Official LangChain integration for the WellMarked API — load any URL as clean Markdown.
Project description
langchain-wellmarked
The official LangChain integration for WellMarked — load any URL as clean Markdown Documents.
pip install langchain-wellmarked
Quick start
Set your API key (get one at wellmarked.io):
export WELLMARKED_API_KEY="wm_..."
Load a single page:
from langchain_wellmarked import WellMarkedLoader
loader = WellMarkedLoader("https://example.com/article")
docs = loader.load()
docs[0].page_content # clean Markdown
docs[0].metadata # {"source": ..., "title": ..., "author": ..., "retrieved_at": ...}
Or crawl a whole site BFS-style — one Document per successfully extracted page (Pro plan and above):
loader = WellMarkedLoader("https://docs.example.com", mode="crawl", depth=2)
docs = loader.load()
docs[0].metadata["depth"] # how far from the root URL this page sits
lazy_load() works too, and the loader passes render_js=True through to the API for JS-heavy pages.
Options
| Parameter | Default | Description |
|---|---|---|
url |
(required) | Page to extract, or root URL to crawl from |
api_key |
env var | WellMarked API key; falls back to WELLMARKED_API_KEY |
mode |
"extract" |
"extract" (single page) or "crawl" (same-site BFS) |
depth |
1 |
Crawl depth (mode="crawl" only) |
render_js |
False |
Render JS-heavy pages with a headless browser (Pro and above) |
job_timeout |
300.0 |
Seconds to wait for a crawl job; None waits forever |
In crawl mode, pages that fail to extract (timeouts, robots-disallowed, no content) are skipped; only successful pages become Documents.
Related
wellmarked— the underlying Python SDK (this package wraps it)- WellMarked API docs
llama-index-readers-wellmarked— the LlamaIndex equivalent
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