langchain/docs/extras/integrations/providers/grobid.mdx

# Grobid

This page covers how to use the Grobid to parse articles for LangChain.
It is separated into two parts: installation and running the server

## Installation and Setup
#Ensure You have Java installed
!apt-get install -y openjdk-11-jdk -q
!update-alternatives --set java /usr/lib/jvm/java-11-openjdk-amd64/bin/java

#Clone and install the Grobid Repo
import os
!git clone https://github.com/kermitt2/grobid.git
os.environ["JAVA_HOME"] = "/usr/lib/jvm/java-11-openjdk-amd64"
os.chdir('grobid')
!./gradlew clean install

#Run the server, 
get_ipython().system_raw('nohup ./gradlew run > grobid.log 2>&1 &')

You can now use the GrobidParser to produce documents
```python
from langchain.document_loaders.parsers import GrobidParser
from langchain.document_loaders.generic import GenericLoader

#Produce chunks from article paragraphs
loader = GenericLoader.from_filesystem(
    "/Users/31treehaus/Desktop/Papers/",
    glob="*",
    suffixes=[".pdf"],
    parser= GrobidParser(segment_sentences=False)
)
docs = loader.load()

#Produce chunks from article sentences
loader = GenericLoader.from_filesystem(
    "/Users/31treehaus/Desktop/Papers/",
    glob="*",
    suffixes=[".pdf"],
    parser= GrobidParser(segment_sentences=True)
)
docs = loader.load()
```
Chunk metadata will include bboxes although these are a bit funky to parse, see https://grobid.readthedocs.io/en/latest/Coordinates-in-PDF/