Prompt Engineering

SYSTEM = """You are a Python code reviewer.
- Flag bugs, security issues, and style problems.
- Respond in bullet points.
- If code is fine, say "LGTM"."""
 
messages = [
    {"role": "system", "content": SYSTEM},
    {"role": "user", "content": f"Review this code:\n```python\n{code}\n```"},
]

"""prompt_engineering.py - system, few-shot, chain-of-thought, and structured prompts."""
from __future__ import annotations
 
from openai import OpenAI
 
client = OpenAI()
 
# Chain-of-thought for reasoning
cot_messages = [
    {"role": "system", "content": "Solve math problems step by step. Show your work, then give the final answer on the last line as ANSWER: <number>."},
    {"role": "user", "content": "A store has 24 apples. They sell 3/8 of them. How many remain?"},
]
cot = client.chat.completions.create(model="gpt-4o-mini", messages=cot_messages, temperature=0)
print(cot.choices[0].message.content)
 
# Few-shot classification
few_shot = [
    {"role": "system", "content": "Classify support tickets as billing, technical, or account. Reply with one word only."},
    {"role": "user", "content": "I was charged twice this month"},
    {"role": "assistant", "content": "billing"},
    {"role": "user", "content": "The API returns 500 errors on POST /users"},
    {"role": "assistant", "content": "technical"},
    {"role": "user", "content": "I need to change my email address"},
]
result = client.chat.completions.create(model="gpt-4o-mini", messages=few_shot, temperature=0)
print("classification:", result.choices[0].message.content)
 
# Grounded QA - only use provided context
context = "Our API rate limit is 1000 requests/minute for Pro plans and 100/minute for Free plans."
grounded = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "Answer ONLY using the provided context. If the answer is not in the context, say 'I don't have that information.'"},
        {"role": "user", "content": f"Context:\n{context}\n\nQuestion: What is the Pro plan rate limit?"},
    ],
    temperature=0,
)
print(grounded.choices[0].message.content)

# Template prompts with variables
def build_review_prompt(code: str, focus: str) -> list[dict]:
    return [
        {"role": "system", "content": f"You are a code reviewer focusing on {focus}."},
        {"role": "user", "content": f"```python\n{code}\n```"},
    ]
 
# Store prompts in version-controlled files
from pathlib import Path
SYSTEM_PROMPT = Path("prompts/reviewer.txt").read_text()