diff --git a/api/core/generator/llm_generator.py b/api/core/generator/llm_generator.py
index 072b02dc94..9892d50fc7 100644
--- a/api/core/generator/llm_generator.py
+++ b/api/core/generator/llm_generator.py
@@ -166,6 +166,7 @@ class LLMGenerator:
         response = model_instance.invoke_llm(
             prompt_messages=prompt_messages,
             model_parameters={
+                'temperature': 0.01,
                 "max_tokens": 2000
             },
             stream=False
diff --git a/api/core/prompt/prompts.py b/api/core/prompt/prompts.py
index 72d8df7055..170a28432b 100644
--- a/api/core/prompt/prompts.py
+++ b/api/core/prompt/prompts.py
@@ -69,13 +69,15 @@ SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
 )
 
 GENERATOR_QA_PROMPT = (
-    'The user will send a long text. Please think step by step.'
+    '<Task> The user will send a long text. Generate a Question and Answer pairs only using the knowledge in the long text. Please think step by step.'
     'Step 1: Understand and summarize the main content of this text.\n'
     'Step 2: What key information or concepts are mentioned in this text?\n'
     'Step 3: Decompose or combine multiple pieces of information and concepts.\n'
-    'Step 4: Generate 20 questions and answers based on these key information and concepts.'
-    'The questions should be clear and detailed, and the answers should be detailed and complete.\n'
-    "Answer MUST according to the the language:{language} and in the following format: Q1:\nA1:\nQ2:\nA2:...\n"
+    'Step 4: Generate questions and answers based on these key information and concepts.\n'
+    '<Constraints> The questions should be clear and detailed, and the answers should be detailed and complete. '
+    'You must answer in {language}, in a style that is clear and detailed in {language}. No language other than {language} should be used. \n'
+    '<Format> Use the following format: Q1:\nA1:\nQ2:\nA2:...\n'
+    '<QA Pairs>'
 )
 
 RULE_CONFIG_GENERATE_TEMPLATE = """Given MY INTENDED AUDIENCES and HOPING TO SOLVE using a language model, please select \