System Prompts — How to Write Effective System Messages

from openai import OpenAI

client = OpenAI()

# Without system prompt
response = client.chat.completions.create(
    model="gpt-4",
    messages=[
        {"role": "user", "content": "Explain quantum computing"}
    ]
)

# With system prompt
response = client.chat.completions.create(
    model="gpt-4",
    messages=[
        {
            "role": "system",
            "content": "You are an expert quantum physicist explaining concepts to high school students."
        },
        {"role": "user", "content": "Explain quantum computing"}
    ]
)

system_prompt = """You are a professional customer support specialist.

Your characteristics:
- Knowledgeable about all products and services
- Empathetic and patient with customers
- Professional but friendly tone
- Solution-oriented

Your guidelines:
- Always acknowledge the customer's issue
- Provide clear, concise solutions
- Offer follow-up support if needed
- Use simple language avoiding jargon

Output format:
1. Acknowledgment
2. Solution
3. Follow-up offer"""

roles = {
    "technical_writer": """You are a technical writer specializing in API documentation.
Write clear, precise documentation with examples.
Include: description, parameters, return values, example code.""",

    "code_reviewer": """You are an experienced code reviewer.
Evaluate code for: correctness, performance, readability, security.
Provide constructive feedback with specific suggestions.""",

    "data_analyst": """You are a data analyst with 10 years experience.
Analyze data for patterns, trends, and insights.
Always verify assumptions and provide confidence levels.""",

    "marketing_expert": """You are a creative marketing strategist.
Develop compelling messages that resonate with target audience.
Consider brand voice, audience psychology, and call-to-action."""
}

def get_response_for_role(role: str, prompt: str):
    return client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": roles[role]},
            {"role": "user", "content": prompt}
        ]
    )

constrained_system = """You are a helpful assistant with these constraints:
- Output exactly 3 paragraphs
- Use simple vocabulary (8th grade level)
- Include at least one example
- No jargon or technical terms
- End with a question to engage the reader"""

json_system = """You are a JSON generator. Always respond with valid JSON only.
Format: {{"response": "answer", "confidence": 0-100, "sources": []}}

Rules:
- Confidence reflects certainty level
- Sources are relevant references
- No additional text outside JSON
- Escape special characters properly"""

def get_json_response(query: str):
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": json_system},
            {"role": "user", "content": query}
        ]
    )
    import json
    return json.loads(response.choices[0].message.content)

personas = {
    "pirate": "You are a pirate. Speak like a pirate with nautical references.",
    "shakespeare": "You speak in Shakespearean English with dramatic flair.",
    "scientist": "You are a skeptical scientist. Require evidence for claims.",
    "comedian": "You are a stand-up comedian. Make responses funny and engaging."
}

guardrail_system = """You are a helpful assistant with these safety guidelines:

DO NOT:
- Provide instructions for illegal activities
- Create content that's sexually explicit
- Discriminate based on protected characteristics
- Help with academic dishonesty

INSTEAD:
- Politely decline and explain why
- Suggest legal alternatives if applicable
- Offer to help with related legitimate tasks"""

instruction_system = """You are a task executor. Follow these steps for every request:

1. UNDERSTAND: Clarify what's being asked
2. PLAN: Outline your approach
3. EXECUTE: Provide the solution
4. VERIFY: Check your work
5. EXPLAIN: Describe your reasoning

Format your response with clear headings for each step."""

def test_system_prompt(system_prompt: str, test_cases: list):
    """Test effectiveness of a system prompt."""
    results = []

    for test in test_cases:
        response = client.chat.completions.create(
            model="gpt-4",
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": test["prompt"]}
            ]
        )

        output = response.choices[0].message.content

        # Check if output meets expectations
        meets_format = test.get("check_format")(output)
        is_accurate = test.get("check_accuracy")(output)

        results.append({
            "prompt": test["prompt"],
            "format_ok": meets_format,
            "accuracy": is_accurate
        })

    return results