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LlamaIndex Cloud / LlamaParse API

LlamaIndex Cloud / LlamaParse API

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LlamaIndex Cloud / LlamaParse API focuses on RAG data pipelines — complex PDF / document parsing, converting documents to LLM-ready structured data.

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Use it when

LlamaParse far better than open-source pdfplumber etc. on complex PDFs (tables + charts)

Watch for

Complex PDF parsing per-page billing ($0.003/page), expensive at scale

First check

Sign up at cloud.llamaindex.ai for API key. Python: from llama_parse import LlamaParse; parser.load_data(["doc.pdf"])

Auth
api_key
CORS
?
HTTPS
Yes
Signup
?
Protocol
REST
Pricing
freemium

Uptime · 30-day window

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01

About this API

LlamaIndex is an open-source project founded by Jerry Liu in 2022 (originally GPT Index), co-leader with LangChain among LLM app frameworks. If LangChain is "general LLM application framework" (chains / agents / RAG / everything), LlamaIndex is "focused on RAG data side" — deeper in ingestion, indexing, retrieval pipeline. Commercialization via LlamaCloud SaaS: (1) LlamaParse — parses complex PDFs (tables, charts, scanned docs), outputs LLM-ready markdown or JSON; industry-leading quality (far better than open-source tools on financial 10-K reports, medical papers, and other complex documents); (2) LlamaCloud hosted vector index pipeline — data ingestion, embedding, indexing, query all managed; enterprise RAG apps with no ops. Customers lean enterprise RAG (finance, legal, medical — fields needing complex document processing).

02

What you can build

  • 1Complex PDFs (with tables, charts) parsing for LLM RAG
  • 2Financial reports / legal contracts / research papers structuring
  • 3Enterprise knowledge base ingestion
  • 4Multi-source data (PDF / Word / web) unified ingestion
03

Strengths & limitations

Strengths

  • LlamaParse far better than open-source pdfplumber etc. on complex PDFs (tables + charts)
  • LlamaIndex Python library is co-leader with LangChain in RAG
  • LlamaCloud SaaS hosts data pipelines

Limitations

  • Complex PDF parsing per-page billing ($0.003/page), expensive at scale
  • Ecosystem slightly smaller than LangChain
04

Example request

Generic template — replace <endpoint> with the real path from the docs.
curl https://www.llamaindex.ai/<endpoint> \
  -H "Authorization: Bearer $API_KEY"
# Some providers use X-Api-Key instead — verify in the docs.
05

Getting started

Sign up at cloud.llamaindex.ai for API key. Python: from llama_parse import LlamaParse; parser.load_data(["doc.pdf"])

06

FAQ

LlamaIndex vs. LangChain?+

RAG-focused: LlamaIndex deeper. General LLM apps: LangChain ecosystem more complete. Many projects use both libs.

How much better is LlamaParse than open-source pdfplumber?+

Complex PDFs (nested tables, charts, scans): completely different tier. Simple PDFs: open-source tools suffice.

07

Technical details

CORS: ?HTTPS: YesSignup: ?Open source: No
Auth type
api_key
Pricing
freemium
Rate limit
LlamaParse free 1000 pages/天；商业按页计费
Protocols
REST
SDKs
python, typescript
08

Tags

llamaindexragpdf-parsingdata-ingestionai