Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥
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Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
- ocr
- chineseocr
- pdf2markdown
- pp-ocr
Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.
Replace 'hub' with 'ingest' in any GitHub URL to get a prompt-friendly extract of a codebase
- ai
- code
- ingestion
- developer-tool
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
- nlp
- embedding
- bert
- ernie
A fast, helpful, and open-source document parser
- document-ocr
- document-processing
- ocr
- ocr-recognition
OCR & Document Extraction using vision models
PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.
- mupdf
- xps
- pdf-documents
- epub
The fast, precise document-intelligence engine for every language: text, tables and metadata from 100+ formats, with OCR, transcription and code intelligence.
- text-extraction
- document-intelligence
- metadata-extraction
- pdf-extraction
A curated, battle-tested AI-coding toolkit: Claude Code plugins, subagent orchestration, quality gates, and ready-to-copy prompts, extracted from real production use.
The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry leaders, 100% pass rate on 3,830 PDFs. MIT/Apache-2.0.
- document-processing
- pdf-editor
- pdf-generation
Turn messy, real-world HTML into clean Markdown, from every major language.
- html-converter
- markdown-converter
- rag
- text-extraction
A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
- artificial-intelligence
- clip
- pathology
- vision-and-language
Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.
Self-hosted web scraper, crawler and document parser for AI agents: URLs, PDFs with OCR and Office files to clean Markdown/JSON. Firecrawl- and Jina-compatible API, MCP server, agent endpoint, Python/Node SDKs. Single Rust binary.
- ai-agents
- browser-automation
- data-extraction
- firecrawl
PDF extraction that audits its own output — and certifies any other extractor's, catching pages they silently dropped. Verify signed manifests offline: free, MIT, no account. 0.903 on opendataloader-bench, #2 of 8 engines. 7-tool MCP server.
AI-Driven Full-Text Screening and Data Extraction for Systematic Reviews and Evidence Synthesis
- academic-research
- ai-assistant
- ai-tool
- data-extraction