探索 Prompt：从基础概念到高级工程技术 - 链载Ai

Prompt : What is the sum of the first 10 positive integers?
Steps: Generate multiple answers to the prompt:Answer 1: "The sum is 55."Answer 2: "The sum is 55."Answer 3: "The sum is 54."Answer 4: "The sum is 55."Answer 5: "The sum is 55."
Select the most consistent answer:The most frequent answer is "55," so the final output is "The sum is 55."
Final Output: The sum of the first 10 positive integers is 55.

Prompt 1: “Generate an outline for a research paper on the impact of climate change on agriculture.”
Model Output 1: Outline including introduction, literature review, methodology, results, discussion, and conclusion.
Prompt 2: “Expand the introduction section based on the outline.”
Model Output 2: Detailed introduction with background information and research questions.
Prompt 3: “Provide a summary of recent literature on the impact of climate change on agriculture.”
Model Output 3: Summary of key studies and findings.
Prompt 4: “Describe the methodology to be used in the research.”
Model Output 4: Detailed description of research methods and data collection techniques.
Prompt 5: “Draft the results section based on hypothetical data.”
Model Output 5: Results with tables, graphs, and analysis.
Prompt 6: “Write the discussion section interpreting the results.”
Model Output 6: Discussion with implications, limitations, and future research directions.
Prompt 7: “Conclude the paper with a summary of findings and recommendations.”
Model Output 7: Conclusion summarizing the research and providing recommendations.

Prompt using Tree of Thought:
Prompt: “You are planning to travel from City A to City B. You have two routes to consider: Route 1 (shorter but has possible traffic) and Route 2 (longer but avoids traffic). Break the problem down, explore both routes, and choose the best one based on overall travel time.”
Thought Process:
Branch 1: Consider Route 1 (Shorter, but has possible traffic)
Thought: Route 1 is 30 km, but it goes through the city center where traffic can be unpredictable.
Scenario 1: If there is no traffic, Route 1 will take about 40 minutes.
Scenario 2: If there is heavy traffic, Route 1 could take up to 70 minutes.
Thought: Route 1 is risky because of the traffic variability.
Branch 2: Consider Route 2 (Longer, but avoids traffic)
Thought: Route 2 is 40 km but avoids the city center.
Scenario: Even with longer distance, Route 2 has more consistent travel times (around 50 minutes).
Thought: Route 2 offers more predictability.
Conclusion:
After evaluating both routes, Route 2 is the safer choice because it provides a more consistent travel time, even though it’s slightly longer.

Manual Prompt: “Write a recipe for chocolate cake.”
However, you might want a more detailed and engaging recipe. Automatic Prompt Engineering (APE) can improve this by testing multiple variations and optimizing them based on the quality of generated recipes.
APE Process:
Initial Prompts Generated:
1. “Write a recipe for chocolate cake, including ingredients, steps, and cooking time.”
2. “Give a step-by-step recipe for a moist chocolate cake with a rich flavor.”
3. “List the ingredients and instructions for baking a chocolate cake for beginners.”
Evaluation: The system checks which recipe is clearer, more accurate, and easier to follow.
Optimized Prompt (Final): “Provide a detailed recipe for a rich and moist chocolate cake, including ingredients, preparation steps, and baking time for beginners.”

Prompt with PALM:
“You are given a list of numbers: [45, 12, 23, 89, 1]. Use a sorting algorithm via an external program to order the list in ascending order.”
Here’s how the process would work:
LLM recognizes the task:
The LLM identifies that sorting is required but instead of attempting to sort itself, it delegates this task to an external program.
Delegating to a Sorting Algorithm:
The external program (Python, for instance) uses a built-in sorting function:
sorted_list = sorted([45, 12, 23, 89, 1])
Program Output: The program returns the sorted list: [1, 12, 23, 45, 89].
Final Response: The LLM outputs: “The sorted list is [1, 12, 23, 45, 89].”
Without PALM, the LLM might attempt to sort the list but could get it wrong, especially with larger or more complex sets of numbers.

Prompt 作为与大型语言模型交互的关键元素，其重要性不可忽视。从基础的定义和作用，到为克服 LLM 局限性而发展出的多种 Prompt 工程技术，我们看到了这一领域的不断发展和创新。这些技术从不同角度和层面提升了模型的性能，使其能够更准确、更有效地生成符合用户需求的输出。