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.
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First, login and get an api-key from https://cloud.llamaindex.ai ↗.
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"])
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.
Several end-to-end indexing examples can be found in the examples folder
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