{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"}],"enrichment":{"capability":"Integrates Docling document conversion with LangChain, enabling you to load and process documents (PDFs, images, etc.) into LangChain-compatible formats for use in language model pipelines.","skillfed_tags":["document-loading","rag-pipeline","langchain-integration"],"use_cases":["Build a RAG pipeline that ingests PDFs and technical documents into LangChain for semantic search and question-answering.","Convert scanned documents or images to structured text using OCR, then feed them into language models for analysis.","Process multiple document formats (PDF, DOCX, images) in bulk and export as Markdown for downstream NLP tasks.","Integrate document conversion into a LangChain agent that needs to extract and reason over document content.","Use a remote Docling service to offload heavy document processing while keeping your application lightweight."],"what_it_does":"langchain-docling bridges Docling, a document conversion and understanding library, with LangChain's document loading and processing ecosystem. It provides a `DoclingLoader` that can ingest documents from URLs or local files and convert them into LangChain-compatible document objects suitable for downstream language model tasks.\n\nYou can run document conversion locally (with the `local` extra, which includes AI runtimes like PyTorch) or remotely via Docling Serve, Managed Docling, or IBM watsonx. The loader supports multiple export modes (doc chunks or Markdown), custom chunking strategies, metadata extraction, and backend-specific conversion options. It's designed for developers building RAG pipelines, document analysis workflows, or AI-powered search systems that need reliable document ingestion.","worth_installing":"Yes. Active maintenance, no vulnerabilities, low install friction, and permissive MIT license make this a safe choice. Install it if you're building a LangChain application that needs to ingest and process documents\u2014either locally (with the `local` extra) or via a remote Docling endpoint. The base install is lightweight; add the `local` extra only if you need local conversion."},"id":"langchain-docling","links":{"html":"https://skillfed.io/packages/langchain-docling","md":"https://skillfed.io/packages/langchain-docling.md","pypi":"https://pypi.org/project/langchain-docling/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":"MIT","license_treatment":"permissive","name":"langchain-docling","python_support":"supports_current","summary":"Docling LangChain integration"},"popularity":{"monthly_downloads":148992,"position":11009,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"3.0.0"}