Exploring OpenAI's API through Elixir for Scheduling Tasks

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Exploring OpenAI's API through Elixir for Scheduling Tasks

Source: revelry.co

Type: Post

Jason Pollentier provides a comprehensive account of his experience using OpenAI's Functions API to build what is termed as 'Agents' in the realm of artificial intelligence. Starting with an abstracted calendar API, he illustrates the potential to orchestrate structured, machine-readable outputs from OpenAI's Language Models (LLMs), which he then uses to perform scheduling tasks. By writing the code in Elixir and utilizing a Livebook for interaction, Pollentier sets up a mock environment to test OpenAI's ability to interpret prompts related to scheduling by making API calls to the mocked functions. The article breaks down into several sections explaining the detailed working of each part of the code, the behavior the agent is expected to exhibit, and the JSON configuration necessary for OpenAI's API to recognize and utilize the provided functions. Pollentier's experiment points towards the potential for integration of such agents into various software ecosystems and ponders upon improvements and differences between different versions of OpenAI's LLMs, particularly GPT-3.5 and GPT-4.

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