diff --git a/config.py b/config.py
index c4fbe78..5be453c 100644
--- a/config.py
+++ b/config.py
@@ -33,6 +33,12 @@ DOC_CONFIG = {
     "max_summary_length": 500,  # 摘要最大长度
 }
 
+# ==================== 索引模式 ====================
+# use_llm_index: 是否使用LLM增强索引
+# True - 使用LLM分析文档，提取关键词、摘要等（需要LLM服务，速度慢）
+# False - 使用简单分词和词频统计（速度快，无需LLM）
+USE_LLM_INDEX = False  # 默认关闭LLM索引
+
 # ==================== 索引配置 ====================
 INDEX_CONFIG = {
     # BM25参数
diff --git a/services.py b/services.py
index 53b6ddd..e451090 100644
--- a/services.py
+++ b/services.py
@@ -12,7 +12,7 @@ from collections import Counter
 from openai import OpenAI
 from flask import current_app
 
-from config import LLM_CONFIG, DOC_CONFIG, INDEX_CONFIG
+from config import LLM_CONFIG, DOC_CONFIG, INDEX_CONFIG, USE_LLM_INDEX
 from models import db, Document, DocumentChunk, InvertedIndex, IndexStats, QueryLog
 
 
@@ -252,15 +252,25 @@ class DocumentIndexer:
             doc.content = content
             doc.word_count = len(content)
             
-            # 使用LLM分析整个文档
-            print(f"  正在分析文档: {doc.filename}")
-            analysis = self.llm.analyze_document(content, doc.title)
+            # 检查是否使用LLM增强索引
+            use_llm = USE_LLM_INDEX
             
-            doc.summary = analysis.get('summary', '')
-            doc.set_keywords(analysis.get('keywords', []))
-            doc.set_topics(analysis.get('topics', []))
-            doc.category = analysis.get('category', '')
-            doc.set_entities(analysis.get('entities', {}))
+            if use_llm:
+                # 使用LLM分析整个文档
+                print(f"  正在使用LLM分析文档: {doc.filename}")
+                analysis = self.llm.analyze_document(content, doc.title)
+                
+                doc.summary = analysis.get('summary', '')
+                doc.set_keywords(analysis.get('keywords', []))
+                doc.set_topics(analysis.get('topics', []))
+                doc.category = analysis.get('category', '')
+                doc.set_entities(analysis.get('entities', {}))
+            else:
+                # 简单模式：不使用LLM
+                print(f"  正在索引文档(简单模式): {doc.filename}")
+                # 从内容中提取简单关键词
+                simple_keywords = self._extract_simple_keywords(content)
+                doc.set_keywords(simple_keywords[:20])
             
             # 分块处理
             chunks = self._split_content(content)
@@ -279,10 +289,14 @@ class DocumentIndexer:
                     end_char=len(chunk_content)
                 )
                 
-                # LLM分析分块
-                chunk_analysis = self.llm.analyze_chunk(chunk_content)
-                chunk.summary = chunk_analysis.get('summary', '')
-                chunk.set_keywords(chunk_analysis.get('keywords', []))
+                if use_llm:
+                    # LLM分析分块
+                    chunk_analysis = self.llm.analyze_chunk(chunk_content)
+                    chunk.summary = chunk_analysis.get('summary', '')
+                    chunk.set_keywords(chunk_analysis.get('keywords', []))
+                else:
+                    # 简单模式：从分块提取关键词
+                    chunk.set_keywords(self._extract_simple_keywords(chunk_content)[:10])
                 
                 # 计算词频
                 term_freq = self._compute_term_freq(chunk_content)
@@ -313,6 +327,25 @@ class DocumentIndexer:
             print(f"  ✗ 索引失败: {e}")
             return False
     
+    def _extract_simple_keywords(self, content):
+        """简单提取关键词（不使用LLM）"""
+        import re
+        from collections import Counter
+        
+        # 提取中文词组（2-4字）
+        chinese_words = re.findall(r'[\u4e00-\u9fff]{2,4}', content)
+        
+        # 过滤常见无意义词
+        stopwords = {'的', '是', '在', '了', '和', '与', '或', '等', '这', '那', 
+                     '有', '为', '对', '也', '被', '把', '给', '向', '从', '到',
+                     '一个', '一些', '这种', '那种', '什么', '怎么', '如何', '为什么'}
+        
+        # 统计词频
+        word_freq = Counter(w for w in chinese_words if w not in stopwords)
+        
+        # 返回高频词
+        return [w for w, _ in word_freq.most_common(30)]
+    
     def _read_document(self, filepath):
         """读取文档内容"""
         ext = os.path.splitext(filepath)[1].lower()