Guide Based on OpenAI’s Blog
Struggling with AI? Our comprehensive guide on prompt engineering with GPT based on OpenAI’s Blog offers strategies for success.
We provide simple and effective methods to improve the efficiency of GPT models.
1. Write Clear Instructions
Clarity is crucial, and direct and precise instructions lead to better responses.
- Include detailed queries for relevance.
- Ask the model to adopt a specific persona.
- Use delimiters for clear input separation.
- Specify step-by-step task completion instructions.
- Provide examples for context.
- State the desired output length.
- Offer reference texts for accuracy.
2. Provide Reference Text
Guiding with Knowledge Equip GPT with the correct information for precise answers.
- Direct the model to answer using the provided texts.
- Instruct the model to include citations from the reference texts.
3. Split Complex Tasks into Simpler Subtasks
Simplifying Complexity Break down tasks for better accuracy and efficiency.
- Use intent classification for relevant instruction identification.
- Summarize or filter long dialogues in dialogue applications.
- Summarize long documents piecewise and construct a full summary recursively.
4. Give Models Time to 'Think'
Deliberation Enhances Quality Allowing GPT-4 time to process leads to more reliable answers.
- Instruct the model to work out its solution first.
- Use an inner monologue or a sequence of queries to guide reasoning.
- Ask the model to review its previous responses.
5. Use External Tools
Leveraging Additional Resources Enhance GPT-4’s capabilities with external tools.
- Implement embeddings-based search for efficient knowledge retrieval.
- Use code execution for precise calculations or to call external APIs.
- Give the model access to specific functions.
6. Test Changes Systematically
Consistent Evaluation for Improvement Regular testing ensures sustained enhancement of performance.
- Check model outputs against gold-standard answers to measure accuracy.