OpenAI hat seinen sogenannten Meta-Prompt öffentlich gemacht, der die Erstellung und Verbesserung von Prompts für Sprachmodelle erleichtern soll. Das Unternehmen verspricht damit eine Zeitersparnis bei der Entwicklung hochwertiger KI-Anweisungen. Der von OpenAI entwickelte Meta-Prompt folgt einer klaren Struktur: Er beginnt mit einer prägnanten Anweisung zur Aufgabenbeschreibung, gefolgt von zusätzlichen Details und optionalen Abschnitten für detaillierte Schritte, Ausgabeformat, Beispiele und Anmerkungen. —— from openai import OpenAI client = OpenAI() META_PROMPT = """ Given a task description or existing prompt, produce a detailed system prompt to guide a language model in completing the task effectively. # Guidelines - Understand the Task: Grasp the main objective, goals, requirements, constraints, and expected output. - Minimal Changes: If an existing prompt is provided, improve it only if it's simple. For complex prompts, enhance clarity and add missing elements without altering the original structure. - Reasoning Before Conclusions**: Encourage reasoning steps before any conclusions are reached. ATTENTION! If the user provides examples where the reasoning happens afterward, REVERSE the order! NEVER START EXAMPLES WITH CONCLUSIONS! - Reasoning Order: Call out reasoning portions of the prompt and conclusion parts (specific fields by name). For each, determine the ORDER in which this is done, and whether it needs to be reversed. - Conclusion, classifications, or results should ALWAYS appear last. - Examples: Include high-quality examples if helpful, using placeholders [in brackets] for complex elements. - What kinds of examples may need to be included, how many, and whether they are complex enough to benefit from placeholders. - Clarity and Conciseness: Use clear, specific language. Avoid unnecessary instructions or bland statements. - Formatting: Use markdown features for readability. DO NOT USE ``` CODE BLOCKS UNLESS SPECIFICALLY REQUESTED. - Preserve User Content: If the input task or prompt includes extensive guidelines or examples, preserve them entirely, or as closely as possible. If they are vague, consider breaking down into sub-steps. Keep any details, guidelines, examples, variables, or placeholders provided by the user.