lumina-invoice-reader 0.0.2

Convert PDF to structured data

This is Lumina Invoice Reader Project

Data_Processor Class Documentation

The Data_Processor class is designed to process various types of data, including images, text, and tables. It sends these data types to a GPT model for classification and translates the results from Vietnamese to English.

Initialization

The class is initialized with a dictionary of credentials that should include the URL and headers for the GPT model.

processor = Data_Processor(credentials)

Methods

send_request_to_gpt

This method sends a request to the GPT model and returns the extracted content from the response.

processor.send_request_to_gpt(system_prompt, user_prompt, temperature, max_tokens, top_p, version)

classify_image

This method classifies the provided image using the GPT model and returns the result as a dictionary. The image should be provided as a base64 encoded string.

processor.classify_image(image_base64, image_extraction_prompt, translation_prompt)

classify_text

This method classifies the provided text using the GPT model and returns the result as a dictionary.

processor.classify_text(classify_prompt, translation_prompt, text)

classify_and_translate_table

This method classifies the provided table data and translates the result. The table data should be provided as a string.

processor.classify_and_translate_table(classification_prompt, translation_prompt, user_prompt, result_key)

classify_and_translate_multiple_tables

This method sends multiple tabular data to GPT for classification and returns the result as JSON. The tabular data should be stored in .txt files in the specified directory.

processor.classify_and_translate_multiple_tables(classification_prompt, translation_prompt, directory_path, file_name, num_workers)

Error Handling

All methods in the Data_Processor class are designed to handle exceptions and will raise an error if something goes wrong during the classification or translation process.

Other note

(invoice_reader_ct) => this is for building the library (invoice_reader_test) => this is for test the library

Further developemnt

How to hide these warnings from camelot: C:\Users\ftt.cuong.ton\anaconda3\envs\invoice_reader_test\lib\site-packages\camelot\parsers\lattice.py:416: UserWarning: No tables found on page-2 C:\Users\ftt.cuong.ton\anaconda3\envs\invoice_reader_test\lib\site-packages\camelot\parsers\lattice.py:411: UserWarning: page-1 is image-based, camelot only works on text-based pages.