Overview of Extract
Introduction to LlamaExtract, a tool for extracting structured data from unstructured documents, available as a web UI, Python SDK, and REST API.
Overview
Section titled “Overview”LlamaExtract provides a simple API for extracting structured data from unstructured documents like PDFs, text files, and images.
LlamaExtract is available as a web UI, Python SDK and REST API.
Is LlamaExtract right for me?
Section titled “Is LlamaExtract right for me?”LlamaExtract is a great fit for when you need:
- Well-typed data for downstream tasks: You want to extract data from documents and use it for downstream tasks like training a model, building a dashboard, entering into a database, etc. LlamaExtract guarantees that your data complies with the provided schema or provides helpful error messages when it doesn’t.
- Accurate data extraction: We use the best in class LLM models to extract data from your documents.
- Iterative schema development: You want to quickly iterate on your schema and get feedback on how well it works on your sample documents. Do you need to provide more examples to extract a certain field? Do you need to make a certain field optional?
- Support for multiple file types: LlamaExtract supports a wide range of file types, including PDFs, text files, and images. Let us know if you need support for another file type!
Quick Start
Section titled “Quick Start”Using the web UI
Section titled “Using the web UI”The simplest way to try out LlamaExtract is to use the web UI.
Just define your Extraction Configuration (schema and settings), drag and drop any supported document into LlamaParse and extract data from your documents.
Get an API key
Section titled “Get an API key”Once you’re ready to start coding, get an API key to use LlamaExtract with the Python SDK.
Use our libraries
Section titled “Use our libraries”We have a library available for Python and Typescript. This is the recommended way to use LlamaExtract for running extraction jobs at scale. Check out the SDK quick start to get started.
REST API
Section titled “REST API”If you are using a language other than Python, you can use the REST API.
Tiers and versions
Section titled “Tiers and versions”LlamaExtract offers three primary tiers in the UI:
- Cost Effective – best when you want lower cost and higher throughput for simpler extraction tasks.
- Agentic – recommended default tier that balances quality, speed, and cost for most real‑world documents.
- Agentic Plus (coming soon) – high‑fidelity tier for very complex or high‑stakes extractions.
LlamaExtract now runs on the v2 APIs by default. If you need to use the legacy Extract v1 experience, see Using Extract v1 below.
When using the SDK or REST API directly, V2 decouples parse and extract tiers. Here is how V2 configurations map to V1 equivalents:
V2 extract tier | V2 parse tier | V1 equivalent (extraction_mode) |
|---|---|---|
cost_effective | fast | FAST |
agentic | agentic | MULTIMODAL |
agentic | agentic_plus | PREMIUM |
Using Extract v1
Section titled “Using Extract v1”LlamaExtract v2 is the default and recommended experience. If you need to use the legacy Extract v1:
- Web UI: Open the main LlamaCloud UI, go to Settings → General, and enable the Extract v1 toggle for your workspace.
- Python SDK: Use the
llama-cloud-servicespackage (shown as the “Python (legacy)” tab in our SDK examples). See the SDK page for details. - REST API: The v1 endpoints are documented on the REST API (v1 Legacy) page.
Extract v1 is legacy and may be deprecated in the future. We recommend migrating to v2 for new projects.