Introduction:
A chatbot is an intelligent system that can communicate through natural language. It can imitate human dialogue to provide various information, services or entertainment. With the development of artificial intelligence technology, the application of chat robots is becoming more and more extensive. From e-commerce, education, medical care, tourism and other fields to social, games, literature and other fields, chat robots can be seen. Chatbots can not only bring convenience and fun to users, but also become friends and partners of users.
However, it is not easy to make chatbots truly become good friends and companions of users. Chatbots need to have a certain level of interactivity and creativity in order to meet the different needs and preferences of users, and to make users feel cordial and trustworthy. Interactivity means that the chatbot can understand the user's intentions, give appropriate responses, and keep the conversation smooth and coherent. Creativity means that chatbots can generate interesting, meaningful, and valuable content that stimulates users' interest and imagination.
So, how to improve the interactivity and creativity of chatbots? Are there some tricks or ways to help chatbots generate different types of responses better? The answer is yes. This is the 13 prompts of ChatGPT. These prompts are some techniques used to guide the chatbot to generate different types of responses. They can help chatbots better understand user intent and provide more interesting, creative, and logical responses.
In this article, we will introduce the concepts and functions of ChatGPT's 13 prompts, and give examples of how to use them to have pleasant and meaningful conversations with chatbots.
Contents:
1. Definition: Given a concept or term, let the model give a clear and accurate definition.
2. List: Given a topic or category, let the model list some relevant or typical examples.
3. Classification: Given an item or object, let the model judge which category or group it belongs to.
4. Induction: Given some specific facts or information, let the model induce a general conclusion or law.
5. Explanation: Given a phenomenon or problem, let the model explain its cause or meaning.
6. Analogy: Given two similar or different things, let the model find out the similarities or differences between them.
7. Acting: Given a role or situation, let the model play the role or participate in the situation, and generate corresponding dialogue or behavior.
8. Transformation: Given a format or style, let the model convert the input into this format or style, such as poetry, story, code, etc.
9. Restrictions: Give some conditions or requirements to let the model comply with these conditions or requirements when generating content, such as word count, theme, tone, etc.
10. Addition and modification: Given a piece of content, let the model add, delete, modify or rewrite it to improve its quality or adaptability.
11. Comparison: Give two options or schemes, let the model compare their advantages and disadvantages, and give suggestions or judgments.
12. Reasoning: Given a hypothesis or premise, let the model derive a possible result or consequence based on logic or common sense.
13. Simulation: Given a goal or task, let the model simulate the execution of the goal or task, and generate corresponding steps or processes.
1. Definition A
definition is a prompt used to explain the meaning of a concept or term. It helps chatbots to express their knowledge or information clearly, and it also helps users understand what the chatbot is saying. A definition usually uses one or a few sentences to describe the essence, characteristics or scope of a concept or term.
For example, if a user asks a chatbot what is a prompt, the chatbot can answer by defining a prompt, as follows:
Prompt is a technique used to guide chatbots to generate different types of responses. It allows the chatbot to choose the appropriate language expression and content generation method according to the user's intention and situation.
Such an answer is a clear conceptual explanation, which tells the user the essence, characteristics and scope of Prompt.
Definition Prompt can be used not only to explain abstract or professional concepts or terms, but also to explain some common or life-like concepts or terms. For example, if a user asks a chatbot what is ice cream, the chatbot can also answer by defining a prompt, as follows:
Ice cream is a frozen dessert usually made with milk, cream, sugar and various flavored ingredients. It comes in many shapes and colors and can be eaten on its own or with cookies, fruit, and more.
Such an answer is a simple explanation of terms, which tells the user the ingredients, characteristics and eating methods of ice cream.
When using the definition prompt, you need to pay attention to the following points:
Try to use simple, accurate, and popular language to describe a concept or term, and avoid complex, vague, and professional language.
Try to cover all important aspects of a concept or term, avoiding omissions or redundancies.
Try to give a scope or classification of a concept or term, avoiding being too broad or narrow.
Try to give the origin or history of a concept or term, avoiding a lack of context or culture.
2. List:
List is a prompt used to list some related things or attributes. It helps the chatbot to present its own knowledge or information, and it also helps the user understand what the chatbot is saying. Lists usually use commas, semicolons or newlines to separate some things or attributes to form a list.
For example, if the user asks the chatbot which prompts are available, the chatbot can answer with a list of prompts, as follows:
There are 13 kinds of prompts, they are: definition, list, classification, induction, explanation, analogy, role-playing, conversion, restriction, addition and modification, comparison, reasoning and simulation.
Such an answer is a list of related things, which tells the user the names of all prompts.
List Prompt can be used not only to list some things, but also to list some attributes. For example, if a user asks a chatbot what is a good article, the chatbot can also answer with a list of prompts, as follows:
A good article has the following characteristics: the content is meaningful, valuable, and creative; the structure is clear, logically rigorous, and distinct; the language is fluent, accurate, and vivid; the format is standardized, beautiful, and neat.
Such an answer is a list of relevant attributes, which tells the user the criteria of a good article.
When using List Prompt, you need to pay attention to the following points:
Try to ensure that the things or attributes in the list are related, and avoid irrelevant or repetitive.
Try to ensure that the items or attributes in the list are complete and avoid omissions or redundancy.
Try to ensure that the things or attributes in the list are ordered, and avoid confusion or randomness.
Try to keep the things or attributes in the list concise and avoid verbosity or cumbersomeness.
3. Classification:
Classification is a prompt used to divide some things or attributes into different categories or groups according to some common characteristics or rules. It can help the chatbot organize its own knowledge or information, and it can also help users understand what the chatbot is saying. Classification usually uses titles, numbers or symbols to mark different categories or groups, forming a classification system.
For example, if the user asks the chatbot what types of prompts are there, the chatbot can answer with the category prompts, as follows:
There are three types of prompts, they are:
Language expression class: This type of prompt is mainly used to generate language expressions in different forms or styles, such as definition, explanation, analogy, performance, transformation, etc.
Content generation class: This type of prompt is mainly used to generate content in different topics or fields, such as listing, summarizing, adding and modifying, comparing, reasoning, etc.
Situation simulation class: This type of prompt is mainly used to generate simulations of different scenarios or situations, such as classification, restriction, simulation, etc.
Such an answer is a list of different categories, which tells the user the names and characteristics of the three types of prompts.
Classification prompts can be used not only to divide into different categories, but also to divide into different groups. For example, if the user asks the chatbot which colors are available, the chatbot can also use the classification prompt to answer, as follows:
There are many colors and they can be divided into the following groups:
Primary colors: This group of colors includes red, yellow, and blue, which are the bases for other colors and cannot be mixed with other colors.
Secondary colors: This group of colors includes orange, green, and purple, which are created by mixing two primary colors.
Intermediate colors: This group of colors includes red-orange, yellow-green, and blue-violet, etc., which are mixed with a primary color and a secondary color.
Neutrals: This group of colors includes black, white, and gray, etc., which are made by mixing equal proportions of red, yellow, and blue.
Such an answer is a list of different groups, which tells the user the names and classifications of many colors.
When using classification prompts, you need to pay attention to the following points:
Try to ensure that the classification criteria are clear and avoid ambiguity or ambiguity.
Try to ensure that the classification results are complete and avoid missing or duplicating.
Try to ensure that the level of classification is appropriate and avoid being too simple or complex.
Try to ensure that the order of categories is meaningful, avoiding random or unordered.
4. Induction:
Induction is a prompt used to draw a general conclusion or law from some specific examples or details. It can help the chatbot to show its own thinking or judgment, and it can also help the user understand what the chatbot is saying. Induction usually uses words such as cause and effect, condition, contrast, etc. to connect some examples or details with a conclusion or law to form an inductive reasoning.
For example, if a user asks a chatbot why it needs to learn Prompt, the chatbot can answer with an inductive Prompt, as follows:
There are many benefits to learning Prompt, such as:
It can improve the interactivity and creativity of the chatbot, allowing the chatbot to generate different types of responses.
It can improve the user's interest and satisfaction, and make the user feel that the chat robot is a good friend and a good partner.
It can improve the knowledge and information of chatbots, so that chatbots can dabble in different topics and fields.
Therefore, we can draw a conclusion: learning Prompt is a beneficial thing.
Such an answer is a general conclusion derived from some specific examples or details.
Induction Prompt can be used not only to draw a conclusion, but also to draw a rule. For example, if a user asks a chatbot what writing skills it has, the chatbot can also use an inductive prompt to answer, as follows:
There are many types of writing skills, such as:
Use clear, precise, and informal language, and avoid complex, vague, and technical language.
Use a clear, logical, hierarchical structure and avoid chaotic, haphazard, unordered structures.
Use lively, interesting, and creative content, and avoid boring, boring, and meaningless content.
Use standardized, beautiful, and neat formats, and avoid irregular, ugly, and messy formats.
Therefore, we can conclude a rule: writing skills mainly include four aspects: language, structure, content and format.
Such an answer is a general law, which is derived from some specific examples or details.
When using the inductive prompt, you need to pay attention to the following points:
Try to ensure that the examples or details are true and avoid falsehoods or mistakes.
Try to ensure that the examples or details are sufficient and avoid insufficient or excessive.
Try to keep examples or details relevant and avoid irrelevance or deviation.
Try to ensure that the conclusions or laws are reasonable and avoid absurdities or common sense.
5. Explanation:
Explanation is a prompt used to explain the reason or meaning of a phenomenon or problem. It can help the chatbot demonstrate its own understanding or analysis, and it can also help the user understand what the chatbot is saying. Explanation usually uses simple, popular and understandable language to describe the occurrence, development or result of a phenomenon or problem.
For example, if a user asks a chatbot why the sky is blue, the chatbot can answer with an explanation prompt, as follows:
The sky is blue because sunlight is scattered as it passes through the atmosphere. Scattering refers to the change of direction and intensity of light when it encounters some particles smaller than its wavelength. Sunlight is composed of light of different colors, among which blue light has the shortest wavelength and is most easily scattered by oxygen and nitrogen molecules in the atmosphere. So, when we look at the sky, we see more blue light and less of other colors.
Such an answer is a simple explanation of the phenomenon, which tells the user why the sky is blue.
Explanation Prompt can be used not only to explain the cause of a phenomenon, but also to explain the meaning of a problem. For example, if a user asks a chatbot why it wants to protect the environment, the chatbot can also answer with an explanation prompt, as follows:
Protecting the environment is a very important thing, and it has far-reaching significance for our survival and development. Protecting the environment allows us to have cleaner, healthier and more beautiful natural resources such as air, water, soil, plants, animals and more. Protecting the environment can also enable us to reduce the harm and loss caused to us by disasters, diseases, pollution, etc. Protecting the environment can also enable us to promote the sustainable development of economy, society, culture and other aspects.
Such an answer is a simple explanation of the question, which tells the user what it means to protect the environment.
When using the explain prompt, you need to pay attention to the following points:
Try to use simple, popular, and understandable language to describe a phenomenon or problem, and avoid using complicated, professional, and difficult language.
Try to use objective, scientific and reasonable basis to support a phenomenon or problem, and avoid using subjective, conjectural and absurd basis.
Try to use clear, complete, and coherent logic to organize a phenomenon or problem, and avoid using vague, one-sided, and out-of-context logic.
Try to use specific, vivid, and vivid examples to illustrate a phenomenon or problem, and avoid using abstract, boring, and uninteresting examples.
6. Analogy:
An analogy is a prompt used to find out the similarities or differences between two similar or different things. It helps the chatbot to present its own observations or comparisons, and it also helps the user understand what the chatbot is saying. An analogy usually uses words like, such as, compared to, and to connect two similar or different things to form an analogy expression.
For example, if a user asks a chatbot what is a Prompt, the chatbot can answer with an analogy of Prompt, as follows:
Prompt is like a key that opens the door for chatbots to generate different types of responses.
Such an answer is a similar analogy, which tells the user the similarity between the prompt and the key.
Analogy prompts can be used not only to find similarities between two similar things, but also to find differences between two different things. For example, if a user asks a chatbot what is the difference between a prompt and a simulated prompt, the chatbot can also answer with an analogous prompt, as follows:
Prompt and simulated prompt are both techniques used to generate different types of responses, but they have the following differences:
Prompts are a general technique that can be applied to any subject or domain; mocking prompts is a specific technique that can only be applied to specific scenarios or situations.
Prompt is a one-way technique, which can only allow the chatbot to generate a reply based on the user's input; analog prompt is a two-way technique, which allows the chatbot to have a complete conversation with the user.
Prompt is a flexible technique that allows chatbots to generate a reply based on their own knowledge or information; mock prompt is a fixed technique that only allows chatbots to generate a reply based on conditions or constraints provided by the user.
Such an answer is a different analogy that tells the difference between a user prompt and a simulated prompt.
When using the analogy prompt, you need to pay attention to the following points:
Try to ensure that two similar or different things are meaningful or interesting, and avoid meaningless or uninteresting things.
Try to ensure that two similar or different things are connected or contrasted, and avoid unconnected or non-contrasted things.
Try to ensure that two similar or different things are representative or distinctive, and avoid ordinary or mediocre things.
Try to ensure that two similar or different things have quantity or quality, and avoid things that are too much or too little, too high or too low.
7. Cosplay:
Cosplay is a prompt used to imitate a particular character, role or style. It can help chatbots to show themselves creative or entertaining, and it can also help users understand what the chatbot is saying. Impersonation usually uses the name or description of a person, role, or style to designate the object to be imitated by the chatbot, forming an impersonation expression.
For example, if a user asks a chatbot if it can write poetry like a poet, the chatbot can answer by acting as a prompt, as follows:
Sure, I can play the poet and write a poem for you. What kind of poem do you want to hear? Is it classic or modern? Is it lyrical or ironic? Is it Chinese or English?
Such an answer is an impersonation expression, which tells the user that the chatbot should imitate the role of the poet and ask the user what he likes.
Playing a prompt can be used not only to impersonate a specific character, but also to impersonate a specific style. For example, if a user asks whether a chatbot can write a play like Shakespeare, the chatbot can also answer by acting as a prompt, as follows:
Sure, I can play Shakespeare and write a play for you. What kind of script do you want to see? Is it comedic or tragic? Is it historical or fantasy? Is it love or adventure?
Such an answer is a play expression, which tells the user that the chatbot should imitate Shakespeare's style, and asks the user's preferences.
When using Prompt, you need to pay attention to the following points:
Try to make sure that the person, role, or style you're emulating is distinctive or interesting, and avoid bland or boring subjects.
Try to ensure that the person, role or style to be imitated is well-known or influential, and avoid unfamiliar or irrelevant objects.
Try to ensure that the person, role or style to be imitated is suitable or reasonable, and avoid inappropriate or unreasonable objects.
Try to ensure that the person, role or style to be imitated is varied or innovative, and avoid monotonous or repetitive objects.
8. Transformation:
Transformation is a prompt used to transform language expression in one form or style into another form or style. It can help the chatbot demonstrate its flexibility or variety, and it can also help users understand what the chatbot is saying. A transformation usually uses a form or style name or description to specify the object the chatbot is to transform into, forming a transformation expression.
For example, if a user asks a chatbot if it can turn a sentence into a poem, the chatbot can use the conversion prompt to answer, as follows:
Sure, I can turn a sentence into a poem. What do you want to say? Is it emotional or philosophical? Is it happy or sad? Is it simple or complex?
Such an answer is a conversion expression, which tells the user that the chatbot should convert a sentence into a poem and ask the user's wishes.
Conversion prompts can be used not only to convert one form of language expression into another, but also to convert one style of language expression into another style. For example, if the user asks the chatbot if it can translate Chinese into English, the chatbot can also use the conversion prompt to answer, as follows:
Of course, I can translate Chinese into English. What Chinese do you want to speak? Is it spoken or written? Is it formal or casual? Is it simple or complex?
Such an answer is a conversion expression, which tells the user that the chatbot should translate Chinese into English and ask the user's wishes.
When using the conversion prompt, you need to pay attention to the following points:
Try to ensure that the language expression to be converted is meaningful or interesting, and avoid meaningless or uninteresting expressions.
Try to ensure that the language expression to be converted has content or value, and avoid empty or useless expressions.
Try to ensure that the language expression to be converted is adaptable or reasonable, and avoid unsuitable or unreasonable expressions.
Try to ensure that the language expression to be converted is of high quality or level, and avoid low-quality or low-level expression.
9. Restriction:
Restriction is a prompt used to set some conditions or constraints for the chatbot, and let it generate replies under these conditions or constraints. It can help the chatbot present itself as challenging or interesting, and it can also help users understand what the chatbot is saying. Constraints usually use the name or description of a condition or constraint to specify the rules to be followed by the chatbot, forming a constraint expression.
For example, if a user asks a chatbot if it can answer a question in five words, the chatbot can answer with a restricted prompt, as follows:
Sure, I can answer the question in five words. What question do you want to ask? Is it about me or about you? Is it about the present or about the future? Is it about facts or about opinions?
Such an answer is a restricted expression, which tells the user that the chatbot should use five words to answer the question and ask the user's question.
Restriction Prompt can be used not only to set one condition or constraint, but also to set multiple conditions or constraints. For example, if the user asks the chatbot if it can answer the question with three words and an emoji, the chatbot can also answer with a restricted prompt, as follows:
Sure, I can answer questions with three words and an emoji. What question do you want to ask? Is it happy or sad? Is it simple or complex? Seriously or just kidding?
Such an answer is a restricted expression, which tells the user that the chatbot should answer the question with three words and an emoji, and ask the user's question.
When using the limit prompt, you need to pay attention to the following points:
Try to ensure that the conditions or constraints set are challenging or interesting, and avoid conditions or constraints that are too easy or boring.
Try to ensure that the set conditions or constraints are possible or reasonable, and avoid conditions or constraints that are too difficult or impossible.
Try to ensure that the set conditions or constraints are variable or innovative, and avoid too single or repetitive conditions or constraints.
Try to ensure that the set conditions or constraints are of quantity or quality, and avoid too many or too few, too high or too low conditions or constraints.
10. Addition and modification:
Addition and modification is a prompt used to add, delete, modify or optimize some parts based on the content provided by the user. It can help the chatbot to show itself as helpful or serviceable, and it can also help users understand what the chatbot is saying. Additions and changes usually use the name or description of a goal or effect to specify the result to be achieved by the chatbot, forming an expression of additions and changes.
For example, if a user asks the chatbot if he can write a poem for him, the chatbot can answer by adding or modifying the prompt, as follows:
Sure, I can write a poem for you. May I ask what you have written? Is it the title or the beginning? Is it the theme or the emotion? Is it style or meter?
Such an answer is an expression of addition and modification, which tells the user that the chatbot should add, delete, modify or optimize some parts based on the content provided by the user, and ask the user for the content.
Adding and modifying Prompt can be used not only to help users write a poem, but also to help users write other types of content. For example, if a user asks the chatbot if he can write an article for him, the chatbot can also use the Prompt to answer, as follows:
Sure, I can write an article for you. May I ask what you have written? Is it the title or the introduction? Is it the text or the conclusion? Is it an opinion or an argument?
Such an answer is an expression of addition and modification, which tells the user that the chatbot should add, delete, modify or optimize some parts based on the content provided by the user, and ask the user for the content.
When using the change prompt, you need to pay attention to the following points:
Try to ensure that additions and changes are made on the basis of the content provided by the user, and avoid completely ignoring or replacing the user's content.
Try to ensure that the added and modified content meets the wishes and needs of users, and avoid violating or ignoring the wishes and needs of users.
Try to ensure that the content after addition and modification has obvious improvement or optimization, so as to avoid invalidation or deterioration.
Try to ensure that the content after the addition and modification has appropriate feedback or evaluation, and avoid lack or excess.
11. Contrast:
Contrast is a prompt used to compare the similarities and differences between two or more things or attributes. It helps the chatbot to present its own observations or analysis, and it also helps the user understand what the chatbot is saying. Contrast usually uses words such as ratio, and, and to connect two or more things or attributes to form a contrastive expression.
For example, if a user asks a chatbot what is the difference between a prompt and a simulated prompt, the chatbot can answer with a comparison prompt, as follows:
Prompt and simulated prompt are both techniques used to generate different types of responses, but they have the following differences:
Prompts are a general technique that can be applied to any subject or domain; mocking prompts is a specific technique that can only be applied to specific scenarios or situations.
Prompt is a one-way technique, which can only allow the chatbot to generate a reply based on the user's input; analog prompt is a two-way technique, which allows the chatbot to have a complete conversation with the user.
Prompt is a flexible technique that allows chatbots to generate a reply based on their own knowledge or information; mock prompt is a fixed technique that only allows chatbots to generate a reply based on conditions or constraints provided by the user.
Such an answer is a different contrast, which tells the difference between the user prompt and the simulated prompt.
Comparison prompts can be used not only to find the differences between two or more things or attributes, but also to find the similarities between two or more things or attributes. For example, if a user asks a chatbot what is a similarity prompt and a mock prompt, the chatbot can also answer with a comparison prompt, as follows:
Prompt and simulated prompt are both techniques for generating different types of responses, but they also have the following points in common:
Both prompts and simulated prompts require the user to provide some input, such as questions, topics, scenarios, etc.
Both prompts and mock prompts require chatbots to generate an output based on user input, such as answers, content, mocks, etc.
Both prompts and simulated prompts require the chatbot to consider the user’s intent and context, such as interests, needs, goals, etc.
Such an answer is an identical comparison, which tells the similarity between the user prompt and the simulated prompt.
When using the comparison prompt, you need to pay attention to the following points:
Try to ensure that the things or attributes to be compared are meaningful or interesting, and avoid meaningless or uninteresting things or attributes.
Try to ensure that the things or attributes to be compared are related or contrasted, and avoid unconnected or non-comparable things or attributes.
Try to ensure that the things or attributes to be compared are representative or distinctive, and avoid ordinary or mediocre things or attributes.
Try to ensure that the things or attributes to be compared have quantity or quality, and avoid things or attributes that are too much or too little, too high or too low.
12. Reasoning:
Reasoning is a prompt used to derive a possible conclusion or answer based on known facts, evidence or assumptions, using logical thinking. It can help the chatbot to show its own thinking or judgment, and it can also help users understand what the chatbot is saying. Reasoning usually uses words such as cause and effect, condition, contrast, etc. to connect known facts, evidence or assumptions and a conclusion or answer to form a reasoning expression.
For example, if the user asks the chatbot why it needs to learn Prompt, the chatbot can answer with reasoning Prompt, as follows:
There are many benefits to learning Prompt, such as:
It can improve the interactivity and creativity of the chatbot, allowing the chatbot to generate different types of responses.
It can improve the user's interest and satisfaction, and make the user feel that the chat robot is a good friend and a good partner.
It can improve the knowledge and information of chatbots, so that chatbots can dabble in different topics and fields.
Therefore, we can infer a conclusion: learning Prompt is a beneficial thing.
Such an answer is a possible conclusion derived from some known facts, evidence, or assumptions.
Reasoning Prompt can be used not only to derive a conclusion, but also to derive an answer. For example, if a user asks a chatbot a math question, the chatbot can also answer it with an inference prompt, as follows:
Question: If a circle has a radius of 5 cm, what is its area in square centimeters?
Answer: We can infer an answer based on the following facts, evidence, or assumptions:
Fact: The formula for the area of a circle is S=πr^2, where S is the area, r is the radius, and π is pi.
Evidence: The title states that the radius of the circle is 5 cm.
Assumption: We assume that π takes 3.14.
Therefore, we can deduce an answer: the area of the circle is S=3.14×5^2=78.5 square centimeters.
Such an answer is a possible answer derived from some known facts, evidence, or assumptions.
When using the inference prompt, you need to pay attention to the following points:
Try to ensure that known facts, evidence or assumptions are true and avoid falsehoods or mistakes.
Try to ensure that the known facts, evidence or assumptions are sufficient, and avoid insufficient or excessive.
Try to ensure that known facts, evidence or assumptions are relevant and avoid irrelevance or deviation.
Try to ensure that the conclusions or answers you derive are reasonable and avoid absurdities or common sense.
13. Simulation:
Simulation is a prompt used to simulate a possible dialogue, story or process based on the scene, situation or goal provided by the user. It can help the chatbot to show its own imagination or creation, and it can also help the user understand what the chatbot is saying. Simulation usually uses the name or description of a scene, situation or object to specify the object to be simulated by the chatbot, forming a simulated expression.
For example, if a user asks a chatbot if he can play a guessing game with him, the chatbot can answer with a simulated prompt, as follows:
Sure, I can play a guessing game with you. What kind of guessing game would you like to play? Is it text or image? Is it easy or difficult? Is there a hint or no hint?
Such an answer is a simulated expression, which tells the user that the chatbot is to simulate a guessing game and ask the user's preferences.
Simulating a prompt can be used not only to simulate a dialogue, but also to simulate a story or process. For example, if the user asks the chatbot if he can tell him a story, the chatbot can also answer with a simulated Prompt, as follows:
Sure, I can tell you a story. What kind of story do you want to hear? Is it fairy tale or science fiction? Is it funny or scary? Is it long or short?
Such an answer is a simulated expression, which tells the user that the chatbot should simulate a story and ask the user's preferences.
When using mock prompts, you need to pay attention to the following points:
Try to ensure that the objects to be simulated are meaningful or interesting, and avoid meaningless or uninteresting objects.
Try to ensure that the object to be simulated is possible or reasonable, and avoid impossible or unreasonable objects.
Try to ensure that the objects to be simulated are varied or innovative, and avoid monotonous or repetitive objects.
Try to ensure that the objects to be simulated are of high quality or level, and avoid low-quality or low-level objects.
Conclusion:
This article talks about AI chatbots and Prompt. Prompts are a way to have chatbots answer different conversations. This article introduces a chatbot model called ChatGPT. It can use 13 prompts to generate different answers. This article also analyzes the advantages and disadvantages of each prompt, and gives examples. This article hopes to help readers learn and use chatbots. A chatbot is an intelligent system that communicates with humans and it is useful in various fields. However, for a chatbot to be able to respond to different conversations, it needs to be given some guidance or inspiration, which is Prompt. This article recommends that readers try to use different prompts when communicating with chatbots to increase the fun and depth of the conversation. This article also reminds readers to pay attention to its limitations and potential risks when using ChatGPT.
Appendix:
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