feat(ssa): Implement dual-channel architecture Phase 1-3 (QPER + LLM Agent pipeline)

Completed:
- Phase 1: DB schema (execution_mode + ssa_agent_executions), ModeToggle component, Session PATCH API
- Phase 2: AgentPlannerService + AgentCoderService (streaming) + CodeRunnerService + R Docker /execute-code endpoint
- Phase 3: AgentCodePanel (3-step confirmation UI), SSE event handling (7 agent events), streaming code display
- Three-step confirmation pipeline: plan -> user confirm -> stream code -> user confirm -> execute R code -> results
- R Docker sandbox /execute-code endpoint with 120s timeout + block_helpers preloaded
- E2E dual-channel test script (8 tests)
- Updated R engine architecture doc (v1.5) and SSA module status doc (v4.0)

Technical details:
- AgentCoderService uses LLM streaming (chatStream) for real-time code generation feedback
- ReviewerAgent temporarily disabled, prioritizing Plan -> Code -> Execute flow
- CodeRunnerService wraps user code with auto data loading (df variable injection)
- Frontend handles agent_planning, agent_plan_ready, code_generating, code_generated, code_executing, code_result events
- ask_user mechanism used for plan and code confirmation steps

Files: 24 files (4 new services, 2 new components, 1 migration, 1 E2E test, 16 modified)
Made-with: Cursor

r-statistics-service/plumber.R

@@ -167,6 +167,123 @@ function(req) {
   })
 }
 
+#* Agent 通道：执行任意 R 代码（沙箱模式）
+#* @post /api/v1/execute-code
+#* @serializer unboxedJSON
+function(req) {
+  tryCatch({
+    input <- jsonlite::fromJSON(req$postBody, simplifyVector = FALSE)
+    
+    code <- input$code
+    session_id <- input$session_id
+    timeout_sec <- as.numeric(input$timeout %||% 120)
+    
+    if (is.null(code) || nchar(trimws(code)) == 0) {
+      return(list(
+        status = "error",
+        error_code = "E400",
+        message = "Missing 'code' parameter",
+        user_hint = "R 代码不能为空"
+      ))
+    }
+    
+    # 安全限制：最长 120 秒
+    if (timeout_sec > 120) timeout_sec <- 120
+    
+    message(glue::glue("[ExecuteCode] session={session_id}, code_length={nchar(code)}, timeout={timeout_sec}s"))
+    
+    # 在隔离环境中执行，预加载 block_helpers 和 data_loader
+    sandbox_env <- new.env(parent = globalenv())
+    
+    # 如果有 session_id，尝试预设数据路径变量
+    if (!is.null(session_id) && nchar(session_id) > 0) {
+      sandbox_env$SESSION_ID <- session_id
+    }
+    
+    start_time <- proc.time()
+    
+    # 捕获输出和结果
+    output_capture <- tryCatch(
+      withTimeout(
+        {
+          # 捕获打印输出
+          captured_output <- utils::capture.output({
+            result <- eval(parse(text = code), envir = sandbox_env)
+          })
+          
+          list(
+            result = result,
+            output = captured_output,
+            error = NULL
+          )
+        },
+        timeout = timeout_sec,
+        onTimeout = "error"
+      ),
+      error = function(e) {
+        list(
+          result = NULL,
+          output = NULL,
+          error = e$message
+        )
+      }
+    )
+    
+    elapsed_ms <- round((proc.time() - start_time)["elapsed"] * 1000)
+    
+    if (!is.null(output_capture$error)) {
+      message(glue::glue("[ExecuteCode] ERROR after {elapsed_ms}ms: {output_capture$error}"))
+      return(list(
+        status = "error",
+        error_code = "E_EXEC",
+        message = output_capture$error,
+        user_hint = paste0("R 代码执行出错 (", elapsed_ms, "ms): ", output_capture$error),
+        duration_ms = elapsed_ms
+      ))
+    }
+    
+    message(glue::glue("[ExecuteCode] SUCCESS in {elapsed_ms}ms"))
+    
+    # 将结果标准化
+    final_result <- output_capture$result
+    
+    # 如果结果是 list 且包含 report_blocks，直接返回
+    if (is.list(final_result) && !is.null(final_result$report_blocks)) {
+      return(list(
+        status = "success",
+        result = final_result,
+        console_output = output_capture$output,
+        duration_ms = elapsed_ms
+      ))
+    }
+    
+    # 否则包装为通用结果
+    return(list(
+      status = "success",
+      result = list(
+        data = final_result,
+        report_blocks = list()
+      ),
+      console_output = output_capture$output,
+      duration_ms = elapsed_ms
+    ))
+    
+  }, error = function(e) {
+    message(glue::glue("[ExecuteCode] FATAL ERROR: {e$message}"))
+    return(map_r_error(e$message))
+  })
+}
+
+#' 超时执行包装器
+#' @param expr 表达式
+#' @param timeout 超时秒数
+#' @param onTimeout 超时行为
+withTimeout <- function(expr, timeout = 120, onTimeout = "error") {
+  setTimeLimit(cpu = timeout, elapsed = timeout, transient = TRUE)
+  on.exit(setTimeLimit(cpu = Inf, elapsed = Inf, transient = FALSE))
+  eval(expr, envir = parent.frame())
+}
+
 #* 执行统计工具
 #* @post /api/v1/skills/<tool_code>
 #* @param tool_code:str 工具代码（如 ST_T_TEST_IND）