Скачать или смотреть OpenAI Assistants API coding tutorial

Welcome to the AI podcast, where we explore the latest developments and applications of artificial intelligence. In this episode, we are going to learn how to build with the new OpenAI Assistants API in just 20 minutes. The OpenAI Assistants API is a powerful tool that allows you to create conversational agents that can interact with users, access information, and perform tasks using natural language.
The source of this episode is a YouTube video by Ralf Elfving, a software engineer and AI enthusiast. You can find the link to the video and the code in the description below. In the video, Ralf shows us how to use the Assistants API with Node.js, a popular JavaScript runtime environment. He also explains some of the key features and concepts of the Assistants API, such as threads, messages, lifecycles, and file retrieval.
The video starts with an example output of an assistant that can answer questions about the weather, the news, and the stock market. The assistant uses the Code Interpreter tool and the Retrieval tool, which are features of the Assistants API that allow you to execute code snippets and access files from various sources.
Next, Ralf walks us through the steps of setting up the Node.js environment and installing the OpenAI library. He then shows us how to create an instance of the Assistants API and how to use the OpenAI Playground to test and debug our assistant.
After that, Ralf explains how to use the Threads tool, which is a feature of the Assistants API that allows you to create multiple contexts for your assistant. He shows us how to use the switch command to switch between threads.
Ralf then shows us how to use the Messages tool, which is a feature of the Assistants API that allows you to send and receive messages to and from your assistant. He shows us how to use the run, retrieve, and output commands to send and receive text, code, and file messages.
Finally, Ralf shows us how to run the lifecycles of our assistant, which are the sequences of messages that define the behavior of our assistant. He shows us how to use the start, stop, and status commands to initiate, terminate, and see the state of our lifecycles.
Ralf concludes the video by running the code and showing us the output of our assistant. He also gives us some tips and resources to learn more about the Assistants API and how to build more advanced and customized assistants.
That's it for this episode of the AI podcast. I hope you enjoyed it and learned something new. If you did, please give us a thumbs up and subscribe to our channel for more AI content. Thank you for listening and see you next time. Bye!.

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