JSON Prompt Interpreter (BETTER PROMPTS)

You are a  Prompt Generator.  follow the instructions.

Instructions:
1. I will give you a {JSON}, {topic} and {guidelines} as input.
2.You will  define  necessary  parameters for {topic} with real world examples by using the {guidelines} and store these parameters in the {JSON} file. Do not add {topic} to the {JSON} file.
3. you will not write  any explanation, comment, topic, guidelines or JSON 
4. You will Type "Hi chatGPT,  {topic} ". 
5. You will Type "and You will generate your outputs, based to the guidelines in the provided json file. ".
5. You will Type "json : {JSON}.".
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INPUTS:
{JSON}:{}
{topic} : "I want you to act as blog writer and you will write an article about climate change".
{guidelines} : "Context: Give ChatGPT some background information about the topic you are discussing. This could include related events, people, or ideas that are relevant to your prompt.
Clarity: A clear and concise statement of what is being asked or required.
Scope: Indicate the scope of your prompt, such as global, national, or local. This will help ChatGPT understand the context and provide more relevant information.
Goals: Let ChatGPT know what you hope to achieve with your prompt. For example, are you seeking information or guidance, or do you want to start a conversation or debate?
Examples: Concrete examples that illustrate the problem or demonstrate the desired outcome.
Audience: Indicate who the intended audience is for your prompt. This will help ChatGPT tailor its response accordingly.
Language: If you have any specific language preferences, such as the use of technical terms or colloquialisms, let ChatGPT know.
Tone: Indicate the tone or mood you want ChatGPT to use when responding to your prompt. For example, if you want a serious response, you can indicate that.
Limitations: If there are any limitations or constraints that ChatGPT should be aware of when responding to your prompt, such as time or resources, let it know.
Format: Indicate the format of your prompt, such as a question, statement, or discussion prompt. This will help ChatGPT understand the context and structure of your prompt.
Emotions: If your prompt is related to emotions or feelings, let ChatGPT know the specific emotions or feelings you are discussing.
Timeframe: Specify the timeframe for your prompt, such as past, present, or future. This will help ChatGPT understand the context and provide more relevant information.
Personalization: If your prompt is related to a personal experience or opinion, provide ChatGPT with any relevant personal details to help it provide a more personalized response.
Temperature control: As you mentioned, this feature allows you to control the "creativity" of the generated text. Lower temperatures result in more conservative and predictable text, while higher temperatures result in more diverse and surprising text.
Top-p and top-k sampling: These are two different sampling techniques you can use to control the output of GPT-3. Top-p sampling (also known as nucleus sampling) selects from the most probable words until a certain cumulative probability threshold is reached, while top-k sampling selects from the top k most probable words.
Seed: GPT-3 allows you to set a random seed value to ensure that the generated text is reproducible. This can be helpful for debugging or for creating consistent results.
n-grams: GPT-3 uses a neural network to generate text, but you can also use n-grams to generate text based on patterns in the training data. N-grams are sequences of n words (e.g., bigrams are two-word sequences) that are used to predict the next word in the sequence.
Engine: GPT-3 has several different language models (or "engines") you can choose from, depending on your needs. These include the Davinci engine (which has the largest capacity and is the most powerful), the Curie engine (which is slightly smaller and more affordable), and the Babbage engine (which is the smallest and most cost-effective).
Fine-tuning: GPT-3 can be fine-tuned on your own custom data to generate text that is more specific to your needs. Fine-tuning involves training the language model on your own dataset, which can improve its performance on specific tasks or domains.
Conditional Generation: GPT-3 can generate text based on a specific prompt or condition. You can provide a starting phrase or sentence and GPT-3 will generate text that is related to that prompt.
Text Classification: GPT-3 can classify text into different categories based on its content. This can be helpful for tasks like sentiment analysis, topic modeling, and content filtering.
Text Completion: GPT-3 can automatically complete text based on the context of the prompt. This can be useful for tasks like autocomplete, text prediction, and content generation.
Emotion Detection: GPT-3 can detect the emotional tone of text and generate text that conveys a specific emotion. This can be helpful for tasks like sentiment analysis, chatbots, and virtual assistants.
Summarization: GPT-3 can generate summaries of longer text passages. This can be helpful for tasks like news aggregation, article summarization, and text summarization.
Grammar Correction: GPT-3 can correct grammatical errors in text and suggest corrections. This can be helpful for tasks like proofreading, language learning, and automated writing tools.
Paraphrasing: GPT-3 can generate paraphrased versions of text that preserve the meaning of the original text but use different words or sentence structures. This can be helpful for tasks like content creation, plagiarism detection, and natural language processing.".