diff --git a/examples/rag_pipeline.py b/examples/rag_pipeline.py
index 7dbca35a6..75888e480 100644
--- a/examples/rag_pipeline.py
+++ b/examples/rag_pipeline.py
@@ -18,13 +18,13 @@ from metagpt.rag.schema import (
 )
 from metagpt.utils.exceptions import handle_exception
 
+LLM_TIP = "If you not sure, just answer I don't know."
+
 DOC_PATH = EXAMPLE_DATA_PATH / "rag/writer.txt"
-QUESTION = "What are key qualities to be a good writer?"
+QUESTION = f"What are key qualities to be a good writer? {LLM_TIP}"
 
 TRAVEL_DOC_PATH = EXAMPLE_DATA_PATH / "rag/travel.txt"
-TRAVEL_QUESTION = "What does Bob like?"
-
-LLM_TIP = "If you not sure, just answer I don't know."
+TRAVEL_QUESTION = f"What does Bob like? {LLM_TIP}"
 
 
 class Player(BaseModel):
@@ -40,21 +40,21 @@ class Player(BaseModel):
 
 
 class RAGExample:
-    """Show how to use RAG.
+    """Show how to use RAG."""
 
-    Default engine use LLM Reranker, if the answer from the LLM is incorrect, may encounter `IndexError: list index out of range`.
-    """
-
-    def __init__(self, engine: SimpleEngine = None):
+    def __init__(self, engine: SimpleEngine = None, use_llm_ranker: bool = False):
         self._engine = engine
+        self._use_llm_ranker = use_llm_ranker
 
     @property
     def engine(self):
         if not self._engine:
+            ranker_configs = [LLMRankerConfig()] if self._use_llm_ranker else None
+
             self._engine = SimpleEngine.from_docs(
                 input_files=[DOC_PATH],
                 retriever_configs=[FAISSRetrieverConfig()],
-                ranker_configs=[LLMRankerConfig()],
+                ranker_configs=ranker_configs,
             )
         return self._engine
 
@@ -105,7 +105,7 @@ class RAGExample:
         """
         self._print_title("Add Docs")
 
-        travel_question = f"{TRAVEL_QUESTION}{LLM_TIP}"
+        travel_question = f"{TRAVEL_QUESTION}"
         travel_filepath = TRAVEL_DOC_PATH
 
         logger.info("[Before add docs]")
@@ -240,8 +240,14 @@ class RAGExample:
 
 
 async def main():
-    """RAG pipeline."""
-    e = RAGExample()
+    """RAG pipeline.
+
+    Note:
+    1. If `use_llm_ranker` is True, then will use LLM Reranker to get better result, but it is not always guaranteed that the output will be parseable for reranking,
+       prefer `gpt-4-turbo`, otherwise might encounter `IndexError: list index out of range` or `ValueError: invalid literal for int() with base 10`.
+    """
+    e = RAGExample(use_llm_ranker=False)
+
     await e.run_pipeline()
     await e.add_docs()
     await e.add_objects()