import openai

response = openai.Completion.create(
  engine="davinci",
  prompt="Once upon a time",
  max_tokens=50
)   

import openai

responses = openai.Completion.create(
  engine="davinci",
  prompt="Once upon a time",
  max_tokens=50,
  n=5,
  best_of=2
)   

openai的api中n是甚么意思的进一步展开说明

OpenAI API: A Powerful Tool for AI-based Language Generation

The OpenAI API is a cutting-edge language model that allows developers to integrate powerful AI capabilities into their applications. Through the API, developers can access state-of-the-art models developed by OpenAI, such as text-davinci-003, to generate high-quality and context-aware completions. In this article, we will explore the various features and capabilities of the OpenAI API, and provide examples of how it can be used in different scenarios.

Introduction: Creating Completions

At the core of the OpenAI API is the ability to generate completions based on a given prompt. The API allows developers to specify a prompt as a string, an array of strings, or a token array, and the model will generate one or more predictions based on the prompt. The API also provides the flexibility to control the generation process by adjusting parameters such as the maximum number of tokens, the sampling temperature, and the top-p probability. Additionally, developers can set stop sequences to limit the generated text.

Requesting Completions

To request completions from the OpenAI API, developers need to make a POST request to the endpoint https://api.openai.com/v1/completions. The request body should include the following parameters:

• model: The ID of the model to be used. Developers can refer to the model API list to find the available models.
• prompt: The prompt for generating completions. If no prompt is provided, the model will generate text from the beginning of a new document.
• suffix: The text to be inserted after the completion.
• max_tokens: The maximum number of tokens to be generated.
• temperature: The sampling temperature, which affects the randomness of the generated text.
• top_p: The top-p probability, which controls the diversity of the generated text.
• n: The number of completions to generate for each prompt.
• stop: A sequence of tokens at which the generation process should stop.
• presence_penalty: A penalty for new tokens not appearing in the context, which increases the likelihood of the model discussing new topics.
• frequency_penalty: A penalty for new tokens appearing frequently in the context, which reduces the likelihood of the model repeating the same lines.
• best_of: The number of candidate completions to generate on the server side, returning the “best” one based on the log probability of each token.
• logit_bias: A map that modifies the likelihood of specific tokens.

Use Cases and Examples

Now, let’s explore some use cases and examples of how the OpenAI API can be utilized:

Use Case 1: Answering Questions Based on Existing Knowledge

In this example, the OpenAI API is used to create a question answering bot. The prompt provides a contextual introduction to the bot, explaining how it will respond to different types of questions. By asking a question based on existing knowledge, the bot can generate an accurate answer. For example, when asked about the life expectancy in the United States, the bot responds with the correct information.

Use Case 2: Open-ended Conversation with an AI Assistant

In this example, the OpenAI API is used to simulate a conversation with an AI assistant. The prompt sets the context for the conversation and introduces the assistant as helpful and friendly. By engaging in a dialogue with the assistant, users can have an open-ended conversation with the AI and get creative and clever responses.

Use Case 3: Translation Functionality

In this example, the OpenAI API is used to provide translation functionality. By inputting a prompt in English and specifying the desired target language, the model can generate the translation. In this case, the prompt is translated into French, Spanish, and Japanese.

Conclusion

The OpenAI API is a powerful tool for integrating AI capabilities into applications, enabling developers to generate high-quality completions based on given prompts. With its flexibility and customizable parameters, the API can be tailored to suit various language generation needs. The provided examples demonstrate the versatility of the API in answering questions, engaging in conversations, and translating text. As AI continues to advance, the OpenAI API opens up new possibilities for natural language processing and understanding.

For more examples and information on using the OpenAI API, please refer to the OpenAI API documentation.

openai的api中n是甚么意思的常见问答Q&A