124 repository-uri
Specialized tools for extracting specific data points into structured formats.
Distinguishing note: Focuses on schema-based extraction from complex documents.
Explore 124 awesome GitHub repositories matching data & databases · Structured Data Extraction. Refine with filters or upvote what's useful.
Firecrawl is a headless browser automation tool and web crawling engine designed to extract structured data from the web. It functions as an API that transforms raw website content and documents into clean markdown and JSON formats to serve as context for large language models. The project distinguishes itself by using natural language prompts to translate human instructions into targeted data extraction tasks and browser actions. It can execute interactive page navigation, such as clicking and scrolling, and perform automated web research to retrieve structured data without manual interventi
Firecrawl extracts information from any website and converts it into formats specifically tailored for large language models.
OpenCV is an open-source computer vision library and visual analysis toolkit. It provides a framework for processing static images and dynamic video frames to analyze visual data and extract information using deep learning. The project functions as a real-time image processing framework, enabling the execution of vision algorithms on live video streams for immediate analysis and data processing. The toolkit covers a broad range of capabilities including image pattern recognition, real-time video analysis, and visual data extraction. It also supports automated visual inspection for detecting
Converts raw visual information from images and video into structured data for automated decision making.
Langextract is a framework designed to transform unstructured text into structured, machine-readable data using language model orchestration. It provides a high-performance pipeline that processes large volumes of narrative text by utilizing parallel execution and sequential extraction passes. The library is built to handle complex data extraction tasks, including specialized support for clinical information and medical entity relationship recognition. The project distinguishes itself through a plugin-based architecture that supports both local hardware execution and cloud-hosted model endpoi
Processes long documents using parallel execution and sequential passes to convert unstructured text into organized data formats.
Marker is an LLM-powered document parser and OCR pipeline designed to convert PDFs and unstructured files into structured markdown, JSON, and HTML. It functions as a data preprocessor that transforms complex documents into machine-readable formats while preserving tables, equations, and layout structures. The system utilizes large language models to refine OCR accuracy, clean mathematical notation, and merge fragmented tables across multiple pages. It employs model-based layout analysis to predict block types and bounding boxes, ensuring a more precise conversion of document elements. Capabi
Maps unstructured document text into specific JSON formats using predefined schemas and language models.
Marker is a comprehensive document processing platform designed to automate the conversion, extraction, and structuring of data from complex files. It functions as an orchestration engine that chains modular processing steps into versioned, reusable pipelines, allowing organizations to standardize document handling and automate repetitive business tasks at scale. The platform distinguishes itself through its support for secure, private infrastructure deployment, enabling users to run containerized services within their own environments to maintain strict data privacy. It features specialized
Identifies and extracts specific information like dates or legal clauses from complex documents.
This project is a high-performance headless browser engine designed for scalable web automation, data extraction, and AI agent integration. It provides a specialized environment that allows autonomous agents and testing frameworks to interact with web content through standardized remote control protocols. By executing pages in a lightweight, headless state, the engine minimizes resource consumption while maintaining the ability to perform complex navigation and dynamic content rendering. The platform distinguishes itself through deep integration with AI-centric communication layers and advanc
Generates pruned, structured representations of live documents including roles and interactivity status to help agents navigate page content efficiently.
Scrapegraph-ai is a Python framework that uses large language models to automate the extraction of structured data from websites and documents. It functions as an AI-driven data extraction pipeline that converts unstructured web content into structured formats using natural language processing and graph-based logic. The project utilizes graph-based task orchestration to model scraping workflows as interconnected nodes. It features a pluggable model interface for connecting to cloud or local artificial intelligence providers and can generate executable Python code on the fly to handle site-spe
Identifies and pulls specific data from websites or local documents into structured formats using natural language processing.
Colly is a web scraping framework and concurrent crawler written in Go. It provides a system for traversing web pages, following links, and extracting structured data from HTML and XML documents. The framework includes a distributed scraping engine designed to spread data collection tasks across multiple instances to increase throughput. It ensures compliance with website owner policies by automatically reading and respecting robots.txt files. The system manages request lifecycles through domain-based rate limiting, concurrency controls, and session management via a stateful cookie jar. It s
Parses HTML content to collect specific, structured data points for mining and archiving.
Kotaemon is an orchestration framework designed for building modular, agentic workflows that integrate document processing, retrieval-augmented generation, and multi-step reasoning. It provides a comprehensive platform for developing document-based question answering systems, allowing users to chain language models, prompt templates, and external tools into complex, automated pipelines. The system distinguishes itself through a highly modular architecture that emphasizes component-based composition and schema-driven data exchange. It supports autonomous agents capable of decomposing complex q
Extracts distinct text, table, and image components from PDFs using cloud-based services.
OpenCLI is an AI browser automation framework designed to automate web navigation, data extraction, and repetitive browser tasks. It functions as a browser-based CLI generator that converts website interfaces into command-line interactions by controlling authenticated web browser sessions. The project features a web-to-CLI adapter platform for mapping web elements to programmatic command-line inputs and outputs. It includes a browser profile manager to organize and switch between isolated session profiles to maintain different user identities. The toolkit provides capabilities for web conten
Provides a mechanism to map website DOM patterns to structured data outputs using predefined rules.
Graphite is a node-based visual design environment that integrates vector illustration, raster image processing, and motion graphics generation into a single platform. It utilizes a functional reactive pipeline and a data-flow execution model to propagate state changes through a graph of interconnected nodes, allowing users to construct complex, automated design workflows. The platform distinguishes itself through a context-aware evaluation engine that injects runtime metadata—such as coordinate data and loop indices—directly into the node graph. This enables the creation of procedural geomet
Retrieves specific named properties from graphic elements and organizes them into structured lists for processing.
Crawlee is a web scraping framework designed for building scalable, reliable, and distributed data extraction pipelines. It provides a unified interface for managing headless browser automation and lightweight HTTP requests, allowing developers to handle complex web navigation, dynamic content rendering, and large-scale data collection within a single, modular architecture. The project distinguishes itself through its resource-aware concurrency controller, which dynamically scales task execution based on real-time CPU and memory usage to prevent host machine exhaustion. It also features a rob
Parses raw HTML or JSON responses using selectors to transform unstructured content into clean data.
simdjson is a high-performance, header-only C++ library designed for parsing, querying, and serializing JSON data with minimal memory overhead. It functions as a hardware-aware data processing engine that leverages vector instructions to achieve gigabyte-per-second parsing speeds. By detecting host processor capabilities at runtime, the library automatically selects the most efficient instruction sets to accelerate structural analysis and validation. The library distinguishes itself through a focus on extreme efficiency and resource management. It utilizes memory mapping and padded buffer ali
Navigating and querying nested JSON structures lazily to retrieve specific values without the overhead of parsing entire documents into memory.
Skyvern is an autonomous web navigation agent and browser-based workflow orchestrator that uses large language models to execute multi-step tasks on websites. By translating natural language instructions into actionable browser commands, the framework enables the automation of complex user workflows, including data extraction and interface interaction, without manual intervention. The platform distinguishes itself through a focus on secure, self-hosted infrastructure and stealth-oriented execution. It utilizes containerized browser isolation to maintain consistent environments and employs pro
Extracts specific data points into structured formats from complex web documents.
This project provides a framework for managing multi-agent systems, designed to automate complex software development, infrastructure, and business workflows. It functions as a multi-agent workflow orchestrator that routes tasks to domain-specific workers while maintaining state persistence and infrastructure automation. By leveraging large language models, the system decomposes high-level objectives into actionable plans, ensuring that complex operations are executed with consistency and reliability. The framework distinguishes itself through its hierarchical agent registry and policy-driven
Searches research databases to extract structured experimental details for evidence-based analysis.
Stagehand is an AI-native browser automation framework that enables developers to build reliable web automations using a hybrid of natural language instructions and deterministic TypeScript code.
Extracts structured information from web pages into organized formats for downstream processing.
Surya is a document processing platform designed to transform unstructured files into structured, machine-readable data. It provides a comprehensive suite of tools for text recognition, layout analysis, and reading order detection, enabling the conversion of PDFs and images into formats such as JSON, HTML, or markdown. The platform is built to handle complex document workflows, offering capabilities for data extraction, document segmentation, and automated form completion. The platform distinguishes itself through a robust pipeline-based architecture that allows users to chain analysis tasks
Parses unstructured document content into predefined fields using centralized schemas for consistent machine-readable output.
GHunt is a Google account investigator and open-source intelligence framework designed to retrieve publicly available information and metadata associated with Google accounts. It functions as an OSINT data extractor and offensive security framework used to identify user identities and uncover hidden metadata. The tool extracts public profile data from various Google services and exports the findings into structured JSON formats. This allows for the collection and analysis of digital footprints to support security research and reconnaissance.
Retrieves account details and service metadata from Google and exports them into structured formats.
Qbot is a multi-purpose platform designed to support automated recruitment, quantitative trading, and distributed service orchestration. It functions as a comprehensive framework that integrates artificial intelligence into specialized workflows, enabling users to build and deploy systems for candidate screening, financial strategy execution, and context-aware knowledge retrieval. The platform distinguishes itself through a modular architecture that combines high-performance distributed communication with domain-specific automation. It provides a robust foundation for managing microservices t
Extracts candidate information from uploaded documents into structured profiles using asynchronous processing and automated retries.
DataX is a distributed data integration framework and plugin-based ETL tool designed for synchronizing large datasets between heterogeneous sources and destinations. It functions as a JDBC data migration engine and offline synchronization tool, enabling the movement of data between relational databases, NoSQL stores, and object storage. The system utilizes a plugin-based connector architecture that decouples reader and writer logic, allowing it to map and transform data types across different storage engines using a standardized internal representation. This design supports heterogeneous data
Extracts text and field names from structured data files such as CSV and TXT using custom delimiters.