What is Unstructured?
It is designed to help preprocess structure unstructured text documents for use in downstream machine learning tasks. Examples of documents that can be processed using the unstructured library include PDFs, XML and HTML documents.
Unstructured is a tool in the Text & Language Models category of a tech stack.
Key Features
Get your data LLM-readyMore data science. Less data cleaningAny document. Any file type. Any layout
Unstructured Pros & Cons
Pros of Unstructured
No pros listed yet.
Cons of Unstructured
No cons listed yet.
Unstructured Alternatives & Comparisons
What are some alternatives to Unstructured?
LangChain
It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.
Vercel AI SDK
It is an open-source library designed to help developers build conversational streaming user interfaces in JavaScript and TypeScript. The SDK supports React/Next.js, Svelte/SvelteKit, and Vue/Nuxt as well as Node.js, Serverless, and the Edge Runtime.
Hugging Face
Build, train, and deploy state of the art models powered by the reference open source in machine learning.
