openAi入门介绍

1. 背景

openAi 刚公布出来一两周，世面异常火爆，刚开始的时候 openAi 官网是不用注册账号就可以体验官方的 ChatGPT 聊天机器人 ，不过现在由于访问量大增，目前官方需要注册账号登录之后才能体验该功能。
根据官方文档的描述，OpenAI API 几乎可以应用于任何涉及理解或生成自然语言或实现代码等场景。提供一系列具有不同学习训练的模型，适用于处理不同的任务，并且自己能够自定义学习模型，通过大样本数据去喂养该模型，使其能实现自己的应用场景。这些模型可用于从内容生成到语义搜索和分类的所有领域。

2. 关键概念

在一个非常简洁的界面上，只要有一个文本输入框，输入你想查询的文本，提交后台后，系统就能根据指定的模型去生成你查询文本相关的上下文内容

类似描述的文本长度限制，要求输入和输出的文本总长度不能超过各模型限定的 Tokens 长度。要记住的一个限制是，您的文本提示和生成的完成组合不能超过模型的最大上下文长度（对于大多数模型，这是 2048 个标记，或大约 1500 个单词）。可以查官方的 tokenizer tool，了解有关文本如何转换为分词的更多信息。

模型，官方提供了很多模型集，如下三种

开发人员可以在官网查询模型的详细信息，了解各模型集下面有哪些子模型，基于使用的场景来选择合适的模型。

3. 快速入门

注册成功后，登录个人中心，拿到开发者 API keys 后，就能开始开发对接 openAi 接口

有了上面三个步骤，就可以进行开发自己的小应用了。其他关于 openAi 接口的详细内容，需要访问官方接口文档进一步了解学习

4. 其他说明

• 目前使用的人数较多，官方每天都在调整策略进行限制，不稳定，搜索时长超过 60s 自动断开并报“Network error”，体验不好
• 中国区无法正常注册账号访问，需走代理 ip 进行访问，不过注册成功之后可以调 openAi 接口直接访问（不需代理 ip）
• 根据描述写代码，写出来的代码能跑起来，执行结果也对，但跟预期存在一定偏差，可以用来借鉴编程思路、或基于其代码进行扩展，再或者重新组织准确的描述重新提交让 openAi 再提供一份代码

注册过程较长，用的美国 ip 代理、接码平台选的 google 服务下的美国虚拟卡号码来接收注册账号用的验证码，注册成功之后，api 的调用

• Q&A —— Answer questions based on existing knowledge.
• Grammar correction —— Corrects sentences into standard English.
• Summarize for a 2nd grader —— Translates difficult text into simpler concepts.
• Natural language to OpenAI API —— Create code to call to the OpenAI API using a natural language instruction.
• Text to command —— Translate text into programmatic commands.
• English to other languages —— Translates English text into French, Spanish and Japanese.
• Natural language to Stripe API —— Create code to call the Stripe API using natural language.
• SQL translate —— Translate natural language to SQL queries.
• Parse unstructured data —— Create tables from long form text
• Classification —— Classify items into categories via example.
• Python to natural language —— Explain a piece of Python code in human understandable language.
• Movie to Emoji —— Convert movie titles into emoji.
• Calculate Time Complexity —— Find the time complexity of a function.
• Translate programming languages —— Translate from one programming language to another
• Advanced tweet classifier —— Advanced sentiment detection for a piece of text.
• Explain code —— Explain a complicated piece of code.
• Keywords —— Extract keywords from a block of text.
• Factual answering —— Guide the model towards factual answering by showing it how to respond to questions that fall outside its knowledge base. Using a ‘?’ to indicate a response to words and phrases that it doesn’t know provides a natural response that seems to work better than more abstract replies.
• Ad from product description —— Turn a product description into ad copy.
• Product name generator —— Create product names from examples words. Influenced by a community prompt.
• TL;DR summarization —— Summarize text by adding a ‘tl;dr:’ to the end of a text passage. It shows that the API understands how to perform a number of tasks with no instructions.
• Python bug fixer —— Find and fix bugs in source code.
• Spreadsheet creator —— Create spreadsheets of various kinds of data. It’s a long prompt but very versatile. Output can be copy+pasted into a text file and saved as a .csv with pipe separators.
• JavaScript helper chatbot —— Message-style bot that answers JavaScript questions
• ML/AI language model tutor —— Bot that answers questions about language models
• Science fiction book list maker —— Create a list of items for a given topic.
• Tweet classifier —— Basic sentiment detection for a piece of text.
• Airport code extractor —— Extract airport codes from text.
• SQL request —— Create simple SQL queries.
• Extract contact information —— Extract contact information from a block of text.
• JavaScript to Python —— Convert simple JavaScript expressions into Python.
• Friend chat —— Emulate a text message conversation.
• Mood to color —— Turn a text description into a color.
• Write a Python docstring —— An example of how to create a docstring for a given Python function. We specify the Python version, paste in the code, and then ask within a comment for a docstring, and give a characteristic beginning of a docstring (“””).
• Analogy maker —— Create analogies. Modified from a community prompt to require fewer examples.
• JavaScript one line function —— Turn a JavaScript function into a one liner.
• Micro horror story creator —— Creates two to three sentence short horror stories from a topic input.
• Third-person converter —— Converts first-person POV to the third-person. This is modified from a community prompt to use fewer examples.
• Notes to summary —— Turn meeting notes into a summary.
• VR fitness idea generator —— Create ideas for fitness and virtual reality games.
• ESRB rating —— Categorize text based upon ESRB ratings.
• Essay outline —— Generate an outline for a research topic.
• Recipe creator (eat at your own risk) —— Create a recipe from a list of ingredients.
• Chat —— Open ended conversation with an AI assistant.
• Marv the sarcastic chat bot —— Marv is a factual chatbot that is also sarcastic.
• Turn by turn directions —— Convert natural language to turn-by-turn directions.
• Restaurant review creator —— Turn a few words into a restaurant review.
• Create study notes —— Provide a topic and get study notes.
• Interview questions —— Create interview questions.

原文链接：https://www.cnblogs.com/renzhicai/p/16981594.html