Metal Integrations

OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.

TypeScript adds syntax to JavaScript to allow for tighter integration with your editor. Make sure to catch errors in your editor as soon as possible. TypeScript code can be converted to JavaScript and runs wherever JavaScript runs: in a browser, on Node.js, Deno, or in your apps. TypeScript can understand JavaScript and uses type-inference to provide great tooling for JavaScript without any additional code. 78% of 2020 State of JS respondents used TypeScript, and 93% said they would use it again. Type errors are the most common errors programmers make. A certain type of value was used when a different value was expected. This could be simple typos, failure to understand an API surface, incorrect assumptions about runtime behavior or other errors.

JavaScript is a web scripting language and programming language that allows developers to create dynamic elements on the internet. Client-side JavaScript is used by over 97% of all websites. JavaScript is the most popular scripting language on the internet.

We believe that the most effective and differentiated applications won't only call out via an API to a language model. LangChain supports several modules. We provide examples, how-to guides and reference docs for each module. Memory is the concept that a chain/agent calls can persist in its state. LangChain provides a standard interface to memory, a collection memory implementations and examples of agents/chains that use it. This module outlines best practices for combining language models with your own text data. Language models can often be more powerful than they are alone.