\\n]+;", "", r_code, perl = TRUE)
+  r_code <- trimws(r_code)
+  r_code <- gsub("(theme_minimal|theme_bw|theme_classic|theme_gray|theme_void|theme_dark)\\b(?!\\s*\\()","\\1()", r_code, perl = TRUE)
+  has_gg <- grepl("ggplot\\(|geom_", r_code)
+  has_tbl <- grepl("data\\.frame\\(|tibble\\(|tbl_summary|tableOne|CreateTableOne", r_code)
+  type <- if (has_gg) "plot" else if (has_tbl) "table" else "text"
+  list(r_code = r_code, type = type, auto_run = TRUE)
+}
+
+#' @export
+chart_get_data_call <- function(dataset, envir) {
+  df_name <- if (is_string(dataset)) dataset else deparse1(substitute(dataset))
+  paste0("df <- eval(quote(get_data(\"", df_name, "\", envir = ", deparse1(substitute(envir)), ")), envir = parent.frame())")
+}
+
+#' @export
+chart_run_code <- function(r_code, envir = parent.frame()) {
+  eval(parse(text = r_code), envir = envir)
+}
\ No newline at end of file
diff --git a/radiant.quickgen/R/quickgen_metrics.R b/radiant.quickgen/R/quickgen_metrics.R
new file mode 100644
index 0000000000000000000000000000000000000000..8cb3dfd6d9c2c9c0e5c719d1e49cf7d2ecaee042
--- /dev/null
+++ b/radiant.quickgen/R/quickgen_metrics.R
@@ -0,0 +1,96 @@
+# === 配置 ===
+OLLAMA_URL <- "http://172.29.2.110:8139/api/generate"  
+MODEL_ID <- "qwen3-coder:30b"  
+
+# === 单次对话 ===
+#' @export
+metrics_completion <- function(user_prompt) {
+  # 构建 Ollama 请求体
+  req <- httr2::request(OLLAMA_URL) %>%
+    httr2::req_headers(
+      "Content-Type" = "application/json"  
+    ) %>%
+    httr2::req_body_json(list(
+      model = MODEL_ID,        
+      prompt = user_prompt,
+      stream = FALSE           
+    ))
+  
+  resp <- httr2::req_perform(req)
+  body <- httr2::resp_body_json(resp)
+  
+  # 解析 Ollama 响应
+  if (is.null(body$response) || trimws(body$response) == "")
+    stop("Ollama API 返回空内容：", jsonlite::toJSON(body))
+  
+  body$response  # 返回 Ollama 生成的核心代码/结果
+}
+# === 构造发给模型的 Prompt ===
+#' @export
+build_metrics_prompt <- function(user_prompt, data_call) {
+  sprintf(
+    "你是 R 语言科研统计专家，精通所有主流统计方法（t检验、方差分析、回归分析、卡方检验、相关性分析等），必须严格遵守以下规则，任何违反均视为无效输出：
+〓 输出格式铁律 〓
+1. 仅返回可直接运行的 R 代码，用 ```r 包裹，无任何解释、注释、空行，代码必须包含「结果输出语句」（否则无法展示统计结果）。
+2. 不符合规范的请求，直接返回空代码块（仅 ```r\n``` ），不额外对话：
+   - 模糊无具体目标的请求
+   - 非科研统计需求（生成图表、翻译、写文章、解释概念等）
+3. 无法计算时（如列不存在、变量类型不匹配、方法不适用），仅输出 `print('无法计算：[具体原因，如“目标列bmi不存在”“卡方检验要求分类变量”]')`，不抛出错误。
+〓 统计逻辑核心约束 〓
+1. 方法匹配：必须根据用户请求选择「标准科研统计方法」（仅用 R 官方 stats 包或主流统计包如 broom、car、nnet 的标准函数，禁止自创方法）。
+2. 参数正确性：
+   - 原假设参数：用户指定的原假设定值（如“原假设均值为0”则 mu=0，“原假设相关系数为0”则 rho=0），禁止设为数据自身的统计量（如 mu=mean(df$bmi) 是严重错误）。
+   - 变量适配：严格匹配方法对变量类型的要求（如 t检验要求连续变量，卡方检验要求分类变量，回归分析因变量需连续），类型不匹配则触发“无法计算”。
+   - 缺失值处理：所有涉及数据计算的函数必须加 na.rm=TRUE（方法不支持则除外）。
+3. 默认参数：用户未指定时，按科研规范设默认值并在结果中体现：
+   - 置信水平默认 0.95（conf.level=0.95）
+   - 多重比较调整方法默认 p.adjust.method=none
+   - 假设检验默认双侧检验（alternative=two.sided）
+〓 技术规范（确保结果结构化、可展示）〓
+1. 数据集已读入为：%s（直接用 df$列名 引用变量，无需重复读入数据）。
+2. 结果输出要求：
+   - 优先用 broom::tidy() 或 broom::glance() 将统计结果转为结构化数据框（包含统计量、p值、置信区间、自由度、显著性标记等核心指标），再用 print() 输出。
+   - 若 broom 包不支持该方法（如部分复杂模型），直接 print(统计函数结果)，确保保留显著性标记（***、**、*）。
+3. 函数规范：统计函数必须写全名+完整括号（如 t.test()、lm()、chisq.test()），禁止省略括号或简写。
+4. 变量校验：自动校验变量存在性和类型（如分组变量必须是因子/字符型，连续变量不能用于卡方检验），校验失败则输出“无法计算”。
+用户请求：%s",
+    data_call, user_prompt
+  )
+}
+
+#' @export
+metrics_generate <- function(prompt, dataset, envir = parent.frame()) {
+  data_call <- metrics_get_data_call(dataset, envir)
+  sys_prompt <- build_metrics_prompt(prompt, data_call)
+  r_code     <- try(metrics_completion(sys_prompt), silent = TRUE)
+  if (inherits(r_code, "try-error"))
+    stop("Metrics API error: ", attr(r_code, "condition")$message)
+  
+  r_code <- gsub("(?s)```r\\s*|```", "", r_code, perl = TRUE)
+  r_code <- trimws(r_code)
+  
+  if (r_code == "") {
+    return(list(r_code = "", 
+                type    = "empty",
+                auto_run = FALSE))
+  }
+  
+  r_code <- paste0(data_call, "\n", r_code)
+  
+  has_gg  <- grepl("ggplot\\(|geom_", r_code)
+  has_tbl <- grepl("data\\.frame\\(|tibble\\(|tbl_summary|tableOne|CreateTableOne|t.test|lm|cor.test|anova", r_code)
+  type    <- if (has_gg) "plot" else if (has_tbl) "table" else "text"
+  list(r_code = r_code, type = type, auto_run = TRUE)
+}
+
+#' @export
+metrics_get_data_call <- function(dataset, envir) {
+  df_name <- if (is_string(dataset)) dataset else deparse1(substitute(dataset))
+  paste0("df <- eval(quote(get_data(\"", df_name, "\", envir = ",
+         deparse1(substitute(envir)), ")), envir = parent.frame())")
+}
+
+#' @export
+metrics_run_code <- function(r_code, envir = parent.frame()) {
+  eval(parse(text = r_code), envir = envir)
+}
diff --git a/radiant.quickgen/inst/app/help.R b/radiant.quickgen/inst/app/help.R
index a62134bcb6fe5e0f703e5c510bf501bba1ffeb18..751b5ed72ff5ac60965df95ea42efb1a23800049 100644
--- a/radiant.quickgen/inst/app/help.R
+++ b/radiant.quickgen/inst/app/help.R
@@ -1,7 +1,8 @@
 help_quickgen <- c(
   "一键生成描述性统计" = "quickgen_basic.md", 
   "大模型对话引导助手" = "quickgen_chat.md",
-  "大模型生成描述性统计" = "quickgen_ai.md"
+  "大模型生成描述性统计（图表）" = "quickgen_chart.md",
+  "大模型生成描述性统计（指标）" = "quickgen_metrics.md"
 )
 output$help_quickgen <- reactive(append_help("help_quickgen", file.path(getOption("radiant.path.quickgen"), "app/tools/help"), Rmd = TRUE))
 
diff --git a/radiant.quickgen/inst/app/init.R b/radiant.quickgen/inst/app/init.R
index 7c3ebf24e3a454a809c9b8713f49e77cd30d3fee..6406319d62d74cf52e1e5dbc5c008f823a03fc50 100644
--- a/radiant.quickgen/inst/app/init.R
+++ b/radiant.quickgen/inst/app/init.R
@@ -2,7 +2,7 @@
 r_url_list <- getOption("radiant.url.list")
 r_url_list[["Generate descriptive statistics with one click"]] <- "quickgen/basic/"
 r_url_list[["AI chat guidance"]] <- "quickgen/chat/"
-r_url_list[["LLM generates descriptive statistics"]] <- "quickgen/ai/"
+r_url_list[["AI generates descriptive statistics(chart)"]] <- "quickgen/chart"
 options(radiant.url.list = r_url_list)
 rm(r_url_list)
 
@@ -15,9 +15,12 @@ options(
         tags$head(
           tags$script(src = "www_quickgen/js/run_return.js")
         ),
+        "----", i18n$t("Quick Statistics"),
         tabPanel(i18n$t("Generate descriptive statistics with one click"), uiOutput("quickgen_basic")),
+        "----", i18n$t("AI assistance"),
         tabPanel(i18n$t("AI chat guidance"), uiOutput("quickgen_chat")),
-        tabPanel(i18n$t("AI generates descriptive statistics"), uiOutput("quickgen_ai"))
+        tabPanel(i18n$t("AI generates descriptive statistics(chart)"), uiOutput("quickgen_chart")),
+        tabPanel(i18n$t("AI generates descriptive statistics(metrics)"), uiOutput("quickgen_metrics")),
       )
     )
 )
\ No newline at end of file
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_ai_ui.R b/radiant.quickgen/inst/app/tools/analysis/quickgen_ai_ui.R
deleted file mode 100644
index 72d9270fe42e1b9c0eae0883f6f486d008353469..0000000000000000000000000000000000000000
--- a/radiant.quickgen/inst/app/tools/analysis/quickgen_ai_ui.R
+++ /dev/null
@@ -1,295 +0,0 @@
-# quickgen_ai_ui.R
-library(shinyjs)
-library(shinyAce)
-
-## ==================== 右下角浮框 ====================
-ui_ai_progress <- tags$div(
-  id = "ai_progress_box",
-  style = "display:none;
-           position:fixed;
-           bottom:15px; right:15px;
-           width:220px; z-index:9999;
-           background:#f5f5f5; color:#333;
-           border:1px solid #337ab7; border-radius:4px;
-           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
-  tags$strong(i18n$t("AI running...")),
-  tags$div(class = "progress",
-           tags$div(class = "progress-bar progress-bar-striped active",
-                    style = "width:100%"))
-)
-
-## ======== 警告弹窗========
-ui_ai_warn <- tags$div(
-  id = "ai_warn_box",
-  style = "display:none;
-           position:fixed;
-           bottom:15px; right:15px;
-           width:220px; z-index:9999;
-           background:#fff3cd; color:#856404;
-           border:1px solid #ffeaa7; border-radius:4px;
-           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
-  tags$strong(i18n$t("Warning:Please enter a request related to descriptive statistics or visualization."))
-)
-
-## ==================== 统一入口 ====================
-output$quickgen_ai <- renderUI({
-  stat_tab_panel(
-    menu      = i18n$t("Oneclick generation > AI generates descriptive statistics"),
-    tool      = i18n$t("AI generates descriptive statistics"),
-    tool_ui   = "ai_main_ui",
-    output_panels = tabPanel(
-      title = i18n$t("AI assistant"),
-      value = "ai_panel",
-      uiOutput("ai_result_area")
-    )
-  )
-})
-
-## ==================== 右侧 AI 面板 ====================
-output$ai_main_ui <- renderUI({
-  tagList(
-    useShinyjs(),
-    ui_ai_progress,
-    ui_ai_warn,
-    wellPanel(
-      i18n$t("Describe your analysis request"),
-      returnTextAreaInput("ai_prompt",
-                          label   = NULL,
-                          placeholder = i18n$t("e. g. Please help me draw a scatter plot of diamonds prices and carats"),
-                          rows    = 4,
-                          value   = state_init("ai_prompt", "")),
-      fluidRow(
-        column(6, uiOutput("ui_ai_submit")),
-        column(6, uiOutput("ai_loading"))
-      )
-    ),
-    
-    wellPanel(
-      i18n$t("Generated R code"),
-      uiOutput("ai_r_code_block"),
-      fluidRow(
-        column(6, actionButton("ai_run_code", i18n$t("Run code"), icon = icon("play"), class = "btn-success")),
-        column(6, actionButton("ai_edit_code", i18n$t("Edit code"), icon = icon("edit"), class = "btn-default"))
-      )
-    ),
-    
-    help_and_report(
-      modal_title = i18n$t("AI generates descriptive statistics"),
-      fun_name    = "quickgen_ai",
-      help_file   = inclMD(file.path(getOption("radiant.path.quickgen"), "app/tools/help/quickgen_ai.md")),
-      lic = "by-sa"
-    )
-  )
-})
-
-## ==================== 控件渲染 ====================
-output$ui_ai_submit <- renderUI({
-  req(input$dataset)
-  actionButton("ai_submit", i18n$t("Send"), icon = icon("magic"), class = "btn-primary")
-})
-
-output$ai_loading <- renderUI({
-  if (isTRUE(r_values$ai_loading))
-    tags$div(class = "progress",
-             tags$div(class = "progress-bar progress-bar-striped active",
-                      style = "width:100%",
-                      i18n$t("Calling AI model...")))
-})
-
-## ==================== reactiveValues ====================
-r_values <- reactiveValues(
-  ai_r_code      = "",
-  ai_result_type = "text",
-  ai_result_ready = FALSE,
-  ai_loading     = FALSE
-)
-
-## ==================== 生成代码 ====================
-observeEvent(input$ai_submit, {
-  if (is.empty(input$ai_prompt))
-    return(showNotification(i18n$t("Please enter an analysis request"), type = "error"))
-  
-  r_values$ai_loading <- TRUE
-  shinyjs::show("ai_progress_box")          # 显示右下角进度框
-  on.exit({
-    r_values$ai_loading <- FALSE
-    shinyjs::hide("ai_progress_box")        # 无论成功失败都隐藏
-  })
-  
-  res <- try(do.call(ai_generate,
-                     list(prompt  = input$ai_prompt,
-                          dataset = input$dataset,
-                          envir   = r_data)),
-             silent = TRUE)
-  if (inherits(res, "try-error")) {
-    showNotification(paste(i18n$t("AI API error:"), res), type = "error")
-    return()
-  }
-  
-  r_values$ai_r_code      <- res$r_code
-  r_values$ai_result_type <- res$type
-  r_values$ai_result_ready <- FALSE
-  r_values$auto_run       <- res$auto_run
-  
-  if (res$type == "empty") {
-    shinyjs::show("ai_warn_box")
-    shinyjs::delay(3000, shinyjs::hide("ai_warn_box"))
-    return()
-  }
-  
-  if (isTRUE(r_values$auto_run))
-    shinyjs::click("ai_run_code")
-})
-
-## ==================== 显示 R 代码 ====================
-output$ai_r_code_block <- renderUI({
-  codes <- r_values$ai_r_code
-  tags$pre(codes, style = "background:#f5f5f5; padding:10px; border-radius:4px;
-                           font-family:monospace; white-space:pre-wrap; min-height:100px;")
-})
-
-## ==================== 运行代码 ====================
-observeEvent(input$ai_run_code, {
-  shinyjs::hide("ai_progress_box")   
-  if (is.empty(r_values$ai_r_code)) return()
-  
-  if (trimws(r_values$ai_r_code) == "" || identical(r_values$ai_result_type, "empty")) {
-    shinyjs::show("ai_warn_box")
-    shinyjs::delay(3000, shinyjs::hide("ai_warn_box"))
-    return()
-  }
-  
-  tryCatch({
-    result <- do.call(ai_run_code,
-                      list(r_code = r_values$ai_r_code, envir = r_data))
-    r_data$ai_temp_result <- result
-    
-    if (inherits(result, "gg") || inherits(result, "ggplot")) {
-      r_values$ai_result_type <- "plot"
-      output$ai_result_plot <- renderPlot(print(result))
-    } else if (is.data.frame(result) || is.matrix(result)) {
-      r_values$ai_result_type <- "table"
-      output$ai_result_table <- DT::renderDataTable(
-        DT::datatable(result, options = list(scrollX = TRUE, pageLength = 10)))
-    } else {
-      r_values$ai_result_type <- "text"
-      output$ai_result_text <- renderText(capture.output(print(result)))
-    }
-    r_values$ai_result_ready <- TRUE
-  }, error = function(e) {
-    r_values$ai_result_type <- "error"
-    output$ai_result_error <- renderText(paste0(i18n$t("Error: "), e$message))
-    r_values$ai_result_ready <- TRUE
-    showNotification(paste0(i18n$t("Run code error: "), e$message),
-                     type = "error", duration = NULL)
-  })
-}, ignoreInit = TRUE)
-
-## ======== 结果展示区========
-output$ai_result_area <- renderUI({
-  req(r_values$ai_result_ready)
-  tagList(
-    conditionalPanel(
-      condition = "output.ai_result_type == 'plot'",
-      download_link("dlp_ai_plot"), br(),            
-      plotOutput("ai_result_plot", width = "100%", height = "500px")
-    ),
-    conditionalPanel(
-      condition = "output.ai_result_type == 'table'",
-      download_link("dlp_ai_table"), br(),          
-      DT::dataTableOutput("ai_result_table")
-    ),
-    conditionalPanel(
-      condition = "output.ai_result_type == 'text' || output.ai_result_type == 'error'",
-      verbatimTextOutput("ai_result_text")
-    )
-  )
-})
-
-
-output$ai_result_type <- reactive({
-  r_values$ai_result_type 
-})
-
-outputOptions(output, "ai_result_type", suspendWhenHidden = FALSE)
-
-## ==================== 编辑代码模态框 ====================
-observeEvent(input$ai_edit_code, {
-  showModal(
-    modalDialog(
-      title = i18n$t("Edit R Code"),
-      size  = "l",
-      footer = tagList(
-        actionButton("ai_save_code", i18n$t("Save Changes"), class = "btn-primary"),
-        modalButton(i18n$t("Cancel"))
-      ),
-      aceEditor(
-        "ai_code_editor",
-        mode = "r",
-        theme = getOption("radiant.ace_theme", "tomorrow"),
-        wordWrap = TRUE,
-        value = r_values$ai_r_code,
-        placeholder = i18n$t("Edit the generated R code here..."),
-        vimKeyBinding = getOption("radiant.ace_vim.keys", FALSE),
-        tabSize = getOption("radiant.ace_tabSize", 2),
-        useSoftTabs = getOption("radiant.ace_useSoftTabs", TRUE),
-        showInvisibles = getOption("radiant.ace_showInvisibles", FALSE),
-        autoScrollEditorIntoView = TRUE,
-        minLines = 15,
-        maxLines = 30
-      )
-    )
-  )
-})
-
-## ==================== 保存代码 ====================
-observeEvent(input$ai_save_code, {
-  r_values$ai_r_code <- input$ai_code_editor
-  r_values$auto_run <- FALSE
-  removeModal()
-})
-
-## ==================== PNG 下载处理器 ====================
-dlp_ai_plot <- function(path) {
-  result <- r_data$ai_temp_result
-  if (inherits(result, "gg") || inherits(result, "ggplot")) {
-    png(path, width = 800, height = 500, res = 96)
-    print(result)
-    dev.off()
-  } else {
-    png(path, width = 400, height = 400)
-    plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
-    text(1, 1, "No plot available", cex = 1.5)
-    dev.off()
-  }
-}
-download_handler(
-  id = "dlp_ai_plot",
-  fun = dlp_ai_plot,
-  fn = function() paste0("plot_", Sys.Date()),
-  type = "png",
-  caption = i18n$t("Save AI-generated plot")
-)
-
-# ======== 表格 CSV 下载处理器 ========
-dlp_ai_table <- function(path) {
-  result <- r_data$ai_temp_result
-  if (is.data.frame(result)) {
-    write.csv(result, file = path, row.names = FALSE)
-  } else {
-    write.csv(data.frame(msg = "No table available"), file = path, row.names = FALSE)
-  }
-}
-download_handler(
-  id      = "dlp_ai_table",
-  fun     = dlp_ai_table,
-  fn      = function() paste0("table_", Sys.Date()),
-  type    = "csv",
-  caption = i18n$t("Save AI-generated table")
-)
-
-## ==================== 报告 / 截图 ====================
-ai_report <- function() {}
-observeEvent(input$ai_report, ai_report())
-observeEvent(input$ai_screenshot, radiant_screenshot_modal("modal_ai_screenshot"))
-observeEvent(input$modal_ai_screenshot, { ai_report(); removeModal() })
\ No newline at end of file
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R b/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R
index 5a5406be9da2c6969971f18bae5a4e321a6ba1e1..ee5ceea089fcf193e704c359007356d1eecf8455 100644
--- a/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R
+++ b/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R
@@ -1145,7 +1145,7 @@ observeEvent(input$qgb_invert_selection, {
 
 output$quickgen_basic <- renderUI({
   stat_tab_panel(
-    menu = i18n$t("Oneclick generation > Generate descriptive statistics"),
+    menu = i18n$t("Oneclick generation > Quick Statistics"),
     tool = i18n$t("Generate descriptive statistics with one click"),
     tool_ui = "ui_quickgen_basic",
     output_panels = tagList(
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_chart_ui.R b/radiant.quickgen/inst/app/tools/analysis/quickgen_chart_ui.R
new file mode 100644
index 0000000000000000000000000000000000000000..234d0a34cdd9f50ec7c916acd8492c36208d9f53
--- /dev/null
+++ b/radiant.quickgen/inst/app/tools/analysis/quickgen_chart_ui.R
@@ -0,0 +1,302 @@
+# quickgen_chart_ui.R
+library(shinyjs)
+library(shinyAce)
+
+## ==================== 右下角浮框 ====================
+ui_chart_progress <- tags$div(
+  id = "chart_progress_box",
+  style = "display:none;
+           position:fixed;
+           bottom:15px; right:15px;
+           width:220px; z-index:9999;
+           background:#f5f5f5; color:#333;
+           border:1px solid #337ab7; border-radius:4px;
+           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
+  tags$strong(i18n$t("AI generating...")),
+  tags$div(class = "progress",
+           tags$div(class = "progress-bar progress-bar-striped active",
+                    style = "width:100%"))
+)
+
+## ======== 警告弹窗========
+ui_chart_warn <- tags$div(
+  id = "chart_warn_box",
+  style = "display:none;
+           position:fixed;
+           bottom:15px; right:15px;
+           width:220px; z-index:9999;
+           background:#fff3cd; color:#856404;
+           border:1px solid #ffeaa7; border-radius:4px;
+           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
+  tags$strong(i18n$t("Warning:Please enter a request related to descriptive statistics or visualization."))
+)
+
+## ==================== 统一入口 ====================
+output$quickgen_chart <- renderUI({
+  stat_tab_panel(
+    menu      = i18n$t("Oneclick generation > AI assistance"),
+    tool      = i18n$t("AI generates descriptive statistics(chart)"),
+    tool_ui   = "chart_main_ui",
+    output_panels = tabPanel(
+      title = i18n$t("Chart Assistant"),
+      value = "chart_panel",
+      uiOutput("chart_result_area")
+    )
+  )
+})
+
+## ==================== 右侧 Chart 面板 ====================
+output$chart_main_ui <- renderUI({
+  tagList(
+    useShinyjs(),
+    ui_chart_progress,
+    ui_chart_warn,
+    wellPanel(
+      i18n$t("Describe your analysis request"),
+      returnTextAreaInput("chart_prompt",
+                          label   = NULL,
+                          placeholder = i18n$t("e. g. Please help me generate a cross frequency histogram of sex and smoker"),
+                          rows    = 4,
+                          value   = state_init("chart_prompt", "")),
+      fluidRow(
+        column(6, uiOutput("ui_chart_submit")),
+        column(6, uiOutput("chart_loading"))
+      )
+    ),
+    
+    wellPanel(
+      i18n$t("Generated R code"),
+      uiOutput("chart_r_code_block"),
+      fluidRow(
+        column(6, actionButton("chart_run_code", i18n$t("Run code"), icon = icon("play"), class = "btn-success")),
+        column(6, actionButton("chart_edit_code", i18n$t("Edit code"), icon = icon("edit"), class = "btn-default"))
+      )
+    ),
+    
+    help_and_report(
+      modal_title = i18n$t("AI generates descriptive statistics(chart)"),
+      fun_name    = "quickgen_chart",
+      help_file   = inclMD(file.path(getOption("radiant.path.quickgen"), "app/tools/help/quickgen_chart.md")),
+      lic = "by-sa"
+    )
+  )
+})
+
+## ==================== 控件渲染 ====================
+output$ui_chart_submit <- renderUI({
+  req(input$dataset)
+  actionButton("chart_submit", i18n$t("Send"), icon = icon("magic"), class = "btn-primary")
+})
+output$chart_loading <- renderUI({
+  if (isTRUE(r_values$chart_loading))
+    tags$div(class = "progress",
+             tags$div(class = "progress-bar progress-bar-striped active",
+                      style = "width:100%",
+                      i18n$t("Calling chart generation model...")))
+})
+
+## ==================== reactiveValues ====================
+r_values <- reactiveValues(
+  chart_r_code      = "",
+  chart_result_type = "text",
+  chart_result_ready = FALSE,
+  chart_loading     = FALSE
+)
+
+## ==================== 生成代码 ====================
+observeEvent(input$chart_submit, {
+  if (is.empty(input$chart_prompt))
+    return(showNotification(i18n$t("Please enter an analysis request"), type = "error"))
+  
+  r_values$chart_loading <- TRUE
+  shinyjs::show("chart_progress_box")          # 显示右下角进度框
+  on.exit({
+    r_values$chart_loading <- FALSE
+    shinyjs::hide("chart_progress_box")        # 无论成功失败都隐藏
+  })
+  
+  res <- try(do.call(chart_generate,
+                     list(prompt  = input$chart_prompt,
+                          dataset = input$dataset,
+                          envir   = r_data)),
+             silent = TRUE)
+  if (inherits(res, "try-error")) {
+    showNotification(paste(i18n$t("Chart API error:"), res), type = "error")
+    return()
+  }
+  
+  r_values$chart_r_code      <- res$r_code
+  r_values$chart_result_type <- res$type
+  r_values$chart_result_ready <- FALSE
+  r_values$auto_run       <- res$auto_run
+  
+  if (res$type == "empty") {
+    shinyjs::show("chart_warn_box")
+    shinyjs::delay(3000, shinyjs::hide("chart_warn_box"))
+    return()
+  }
+  
+  if (isTRUE(r_values$auto_run))
+    shinyjs::click("chart_run_code")
+})
+
+## ==================== 显示 R 代码 ====================
+output$chart_r_code_block <- renderUI({
+  codes <- r_values$chart_r_code
+  tags$pre(codes, style = "background:#f5f5f5; padding:10px; border-radius:4px;
+                           font-family:monospace; white-space:pre-wrap; min-height:100px;")
+})
+
+## ==================== 运行代码 ====================
+observeEvent(input$chart_run_code, {
+  shinyjs::hide("chart_progress_box")   
+  if (is.empty(r_values$chart_r_code)) return()
+  
+  if (trimws(r_values$chart_r_code) == "" || identical(r_values$chart_result_type, "empty")) {
+    shinyjs::show("chart_warn_box")
+    shinyjs::delay(3000, shinyjs::hide("chart_warn_box"))
+    return()
+  }
+  
+  tryCatch({
+    result <- do.call(chart_run_code,
+                      list(r_code = r_values$chart_r_code, envir = r_data))
+    r_data$chart_temp_result <- result
+    
+    if (inherits(result, "gg") || inherits(result, "ggplot")) {
+      r_values$chart_result_type <- "plot"
+      output$chart_result_plot <- renderPlot(print(result))
+    } else if (is.data.frame(result) || is.matrix(result)) {
+      r_values$chart_result_type <- "table"
+      output$chart_result_table <- DT::renderDataTable(
+        DT::datatable(result, options = list(scrollX = TRUE, pageLength = 10)))
+    } else {
+      r_values$chart_result_type <- "text"
+      output$chart_result_text <- renderText(capture.output(print(result)))
+    }
+    r_values$chart_result_ready <- TRUE
+  }, error = function(e) {
+    r_values$chart_result_type <- "error"
+    output$chart_result_error <- renderText(paste0(i18n$t("Error: "), e$message))
+    r_values$chart_result_ready <- TRUE
+    showNotification(paste0(i18n$t("Run code error: "), e$message),
+                     type = "error", duration = NULL)
+  })
+}, ignoreInit = TRUE)
+
+## ======== 结果展示区========
+output$chart_result_area <- renderUI({
+  req(r_values$chart_result_ready)
+  tagList(
+    conditionalPanel(
+      condition = "output.chart_result_type == 'plot'",
+      download_link("dlp_chart_plot"), br(),            
+      plotOutput("chart_result_plot", width = "100%", height = "500px")
+    ),
+    conditionalPanel(
+      condition = "output.chart_result_type == 'table'",
+      download_link("dlp_chart_table"), br(),          
+      DT::dataTableOutput("chart_result_table")
+    ),
+    conditionalPanel(
+      condition = "output.chart_result_type == 'text' || output.chart_result_type == 'error'",
+      verbatimTextOutput("chart_result_text")
+    )
+  )
+})
+output$chart_result_type <- reactive({
+  r_values$chart_result_type 
+})
+outputOptions(output, "chart_result_type", suspendWhenHidden = FALSE)
+
+## ==================== 编辑代码模态框 ====================
+observeEvent(input$chart_edit_code, {
+  showModal(
+    modalDialog(
+      title = i18n$t("Edit R Code"),
+      size  = "l",
+      footer = tagList(
+        actionButton("chart_save_code", i18n$t("Save Changes"), class = "btn-primary"),
+        modalButton(i18n$t("Cancel"))
+      ),
+      aceEditor(
+        "chart_code_editor",
+        mode = "r",
+        theme = getOption("radiant.ace_theme", "tomorrow"),
+        wordWrap = TRUE,
+        value = r_values$chart_r_code,
+        placeholder = i18n$t("Edit the generated R code here..."),
+        vimKeyBinding = getOption("radiant.ace_vim.keys", FALSE),
+        tabSize = getOption("radiant.ace_tabSize", 2),
+        useSoftTabs = getOption("radiant.ace_useSoftTabs", TRUE),
+        showInvisibles = getOption("radiant.ace_showInvisibles", FALSE),
+        autoScrollEditorIntoView = TRUE,
+        minLines = 15,
+        maxLines = 30
+      )
+    )
+  )
+})
+
+## ==================== 保存代码 ====================
+observeEvent(input$chart_save_code, {
+  r_values$chart_r_code <- input$chart_code_editor
+  r_values$auto_run <- FALSE
+  removeModal()
+})
+
+## ==================== PNG 下载处理器 ====================
+dlp_chart_plot <- function(path) {
+  result <- r_data$chart_temp_result
+  if (inherits(result, "gg") || inherits(result, "ggplot")) {
+    png(path, width = 800, height = 500, res = 96)
+    print(result)
+    dev.off()
+  } else {
+    png(path, width = 400, height = 400)
+    plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
+    text(1, 1, "No plot available", cex = 1.5)
+    dev.off()
+  }
+}
+
+download_handler(
+  id = "dlp_chart_plot",
+  fun = dlp_chart_plot,
+  fn = function() paste0("plot_", Sys.Date()),
+  type = "png",
+  caption = i18n$t("Save chart-generated plot")
+)
+
+# ======== 表格 CSV 下载处理器 ========
+dlp_chart_table <- function(path) {
+  result <- r_data$chart_temp_result
+  if (is.data.frame(result)) {
+    df <- result
+  } else if (is.table(result)) {
+    df <- as.data.frame(result, stringsAsFactors = FALSE)
+  } else if (is.matrix(result)) {
+    df <- as.data.frame(result, stringsAsFactors = FALSE)
+    if (!is.null(rownames(result))) {
+      df <- cbind(row_name = rownames(result), df, row.names = NULL)
+    }
+  } else {
+    df <- data.frame(msg = "No valid table available")
+  }
+  
+  write.csv(df, file = path, row.names = FALSE, fileEncoding = "UTF-8")
+}
+
+download_handler(
+  id      = "dlp_chart_table",
+  fun     = dlp_chart_table,
+  fn      = function() paste0("table_", Sys.Date()),
+  type    = "csv",
+  caption = i18n$t("Save chart-generated table")
+)
+
+## ==================== 报告 / 截图 ====================
+chart_report <- function() {}
+observeEvent(input$chart_report, chart_report())
+observeEvent(input$chart_screenshot, radiant_screenshot_modal("modal_chart_screenshot"))
+observeEvent(input$modal_chart_screenshot, { chart_report(); removeModal() })
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_chat_ui.R b/radiant.quickgen/inst/app/tools/analysis/quickgen_chat_ui.R
index 2504f5c586e4edfda7ba74b2661fb2823171f701..5ebdf9324266ec3a216737457b4993844dfd4ef9 100644
--- a/radiant.quickgen/inst/app/tools/analysis/quickgen_chat_ui.R
+++ b/radiant.quickgen/inst/app/tools/analysis/quickgen_chat_ui.R
@@ -6,7 +6,7 @@ output$quickgen_chat <- renderUI({
   tagList(
     useShinyjs(),
     stat_tab_panel(
-      menu      = i18n$t("One-click generation > AI chat guidance"),
+      menu      = i18n$t("Oneclick generation > AI assistance"),
       tool      = i18n$t("AI chat guidance"),
       tool_ui   = "chat_main_ui",  
       output_panels = tabPanel(
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_metrics_ui.R b/radiant.quickgen/inst/app/tools/analysis/quickgen_metrics_ui.R
new file mode 100644
index 0000000000000000000000000000000000000000..bdbfb4143d9c8b9acaefbc3b11162d8b1bd9eeda
--- /dev/null
+++ b/radiant.quickgen/inst/app/tools/analysis/quickgen_metrics_ui.R
@@ -0,0 +1,419 @@
+# quickgen_metrics_ui.R
+library(shinyjs)
+library(shinyAce)
+
+# 新增：统计结果文本格式化函数
+format_stat_text <- function(result, dataset_name) {
+  # 1. 处理“无法计算”的情况
+  if (is.character(result) && grepl("无法计算", result)) {
+    return(result)
+  }
+  
+  # 2. 单样本t检验（htest类）
+  if (inherits(result, "htest") && grepl("One Sample t-test", result$method)) {
+    # 提取关键指标
+    var_name <- gsub("^x = df\\$|^df\\$", "", as.character(result$data.name))
+    mean_val <- round(mean(result$data, na.rm = TRUE), 3)
+    n_val <- length(na.omit(result$data))
+    n_missing <- sum(is.na(result$data))
+    sd_val <- round(sd(result$data, na.rm = TRUE), 3)
+    se_val <- round(result$stderr, 3)
+    me_val <- round(se_val * qt(0.975, df = result$parameter), 3)  # 边际误差
+    diff_val <- round(result$estimate, 3)
+    t_val <- round(result$statistic, 3)
+    p_val <- if (result$p.value < 0.001) "< .001" else round(result$p.value, 4)
+    df_val <- result$parameter
+    ci_lower <- round(result$conf.int[1], 3)
+    ci_upper <- round(result$conf.int[2], 3)
+    conf_level <- round(attr(result$conf.int, "conf.level") * 100, 1)
+    # 显著性标记
+    signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
+    
+    # 组织文本（完全匹配示例格式）
+    text <- sprintf(paste0(
+      "Single mean test\n",
+      "Data      : %s \n",
+      "Variable  : %s \n",
+      "Confidence: %.1f%% \n",
+      "Null hyp. : the mean of %s = %.1f \n",
+      "Alt. hyp. : the mean of %s is not equal to %.1f \n",
+      "   mean     n n_missing     sd    se    me\n",
+      " %6.3f %5s         %d %6.3f %5.3f %5.3f\n",
+      "   diff    se t.value p.value   df   2.5%%  97.5%%    \n",
+      " %6.3f %5.3f %6.3f %8s %5.0f %6.3f %6.3f %s\n",
+      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
+    ),
+    dataset_name, var_name, conf_level, var_name, result$null.value,
+    var_name, result$null.value, mean_val, format(n_val, big.mark = ","),
+    n_missing, sd_val, se_val, me_val, diff_val, se_val, t_val, p_val,
+    df_val, ci_lower, ci_upper, signif
+    )
+    return(text)
+  }
+  
+  # 3. 独立样本t检验（htest类）
+  if (inherits(result, "htest") && grepl("Welch Two Sample t-test|Two Sample t-test", result$method)) {
+    # 提取分组变量和数值变量
+    data_parts <- strsplit(result$data.name, " ~ ")[[1]]
+    var_name <- data_parts[1]
+    group_var <- data_parts[2]
+    group_vals <- levels(factor(df[[group_var]]))
+    # 分组统计
+    group1_data <- df[[var_name]][df[[group_var]] == group_vals[1]]
+    group2_data <- df[[var_name]][df[[group_var]] == group_vals[2]]
+    mean1 <- round(mean(group1_data, na.rm = TRUE), 3)
+    mean2 <- round(mean(group2_data, na.rm = TRUE), 3)
+    n1 <- length(na.omit(group1_data))
+    n2 <- length(na.omit(group2_data))
+    n_missing1 <- sum(is.na(group1_data))
+    n_missing2 <- sum(is.na(group2_data))
+    sd1 <- round(sd(group1_data, na.rm = TRUE), 3)
+    sd2 <- round(sd(group2_data, na.rm = TRUE), 3)
+    se1 <- round(sd1 / sqrt(n1), 3)
+    se2 <- round(sd2 / sqrt(n2), 3)
+    me1 <- round(se1 * qt(0.975, df = n1 - 1), 3)
+    me2 <- round(se2 * qt(0.975, df = n2 - 1), 3)
+    # 检验结果
+    diff_val <- round(result$estimate[1] - result$estimate[2], 3)
+    t_val <- round(result$statistic, 3)
+    p_val <- if (result$p.value < 0.001) "< .001" else round(result$p.value, 4)
+    df_val <- round(result$parameter, 0)
+    ci_lower <- round(result$conf.int[1], 3)
+    ci_upper <- round(result$conf.int[2], 3)
+    conf_level <- round(attr(result$conf.int, "conf.level") * 100, 1)
+    signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
+    
+    # 组织文本
+    text <- sprintf(paste0(
+      "Pairwise mean comparisons (t-test)\n",
+      "Data      : %s \n",
+      "Variables : %s, %s \n",
+      "Samples   : independent \n",
+      "Confidence: %.1f%% \n",
+      "Adjustment: None \n",
+      "           mean     n n_missing     sd    se    me\n",
+      " %6s %6.3f %5s         %d %6.3f %5.3f %5.3f\n",
+      " %6s %6.3f %5s         %d %6.3f %5.3f %5.3f\n",
+      " Null hyp.               Alt. hyp.                  diff  p.value    \n",
+      " %s = %s   %s not equal to %s   %6.3f %8s  %s\n",
+      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
+    ),
+    dataset_name, group_var, var_name, conf_level,
+    group_vals[1], mean1, format(n1, big.mark = ","), n_missing1, sd1, se1, me1,
+    group_vals[2], mean2, format(n2, big.mark = ","), n_missing2, sd2, se2, me2,
+    group_vals[1], group_vals[2], group_vals[1], group_vals[2], diff_val, p_val, signif
+    )
+    return(text)
+  }
+  
+  # 4. 线性回归（lm类）
+  if (inherits(result, "lm")) {
+    # 提取模型信息
+    model_formula <- as.character(result$call$formula)
+    var_dep <- model_formula[2]
+    vars_indep <- gsub("^ ~ ", "", model_formula[1])
+    # 系数表
+    coef_sum <- summary(result)$coefficients
+    coef_text <- "            Estimate Std.Error t.value p.value    Signif.\n"
+    for (i in 1:nrow(coef_sum)) {
+      term <- rownames(coef_sum)[i]
+      est <- round(coef_sum[i, 1], 4)
+      se <- round(coef_sum[i, 2], 4)
+      t_val <- round(coef_sum[i, 3], 3)
+      p_val <- if (coef_sum[i, 4] < 0.001) "< .001" else round(coef_sum[i, 4], 4)
+      signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
+      coef_text <- paste0(coef_text, sprintf(" %12s %8.4f %8.4f %6.3f %8s  %3s\n", term, est, se, t_val, p_val, signif))
+    }
+    # 模型拟合度
+    r2 <- round(summary(result)$r.squared, 4)
+    r2_adj <- round(summary(result)$adj.r.squared, 4)
+    n_val <- nrow(result$model)
+    n_missing <- nrow(df) - n_val
+    
+    # 组织文本
+    text <- sprintf(paste0(
+      "Linear Regression Model\n",
+      "Data      : %s \n",
+      "Formula   : %s ~ %s \n",
+      "Dependent : %s \n",
+      "Independent: %s \n",
+      "Sample    : n = %s, n_missing = %d \n",
+      "Fit       : R² = %.4f, Adjusted R² = %.4f \n",
+      "%s",
+      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
+    ),
+    dataset_name, var_dep, vars_indep, var_dep, vars_indep,
+    format(n_val, big.mark = ","), n_missing, r2, r2_adj, coef_text
+    )
+    return(text)
+  }
+  
+  # 5. 其他统计方法（卡方检验、方差分析等，按示例风格扩展）
+  if (inherits(result, "htest") && grepl("Chi-squared test", result$method)) {
+    # 卡方检验文本格式化（类似逻辑，提取列联表、卡方值、p值等）
+    data_parts <- strsplit(result$data.name, " ~ ")[[1]]
+    var1 <- data_parts[1]
+    var2 <- data_parts[2]
+    contingency <- table(df[[var1]], df[[var2]], useNA = "no")
+    chi_val <- round(result$statistic, 3)
+    df_val <- result$parameter
+    p_val <- if (result$p.value < 0.001) "< .001" else round(result$p.value, 4)
+    signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
+    
+    text <- sprintf(paste0(
+      "Chi-squared Test of Independence\n",
+      "Data      : %s \n",
+      "Variables : %s (row), %s (column) \n",
+      "Contingency Table:\n%s\n",
+      "Test Statistic: Chi-squared = %.3f, df = %.0f, p-value = %s %s\n",
+      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
+    ),
+    dataset_name, var1, var2, capture.output(print(contingency)),
+    chi_val, df_val, p_val, signif
+    )
+    return(text)
+  }
+  
+  # 6. 直接输出原始结果
+  return(capture.output(print(result)))
+}
+
+## ==================== 右下角浮框 ====================
+ui_metrics_progress <- tags$div(
+  id = "metrics_progress_box",
+  style = "display:none;
+           position:fixed;
+           bottom:15px; right:15px;
+           width:220px; z-index:9999;
+           background:#f5f5f5; color:#333;
+           border:1px solid #337ab7; border-radius:4px;
+           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
+  tags$strong(i18n$t("AI calculating...")),
+  tags$div(class = "progress",
+           tags$div(class = "progress-bar progress-bar-striped active",
+                    style = "width:100%"))
+)
+## ======== 警告弹窗========
+ui_metrics_warn <- tags$div(
+  id = "metrics_warn_box",
+  style = "display:none;
+           position:fixed;
+           bottom:15px; right:15px;
+           width:220px; z-index:9999;
+           background:#fff3cd; color:#856404;
+           border:1px solid #ffeaa7; border-radius:4px;
+           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
+  tags$strong(i18n$t("Warning:Please enter a request related to scientific research statistical calculation."))
+)
+## ==================== 统一入口 ====================
+output$quickgen_metrics <- renderUI({
+  stat_tab_panel(
+    menu      = i18n$t("Oneclick generation > AI assistance"),
+    tool      = i18n$t("AI generates descriptive statistics(metrics)"),
+    tool_ui   = "metrics_main_ui",
+    output_panels = tabPanel(
+      title = i18n$t("Metrics Assistant"),
+      value = "metrics_panel",
+      uiOutput("metrics_result_area")
+    )
+  )
+})
+## ==================== 右侧 Metrics 面板 ====================
+output$metrics_main_ui <- renderUI({
+  tagList(
+    useShinyjs(),
+    ui_metrics_progress,
+    ui_metrics_warn,
+    wellPanel(
+      i18n$t("Describe your analysis request:"),
+      returnTextAreaInput("metrics_prompt",
+                          label   = NULL,
+                          placeholder = i18n$t("e. g. 1. Single mean test for age (null mean=35) in insurance; 2. Chi-squared test between sex and smoker; 3. Linear regression of charges on bmi+age"),
+                          rows    = 4,
+                          value   = state_init("metrics_prompt", "")),
+      fluidRow(
+        column(6, uiOutput("ui_metrics_submit")),
+        column(6, uiOutput("metrics_loading"))
+      )
+    ),
+    
+    wellPanel(
+      i18n$t("Generated R code"),
+      uiOutput("metrics_r_code_block"),
+      fluidRow(
+        column(6, actionButton("metrics_run_code", i18n$t("Run code"), icon = icon("play"), class = "btn-success")),
+        column(6, actionButton("metrics_edit_code", i18n$t("Edit code"), icon = icon("edit"), class = "btn-default"))
+      )
+    ),
+    
+    help_and_report(
+      modal_title = i18n$t("AI generates descriptive statistics(metrics)"),
+      fun_name    = "quickgen_metrics",
+      help_file   = inclMD(file.path(getOption("radiant.path.quickgen"), "app/tools/help/quickgen_metrics.md")),
+      lic = "by-sa"
+    )
+  )
+})
+## ==================== 控件渲染 ====================
+output$ui_metrics_submit <- renderUI({
+  req(input$dataset)
+  actionButton("metrics_submit", i18n$t("Send"), icon = icon("magic"), class = "btn-primary")
+})
+output$metrics_loading <- renderUI({
+  if (isTRUE(r_values$metrics_loading))
+    tags$div(class = "progress",
+             tags$div(class = "progress-bar progress-bar-striped active",
+                      style = "width:100%",
+                      i18n$t("Calling metrics calculation model...")))
+})
+## ==================== reactiveValues ====================
+r_values <- reactiveValues(
+  metrics_r_code      = "",
+  metrics_result_type = "text",  # 仅保留text/plot/error
+  metrics_result_ready = FALSE,
+  metrics_loading     = FALSE
+)
+## ==================== 生成代码 ====================
+observeEvent(input$metrics_submit, {
+  if (is.empty(input$metrics_prompt))
+    return(showNotification(i18n$t("Please enter a statistical calculation request"), type = "error"))
+  
+  r_values$metrics_loading <- TRUE
+  shinyjs::show("metrics_progress_box")          # 显示右下角进度框
+  on.exit({
+    r_values$metrics_loading <- FALSE
+    shinyjs::hide("metrics_progress_box")        # 无论成功失败都隐藏
+  })
+  
+  res <- try(do.call(metrics_generate,
+                     list(prompt  = input$metrics_prompt,
+                          dataset = input$dataset,
+                          envir   = r_data)),
+             silent = TRUE)
+  if (inherits(res, "try-error")) {
+    showNotification(paste(i18n$t("Metrics API error:"), res), type = "error")
+    return()
+  }
+  
+  r_values$metrics_r_code      <- res$r_code
+  r_values$metrics_result_type <- res$type
+  r_values$metrics_result_ready <- FALSE
+  r_values$auto_run       <- res$auto_run
+  
+  if (res$type == "empty") {
+    shinyjs::show("metrics_warn_box")
+    shinyjs::delay(3000, shinyjs::hide("metrics_warn_box"))
+    return()
+  }
+  
+  if (isTRUE(r_values$auto_run))
+    shinyjs::click("metrics_run_code")
+})
+## ==================== 显示 R 代码 ====================
+output$metrics_r_code_block <- renderUI({
+  codes <- r_values$metrics_r_code
+  tags$pre(codes, style = "background:#f5f5f5; padding:10px; border-radius:4px;
+                           font-family:monospace; white-space:pre-wrap; min-height:100px;")
+})
+## ==================== 运行代码 ====================
+observeEvent(input$metrics_run_code, {
+  shinyjs::hide("metrics_progress_box")   
+  if (is.empty(r_values$metrics_r_code)) return()
+  
+  if (trimws(r_values$metrics_r_code) == "" || identical(r_values$metrics_result_type, "empty")) {
+    shinyjs::show("metrics_warn_box")
+    shinyjs::delay(3000, shinyjs::hide("metrics_warn_box"))
+    return()
+  }
+  
+  tryCatch({
+    # 执行代码并获取原始结果
+    result <- do.call(metrics_run_code,
+                      list(r_code = r_values$metrics_r_code, envir = r_data))
+    r_data$metrics_temp_result <- result
+    dataset_name <- input$dataset  # 获取当前数据集名称
+    
+    # 分支1：屏蔽图表输出
+    if (inherits(result, "gg") || inherits(result, "ggplot") || inherits(result, "lattice")) {
+      r_values$metrics_result_type <- "text"
+      output$metrics_result_text <- renderText(i18n$t("This tool only supports statistical metrics calculation, not chart generation"))
+    } 
+    # 分支2：所有统计结果转为结构化文本
+    else {
+      r_values$metrics_result_type <- "text"
+      # 调用格式化函数，生成示例风格的文本
+      formatted_text <- format_stat_text(result, dataset_name)
+      # 输出文本（保留换行和空格对齐）
+      output$metrics_result_text <- renderText(paste(formatted_text, collapse = "\n"))
+    }
+    
+    r_values$metrics_result_ready <- TRUE
+  }, error = function(e) {
+    r_values$metrics_result_type <- "error"
+    # 错误文本格式化
+    err_msg <- if (grepl("object .* not found", e$message)) {
+      paste0(i18n$t("Error: Target column does not exist - "), e$message)
+    } else if (grepl("non-numeric argument", e$message)) {
+      paste0(i18n$t("Error: Variable type mismatch (e.g., t-test requires numeric variables) - "), e$message)
+    } else {
+      paste0(i18n$t("Error: "), e$message)
+    }
+    output$metrics_result_error <- renderText(err_msg)
+    r_values$metrics_result_ready <- TRUE
+    showNotification(err_msg, type = "error", duration = NULL)
+  })
+}, ignoreInit = TRUE)
+## ======== 结果展示区（仅文本/错误输出）========
+output$metrics_result_area <- renderUI({
+  req(r_values$metrics_result_ready)
+  tagList(
+    # 所有结果均用文本框展示（含图表屏蔽提示、统计结果、错误）
+    conditionalPanel(
+      condition = "output.metrics_result_type == 'text' || output.metrics_result_type == 'error'",
+      verbatimTextOutput("metrics_result_text", placeholder = TRUE)
+    )
+  )
+})
+output$metrics_result_type <- reactive({
+  r_values$metrics_result_type 
+})
+outputOptions(output, "metrics_result_type", suspendWhenHidden = FALSE)
+## ==================== 编辑代码模态框 ====================
+observeEvent(input$metrics_edit_code, {
+  showModal(
+    modalDialog(
+      title = i18n$t("Edit R Code"),
+      size  = "l",
+      footer = tagList(
+        actionButton("metrics_save_code", i18n$t("Save Changes"), class = "btn-primary"),
+        modalButton(i18n$t("Cancel"))
+      ),
+      aceEditor(
+        "metrics_code_editor",
+        mode = "r",
+        theme = getOption("radiant.ace_theme", "tomorrow"),
+        wordWrap = TRUE,
+        value = r_values$metrics_r_code,
+        placeholder = i18n$t("Edit the generated R code here..."),
+        vimKeyBinding = getOption("radiant.ace_vim.keys", FALSE),
+        tabSize = getOption("radiant.ace_tabSize", 2),
+        useSoftTabs = getOption("radiant.ace_useSoftTabs", TRUE),
+        showInvisibles = getOption("radiant.ace_showInvisibles", FALSE),
+        autoScrollEditorIntoView = TRUE,
+        minLines = 15,
+        maxLines = 30
+      )
+    )
+  )
+})
+## ==================== 保存代码 ====================
+observeEvent(input$metrics_save_code, {
+  r_values$metrics_r_code <- input$metrics_code_editor
+  r_values$auto_run <- FALSE
+  removeModal()
+})
+## ==================== 报告 / 截图 ====================
+metrics_report <- function() {}
+observeEvent(input$metrics_report, metrics_report())
+observeEvent(input$metrics_screenshot, radiant_screenshot_modal("modal_metrics_screenshot"))
+observeEvent(input$modal_metrics_screenshot, { metrics_report(); removeModal() })
diff --git a/radiant.quickgen/inst/app/tools/help/quickgen_ai.md b/radiant.quickgen/inst/app/tools/help/quickgen_ai.md
deleted file mode 100644
index 983dea5822d7e7d5fed161d45abb9016e31d809a..0000000000000000000000000000000000000000
--- a/radiant.quickgen/inst/app/tools/help/quickgen_ai.md
+++ /dev/null
@@ -1,27 +0,0 @@
-> 大模型生成描述性统计
-
-## 使用方法
-
-以下是 `大模型生成描述性统计`的使用方法。
-
-1.`数据对象`必须要有，且必须和数据集中的名字一致（大小写也一致）
-
-2.`图像类型`必须要有，比如分布图、散点图等。可以要求模型返回多张图表，需向模型明确。
-
-3.`生成代码`如果有误，或者想要修改，可以点击`编辑`按钮对R代码进行修改，保存后点击`运行`按钮即可。
-## 示例
-
-**1. 散点图**  
-请用diamonds画一个散点图，X轴是carat，Y轴是price，用color来区分颜色，并加上theme_bw()。  
-**2. 箱线图**  
-请用diamonds画箱线图，把price按cut分组，看看不同切工的价格分布。  
-**3. 直方图**  
-请用diamonds画carat的直方图，分面按clarity排布，bin宽度取0.1。  
-**4. 柱状图**  
-请用diamonds统计各color等级的数量，画一个柱状图，颜色按实际颜色填充。  
-**5. 密度图**  
-请用diamonds画出0.5~2克拉范围内，不同color的carat密度曲线，要求半透明重叠。  
-**6. 分组均值表**  
-请用diamonds按cut分组，计算每组price与carat的平均值、标准差，输出成表格。  
-**7. 价格对数-克拉线性拟合图**  
-请用diamonds画log(price)和carat的散点图，并加上回归直线，颜色按clarity区分，用theme_minimal()。  
\ No newline at end of file
diff --git a/radiant.quickgen/inst/app/tools/help/quickgen_chart.md b/radiant.quickgen/inst/app/tools/help/quickgen_chart.md
new file mode 100644
index 0000000000000000000000000000000000000000..ca5a6eef99bed1bf6bbf71c33e1b51236a9a9904
--- /dev/null
+++ b/radiant.quickgen/inst/app/tools/help/quickgen_chart.md
@@ -0,0 +1,52 @@
+> 大模型生成描述性统计（图表）
+
+## 使用方法
+
+以下是 `大模型生成描述性统计`的使用方法。
+
+1.`数据对象`必须要有，且必须和数据集中的名字一致（大小写也一致）
+
+2.`图像类型`必须要有，比如分布图、散点图等。可以要求模型返回多张图表，需向模型明确。
+
+3.`生成代码`如果有误，或者想要修改，可以点击`编辑`按钮对R代码进行修改，保存后点击`运行`按钮即可。
+## 示例
+
+**1. 散点图**
+
+请用该数据集画一个散点图，X 轴是 bmi（身体质量指数），Y 轴是 charges（年度医疗费用），用 smoker（吸烟状态）来区分颜色。
+
+**2. 箱线图**
+
+请用该数据集画箱线图，把 charges 按 smoker 分组，看看吸烟 / 不吸烟人群的医疗费用分布。
+
+**3. 直方图**
+
+请用该数据集画 age（年龄）的直方图，分面按 sex（性别）排布，bin 宽度取 2（年龄区间）。
+
+**4. 柱状图**
+
+请用该数据集统计各 region（居住区域）的样本数量，画一个柱状图，颜色按 region 实际类别填充。
+
+**5. 密度图**
+
+请用该数据集画出 bmi 在 18~35 范围内，不同 sex 的 bmi 密度曲线，要求半透明重叠展示。
+
+**6. 分组均值表**
+
+请用该数据集按 sex 分组，计算每组 age、bmi、charges 的平均值、标准差，输出成结构化表格。
+
+**7. 费用 - 年龄线性拟合图**
+
+请用该数据集画 charges 和 age 的散点图，并加上回归直线，颜色按 smoker 区分。
+
+**8. 交叉频数表**
+
+请用该数据集统计 sex 与 smoker 的交叉频数（即 “男性吸烟 / 不吸烟人数、女性吸烟 / 不吸烟人数”），输出二维汇总表格。
+
+**9. 儿童数量分布柱状图**
+
+请用该数据集统计 children（受抚养者数量）的不同取值对应的样本数，画一个柱状图展示各数量的分布。
+
+**10. 区域 - 费用箱线图**
+
+请用该数据集画箱线图，把 charges 按 region 分组，对比不同区域的医疗费用差异，并用不同颜色标注。
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diff --git a/radiant.quickgen/inst/app/tools/help/quickgen_chat.md b/radiant.quickgen/inst/app/tools/help/quickgen_chat.md
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..12c42ea4f947579b45ba227804fcd65d275b7eee 100644
--- a/radiant.quickgen/inst/app/tools/help/quickgen_chat.md
+++ b/radiant.quickgen/inst/app/tools/help/quickgen_chat.md
@@ -0,0 +1,44 @@
+> 大模型对话引导助手
+
+### 1. 界面概述
+
+本工具是 **“一键生成” 模块下的 R 语言科研辅助助手 **，专为数据集的科研分析设计，可自动结合数据集字段信息，为你提供字段解读、分析方法建议、统计结果解读等科研支持。
+
+### 2. 使用步骤
+
+1. **确认数据集**：进入工具后，，字段信息会自动加载至智能体；
+
+2. 发起对话
+   - 方式 1：点击预设问题按钮，快速发起提问；
+   - 方式 2：在底部输入框中自定义科研问题，点击右侧发送按钮提交；
+
+3. **获取回复**：AI 会结合传入的字段信息，生成科研场景下的专业回复；
+
+4. **重置对话**：若需切换分析主题，点击 “开启新对话” 清空历史即可。
+
+### 3. 常见操作示例
+
+#### 示例 1：字段解读（预设问题 1）
+
+- 操作：点击 “这个数据集中的字段是什么意思？有什么科研分析用途？” 按钮
+- 效果：AI 会解释`insurance`中`age`（年龄）、`smoker`（吸烟状态）、`charges`（医疗费用）等字段的含义，并说明各字段的科研分析场景（如`smoker`可用于分析吸烟对医疗费用的影响）。
+
+#### 示例 2：分析方法建议（预设问题 2）
+
+- 操作：点击 “基于当前数据集的字段信息，我该选择什么科研分析方法？” 按钮
+- 效果：AI 会根据`insurance`的字段类型（如分类变量`sex`、数值变量`charges`），推荐适配的统计方法（如箱线图分析分组费用差异、线性回归分析年龄对费用的影响）。
+
+#### 示例 3：统计结果解读（预设问题 3）
+
+- 操作：点击 “我得到的科研结果（比如模型参数、统计指标）该怎么解读？” 按钮
+- 效果：若你提供具体结果（如 “`smoker`对`charges`的回归系数是 20000”），AI 会解读该指标的科研意义（如 “吸烟人群的年度医疗费用平均比非吸烟人群高 20000 单位”）。
+
+#### 示例 4：自定义科研问题
+
+- 输入：“帮我说明用`insurance`数据集中`bmi`和`charges`做散点图的科研意义是什么？”
+- 效果：AI 会结合两个字段的含义，解释散点图可用于观察身体质量指数与医疗费用的相关性，为后续回归分析提供可视化依据。
+
+### 4. 注意事项
+
+1. 字段信息会**自动传递给 AI**，无需手动输入数据集字段内容；
+2. “开启新对话” 会清空当前历史，若需保留对话记录，请勿点击该按钮。
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diff --git a/radiant.quickgen/inst/app/tools/help/quickgen_metrics.md b/radiant.quickgen/inst/app/tools/help/quickgen_metrics.md
new file mode 100644
index 0000000000000000000000000000000000000000..544f2ae3b0d41b263f80359e4a4b3c2e254b6744
--- /dev/null
+++ b/radiant.quickgen/inst/app/tools/help/quickgen_metrics.md
@@ -0,0 +1 @@
+xxxxxx
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