Search Results for "data extract" - Page 4
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Showing 623 open source projects for "data extract"
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OpenRecall
OpenRecall is a fully open-source, privacy-first alternative
OpenRecall is an open-source, privacy-first system designed to capture, index, and make searchable a user’s entire digital activity history, effectively acting as a personal memory layer for computing environments. It works by taking periodic screenshots of a user’s screen and applying local AI processing, including OCR and semantic analysis, to extract and structure information from both text and images. This data is then indexed into a searchable database, allowing users to retrieve past information quickly using natural language queries. Unlike proprietary alternatives, OpenRecall operates entirely locally, ensuring that all captured data remains on the user’s device and is never transmitted to external servers. ... -
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MCP Server RAG Web Browser
A MCP Server for the RAG Web Browser Actor
The MCP Server for the RAG Web Browser Actor allows AI assistants and LLMs to perform web searches and extract information from web pages. It facilitates interaction with the web, enabling up-to-date context retrieval for AI applications. -
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imodelsX
Interpretable prompting and models for NLP
Interpretable prompting and models for NLP (using large language models). Generates a prompt that explains patterns in data (Official) Explain the difference between two distributions. Find a natural-language prompt using input-gradients. Fit a better linear model using an LLM to extract embeddings. Fit better decision trees using an LLM to expand features. Finetune a single linear layer on top of LLM embeddings. Use these just a like a sci-kit-learn model. -
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Vedo
A python module for scientific analysis of 3D data
A lightweight and powerful python module for scientific analysis and visualization of 3d objects. Inspired by the vpython manifesto "3D programming for ordinary mortals", vedo makes it easy to work with 3D pointclouds, meshes and volumes, in just a few lines of code, even for less experienced programmers. vedo is based on VTK and numpy, with no other dependencies. Import meshes from VTK format, STL, Wavefront OBJ, 3DS, Dolfin-XML, Neutral, GMSH, OFF, PCD (PointCloud). Export meshes as ASCII... -
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The ReflectionDocBlock Component
Component of phpDocumentor provides a DocBlock parser
...Developers can install it through Composer and use it as a reusable parser rather than writing custom DocBlock handling. The project helps PHP tooling turn human-written comments into structured data that software can inspect. -
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DeepSeek-OCR
Contexts Optical Compression
DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body... -
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GoCV
Go package for computer vision using OpenCV 4 and beyond
...Computer Vision (CV) is the ability of computers to process visual information, and perform tasks normally associated with those performed by humans. CV software typically processes video images, then uses the data to extract information in order to do something useful. Since memory allocations for images in GoCV are done through C based code, the go garbage collector will not clean all resources associated with a Mat. As a result, any Mat created must be closed to avoid memory leaks. -
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Browserbase MCP Server
Allow LLMs to control a browser with Browserbase and Stagehand
Browserbase MCP Server is a server implementation of the Model Context Protocol (MCP) that enables large language models to interact with web browsers programmatically through cloud-based automation. The project provides a standardized interface for connecting AI systems to real-world web environments, allowing them to navigate pages, extract structured data, and perform user-like actions such as clicking, typing, and form submission. It leverages Browserbase infrastructure along with Stagehand to deliver high-performance browser automation with improved speed and efficiency through caching and optimized execution pipelines. The system supports multiple AI models and integrates seamlessly into agent workflows, making it suitable for applications such as web scraping, testing, and intelligent automation. ... -
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TimeMixer
Decomposable Multiscale Mixing for Time Series Forecasting
TimeMixer is a deep learning framework designed for advanced time series forecasting and analysis using a multiscale neural architecture. The model focuses on decomposing time series data into multiple temporal scales in order to capture both short-term seasonal patterns and long-term trends. Instead of relying on traditional recurrent or transformer-based architectures, TimeMixer is implemented as a fully multilayer perceptron–based model that performs temporal mixing across different resolutions of the data. The architecture introduces specialized components such as Past-Decomposable-Mixing blocks, which extract information from historical sequences at different scales, and Future-Multipredictor-Mixing modules that combine predictions from multiple forecasting paths. ... -
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Text2Code for Jupyter notebook
A proof-of-concept jupyter extension which converts english queries
Text2Code for Jupyter notebook project is a proof-of-concept extension for Jupyter Notebook that allows users to generate Python code directly from natural language queries written in English. The tool is designed to simplify data analysis workflows by enabling users to describe their intended operation in plain language instead of manually writing code. When a user enters a textual command, the extension interprets the request and generates a corresponding Python code snippet that can be inserted into the notebook and executed automatically. The system uses natural language processing techniques to identify the intent of the query, extract relevant variables, and map the request to predefined code templates. ... -
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TaxHacker
Self-hosted AI accounting app. LLM analyzer for receipts
...The system is designed to simplify bookkeeping by automatically processing financial documents such as receipts, invoices, and transaction records. It integrates large language models to analyze these documents, extract relevant financial information, and categorize expenses or income based on configurable rules. Users can deploy the application on their own infrastructure, ensuring that financial data remains private and under their control rather than being processed by external services. The software provides tools for tracking income streams, monitoring expenses, and organizing financial records in a structured format. ... -
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Instructor
Structured outputs for llms
Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. -
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Jenkins Docker
Docker jenkins repo
...Treat the jenkins_home directory as you would a database, in Docker you would generally put a database on a volume. If your volume is inside a container, you can use a Docker command to extract the data, or other options to find where the volume data is. Note that some symlinks on some OSes may be converted to copies (this can confuse jenkins with lastStableBuild links etc). You can define the number of executors on the Jenkins built-in node using a groovy script. By default it is set to 2 executors, but you can extend the image and change it to your desired number of executors. -
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Doctrine Lexer
Base library for a lexer that can be used in Recursive Descent Parsers
PHP Doctrine Lexer parser library that can be used in Top-Down, Recursive Descent Parsers. This lexer is used in Doctrine Annotations and in Doctrine ORM (DQL). To write your own parser you just need to extend Doctrine\Common\Lexer\AbstractLexer and implement three abstract methods. These methods define the lexical catchable and non-catchable patterns and a method for returning the type of a token and filtering the value if necessary. The Lexer is responsible for giving you an API to walk... -
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Android Use
Automate native Android apps with AI using accessibility APIs
android-action-kernel is an open source Python library designed to let AI agents control and automate native Android applications running on real devices or emulators. It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets. The project works by using Android’s accessibility API to extract structured UI state... -
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FFmpeg Sidecar
Wrap a standalone FFmpeg binary in an intuitive Iterator interface
...It allows developers to interact with video streams as sequences of raw frames, abstracting the complexity of decoding and processing media. The library leverages FFmpeg’s CLI instead of low-level bindings, simplifying setup and avoiding heavy dependencies. It enables streaming data through stdin and stdout, making it suitable for real-time processing pipelines. Additionally, it parses FFmpeg logs to extract structured information such as progress, metadata, and errors. The project is designed for cross-platform compatibility and minimal configuration. Its architecture emphasizes simplicity while retaining access to FFmpeg’s powerful capabilities. -
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deepdoctection
A Repo For Document AI
DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for fine-tuning, evaluating and running models. ... -
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Reader LLM
Convert any URL to an LLM-friendly input with a simple prefix
Reader LLM is an open-source tool designed to convert web content into formats that are easier for large language models to process. The system works by transforming a webpage into a clean text or Markdown representation that removes unnecessary formatting and highlights the core information within the page. Developers can use a simple URL prefix to retrieve a version of a webpage that has been optimized for machine consumption, making it suitable for use in AI agents or retrieval-augmented... -
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Scope Sentry
Cyberspace asset mapping and vulnerability scanning platform
...ScopeSentry combines multiple reconnaissance and vulnerability assessment capabilities such as subdomain enumeration, port scanning, directory scanning, and sensitive information detection. ScopeSentry can automatically identify assets and services, extract URLs, and crawl websites to collect useful security data for further analysis. It also includes vulnerability scanning and subdomain takeover detection to help identify common security weaknesses across web infrastructure. It supports distributed scanning with multiple nodes, allowing large scanning tasks to be performed efficiently across different systems. -
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The Hypersim Dataset
Photorealistic Synthetic Dataset for Holistic Indoor Scene
...The dataset spans diverse furniture layouts, room types, and camera trajectories, enabling robust training for geometry, segmentation, and SLAM-adjacent tasks. Rendering pipelines and utilities allow researchers to reproduce sequences, generate novel views, or extract task-specific supervision. Because the data are perfectly labeled and controllable, Hypersim is well suited for pretraining and for studying domain transfer to real imagery. The repository acts as both a dataset index and a set of scripts for downloading, managing, and evaluating on standardized splits. -
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GitHub Workflows Kt
Authoring GitHub Actions workflows in Kotlin
GitHub-workflows-kt is a tool for creating GitHub Actions workflows in a type-safe script, helping you to build robust workflows for your GitHub projects without mistakes, with pleasure, in Kotlin. We're often surrounded by YAML configuration. It's a powerful format that provides a simple syntax for defining hierarchical data, but it is sometimes used (abused?) to configure complicated scenarios which lead to complicated files that are difficult to write and maintain. Who among us hasn't accidentally used the wrong indentation, missed a possibility to extract a reusable piece of code, or been confused by ambiguous types? The power of a generic-purpose would come in handy in these cases. ... -
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Point Cloud Library
A standalone, large scale, open project for 2D/3D image processing
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available too. To simplify both usage and... -
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SemTools
Semantic search and document parsing tools for the command line
SemTools is an open-source command-line toolkit designed for document parsing, semantic indexing, and semantic search workflows. The project focuses on enabling developers and AI agents to process large document collections and extract meaningful semantic representations that can be searched efficiently. Built with Rust for performance and reliability, the toolchain provides fast processing of text and structured documents while maintaining low system overhead. SemTools can parse documents,... -
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browserable
Open source and self-hostable browser automation library for AI agents
...The platform enables the creation of browser-based agents capable of performing complex online workflows such as data collection, research tasks, and automated interactions with web platforms. -
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DocStrange
Extract and convert data from any document, images, pdfs, word doc
DocStrange is an open-source document understanding and extraction library designed to convert complex files into structured, LLM-ready outputs such as Markdown, JSON, CSV, and HTML. Developed by Nanonets, the project combines OCR, layout detection, table understanding, and structured extraction into one end-to-end pipeline, which reduces the need to stitch together multiple separate services. It is built for developers who need high-quality parsing from scans, photos, PDFs, office files,...
