diff --git a/cucyuqing/cmd/risk-analyze.py b/cucyuqing/cmd/risk-analyze.py
index 24c314c..14d16a6 100644
--- a/cucyuqing/cmd/risk-analyze.py
+++ b/cucyuqing/cmd/risk-analyze.py
@@ -1,6 +1,7 @@
 from dataclasses import dataclass
 from os import system
 from typing import Iterable, Required
+from typing_extensions import Doc
 import openai
 import asyncio
 from openai.types.chat import ChatCompletionMessageParam
@@ -11,7 +12,7 @@ from cucyuqing.utils import print
 from cucyuqing.config import OPENAI_RISK_LLM_API_KEY, OPENAI_RISK_LLM_BASE_URL
 from cucyuqing.pg import pool, get_cur
 from cucyuqing.mysql import mysql
-from cucyuqing.dbscan import run_dbscan
+from cucyuqing.dbscan import Document, run_dbscan
 
 
 async def main():
@@ -26,11 +27,11 @@ async def main():
     dbscan_result = await run_dbscan()
     docs = [cluster[0] for cluster in dbscan_result.clusters]
 
-    analyze_result = await batch_risk_analyze([doc.title for doc in docs], risk_types)
-    for result, doc in zip(analyze_result, docs):
-        if "是" not in result:
+    analyze_result = await batch_risk_analyze(docs, risk_types)
+    for task in analyze_result:
+        if "是" not in task.response:
             continue
-        print(f"风险: {result} 标题: {doc.title}")
+        print(f"风险: {task.risk_type.name} 标题: {task.doc.title}")
 
 
 @dataclass
@@ -41,7 +42,7 @@ class RiskType:
 
 @dataclass
 class Task:
-    text: str
+    doc: Document
     risk_type: RiskType
     response: str = ""
 
@@ -61,16 +62,16 @@ async def get_risk_type_prompt() -> list[RiskType]:
 
 
 async def batch_risk_analyze(
-    texts: list,
+    docs: list[Document],
     risk_types: list[RiskType],
     model: str = "gpt-4o-mini",
     threads: int = 10,
-) -> list[str]:
+) -> list[Task]:
     """文本风险分析（并行批批处理）"""
 
-    # 从 text, risk_types 两个列表交叉生成任务列表
+    # 从 docs, risk_types 两个列表交叉生成任务列表
     tasks: list[Task] = [
-        Task(text=text, risk_type=rt) for text in texts for rt in risk_types
+        Task(doc=doc, risk_type=rt) for doc in docs for rt in risk_types
     ]
     bar = tqdm.tqdm(total=len(tasks))
     queue = asyncio.Queue()
@@ -96,7 +97,7 @@ async def batch_risk_analyze(
         await queue.put(None)
     await asyncio.gather(*workers)
 
-    return [task.response for task in tasks]
+    return tasks
 
 
 async def risk_analyze(task: Task, model: str) -> str:
@@ -105,7 +106,7 @@ async def risk_analyze(task: Task, model: str) -> str:
         api_key=OPENAI_RISK_LLM_API_KEY, base_url=OPENAI_RISK_LLM_BASE_URL
     )
     hash = hashlib.md5(
-        f"{model}|{task.text}|{task.risk_type.prompt}".encode()
+        f"{model}|{task.doc.get_text_for_llm()}|{task.risk_type.prompt}".encode()
     ).hexdigest()
 
     # 查询缓存
@@ -119,7 +120,7 @@ async def risk_analyze(task: Task, model: str) -> str:
 
     messages: Iterable[ChatCompletionMessageParam] = [
         {"role": "system", "content": task.risk_type.prompt},
-        {"role": "user", "content": task.text},
+        {"role": "user", "content": task.doc.get_text_for_llm()},
     ]
     resp = await llm.chat.completions.create(
         messages=messages,
diff --git a/cucyuqing/dbscan.py b/cucyuqing/dbscan.py
index a02cf34..0de484f 100644
--- a/cucyuqing/dbscan.py
+++ b/cucyuqing/dbscan.py
@@ -15,6 +15,14 @@ class Document:
     content: str
     similarity: float = 0.0
 
+    def get_text_for_llm(self) -> str:
+        """只使用标题进行风险分析
+        
+        对于空标题，在入库时已经处理过。
+        如果入库时标题为空，则使用content的前20个字符或第一句中文作为标题。
+        """
+        return self.title 
+
 @dataclass
 class DBScanResult:
     noise: list[Document]