ModelRefs / Document Loader — AI Glossary
Document Loader — AI Glossary
A connector that reads raw documents from a source (file system, URL, API, database) and converts them to a standardized text format.
Overview
Document loaders handle format heterogeneity: PDFs (PyMuPDF, pdfplumber), HTML (BeautifulSoup), DOCX, CSV, JSON, Confluence, Notion, Google Drive, SharePoint. LangChain and LlamaIndex provide 200+ loader integrations. Output: Document objects with page_content and metadata fields ready for splitting and embedding.
Reference details
| Topic | rag |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
Runs before any of this: it reads a source and produces text, where the splitter divides that text. Confusing the two hides the most common RAG failure — a PDF loader that returns garbled column order or drops table structure means the chunks were wrong before chunking began. When retrieval quality is poor, read the loader's raw output before touching chunk size.
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Frequently asked questions
What is Document Loader?
A connector that reads raw documents from a source (file system, URL, API, database) and converts them to a standardized text format.
What concepts are related to Document Loader?
Closely related concepts include indexing pipeline, text splitter, retrieval pipeline.