llama-index-readers-wellmarked 0.1.0

Official LlamaIndex reader for the WellMarked API — load any URL as clean Markdown.

llama-index-readers-wellmarked

The official LlamaIndex reader for WellMarked — load any URL as clean Markdown Documents.

pip install llama-index-readers-wellmarked

Quick start

Set your API key (get one at wellmarked.io):

export WELLMARKED_API_KEY="wm_..."

Load a single page:

from llama_index.readers.wellmarked import WellMarkedReader

reader = WellMarkedReader()
docs = reader.load_data("https://example.com/article")

docs[0].text       # 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):

reader = WellMarkedReader(mode="crawl", depth=2)
docs = reader.load_data("https://docs.example.com")

docs[0].metadata["depth"]   # how far from the root URL this page sits

Drop the documents straight into an index:

from llama_index.core import VectorStoreIndex

index = VectorStoreIndex.from_documents(docs)

Options

All options are constructor arguments; load_data(url) takes only the URL.

Parameter	Default	Description
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
• langchain-wellmarked — the LangChain equivalent