from PyPDF2 import PdfReader
import openai
import fitz  # PyMuPDF
import gradio as gr


class AggressiveContentFinder:
    """
    This class identifies and extracts aggressive terms in a contract document using OpenAI's GPT-3.

    """

    def __init__(self):
        """
        Initialize the AggressiveContentFinder with your OpenAI API key.
        """
        # openai.api_key = openai_api_key
        pass

    def _extract_aggressive_content(self, contract_text: str) -> str:
        """
        Use OpenAI's GPT-3 to identify aggressive terms in the given contract text.

        Args:
            contract_text (str): Text extracted from the contract.

        Returns:
            str: Identified aggressive terms.
        """
        try:
            response = openai.Completion.create(
                engine="text-davinci-003",
                prompt=f"""This is a contract document content. Your task is to identify aggressive terms like warning terms, penalties in the given contract:
                (Example: "The bank may take possession of the property.")
                ```contract: {contract_text}```
                """,
                max_tokens=70,
                temperature=0
            )
            aggressive_terms = response.choices[0].text.strip()
            return aggressive_terms
        except Exception as e:
            print(f"An error occurred during text analysis: {str(e)}")

    def get_aggressive_content(self, pdf_file_path: str):
        """
        Extract text from a PDF document and identify aggressive terms.

        Args:
            pdf_file_path (str): Path to the PDF document.

        Returns:
            str: Identified aggressive terms in the contract document.

        This method opens a multi-page PDF using PdfReader and iterates through each page. For each page, it extracts
        the text and passes it to the _extract_aggressive_content method for further processing. The identified
        aggressive terms are concatenated and returned. If any errors occur during PDF processing, they are logged for
        debugging.
        """
        try:

            # Open the multi-page PDF using PdfReader
            pdf = PdfReader(pdf_file_path.name)

            aggressive_terms = ""

            # Extract text from each page and pass it to the process_text function
            for page_number in range(len(pdf.pages)):
                # Extract text from the page
                page = pdf.pages[page_number]
                text = page.extract_text()

                # Pass the text to the process_text function for further processing
                aggressive_terms += self._extract_aggressive_content(text)
            return aggressive_terms

        except Exception as e:
            print(f"An error occurred while processing the PDF document: {str(e)}")

    def file_output_fnn(self,file_path):
        file_path = file_path.name
        return file_path

    def gradio_interface(self):
        with gr.Blocks(css="style.css",theme='xiaobaiyuan/theme_brief') as demo:    
            with gr.Row(elem_id = "col-container",scale=0.80):
              # with gr.Column(elem_id = "col-container",scale=0.80):
              #   file1 = gr.File(label="File",elem_classes="filenameshow")
            
              # with gr.Column(elem_id = "col-container",scale=0.20):  
              #   upload_button1 = gr.UploadButton(
              #       "Browse File",file_types=[".txt", ".pdf", ".doc", ".docx",".json",".csv"],
              #       elem_classes="uploadbutton")
                aggressive_content = gr.Button("Get Aggressive Content",elem_classes="uploadbutton")
            
            with gr.Row(elem_id = "col-container",scale=0.60):    
                headings = gr.Textbox(label = "Aggressive Content")

        # upload_button1.upload(self.file_output_fnn,upload_button1,file1)
        aggressive_content.click(self.get_aggressive_content,[],headings)