LlamaIndex data reader for Reader. Load web pages as LlamaIndex Documents for RAG pipelines and knowledge bases.
pip install llama-index-readers-readerfrom llama_index_readers_reader import ReaderWebReader
reader = ReaderWebReader(api_key="rdr_...")
# Single URL
docs = reader.load_data(urls=["https://example.com"])
print(docs[0].text) # Markdown content
print(docs[0].metadata) # {"url": "...", "title": "..."}
# Multiple URLs (batch)
docs = reader.load_data(urls=[
"https://example.com/page1",
"https://example.com/page2",
])from llama_index.core import VectorStoreIndex
reader = ReaderWebReader(api_key="rdr_...")
docs = reader.load_data(urls=["https://docs.example.com/getting-started"])
index = VectorStoreIndex.from_documents(docs)
query_engine = index.as_query_engine()
response = query_engine.query("How do I get started?")| Parameter | Type | Default | Description |
|---|---|---|---|
api_key |
str | required | Reader API key |
base_url |
str | None | Custom API URL for self-hosted Reader |
proxy_mode |
str | None | "standard" or "premium" |
only_main_content |
bool | True | Extract main content only |
MIT