Fix: table parser metadata (#15127)

### What problem does this PR solve?

This PR improves the table upload flow for CSV/Excel files by allowing
table column role configuration at upload time.

Previously, users had to:
1. Upload and parse a table file.
2. Open parser settings and manually set table column roles.
3. Re-parse the file for the roles to take effect.

This was inefficient and required an unnecessary second parse.

With this change:
1. When the knowledge base uses table parsing, the upload dialog
extracts CSV/Excel headers client-side.
2. Users can choose Auto mode or Manual mode.
3. In Manual mode, users can assign per-column roles before upload.
4. The selected parser config is sent with the upload request and
applied server-side during document creation.

Result: configured table column roles are applied from the first parse.

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

Co-authored-by: Ahmad Intisar <ahmadintisar@Ahmads-MacBook-M4-Pro.local>

web/src/utils/table-column-extract.ts

@@ -0,0 +1,76 @@
+import Papa from 'papaparse';
+import * as XLSX from 'xlsx';
+
+/**
+ * Extracts column headers from a CSV or Excel file.
+ * Returns an empty array if the file type is not supported or headers cannot be read.
+ */
+export async function extractTableColumns(file: File): Promise<string[]> {
+  const ext = file.name.split('.').pop()?.toLowerCase() ?? '';
+
+  if (ext === 'csv') {
+    return extractCsvColumns(file);
+  }
+
+  if (['xlsx', 'xls'].includes(ext)) {
+    return extractExcelColumns(file);
+  }
+
+  return [];
+}
+
+function extractCsvColumns(file: File): Promise<string[]> {
+  return new Promise((resolve) => {
+    Papa.parse(file, {
+      preview: 1, // Only read the first row (header)
+      header: true,
+      skipEmptyLines: true,
+      complete(results) {
+        const fields = results.meta?.fields ?? [];
+        resolve(fields.filter((f) => f.trim().length > 0));
+      },
+      error() {
+        resolve([]);
+      },
+    });
+  });
+}
+
+function extractExcelColumns(file: File): Promise<string[]> {
+  return new Promise((resolve) => {
+    const reader = new FileReader();
+    reader.onload = (e) => {
+      try {
+        const data = new Uint8Array(e.target?.result as ArrayBuffer);
+        const workbook = XLSX.read(data, { type: 'array', sheetRows: 1 });
+        const firstSheetName = workbook.SheetNames[0];
+        if (!firstSheetName) {
+          resolve([]);
+          return;
+        }
+        const sheet = workbook.Sheets[firstSheetName];
+        const rows = XLSX.utils.sheet_to_json<string[]>(sheet, { header: 1 });
+        if (rows.length > 0) {
+          const headers = rows[0]
+            .map((h) => String(h ?? '').trim())
+            .filter((h) => h.length > 0);
+          resolve(headers);
+        } else {
+          resolve([]);
+        }
+      } catch {
+        resolve([]);
+      }
+    };
+    reader.onerror = () => resolve([]);
+    reader.readAsArrayBuffer(file);
+  });
+}
+
+/**
+ * Check if a file is a table file (CSV or Excel).
+ */
+export function isTableFile(file: File): boolean {
+  const ext = file.name.split('.').pop()?.toLowerCase() ?? '';
+  return ['csv', 'xlsx', 'xls'].includes(ext);
+}