LlamaParse

LlamaParse is an API created by LlamaIndex to efficiently parse and represent files for efficient retrieval and context augmentation using LlamaIndex frameworks.

LlamaParse directly integrates with LlamaIndex.

Free plan is up to 1000 pages a day. Paid plan is free 7k pages per week + 0.3c per additional page.

There is a sandbox available to test the API https://cloud.llamaindex.ai/parse ↗.

Read below for some quickstart information, or see the full documentation.

Getting Started

First, login and get an api-key from https://cloud.llamaindex.ai/api-key ↗.

Then, make sure you have the latest LlamaIndex version installed.

NOTE: If you are upgrading from v0.9.X, we recommend following our migration guide, as well as uninstalling your previous version first.

pip uninstall llama-index  # run this if upgrading from v0.9.x or older
pip install -U llama-index --upgrade --no-cache-dir --force-reinstall

Lastly, install the package:

pip install llama-parse

Now you can run the following to parse your first PDF file:

import nest_asyncio

nest_asyncio.apply()

from llama_parse import LlamaParse

parser = LlamaParse(
    api_key="llx-...",  # can also be set in your env as LLAMA_CLOUD_API_KEY
    result_type="markdown",  # "markdown" and "text" are available
    num_workers=4,  # if multiple files passed, split in `num_workers` API calls
    verbose=True,
    language="en",  # Optionally you can define a language, default=en
)

# sync
documents = parser.load_data("./my_file.pdf")

# sync batch
documents = parser.load_data(["./my_file1.pdf", "./my_file2.pdf"])

# async
documents = await parser.aload_data("./my_file.pdf")

# async batch
documents = await parser.aload_data(["./my_file1.pdf", "./my_file2.pdf"])

Using with file object

You can parse a file object directly:

import nest_asyncio

nest_asyncio.apply()

from llama_parse import LlamaParse

parser = LlamaParse(
    api_key="llx-...",  # can also be set in your env as LLAMA_CLOUD_API_KEY
    result_type="markdown",  # "markdown" and "text" are available
    num_workers=4,  # if multiple files passed, split in `num_workers` API calls
    verbose=True,
    language="en",  # Optionally you can define a language, default=en
)

with open("./my_file1.pdf", "rb") as f:
    documents = parser.load_data(f)

# you can also pass file bytes directly
with open("./my_file1.pdf", "rb") as f:
    file_bytes = f.read()
    documents = parser.load_data(file_bytes)

Using with SimpleDirectoryReader

You can also integrate the parser as the default PDF loader in SimpleDirectoryReader:

import nest_asyncio

nest_asyncio.apply()

from llama_parse import LlamaParse
from llama_index.core import SimpleDirectoryReader

parser = LlamaParse(
    api_key="llx-...",  # can also be set in your env as LLAMA_CLOUD_API_KEY
    result_type="markdown",  # "markdown" and "text" are available
    verbose=True,
)

file_extractor = {".pdf": parser}
documents = SimpleDirectoryReader(
    "./data", file_extractor=file_extractor
).load_data()

Full documentation for SimpleDirectoryReader can be found on the LlamaIndex Documentation.

Examples

Several end-to-end indexing examples can be found in the examples folder

• Getting Started
• Advanced RAG Example
• Raw API Usage

Documentation

https://docs.cloud.llamaindex.ai/

Terms of Service

See the Terms of Service Here.