Refine Your Query
Refine your prompt using the System 2 Attention (S2A) technique1.
- Ask the LLM to rewrite the prompt by removing any information unrelated to the question.
- Pass this new, focused prompt back to the LLM to generate the final response.
This method helps in producing more factual and less opinionated outputs1.*. We can implement this using instructor
as seen below.
import openai
import instructor
from pydantic import BaseModel, Field
client = instructor.from_openai(openai.OpenAI())
class Step1(BaseModel):
relevant_context: str = Field(..., description="Relevant context")
user_query: str = Field(..., description="The question from the user")
class Step2(BaseModel):
answer: int
def rewrite_prompt():
rewritten_prompt = client.chat.completions.create(
model="gpt-4o",
response_model=Step1,
messages=[
{
"role": "user",
"content": f"""
Given the following text by a user, extract the part
that is actually relevant to their question. Please
include the actual question or query that the user
is asking.
Text by user:
Mary has 3 times as much candy as Megan. Mary then
adds 10 more pieces of candy to her collection. Max
is 5 years older than Mary. If Megan has 5 pieces of
candy, how many does Mary have in total?
""",
}
],
)
return rewritten_prompt
def generate_final_response(rewritten_prompt):
final_response = client.chat.completions.create(
model="gpt-4o",
response_model=Step2,
messages=[
{
"role": "user",
"content": f"""{rewritten_prompt.relevant_context}
Question: {rewritten_prompt.user_query}""",
}
],
)
return final_response
if __name__ == "__main__":
# Step 1: Rewrite the prompt
rewritten_prompt = rewrite_prompt()
print(rewritten_prompt.relevant_context)
"""
Mary has 3 times as much candy as Megan.
Mary then adds 10 more pieces of candy to her collection.
If Megan has 5 pieces of candy, how many does Mary have in total?
"""
print(rewritten_prompt.user_query)
#> how many does Mary have in total?
# Step 2: Generate the final response
final_response = generate_final_response(rewritten_prompt)
print(final_response.answer)
#> 25
References¶
1: System 2 Attention (is something you might need too)
*: The Prompt Report: A Systematic Survey of Prompting Techniques