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.

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 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 ⚙️ 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. 🔩 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.🔌 Integrations Key integrations include Docker for deployment, LangChain libraries, TogetherAI's LLM models, Vectara for Chat. 🧩 Modularity 📦 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.

Search Engine Powered AI Agent and more

Search Engine Powered AI Agent and more

Code: https://github.com/sprites20/Anthroid-AI Using together.ai to host the LLM serverless, Vectara for querying the documents, LLamaIndex for text embeddings (or LLM), and unstructured.io cleaning and translating the HTML or maybe even formatting the prompts. Uses Google Search API or Azure Bing Search service API to query the search engine, returns links, and sends to Vectara for indexing and querying, (perhaps more options in the future). For now, it uses only Vectara but will implement the LLamaindex soon. Shall also use the Meta's Graph API to gather posts, not only from search engines but social media apps like Facebook for the latest news about a topic using its query engine and more content not only from websites but from actual people in real-time. (WIP) It is also capable of choosing, retrieving code, and running code. With a built-in Python interpreter; the exec() function, that can also run other languages via bindings like jnius (Java), Cython/CPython (C/C++), C# DLLs, and whatever binding in the Python library there is. Even OpenGL for 3D rendering for true multimodality, OpenCV for RTSP streaming, image processing, and computer vision, matplotlib for mathematical visualizations, or even a custom web browser like Chrome and Edge that can also run JS evaluate to execute JS code for websites. A cross-platform native app, that in the future should be able to run on most operating systems, not only on PC but also for mobile phones like Android and Ios.

Super Human AI

Super Human AI

The job application process can be daunting and time-consuming, especially in today's dynamic job market. With advancements in AI and the proliferation of job platforms, there is a growing need for a solution that streamlines and automates the job application process. Inspired by this challenge, we introduce Super Human AI, an advanced AI agent designed to revolutionize job application procedures. Super Human AI is an ultimate hyper-personalized AI agent that help to increase and automate the process of reaching companies. Problem statement: Job seekers, experienced or freshers, encounter significant obstacles in reaching out to companies and securing employment opportunities. Despite possessing relevant education and skills, many struggle to connect with a sufficient number of potential employers. The fragmentation of job listings across various platforms exacerbates this issue, highlighting the need for a platform-agnostic solution to automate and optimize the job application process. Solution: Super Human AI is an AI Agent to simplify and optimize the job application process. Here are the core components: 1. Selenium Browser Automation Integration: Selenium is utilized to automate web browsers, enabling Super Human AI to navigate job platforms, search for relevant positions, and fill out application forms seamlessly. 2. Advanced RAG-based Job Application Filler: The AI agent incorporates a sophisticated algorithm based on Red, Amber, and Green (RAG) indicators to prioritize job listings and customize application responses. This ensures that job seekers focus their efforts on opportunities that align closely with their qualifications and preferences. 3. Email Automation Integration: Super Human AI integrates email automation capabilities to facilitate communication with employers. Automated email responses are sent to confirm application submissions, follow up on application status, and schedule interviews, streamlining the entire job application process.