Search Results for "data extraction"
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Showing 377 open source projects for "data extraction"
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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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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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webclaw
Fast, local-first web content extraction for LLMs
webclaw is a high-performance web content extraction tool designed specifically for AI agents and large language models, focusing on delivering clean, structured data instead of raw HTML. It is built in Rust and operates without a headless browser, using advanced techniques such as TLS fingerprinting to bypass common scraping barriers and mimic real browser behavior. The tool addresses a major inefficiency in AI workflows by removing irrelevant elements like navigation menus, ads, and scripts, significantly reducing token usage when feeding data into language models. ... -
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Sparrow
Structured data extraction and instruction calling with ML, LLM
...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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Scanopy
Clean network diagrams, One-time setup, zero upkeep
Scanopy is a powerful multi-modal data capture and analysis toolkit that enables users to collect, process, and visualize structured and unstructured information from a variety of sources in a flexible pipeline. It is built to handle complex scanning tasks — such as OCR, document analysis, audio transcription, network data capture, and image extraction — while providing unified APIs and workflows that make managing heterogeneous data sources seamless. ... -
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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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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. The core output is designed for downstream automation, producing structured... -
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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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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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AI-Crawler
Crawl a website starting from a URL, find relevant pages
AI Crawler is an experimental AI-powered web crawling and data extraction tool that uses natural language prompts to guide the discovery and retrieval of relevant information across websites. Unlike traditional web scrapers that rely on static selectors and manual scripting, it uses AI to dynamically identify and prioritize pages based on user intent, making it more flexible and resilient to changes in website structure. -
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kimuraframework
AI-first Ruby framework for building fast, flexible web scraping spide
Kimurai is an open source web scraping framework written in Ruby that simplifies the process of building automated data extraction tools. It provides a clean domain-specific language that allows developers to define scraping logic and data schemas with minimal boilerplate code. Kimurai can use AI-assisted extraction to identify where data resides in HTML pages, automatically generating selectors that are cached for future use so subsequent scraping runs operate with pure Ruby performance. ... -
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AgentQL MCP
Model Context Protocol server that integrates AgentQL's data
The AgentQL MCP Server is a Model Context Protocol (MCP) server that integrates AgentQL's data extraction capabilities, enabling users to extract structured data from web pages using natural language prompts. -
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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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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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book-to-skill
Turn any technical book PDF into a Claude Code skill
book-to-skill is a Claude Code skill that turns technical books and documents into reusable AI reference skills. It extracts content from PDFs and EPUBs, then organizes the material so an assistant can study, reference, and apply it while working. The project is useful for transforming dense manuals, textbooks, internal documentation, or technical guides into practical agent-accessible knowledge. It includes an extraction script and a SKILL.md workflow that guides how the resulting content... -
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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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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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watercrawl
AI-ready web crawler that extracts and structures website content
...WaterCrawl supports customizable extraction rules so users can focus only on relevant elements while ignoring unnecessary page components. WaterCrawl also offers real-time monitoring capabilities, allowing users to track crawling progress, performance metrics, and errors during large data collection jobs. Developers can integrate the tool into applications through a REST API and multiple client SDKs, enabling automated data pipelines and AI data preparation workflows. -
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BlockArrays.jl
BlockArrays for Julia
A block array is a partition of an array into blocks or subarrays, see Wikipedia for a more extensive description. This package has two purposes. Firstly, it defines an interface for an AbstractBlockArray block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays. Secondly, it also implements two different types of block arrays that follow the AbstractBlockArray interface. The type... -
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Ferret
Declarative web scraping
A web scraping system aiming to simplify data extraction from the web. ferret has a declarative query language that makes it easy to focus on the data that you need to get. ferret has the ability to scrape JS rendered pages, handle all page events, and emulate user interactions. the ferret was designed as a library from the ground up. it can be easily embedded into any Go application. ferret helps you to focus on the data you need using an easy-to-learn declarative language. ferret uses Chrome/Chromium via Chrome Devtools Protocol to handle dynamically rendered web pages. ferret is extremely extensible, and creating custom functions and types is super easy. ferret allows users to focus on the data. ... -
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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. It is built for developers who need high-quality parsing from scans, photos, PDFs, office files,... -
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mtail
Extract internal monitoring data from application logs
Extract internal monitoring data from application logs for collection in a time-series database. mtail is a tool for extracting metrics from application logs to be exported into a timeseries database or timeseries calculator for alerting and dashboarding. 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. ... -
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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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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.
