LangExtract is a Python library for extracting structured information (entities, relationships) from unstructured text using large language models (LLMs). It provides a production-grade pipeline: chunking long documents, building prompts with few-shot examples, invoking LLMs (Gemini, OpenAI, Ollama, or custom providers), parsing and fuzzy-aligning the output to source text, and generating interactive HTML visualizations. The architecture is modular with a plugin system for providers, a schema system for output constraints, and a resolver for alignment. It includes comprehensive tests, benchmarks, and CI/CD. The library is actively maintained with a clear deprecation path for v2.0.0. Notable strengths are the provider plugin system, fuzzy alignment algorithms, and format handling. Weaknesses include some deprecation debt and complex alignment code.
This repository is a comprehensive survey paper on the intersection of knowledge graphs and multi-modal learning. It organizes the literature into two main directions: KG-driven multi-modal learning (KG4MM) and multi-modal knowledge graphs (MM4KG). The survey covers various tasks such as visual question answering, image classification, multi-modal named entity recognition, and knowledge graph completion, among others. Each section includes a list of relevant papers with links to their sources (e.g., arXiv, conference proceedings). The repository is maintained through updates that include adding new papers and fixing links, as evidenced by the recent commit in 2026 and the news items up to 2024-12.
The AIL (Advanced Information Leak) framework is a threat intelligence platform designed for collecting, processing, analyzing, and correlating digital artifacts from various sources including web crawlers, darknet content, forums, chats, and file submissions. It features a modular architecture with a Flask-based web interface, REST API, and background processing workers that communicate via Redis queues. The system extracts entities and relationships from raw data, stores them in Kvrocks (with Redis for caching), provides correlation analysis, and exports processed information to threat intelligence platforms like MISP and TheHive. Key components include extensible processing modules, a flexible object modeling system, and robust queue management for distributed processing.