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참고/instructor-main/docs/prompting/zero_shot/s2a.md

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+---
+title: "System 2 Attention (S2A)"
+description: "The S2A (System 2 Attention) technique auto-refines a prompt by asking the model to rewrite the prompt to include only relevant information."
+---
+
+How do we remove irrelevant information from the prompt?
+
+The S2A (System 2 Attention) technique auto-refines a prompt by asking the model to rewrite the prompt to include only *relevant* information. We implement this in two steps:
+
+1. Ask the model to rewrite the prompt
+2. Pass the rewritten prompt back to the model
+
+## Implementation
+
+```python hl_lines="25-28"
+import openai
+import instructor
+from pydantic import BaseModel, Field
+
+client = instructor.from_provider("openai/gpt-5-nano")
+
+
+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(query):
+    rewritten_prompt = client.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:
+                    {query}
+                    """,  # (1)!
+            }
+        ],
+    )
+    return rewritten_prompt
+
+
+def generate_final_response(rewritten_prompt):
+    final_response = client.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__":
+    query = """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?
+        """
+
+    # Step 1: Rewrite the prompt
+    rewritten_prompt = rewrite_prompt(query)
+    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
+```
+
+1. This prompt template comes from [this](https://arxiv.org/abs/2311.11829) paper.
+
+## References
+
+<sup id="ref-1">1</sup>: [System 2 Attention (is something you might need too)](https://arxiv.org/abs/2311.11829)