Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling
-
Updated
Apr 3, 2026 - Python
#
docling
Here are 139 public repositories matching this topic...
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.
react streaming citation gemini knowledge-graph knowledge-base reranking rag fastapi vector-search document-parsing chromadb retrieval-augmented-generation ollama docling lightrag
-
Updated
Apr 4, 2026 - Python
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.
open-source pdf-to-text image-to-text marker agents pypi-package table-to-text markitdown llm pdf-to-markdown docling markdrop
-
Updated
Mar 18, 2026 - Python
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.
ocr openai claude camelot pymupdf pypdf ocr-python markitdown gemini-pro gemini-ai llama-parse omniai unstructured-io docling llama-vision mistral-ocr smoldocling llama4
-
Updated
Mar 27, 2026 - Python
PDFStract - Extract, Chunking and Embedding Layer in Your RAG Pipeline - Available as CLI - WEBUI - API
pdf ocr ai knowledgebase data-extraction chunking dataengineering unstructured rag rag-pipeline docling pdfconversion
-
Updated
Mar 18, 2026 - Python
Transform unstructured documents into validated, rich and queryable knowledge graphs.
-
Updated
Apr 3, 2026 - Python
Docling with Ollama - RAG on Local Files with Local Models
-
Updated
Jan 1, 2025 - Python
PDF extraction that checks its own work. #2 reading order accuracy — zero AI, zero GPU, zero cost.
python pdf ocr mcp self-healing structured-extraction rag pdf-to-json pdf-extraction ai-agent llm document-parsing pdf-to-markdown docling opendataloader
-
Updated
Mar 31, 2026 - Python
Convert and validate your Markdown, then choose the best chunking strategy for your RAG pipeline.
markdown chunking document-processing document-extraction rag pdf-processing chunking-algorithm text-splitter llms langchain retrieval-augmented-generation ollama rag-evaluation rag-pipeline pdf-to-markdown chonkie docling document-chunking semantic-chunker chunk-validation
-
Updated
Apr 3, 2026 - TypeScript
A python library and CLI tool to convert PDF files to CSV files.
-
Updated
Jan 6, 2025 - Python
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. 🚀
-
Updated
Oct 6, 2025 - Python
Autonomous agent networks for task automation that requires multi-step reasoning
orchestration-framework python3 networkx graph-theory matplotlib multi-agent-systems autonomous-agents pygraphviz self-directed-learning rag pydantic multi-step-reasoning langchain litellm agentic-ai composiotool mem0ai docling
-
Updated
Sep 1, 2025 - Python
Docling4j brings the functionalities of Docling in document understanding to Java® projects
java pdf ai pdf-converter documents document-parser pdf-to-json document-understanding document-parsing docling
-
Updated
Mar 31, 2025 - Java
A TypeScript SDK for Docling - Bridge between the Python Docling ecosystem and JavaScript/TypeScript.
-
Updated
Apr 2, 2026 - TypeScript
OnnxTR OCR plugin for Docling
ocr deep-learning text-recognition text-detection document-processing onnx onnxruntime docling onnxtr
-
Updated
Mar 29, 2026 - Python
Improve this page
Add a description, image, and links to the docling topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the docling topic, visit your repo's landing page and select "manage topics."