diff --git a/deepsearcher/agent/deep_search.py b/deepsearcher/agent/deep_search.py
index 31bccdf..b3b21e7 100644
--- a/deepsearcher/agent/deep_search.py
+++ b/deepsearcher/agent/deep_search.py
@@ -91,7 +91,7 @@ REFLECT_PROMPT = """
 
 SUMMARY_PROMPT = """
 你是一个内容分析专家
-请你综合已经提出的问题和检索到的信息，以原问题为中心，生成详细准确、层次分明、尽可能长的回答。
+请你综合已经提出的问题和检索到的信息，以原问题为中心，生成详细准确、层次分明（多级标题，从一级开始）、尽可能长的回答。
 如果检索到的信息不足以回答问题，你应该使用你的知识来进行扩展补充。
 注意，不要逐个回答问题，而是应该综合所有问题和信息，生成一个完整的回答。
 同时，你应该根据提供的信息生成文内引用"[^index]"(markdown文内引用)。
@@ -149,7 +149,7 @@ class DeepSearch(BaseAgent):
             max_iter: The maximum number of iterations for the search process.
             route_collection: Whether to use a collection router for search.
             text_window_splitter: Whether to use text_window splitter.
-            enable_web_search: Whether to enable web search functionality.
+            web_search: Whether to enable web search functionality.
             **kwargs: Additional keyword arguments for customization.
         """
         self.llm = llm
diff --git a/main.py b/main.py
index 4b34478..4c83a16 100644
--- a/main.py
+++ b/main.py
@@ -10,10 +10,10 @@ import os
 import asyncio
 import json
 import queue
-from typing import AsyncGenerator
+from collections.abc import AsyncGenerator
 
 from deepsearcher.configuration import Configuration, init_config
-from deepsearcher.offline_loading import load_from_local_files, load_from_website
+from deepsearcher.offline_loading import load_from_local_files
 from deepsearcher.online_query import query
 from deepsearcher.utils.message_stream import get_message_stream
 
@@ -146,63 +146,6 @@ def load_files(
         raise HTTPException(status_code=500, detail=str(e))
 
 
-@app.post("/load-website/")
-def load_website(
-    urls: str | list[str] = Body(
-        ...,
-        description="A list of URLs of websites to be loaded.",
-        examples=["https://milvus.io/docs/overview.md"],
-    ),
-    collection_name: str = Body(
-        None,
-        description="Optional name for the collection.",
-        examples=["my_collection"],
-    ),
-    collection_description: str = Body(
-        None,
-        description="Optional description for the collection.",
-        examples=["This is a test collection."],
-    ),
-    batch_size: int = Body(
-        None,
-        description="Optional batch size for the collection.",
-        examples=[256],
-    ),
-    force_rebuild: bool = Body(
-        False,
-        description="Whether to force rebuild the collection if it already exists.",
-        examples=[False],
-    ),
-):
-    """
-    Load website content into the vector database.
-
-    Args:
-        urls (Union[str, List[str]]): URLs of websites to load.
-        collection_name (str, optional): Name for the collection. Defaults to None.
-        collection_description (str, optional): Description for the collection. Defaults to None.
-        batch_size (int, optional): Batch size for processing. Defaults to None.
-        force_rebuild (bool, optional): Whether to force rebuild the collection. Defaults to False.
-
-    Returns:
-        dict: A dictionary containing a success message.
-
-    Raises:
-        HTTPException: If loading website content fails.
-    """
-    try:
-        load_from_website(
-            urls=urls,
-            collection_name=collection_name,
-            collection_description=collection_description,
-            batch_size=batch_size if batch_size is not None else 8,
-            force_rebuild=force_rebuild,
-        )
-        return {"message": "成功加载"}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-
 @app.get("/query-stream/")
 async def perform_query_stream(
     original_query: str = Query(