Search Results for "data extraction"
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Showing 120 open source projects for "data extraction"
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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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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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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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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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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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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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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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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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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. -
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LiteParse
A fast, helpful, and open-source document parser
...It also includes mechanisms for validation and error handling, ensuring that outputs conform to expected schemas and reducing the need for manual postprocessing. The library is particularly useful for tasks such as data extraction, document processing, and building pipelines that require structured outputs from natural language input. -
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RAGFlow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data. -
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Bespoke Curator
Synthetic data curation for post-training and data extraction
Curator is an open-source Python library designed to build synthetic data pipelines for training and evaluating machine learning models, particularly large language models. The system helps developers generate, transform, and curate high-quality datasets by combining automated generation with structured validation and filtering. It supports workflows where models are used to produce synthetic examples that can later be refined into reliable training datasets for reasoning, question answering, or structured information extraction tasks. ... -
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Vectorize MCP Server
Official Vectorize MCP Server
The Vectorize MCP Server is a Model Context Protocol server that integrates with Vectorize, offering advanced vector retrieval and text extraction capabilities. -
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The Web MCP
A powerful Model Context Protocol (MCP) server
Bright Data’s Web MCP server gives AI assistants robust, real-time web capabilities through an MCP interface designed to avoid blocks, rate limits, and CAPTCHAs. It presents search, crawl, navigate, and extraction tools that agents can call directly, replacing brittle scraping prompts with typed operations. The README markets it as a “gateway” to the live web so assistants don’t fall back to stale training data. Bright Data also advertises a getting-started tier with a free monthly allotment, plus options for remote or self-hosted operation depending on governance needs. ... -
18
web-access
Skill for installing full networking capabilities for Claude Code
web-access is a tool designed to give AI agents structured and controlled access to web content, enabling them to retrieve, navigate, and process information from online sources in real time. It abstracts common web interactions such as page loading, data extraction, and navigation into reusable functions that can be invoked by agents. The system emphasizes safety and control, likely including mechanisms to manage permissions, rate limits, and content filtering. This allows agents to operate within defined boundaries while still benefiting from dynamic, up-to-date information. The architecture supports integration with broader agent frameworks, making it a key component for building systems that require external knowledge. ... -
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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. ... -
20
Magnitude
Vision AI browser agent for automation, testing, and extraction
...This approach allows the agent to generalize better across complex and modern websites, making it more robust than traditional selector-based automation tools. Browser Agent by Magnitude supports a wide range of capabilities including navigation, interaction, data extraction, and automated verification through built-in testing features. Developers can use it to automate repetitive web tasks, integrate services without APIs, or build advanced browser-based agents. It also provides flexible abstraction levels, allowing both high-level task execution and precise low-level control of actions like mouse movements and keyboard input. -
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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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Browser Agent
AI Browser Agent is an advanced Browser AI tool
Browser Agent Python is an AI-powered browser automation tool developed by Oxylabs that enables users to control web interactions through natural language instead of traditional scripting. The tool allows developers to describe tasks in plain English, such as navigating pages, clicking elements, filling forms, and extracting data, and the system executes those actions as if a human were interacting with the browser. It is designed to simplify complex automation workflows by removing the need... -
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video2robot
End-to-end pipeline converting generative videos
...Video2robot includes scripts for each stage of the pipeline (generation, extraction, conversion, visualization) and can run as a CLI or through a basic web UI. -
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Superlinked
Superlinked is a Python framework for AI Engineers
Superlinked is a Python framework designed for AI engineers to build high-performance search and recommendation applications that combine structured and unstructured data. -
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docext
An on-premises, OCR-free unstructured data extraction
docext is a document intelligence toolkit that uses vision-language models to extract structured information from documents such as PDFs, forms, and scanned images. The system is designed to operate entirely on-premises, allowing organizations to process sensitive documents without relying on external cloud services. Unlike traditional document processing pipelines that rely heavily on optical character recognition, docext leverages multimodal AI models capable of understanding both visual...