blob42/langchain
1
0
Fork 0
forked from Archives/langchain
Code Issues Pull Requests Packages Projects Releases Wiki Activity
3207a74829
langchain/docs/ecosystem/unstructured.md
Matt Robinson 63aa28e2a6
feat: allow the unstructured kwargs to be passed in to Unstructured document loaders (#1667) 
### Summary

Allows users to pass in `**unstructured_kwargs` to Unstructured document
loaders. Implemented with the `strategy` kwargs in mind, but will pass
in other kwargs like `include_page_breaks` as well. The two currently
supported strategies are `"hi_res"`, which is more accurate but takes
longer, and `"fast"`, which processes faster but with lower accuracy.
The `"hi_res"` strategy is the default. For PDFs, if `detectron2` is not
available and the user selects `"hi_res"`, the loader will fallback to
using the `"fast"` strategy.


### Testing

#### Make sure the `strategy` kwarg works

Run the following in iPython to verify that the `"fast"` strategy is
indeed faster.

```python
from langchain.document_loaders import UnstructuredFileLoader

loader = UnstructuredFileLoader("layout-parser-paper-fast.pdf", strategy="fast", mode="elements")
%timeit loader.load()

loader = UnstructuredFileLoader("layout-parser-paper-fast.pdf", mode="elements")
%timeit loader.load()
```

On my system I get:

```python
In [3]: from langchain.document_loaders import UnstructuredFileLoader

In [4]: loader = UnstructuredFileLoader("layout-parser-paper-fast.pdf", strategy="fast", mode="elements")

In [5]: %timeit loader.load()
247 ms ± 369 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)

In [6]: loader = UnstructuredFileLoader("layout-parser-paper-fast.pdf", mode="elements")

In [7]: %timeit loader.load()
2.45 s ± 31 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
```

#### Make sure older versions of `unstructured` still work

Run `pip install unstructured==0.5.3` and then verify the following runs
without error:

```python
from langchain.document_loaders import UnstructuredFileLoader

loader = UnstructuredFileLoader("layout-parser-paper-fast.pdf",  mode="elements")
loader.load()
```
2023-03-14 18:15:28 -07:00

1.8 KiB
Raw Blame History

Unstructured

This page covers how to use the unstructured ecosystem within LangChain. The unstructured package from Unstructured.IO extracts clean text from raw source documents like PDFs and Word documents.

This page is broken into two parts: installation and setup, and then references to specific unstructured wrappers.

Installation and Setup

  • Install the Python SDK with pip install "unstructured[local-inference]"
  • Install the following system dependencies if they are not already available on your system. Depending on what document types you're parsing, you may not need all of these.
    • libmagic-dev
    • poppler-utils
    • tesseract-ocr
    • libreoffice
  • If you are parsing PDFs using the "hi_res" strategy, run the following to install the detectron2 model, which unstructured uses for layout detection:
    • pip install "detectron2@git+https://github.com/facebookresearch/detectron2.git@v0.6#egg=detectron2"
    • If detectron2 is not installed, unstructured will fallback to processing PDFs using the "fast" strategy, which uses pdfminer directly and doesn't require detectron2.

Wrappers

Data Loaders

The primary unstructured wrappers within langchain are data loaders. The following shows how to use the most basic unstructured data loader. There are other file-specific data loaders available in the langchain.document_loaders module.

from langchain.document_loaders import UnstructuredFileLoader

loader = UnstructuredFileLoader("state_of_the_union.txt")
loader.load()

If you instantiate the loader with UnstructuredFileLoader(mode="elements"), the loader will track additional metadata like the page number and text type (i.e. title, narrative text) when that information is available.