langchain/docs/extras/integrations/providers/grobid.mdx
2023-07-23 23:23:16 -07:00

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# 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/