Search Results for "data extraction"
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Showing 441 open source projects for "data extraction"
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dude uncomplicated data extraction
dude uncomplicated data extraction: A simple framework
Dude is a very simple framework for writing web scrapers using Python decorators. The design, inspired by Flask, was to easily build a web scraper in just a few lines of code. Dude has an easy-to-learn syntax. Dude is currently in Pre-Alpha. Please expect breaking changes. You can run your scraper from terminal/shell/command-line by supplying URLs, the output filename of your choice and the paths to your python scripts to dude scrape command. -
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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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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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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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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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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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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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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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OpenDataLoader PDF
PDF Parser for AI-ready data. Automate PDF accessibility
OpenDataLoader PDF is an open-source document processing system designed to convert complex PDF files into structured, AI-ready formats such as Markdown, JSON, and HTML while preserving layout, hierarchy, and semantic meaning. It focuses on enabling downstream use cases like retrieval-augmented generation (RAG), knowledge extraction, and document intelligence pipelines by maintaining accurate reading order and spatial metadata through bounding boxes. The tool combines deterministic parsing... -
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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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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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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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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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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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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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Wiseflow
Enhance any agent's browser use skill
Wiseflow is an open-source information extraction and knowledge discovery system designed to collect, filter, and organize valuable information from large volumes of online content. The platform continuously monitors specified sources such as websites, social platforms, and other digital channels to identify relevant data according to user-defined interests or topics. By combining web crawling, content parsing, and large language model analysis, the system extracts concise insights from raw information streams and converts them into structured data that can be stored or analyzed. ... -
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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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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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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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fireworks-tech-graph
Claude Code skill for generating production-quality SVG+PNG technical
fireworks-tech-graph is an AI-driven project focused on building structured knowledge graphs that map relationships between technologies, concepts, and entities within technical domains. It aims to transform unstructured information into interconnected graphs that can be queried and analyzed for insights, making it easier to understand complex ecosystems such as software stacks or research fields. The system likely leverages AI techniques for entity extraction, relationship mapping, and... -
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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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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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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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skycaiji
Open source web scraping system for automated data collection tasks
SkyCaiji is an open source web scraping and data collection system designed to gather information from websites through configurable extraction rules. It focuses on simplifying the process of building crawlers by allowing users to visually define scraping rules rather than writing complex code. It can collect structured or unstructured data from many types of webpages and automate the extraction process for large datasets.
