GML-2086 add Excel and CSV extraction support with UI warning

common/requirements.txt

@@ -105,6 +105,8 @@ nest-asyncio==1.6.0
 nltk==3.9.1
 numpy>=1, <2
 openai==1.92.2
+openpyxl>=3.1.0
+xlrd>=2.0.1
 ordered-set==4.1.0
 orjson==3.10.18
 packaging==24.2

common/utils/text_extractors.py

@@ -290,7 +290,7 @@ async def process_with_semaphore(file_path):
                     'error': result.get('error', 'Unknown error')
                 })
 
-        logger.info(f"Prepared {len(processed_files_info)} files ({len(jsonl_files_copied)} JSONL copied, {len(files_to_process)} converted), {total_docs} total documents")
+        logger.info(f"Processed {len(processed_files_info)} files, extracted {total_docs} total documents")
         logger.info(f"Created {len([f for f in processed_files_info if f.get('status') == 'success'])} JSONL files in {temp_folder}")
 
         return {
@@ -613,9 +613,22 @@ def extract_text_from_file(file_path, graphname=None):
         if extension in ['.txt', '.md']:
             with open(file_path, 'r', encoding='utf-8') as f:
                 return f.read().strip()
-        elif extension in ['.html', '.htm', '.csv']:
+        elif extension in ['.html', '.htm']:
             with open(file_path, 'r', encoding='utf-8') as f:
                 return f.read().strip()
+        elif extension == '.csv':
+            raw = file_path.read_bytes()
+            # utf-8-sig handles UTF-8 with BOM (common Excel CSV export)
+            try:
+                return raw.decode('utf-8-sig').strip()
+            except UnicodeDecodeError:
+                pass
+            # Fall back to chardet detection
+            import chardet
+            detected = chardet.detect(raw)
+            encoding = detected.get('encoding') if detected.get('confidence', 0) >= 0.5 else None
+            # latin-1 as final fallback — never raises DecodeError
+            return raw.decode(encoding or 'latin-1').strip()
         elif extension == '.json':
             with open(file_path, 'r', encoding='utf-8') as f:
                 data = json.load(f)
@@ -624,6 +637,32 @@ def extract_text_from_file(file_path, graphname=None):
             import docx
             doc = docx.Document(file_path)
             return "\n".join(p.text for p in doc.paragraphs if p.text.strip())
+        elif extension in ['.xlsx', '.xls']:
+            import pandas as pd
+            engine = 'openpyxl' if extension == '.xlsx' else 'xlrd'
+            try:
+                xl = pd.ExcelFile(file_path, engine=engine)
+            except Exception:
+                xl = pd.ExcelFile(file_path)
+            sheet_texts = []
+            for sheet_name in xl.sheet_names:
+                # Always read with header=None so no data row is silently
+                # consumed as column names for headerless spreadsheets.
+                df = xl.parse(sheet_name, header=None)
+                if df.empty:
+                    continue
+                df = df.fillna('')
+                # Detect header row: first row is all non-empty strings with
+                # no purely numeric values → treat as column names.
+                first_row = df.iloc[0]
+                if all(isinstance(v, str) and v.strip() for v in first_row):
+                    df.columns = first_row.tolist()
+                    df = df.iloc[1:].reset_index(drop=True)
+                else:
+                    df.columns = [f"Column {i + 1}" for i in range(len(df.columns))]
+                sheet_md = df.to_markdown(index=False)
+                sheet_texts.append(f"## Sheet: {sheet_name}\n\n{sheet_md}")
+            return "\n\n".join(sheet_texts) if sheet_texts else "[Excel file is empty or contains no data]"
         elif extension == '.xml':
             import xml.etree.ElementTree as ET
             tree = ET.parse(file_path)
@@ -663,7 +702,7 @@ def get_doc_type_from_extension(extension):
 
 def get_supported_extensions():
     """Get list of supported file extensions."""
-    return {'.txt', '.md', '.html', '.htm', '.csv', '.json', '.pdf', '.docx', '.xml', '.jpeg', '.jpg', '.png', '.gif'}
+    return {'.txt', '.md', '.html', '.htm', '.csv', '.json', '.pdf', '.docx', '.doc', '.xml', '.jpeg', '.jpg', '.png', '.gif', '.xlsx', '.xls', '.jsonl'}
 
 def is_supported_file(file_path):
     """Check if a file is supported for text extraction."""

graphrag-ui/src/pages/setup/IngestGraph.tsx

@@ -1006,6 +1006,32 @@ const IngestGraph: React.FC<IngestGraphProps> = ({ isModal = false }) => {
                       ? `Upload destination: uploads/${ingestGraphName}/`
                       : ""}
                   </p>
+                  {selectedFiles && (() => {
+                    const SUPPORTED_EXTENSIONS = new Set([".txt", ".md", ".pdf", ".docx", ".doc", ".html", ".htm", ".json", ".csv", ".xlsx", ".xls", ".xml", ".jpeg", ".jpg", ".png", ".gif", ".jsonl"]);
+                    const files = Array.from(selectedFiles);
+                    const unsupported = files.filter((f) => !SUPPORTED_EXTENSIONS.has(f.name.slice(f.name.lastIndexOf(".")).toLowerCase()));
+                    const hasCsvExcel = files.some((f) => [".csv", ".xlsx", ".xls"].includes(f.name.slice(f.name.lastIndexOf(".")).toLowerCase()));
+                    return (
+                      <>
+                        {unsupported.length > 0 && (
+                          <div className="flex items-start gap-2 mt-2 p-2 rounded-md bg-red-50 dark:bg-red-900/20 border border-red-200 dark:border-red-700">
+                            <span className="text-red-500 mt-0.5 shrink-0">⚠️</span>
+                            <p className="text-xs text-red-700 dark:text-red-300">
+                              Unsupported file type{unsupported.length > 1 ? "s" : ""}: <strong>{unsupported.map((f) => f.name).join(", ")}</strong>. These files will be skipped during ingestion.
+                            </p>
+                          </div>
+                        )}
+                        {hasCsvExcel && (
+                          <div className="flex items-start gap-2 mt-2 p-2 rounded-md bg-amber-50 dark:bg-amber-900/20 border border-amber-200 dark:border-amber-700">
+                            <span className="text-amber-500 mt-0.5 shrink-0">ℹ️</span>
+                            <p className="text-xs text-amber-700 dark:text-amber-300">
+                              CSV and Excel files will be treated as unstructured text documents.
+                            </p>
+                          </div>
+                        )}
+                      </>
+                    );
+                  })()}
                 </div>
 
                 <div className="flex gap-2">