Search Results for "extraction"
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Showing 830 open source projects for "extraction"
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GROBID
A machine learning software for extracting information
...In 2011 the tool has been made available in open source. Work on GROBID has been steady as a side project since the beginning and is expected to continue as such. Header extraction and parsing from article in PDF format. The extraction here covers the usual bibliographical information (e.g. title, abstract, authors, affiliations, keywords, etc.). References extraction and parsing from articles in PDF format, around .87 F1-score against on an independent PubMed Central set of 1943 PDF containing 90,125 references, and around .89 on a similar bioRxiv set of 2000 PDF (using the Deep Learning citation model). ... -
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webclaw
Fast, local-first web content extraction for LLMs
...It supports multiple modes of operation, including CLI usage, REST API access, and an MCP server for direct integration with agent-based systems. Webclaw also provides advanced capabilities such as recursive crawling, structured JSON extraction, summarization, and content comparison, making it suitable for research and data pipelines. Its local-first architecture ensures privacy and eliminates the need for API keys. -
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Unstract
No-code LLM Platform to launch APIs and ETL Pipelines
Unstract is a powerful open-source, no-code platform built to automate the extraction and structuring of unstructured documents using large language models and flexible workflows, enabling developers and data teams to turn messy files into organized JSON content without complex coding. It integrates a visual Prompt Studio environment where users can iteratively design extraction schemas, compare outputs from different models, and monitor costs and accuracy side by side, making it easier to refine prompts and extraction logic before deploying at scale. ... -
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Sparrow
Structured data extraction and instruction calling with ML, LLM
...It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to identify and extract meaningful data fields from heterogeneous document layouts. The architecture is modular, allowing developers to build customizable processing pipelines that integrate with external tools and data extraction frameworks. Sparrow also includes workflow orchestration tools that allow multiple extraction tasks to be combined into automated pipelines for large-scale document processing. -
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ExtractThinker
ExtractThinker is a Document Intelligence library for LLMs
ExtractThinker is a tool designed to facilitate the extraction and analysis of information from various data sources, aiding in data processing and knowledge discovery. -
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pdfly
CLI tool to extract (meta)data from PDF and manipulate PDF files
A Python library designed for manipulating PDF files with functionalities for extraction, transformation, and document generation. -
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zpdf
Zero-copy PDF text extraction library written in Zig
zpdf is a high-performance PDF text extraction library written in Zig that focuses on speed, low overhead, and modern parsing techniques. It leans heavily on memory-mapped file reading and zero-copy patterns where possible, so it can scan large PDFs without repeatedly copying data around in memory. The library supports streaming extraction using efficient arena allocation, making it well suited for workloads that need to process big documents quickly or in batches. -
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MinerU
A high-quality tool for convert PDF to Markdown and JSON
MinerU is an open-source, high-quality document extraction toolkit focused on converting PDFs (and other document formats) into structured Markdown and JSON. It leverages OCR and layout analysis to preserve semantic structure and metadata, ideal for research and data science workflows. -
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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. -
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Extractous
Fast and efficient unstructured data extraction
Extractous is a Rust-based unstructured data extraction library focused on fast local parsing of documents and other content-heavy files. Its purpose is to extract text and metadata efficiently from formats such as PDF, Word, HTML, email archives, images, and more, without depending on external APIs or separate parsing servers. The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. ... -
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ContextGem
ContextGem: Effortless LLM extraction from documents
ContextGem is an open-source framework designed to simplify the extraction of structured data and insights from documents using large language models (LLMs). It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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text-extract-api
Document (PDF, Word, PPTX ...) extraction and parse API
...The project focuses on converting complex files such as PDFs, images, scanned documents, and office files into structured plain text that can be processed by downstream applications or language models. Instead of requiring developers to integrate multiple document parsing libraries individually, the system centralizes text extraction capabilities into a unified API that standardizes the output. The platform supports automated processing pipelines that detect file types and apply the appropriate extraction method to obtain the most accurate text representation possible. It can be integrated into document analysis systems, knowledge retrieval tools, and AI pipelines that rely on clean textual data. ... -
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OCRBase
MD/.JSON Document OCR and structured data extraction API
OCRBase is a self-hostable document OCR and structured extraction system built to turn PDFs into machine-usable outputs at scale, aiming to bridge the gap between raw text extraction and production-ready pipelines. Instead of treating OCR as a one-off script, it presents an API-driven workflow where documents are submitted as jobs and processed through a queue-based architecture that can handle high throughput. -
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NLP
Open source NLP guide with models, methods, and real use cases
...It explains how machines process and understand human language, combining theory with practical examples. Its covers core NLP concepts such as text representation, feature extraction, and model evaluation, alongside hands-on implementations using tools like Word2Vec, TF-IDF, and FastText. It also introduces topic modeling with LDA, keyword extraction techniques, and document similarity methods. NLP extends into real-world applications, including sentiment analysis and text classification, helping readers connect concepts to use cases. ... -
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xq
Command-line XML and HTML beautifier and content extractor
Command-line XML and HTML beautifier and content extractor. Syntax highlighting, automatic indentation, and formatting. Automatic pagination and node content extraction. -
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Youwee
A beautiful, cross-platform downloader for YouTube, TikTok, Instagram
...It provides a polished graphical interface that simplifies media downloading while leveraging powerful tools like yt-dlp and FFmpeg under the hood. The application supports advanced features such as batch downloads, playlist management, and extraction of audio or subtitles. It also integrates AI capabilities, allowing users to generate summaries and perform natural language-based video editing tasks. youwee includes browser extension support for one-click downloads directly from webpages. It emphasizes performance and efficiency through a lightweight architecture. Overall, it delivers a feature-rich and user-friendly experience for managing online media downloads. -
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X-Crawl
Flexible Node.js AI-assisted crawler library
A high-performance web crawling and scraping framework for Node.js, designed for large-scale data extraction. -
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Firecrawl
Turn entire websites into LLM-ready markdown or structured data
Crawl and convert any website into LLM-ready markdown or structured data. Built by Mendable.ai and the Firecrawl community. Includes powerful scraping, crawling, and data extraction capabilities. Firecrawl is an API service that takes a URL, crawls it, and converts it into clean markdown or structured data. We crawl all accessible subpages and give you clean data for each. No sitemap is required. -
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FModel
Unreal Engine Archives Explorer
FModel is a freeware application designed to explore Unreal Engine games archives, allowing users to delve into the assets and structures of games developed with Unreal Engine. -
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mtail
Extract internal monitoring data from application logs
...It fills a monitoring niche by being the glue between applications that do not export their own internal state (other than via logs) and existing monitoring systems, such that system operators do not need to patch those applications to instrument them or writing custom extraction code for every such application. The extraction is controlled by mtail programs which define patterns and actions. Metrics are exported for scraping by a collector as JSON or Prometheus format over HTTP, or can be periodically sent to a collectd, StatsD, or Graphite collector socket. Precompiled binaries for released versions are available in the Releases page on Github. ... -
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ZeroGPU Router
Cut inference costs without dumbing down your agent
...It is designed to reduce inference costs without replacing the main reasoning model used by the agent. The router exposes tools for tasks such as summarization, classification, PII redaction, entity extraction, JSON extraction, follow-up generation, and short chat. It works through MCP for OpenClaw and through a CLI plus plugin workflow for Claude Code. Each routed call can report useful metadata such as the selected model, latency, and estimated savings. Its main value is letting agents reserve expensive frontier models for complex reasoning while offloading routine language tasks to cheaper specialized routes. -
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NeMo Retriever Library
Document content and metadata extraction microservice
...It processes various document types by splitting them into components such as text, tables, charts, and images, and then applies OCR and contextual analysis to convert them into structured data formats. The system is built on NVIDIA NIM microservices, enabling high-performance parallel processing and efficient handling of large datasets. It supports multiple extraction strategies for different document formats, balancing accuracy and throughput depending on the use case. Additionally, it can generate embeddings for extracted content and integrate with vector databases like Milvus, making it well-suited for retrieval-augmented generation pipelines. -
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MatImage
Image Processing library for Matlab
matImage is an open-source MATLAB library for image processing and analysis. It provides a variety of tools for image enhancement, segmentation, and feature extraction. It’s especially useful for users working on biomedical images or those needing detailed image analysis in MATLAB. -
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tsfresh
Automatic extraction of relevant features from time series
tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python.... -
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Scribe.js
JavaScript OCR and text extraction for images and PDFs
...In addition to simple text extraction, Scribe.js supports writing or injecting a high-quality invisible text layer back into PDFs, effectively making them searchable and improving usability for indexing or accessibility. It is written in modern ECMAScript Modules (ESM), so it can be imported in both browser and Node.js environments without a build step, though browser usage requires same-origin hosting of the files.