Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling
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Updated
May 15, 2026 - Python
Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling
Hybrid RAG system combining vector search, knowledge graph (LightRAG), and cross-encoder reranking — with Docling document parsing, visual intelligence (image/table captioning), agentic streaming chat, and inline citations. Powered by Gemini or local Ollama models.
A Python package for converting PDFs to markdown while extracting images and tables, generate descriptive text descriptions for extracted tables/images using several LLM clients. And many more functionalities. Markdrop is available on PyPI.
Collection of PDF parsing libraries like AI based docling, claude, openai, gemini, meta's llama-vision, unstructured-io, and pdfminer, pymupdf, pdfplumber etc for efficient snapshot, text, table, and metadata extraction.
Transform unstructured documents into validated, rich and queryable knowledge graphs.
PDFStract - Extract, Chunking and Embedding Layer in Your RAG Pipeline - Available as CLI - WEBUI - API
Python, LlamaIndex, LangChain, Docker Compose: 15 Property Graph, 4 RDF , 10 Vector, OpenSearch, Elasticsearch, Alfresco DBs. 13 data sources (9 auto-sync), KG auto-building, Ontologies, LLMs, Docling or LlamaParse doc processing, GraphRAG, RAG only, Hybrid Search, AI Chat. TypeScript React, Vue, Angular frontends, FastAPI REST backend, MCP Server.
Convert and validate your Markdown, then choose the best chunking strategy for your RAG pipeline.
Docling with Ollama - RAG on Local Files with Local Models
PDF extraction that checks its own work. #2 reading order accuracy — zero AI, zero GPU, zero cost.
A python library and CLI tool to convert PDF files to CSV files.
DocChat is an AI-powered Multi-Agent RAG system using Docling for structured document parsing and BM25 + vector search retrievers to retrieve fact-checked answers from PDFs, DOCX, and text files, preventing hallucinations. 🚀
Autonomous agent networks for task automation that requires multi-step reasoning
A TypeScript SDK for Docling - Bridge between the Python Docling ecosystem and JavaScript/TypeScript.
Docling4j brings the functionalities of Docling in document understanding to Java® projects
Privacy-first document intelligence engine — parse PDFs, DOCX, PPTX, XLSX & CSV into AI-ready chunks for RAG pipelines. Includes HITL review, 3-layer memory chat, and a production FastAPI server.
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