pdf-processing

Document chatbot — multiple files, topics, chat windows and chat history. Powered by GPT.

library supporting NLP and CV research on scientific papers

Open-source toolkit for reliable RAG pipelines: convert PDFs to Markdown, clean documents, inspect chunks, compare chunking strategies, and enrich metadata for LLM applications.

A Model Context Protocol (MCP) server implementation that integrates with the Nutrient Document Web Service (DWS) Processor API, providing powerful PDF processing capabilities for AI assistants.

Anthropic's Contextual Retrieval implementation with visual chunk comparison. Preview context enrichment before/after embedding.

Turn documents into high-quality instruction datasets with grounding, quality filtering, deduplication, and provenance.

Vortex is a self-hosted RAG (Retrieval-Augmented Generation) application that lets you chat with your documents using any LLM provider. Upload PDFs, ingest URLs, and get accurate answers grounded in your own knowledge bases — all with a clean, modern interface.

Local RAG app with zero-config Docker setup. FastAPI + Streamlit + Qdrant + Ollama. Just run `docker-compose up --build`! 🚀

LangGraphRAG: A terminal-based Retrieval-Augmented Generation system using LangGraph. Features include message history caching, query transformation, and vector database retrieval. Ideal for NLP researchers and developers working on advanced conversational AI and information retrieval systems.

LegalEase AI is a document simplification tool built using Gemini API, Streamlit, and Hugging Face models. It allows users to upload legal PDFs and automatically receive simplified summaries, clause-level insights, and structured information designed for clarity and accessibility.