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Navigator Document Parser

Overview

This repo contains a CLI application used for extracting text from pdf and html documents before translating these to a target language (default is English) if they are in a different language to the target language.

HTML Text Extraction:

  • HTML webpages are processed by making a request to the webpage and extracting text from the html content using a combination of the news-please and readability python packages.

PDF Text Extraction:

  • PDF documents are processed by downloading the pdf from the cdn (Content Delivery Network accessible via an endpoint) and using the Azure form recognizer API to extract text from the pdf.

Translation:

  • Text is translated using the Google translation api.

Setup

To operate and run the CLI the repo provides useful commands in the Makefile. This reads environment variables from a .env file. Create this locally by running the following command and then enter the relevant values.

make setup

Once this is done we can then run the commands in the "Makefile". These split into two main groups, running directly on your machine, or in a Docker container.

To run locally run the following commands to install dependencies using Poetry and set up playwright and pre-commit. Then run the CLI locally.

Note that you will need a Python version in your virtual environment of that matches the project version. It is also recommended to run within a virtual environment.

make install
make run_local

Running the CLI

To run in Docker with the data/raw folder as input and data/processed as output run:

make run_docker

The CLI operates on an input folder of tasks defined by JSON files in the following format as defined in cpr_sdk library dependency. This can be found here.

class ParserInput(BaseModel):
    """Base class for input to a parser."""

    document_id: str
    document_metadata: BackendDocument
    document_name: str
    document_description: str
    document_source_url: Optional[AnyHttpUrl]
    document_cdn_object: Optional[str]
    document_content_type: Optional[str]
    document_md5_sum: Optional[str]
    document_slug: str

It outputs JSON files named ${id}.json, with id being the document_id of each input document, to an output folder in one of these formats:

class ParserOutput(BaseModel):
    """Base class for an output to a parser."""

    document_id: str
    document_metadata: BackendDocument
    document_name: str
    document_description: str
    document_source_url: Optional[AnyHttpUrl]
    document_cdn_object: Optional[str]
    document_content_type: Optional[str]
    document_md5_sum: Optional[str]
    document_slug: str

    languages: Optional[Sequence[str]] = None
    translated: bool = False
    html_data: Optional[HTMLData] = None
    pdf_data: Optional[PDFData] = None