LangChain is a powerful framework designed to simplify the development of applications that utilize language models. One of its standout features is the Document Loaders.
Document Loaders allow developers to easily ingest a variety of document types, converting them into a format that can be processed by language models. This is particularly helpful when dealing with large datasets or documents in different formats. Here’s a simple example of how to use a Document Loader in LangChain:
from langchain.document_loaders import TextLoader
# Load a text document
loader = TextLoader("path/to/your/document.txt")
documents = loader.load()
# Print the loaded documents
for doc in documents:
print(doc)
This code snippet demonstrates how to load a text file using LangChain's TextLoader. Once loaded, the document is ready to be processed further, enabling seamless interaction with any downstream language model tasks.
Whether you're working with PDFs, text files, or web pages, LangChain’s Document Loaders can help streamline your workflow and enhance your application’s capabilities.