dosubot[bot]
commented
11 months ago 🤖
Hello,
The error you're encountering is due to the fact that the extract_images_in_pdf argument is not a valid argument for the UnstructuredYoloXModel.initialize() method. However, in the provided context, the extract_images_in_pdf argument is being used in the partition_pdf function from the unstructured.partition.pdf module, not in the UnstructuredYoloXModel.initialize() method.
Here is the relevant code snippet:
from unstructured.partition.pdf import partition_pdf
# Get elements
raw_pdf_elements = partition_pdf(filename=path+"LLaVA.pdf",
extract_images_in_pdf=True,
infer_table_structure=True,
chunking_strategy="by_title",
max_characters=4000,
new_after_n_chars=3800,
combine_text_under_n_chars=2000,
image_output_dir_path=path)The extract_images_in_pdf argument is used to specify whether to extract images from the PDF document. If you're encountering an error related to this argument, it's possible that the version of the unstructured library you're using does not support this argument.
To resolve this issue, you can try updating the unstructured library to the latest version. If the problem persists, you may need to check the documentation or source code of the unstructured library to see if the extract_images_in_pdf argument is supported in the partition_pdf function. If it's not supported, you may need to remove this argument from your function call.
Regarding the partition_pdf function in the LangChain codebase, it is used to split a PDF document into different elements such as Title and NarrativeText. The function takes a filename and additional arguments for different unstructured settings. The function is called in the _get_elements method of the UnstructuredPDFLoader class.
Here is the relevant code snippet:
class UnstructuredPDFLoader(UnstructuredFileLoader):
"""Load `PDF` files using `Unstructured`.
You can run the loader in one of two modes: "single" and "elements".
If you use "single" mode, the document will be returned as a single
langchain Document object. If you use "elements" mode, the unstructured
library will split the document into elements such as Title and NarrativeText.
You can pass in additional unstructured kwargs after mode to apply
different unstructured settings.
Examples
--------
from langchain.document_loaders import UnstructuredPDFLoader
loader = UnstructuredPDFLoader(
"example.pdf", mode="elements", strategy="fast",
)
docs = loader.load()
References
----------
https://unstructured-io.github.io/unstructured/bricks.html#partition-pdf
"""
def _get_elements(self) -> List:
from unstructured.partition.pdf import partition_pdf
return partition_pdf(filename=self.file_path, **self.unstructured_kwargs)In the context of the LangChain codebase, the partition_pdf function is used to split a PDF document into different elements when the UnstructuredPDFLoader is run in "elements" mode.
I hope this helps! If you have any other questions, feel free to ask.
Best, Dosu
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When running on colab, it has following error:
https://github.com/langchain-ai/langchain/blob/5dbe456aae755e3190c46316102e772dfcb6e148/cookbook/Semi_structured_and_multi_modal_RAG.ipynb#L103