Principle:Hpcaitech ColossalAI Document Loading

Knowledge Sources	ColossalAI LangChain Document Loaders
Domains	RAG, Data_Engineering
Last Updated	2026-02-09 00:00 GMT

Overview

A multi-format document ingestion pattern that loads various file types into a unified Document representation for downstream processing in RAG pipelines.

Description

Document Loading abstracts the complexity of reading different file formats (PDF, CSV, JSON, HTML, Markdown, TXT) into a common Document object containing text content and metadata. This is the entry point for the RAG pipeline, converting heterogeneous data sources into processable text.

Usage

Use this as the first step in any RAG application to ingest user documents.

Theoretical Basis

The loading pattern uses format-specific loaders dispatched by file extension:

• .pdf -> PyPDFLoader
• .csv -> CSVLoader
• .json/.jsonl -> JSONLoader with JQ schema
• .html -> UnstructuredHTMLLoader
• .md -> UnstructuredMarkdownLoader
• .txt -> TextLoader

Related Pages

Implemented By

• Implementation:Hpcaitech_ColossalAI_DocumentLoader