Unstructured IO AI technology page Top Builders

Explore the top contributors showcasing the highest number of Unstructured IO AI technology page app submissions within our community.

Unstructured: Transforming Data for LLM Success

Unstructured flawlessly extracts and transforms data into clean, consistent JSON, tailored for integration into vector databases and LLM frameworks. Experience efficient data processing for optimal LLM performance.

General
AuthorUnsctructured.io
Repositoryhttps://github.com/Unstructured-IO/unstructured
TypeData Transformation Tool

Key Features

  • Document preprocessing: Unstructured provides an API for document preprocessing without a custom code need.
  • Accurate data: Unstructured focuses on delivering clean, LLM-ready data, ensuring efficient performance.
  • Rapid integration: Integrates into existing workflows with a smooth setup.
  • High scalability Unstructured automatically retrieves, transforms, and stages large volumes of data for LLMs, ensuring scalability and efficiency.

Start building with Unsctructured's products

Explore Unstructured's products tailored to meet the your needs of your data transformation for LLMs.

List of Unstructured's products

API (SaaS & Marketplace)

The API offers a document preprocessing with production grading and doesn't require a custom code. Ideal for getting started quickly with document processing tasks.

Platform (Paid)

The Platform serves enterprises and companies with large data volumes. It enables automatic retrieval, transformation, and staging of data for LLMs, ensuring efficiency.

RAG Support (with LangChain)

Unstructured collaborates with LangChain to provide RAG support, optimizing the transition of your RAG from prototype to production. Make the most of expert guidance and seamless integration with LangChain's support.

System Requirements

Unstructured is compatible with major operating systems, including Windows, macOS, and Linux. A minimum of 4 GB of RAM is recommended for optimal performance. For intensive data processing tasks, a multicore processor is recommended to ensure the efficient outcome.

Unstructured IO AI technology page Hackathon projects

Discover innovative solutions crafted with Unstructured IO AI technology page, developed by our community members during our engaging hackathons.

Edulance-AI

Edulance-AI

Edulance is an open-source project that utilizes advanced technologies such as Unstructured, machine learning models, and APIs to transform text documents and PDFs into interactive educational resources. The software accepts user-uploaded files, applies optical character recognition (OCR) for text documents, or extracts valuable content from PDFs. It then generates lessons, quizzes, and lesson plans based on the content using its Lesson Graph model and agents like LessonGenerator, LessonPlanner, OCRAgent, PdfAgent, QuizAgent, and TogetherLLM. Edulance provides an immersive learning experience, enabling effective teaching and interactive knowledge acquisition. Overall this project incorporates the following: TogetherAI's LLM Models Unstructured Partition pdf for making PDFs LLM Ready Agentic AI with state management. Features Feature Description โš™๏ธ Architecture Edulance is a Python-based project using FastAPI as the web framework and Uvicorn for runtime serving. The application leverages containers with Docker for deployment, installing required dependencies from requirements.txt. It utilizes libraries like LangChain, PikePDF, PyTesseract for OCR, and TogetherAI's LLM models. ๐Ÿ”ฉ Code Quality The codebase follows a modular structure with clearly defined agents and graph files, ensuring high cohesion and low coupling. Python style guides are followed consistently, including PEP8 and PEP534. There is adequate usage of comments throughout the codebase.๐Ÿ”Œ Integrations Key integrations include Docker for deployment, LangChain libraries, TogetherAI's LLM models, Vectara for Chat. ๐Ÿงฉ Modularity ๐Ÿ“ฆ Dependencies Main dependencies include FastAPI, Docker, Python 3.10, requirements.txt, LangChain package, PikePDF, PyTesseract, and related tools.

Longevity Copilot

Longevity Copilot

Longevity-Copilot is an advanced RAG (Retrieval-Augmented Generation) chatbot designed to democratize access to the latest longevity research and practical applications. By providing real-time, personalized responses, this chatbot helps users integrate longevity-enhancing practices into their daily lives. Whether you're looking to understand complex scientific research or seeking practical advice on lifestyle adjustments, Longevity-Copilot offers tailored recommendations based on individual age, dietary habits, health conditions, and exercise routines. This tool makes longevity science accessible and actionable for everyone, ensuring that users can make informed decisions about their health and well-being. Features - **Tailored Recommendations:** Get personalized health and lifestyle advice that considers your unique circumstances such as age, diet, health issues, and physical activity levels. - **Cutting-Edge Research:** Stay updated with the latest findings in longevity science. Longevity-Copilot integrates contemporary research directly into your interaction with the AI. - **User-Friendly AI:** Engage in natural, easy-to-understand conversations with our AI, making complex longevity research relatable and easy to comprehend. - **Real-Time Answers:** Have a question about longevity? Our chatbot provides real-time responses to help you apply longevity science in your daily life effectively. Longevity-Copilot is aimed for receiving information, and by no mean is it a replacement for a professional healthcare provider. It is a tool that can be used by anyone, anywhere, and at any time.