.ipynb
.pdf
2Markdown
2Markdown#
2markdown service transforms website content into structured markdown files.
# You will need to get your own API key. See https://2markdown.com/login
api_key = ""
from langchain.document_loaders import ToMarkdownLoader
loader = ToMarkdownLoader.from_api_key(url="https://python.langchain.com/en/latest/", api_key=api_key)
docs = loader.load()
print(docs[0].page_content)
## Contents
- [Getting Started](#getting-started)
- [Modules](#modules)
- [Use Cases](#use-cases)
- [Reference Docs](#reference-docs)
- [LangChain Ecosystem](#langchain-ecosystem)
- [Additional Resources](#additional-resources)
## Welcome to LangChain [\#](\#welcome-to-langchain "Permalink to this headline")
**LangChain** is a framework for developing applications powered by language models. We believe that the most powerful and differentiated applications will not only call out to a language model, but will also be:
1. _Data-aware_: connect a language model to other sources of data
2. _Agentic_: allow a language model to interact with its environment
The LangChain framework is designed around these principles.
This is the Python specific portion of the documentation. For a purely conceptual guide to LangChain, see [here](https://docs.langchain.com/docs/). For the JavaScript documentation, see [here](https://js.langchain.com/docs/).
## Getting Started [\#](\#getting-started "Permalink to this headline")
How to get started using LangChain to create an Language Model application.
- [Quickstart Guide](https://python.langchain.com/en/latest/getting_started/getting_started.html)
Concepts and terminology.
rtdocs_stable/api.python.langchain.com/en/stable/modules/indexes/document_loaders/examples/tomarkdown.html