DirectoryLoader
DirectoryLoader is a LangChain document-loading component that discovers files in a directory and delegates format-specific extraction to an underlying loader.
Build Python Web Apps with Streamlit
DirectoryLoader is a LangChain loader that discovers and loads files from a specified directory.
- How it is used
- Loads text files from a directory as the ingestion stage of a retrieval-augmented application.
- How deep it goes
- Defines glob selection, delegated file loading, and Document output, then defers chunking to a separate splitter.
- Examples
- Uses an articles/ folder, the **/*.txt pattern, TextLoader, and a loader.load() call.
- What you can do after
- Apply it via LangChain to turn a directory of text files into documents ready for splitting and vector storage.
Read how Build Python Web Apps with Streamlit explains DirectoryLoader →
Machine Learning Platform Engineering
DirectoryLoader is a document-loading component that recursively discovers files in directories and converts them into standardized document objects.
- How it is used
- Loads recursively organized documentation into the retrieval pipeline used to build a searchable knowledge base.
- How deep it goes
- Explains recursive traversal, file matching, loader selection, encoding, and loading, then hands documents to chunking.
- Examples
- Uses nested Markdown documentation, TextLoader, UTF-8 decoding, and a FAISS indexing pipeline as concrete examples.
- What you can do after
- Build it from scratch by loading selected files into standardized documents for chunking and vector indexing.
Read how Machine Learning Platform Engineering explains DirectoryLoader →
Related concepts
- glob moduleuses · The glob module is a Python standard-library module for finding filesystem pathnames that match shell-style wildcard patterns.
- Documentproduces · A discrete representation of information, such as content or a structured record, optionally accompanied by metadata.
- vector databaseuses · A vector database is a data-management system that stores and indexes numerical vector representations and supports retrieval through similarity or distance searches.
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