diff --git a/pilot/server/knowledge/service.py b/pilot/server/knowledge/service.py
index cde2b7bb7..81e1dbdcc 100644
--- a/pilot/server/knowledge/service.py
+++ b/pilot/server/knowledge/service.py
@@ -429,14 +429,15 @@ class KnowledgeService:
         from llama_index import PromptHelper
         from llama_index.prompts.default_prompt_selectors import DEFAULT_TREE_SUMMARIZE_PROMPT_SEL
         texts = [doc.page_content for doc in chunk_docs]
-        prompt_helper = PromptHelper()
+        prompt_helper = PromptHelper(context_window=5000)
         texts = prompt_helper.repack(prompt=DEFAULT_TREE_SUMMARIZE_PROMPT_SEL, text_chunks=texts)
+        logger.info(
+            f"async_document_summary, doc:{doc.doc_name}, chunk_size:{len(texts)}, begin generate summary"
+        )
         summary = self._llm_extract_summary(texts[0])
         # summaries = self._mapreduce_extract_summary(texts)
         outputs, summary = self._refine_extract_summary(texts[1:], summary)
-        logger.info(
-            f"async_document_summary, doc:{doc.doc_name}, chunk_size:{len(chunk_docs)}, begin embedding to graph store"
-        )
+
         doc.summary = summary
         return knowledge_document_dao.update_knowledge_document(doc)
 
@@ -525,14 +526,18 @@ class KnowledgeService:
                 ChatScene.ExtractSummary.value(), **{"chat_param": chat_param}
             )
         )
+        logger.info(
+            f"initialize summary is :{summary}"
+        )
         return summary
-    def _refine_extract_summary(self, docs, summary: str):
+    def _refine_extract_summary(self, docs, summary: str, max_iteration:int = 5):
         """Extract refine summary by llm"""
         from pilot.scene.base import ChatScene
         from pilot.common.chat_util import llm_chat_response_nostream
         import uuid
         outputs = []
-        for doc in docs:
+        max_iteration = max_iteration if len(docs) > max_iteration else len(docs)
+        for doc in docs[0:max_iteration]:
             chat_param = {
                 "chat_session_id": uuid.uuid1(),
                 "current_user_input": doc,
@@ -547,6 +552,9 @@ class KnowledgeService:
                 )
             )
             outputs.append(summary)
+            logger.info(
+                f"iterator is {len(outputs)} current summary is :{summary}"
+            )
         return outputs, summary
 
     def _mapreduce_extract_summary(self, docs):
@@ -567,7 +575,8 @@ class KnowledgeService:
                     ChatScene.ExtractSummary.value(), **{"chat_param": chat_param}
             ))
         from pilot.common.chat_util import run_async_tasks
-        summaries = run_async_tasks(tasks)
+        summary_iters = run_async_tasks(tasks)
+        summary = self._llm_extract_summary(" ".join(summary_iters))
             # from pilot.utils import utils
             # loop = utils.get_or_create_event_loop()
             # summary = loop.run_until_complete(
@@ -576,6 +585,6 @@ class KnowledgeService:
             #     )
             # )
             # outputs.append(summary)
-        return summaries
+        return summary